- Email: [email protected]
A new integrated instrumental approach to autonomic nervous system assessment
Accepted Manuscript Title: A new integrated instrumental approach to autonomic nervous system assessment Author: I. Corazza G. Barletta P. Guaraldi A. Cecere G. Calandra-Buonaura E. Altini R. Zannoli P. Cortelli PII: DOI: Reference:
S0169-2607(14)00304-6 http://dx.doi.org/doi:10.1016/j.cmpb.2014.08.002 COMM 3843
To appear in:
Computer Methods and Programs in Biomedicine
Received date: Revised date: Accepted date:
4-3-2014 15-7-2014 5-8-2014
Please cite this article as: I. Corazza, G. Barletta, P. Guaraldi, A. Cecere, G. CalandraBuonaura, E. Altini, R. Zannoli, P. Cortelli, A new integrated instrumental approach to autonomic nervous system assessment., Computer Methods and Programs in Biomedicine (2014), http://dx.doi.org/10.1016/j.cmpb.2014.08.002 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
A new integrated instrumental approach to autonomic nervous system assessment I Corazza1*, G Barletta2,3*, P Guaraldi2,3, A Cecere2,3,G Calandra-Buonaura2,3, E Altini1, R Zannoli1 and P Cortelli2,3 (1) Experimental, Diagnostic and Specialty Medicine Department, University of Bologna, Italy
(3) IRCCS, Institute of Neurological Sciences of Bologna, Bologna, Italy
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* These authors contributed equally to this work
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Corresponding author: Ivan Corazza
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DIMES – University of Bologna Via Massarenti, 9
Phone: +390516363588
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40138 Bologna Italy
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(2) Department of Biomedical and Neuromotor Sciences, University of Bologna, Italy
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Email: [email protected]
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Abstract Background and Objectives The autonomic nervous system (ANS) regulates involuntary body functions and is commonly evaluated by measuring reflex responses of systolic and diastolic blood pressure (BP) and heart rate (HR) to physiological and pharmacological stimuli. However, BP and HR values may not sufficient
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be to explain specific ANS events and other parameters like the electrocardiogram (ECG), BP waves, the respiratory rate and the electroencephalogram (EEG) are mandatory. Although ANS
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behaviour and its response to stimuli are well-known, their clinical evaluation is often based on individual medical training and experience. As a result, ANS laboratories have been customized,
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making it impossible to standardize procedures and share results with colleagues.
The aim of our study was to build a powerful versatile instrument easy-to-use in clinical practice to
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standardize procedures and allow a cross-analysis of all the parameters of interest for ANS evaluation. Methods
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The new ANScovery System developed by neurologists and technicians is a two-step device: 1) integrating physiological information from different already existing commercial modules, making
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it possible to cross-analyse, store and share data; 2) standardizing procedures by an innovative tutor
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monitor able to guide the patient throughout ANS testing. Results and Conclusions
The daily use of the new ANScovery System in clinical practice has proved it is a versatile easy to use instrument. Standardization of the manoeuvres and step-by-step guidance throughout the procedure avoid repetitions and allow intra and inter-patient data comparison.
Keywords: autonomic nervous system, cardiovascular reflexes, integrated solution, signal analysis
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1. Introduction The ANS consists of several interconnected areas distributed throughout the neuraxis and known as the central autonomic network (CAN). The CAN is involved in tonic, reflex and adaptive control of autonomic functions receiving visceroceptive, humoral and exteroceptive information and modulating sympathetic and parasympathetic neuronal outputs of the CAN. [1]
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Because the anatomical location of the ANS renders it inaccessible to simple and direct physiological testing, a series of clinical tests assessing autonomic function and dysfunction have
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been developed to overcome this problem by measuring the end-organ responses to various physiological perturbations. [2-5]
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In 1982, Ewing and Clarke advocated a battery of five tests suitable for bedside autonomic function testing. These tests provided an assessment of both sympathetic and parasympathetic nervous
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system function. With some modifications, this test battery still forms the core of the cardiovascular autonomic evaluation performed by many autonomic laboratories. [6]
The background physiology of these cardiovascular tests includes parasympathetic cardiac control
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and sympathetic cardiovascular control. The preganglionic parasympathetic nerves are located in the nucleus ambiguus and the dorsal motor nucleus of the vagus in the medulla oblongata of the
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brain stem and project to the heart via vagus nerves terminating in cardiac ganglia that innervate the
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sino-atrial node, right and left atria, and atrio-ventricular node, where the neurotransmitter acetylcholine binds to muscarinic receptors to decrease heart rate (HR), atrial contractility, and A-V nodal conduction. Inputs from the arterial baroreflex, arterial chemoreflex, and cardiopulmonary receptors mediate cardiovascular reflexes that alter cardiovagal nerve activity. The activity of the sympathetic nervous system influences mean arterial pressure through many mechanisms, including effects on total peripheral vascular resistance, HR, myocardial contractility, venous vascular tone, and blood volume. The tonic excitatory drive to preganglionic sympathetic neurons located in the intermediolateral column of the thoracolumbar spinal cord originates primarily in premotor neurons
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in the rostral ventrolateral medulla, with other central nervous system sites such as the hypothalamic paraventricular nucleus contributing to variable degrees depending on the physiological and pathological state. Preganglionic sympathetic neurons project to sympathetic ganglia where they release acetylcholine as the primary neurotransmitter and they provide widespread innervation of arterial and venous systems, visceral organs and adrenal glands. The arterial baroreflex, arterial chemoreflex, and cardiopulmonary receptors mediate cardiovascular
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reflexes that also alter blood pressure. In addition, neural activity originating within the CAN associated with various behaviours (stress, anxiety, and/or fear) may trigger changes in sympathetic
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output that influence cardiovascular control. [7, 8]
Autonomic function in health and disease is now widely assessed myriad disciplines (neurology,
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cardiology, psychology, psychophysiology, obstetrics, anaesthesiology, and psychiatry) and ANS laboratories are increasingly required to disclose autonomic dysfunction, determine the anatomic
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and physiologic distribution of the deficit, grade its severity, and monitor the patient’s response to therapy. [2]
According to the well-known physiology of cardiovascular reflex tests the BP responses to head-up
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tilt test (HUTT), Valsalva manoeuvre (VM), and isometric exercise (IE) are considered a good estimate of sympathetic function while the HR response to deep breathing (DB), and VM are
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considered a good estimate of cardiovagal function. [2-5]
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In order to understand and analyse the beat-to-beat changes in BP and HR induced by the manoeuvres and to check the correctness of the procedure ECG and pressures waves must be acquired in real time [9] with instrumentation such as the Finometer (FMS, Amsterdam, The Netherlands) or Nexfin System (Edwards Lifesciences, Irvine, CA, USA; NIBP100D, Biopac, Goleta, CA, USA). [10]
However, measuring only BP and HR without real-time monitoring and simultaneous measurement of the respiratory rate and EEG signals with video recordings may lead to the wrong diagnosis (i.e.
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mistaking a seizure or the effects of hyperventilation for syncope). EEG monitoring provides dynamic information on brain function, disclosing early changes in neurologic status and a possible correlation between the central nervous system and the ANS [11-13]. Respiratory rate assessment is fundamental to evaluate physiological sinus arrhythmia and the possible effects of hyperventilation, apnoeas or breath-holding on cardiovascular parameters [6]. Video recording is crucial during the post-processing phase to relate the patient’s physiological responses to the accuracy of manoeuvres,
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evaluating any extraneous body movements and artifacts. Unfortunately, few ANS laboratories use standard procedures and new acquisition modules (AM)
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are usually added to those already present without the possibility to interconnect; other laboratories
adopt all-in-one solutions, allowing the integration and cross-analysis of some but not all
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parameters depending on the manufacturer. [10]
The wide variety of instrumentation and the lack of standardization in today’s ANS laboratories are
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critical shortcomings for diagnosis, results comparison and clinical advances. Since the cost of equipment is high and health system budgets are limited, it is unrealistic to think that standardization could be achieved with a powerful but expensive all-in-one system. For this reason,
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a good solution to the problem could be a modular system able to interface the AM already present in an ANS laboratory and open to improvement with new devices.
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The aim of our study was to build a powerful versatile instrument to guide the patient through test
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procedures and cross-analyse all the cardiovascular parameters of interest for ANS evaluation. Our solution was designed and built in the ANS laboratory of the University of Bologna (Bologna, Italy) based on the clinical and research experience of ANS specialists. [14] Our approach was to collect signals from commercial AM by means of a specific analogue-to-digital (AD) converter and dedicated open software to visualize, store and analyse the clinical information and generate a final report with the results. This guarantees standardization of the procedures, simultaneous acquisition of all the parameters required, the addition of any new AM to upgrade the system, and storage of all patient data in only one repository for statistical analysis and research purposes. Standard protocols
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were followed for each clinical procedure. [2-4, 6, 15] An example is reported of the results obtained by applying a standard battery of tests to two groups of healthy and pathological subjects.
2. Material and methods The core of our proposal was the possibility to integrate physiological information from different commercial modules during ANS evaluation in order to cross-analyse and store data. The solution
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was based on an analogue-digital approach and comprises four main blocks: 1) Commercial AM with analogue outputs;
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2) Multipurpose AD converter connected with a medical grade personal computer (PC) to integrate, analyse and store all the signals of interest;
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3) Video recorder directly interfaced to the PC; 4) Centralized web-based database to store data.
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To complete the proposal, an external device (tutor monitor, TM) was developed and interfaced to the system to guide the patient through test procedures, standardizing execution of the manoeuvres.
2.1 Commercial AM
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A schematic view of our system (ANScovery) is shown in figure 1.
For ANS evaluation acquiring all the parameters of interest (BP, ECG, EEG, nasal and abdominal
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breathing), the following commercial AM were used:
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Model 15LT (GRASS TECHNOLOGIES, Quincy, MA) polygraph amplifiers for: - ECG: Lead II with foam, wet, gel, ECG Electrodes ( Kendall™); - BREATH: Abdominal or chest respiration motions with piezo-crystal respiration effort sensor (SleepSense) and respiratory airflow with thermal flow sensor (SleepSense);
- PERIPHERAL VASOMOTOR TONE: with finger photoelectric transducer (51P35H GRASS TECHNOLOGIES):
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- EEG: two or four bipolar leads derived from Ag/AgCl disk electrodes positioned on the scalp according to the10/20 international system; - Finometer MIDI (Finapres Medical Systems, Amsterdam) for continuous beat-to-beat BP measurement.
ch
ECG
Model 15 LT 15A54
3
EEG
Model 15 LT 15A54
2
BREATH
Model 15 LT 15A94
2
Model 15 LT 15A12
1
VASOMOTOR TONE Finometer Midi
1
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BLOOD PRESSURE
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PERIPHERAL
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Monitoring device
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Parameter
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Table 1 shows the technical number of channels for each parameter.
Table 1. Clinical parameters, acquisition module and number of channels (ch) for each device.
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2.2 Data acquisition (multipurpose AD converter)
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The AD unit was designed and built in collaboration with SparkBio Srl (Bologna, Italy) and acquires up to 16 analogical signals at a sample rate of 500 Hz with a resolution of 12 bits. The sampling rate and number of channels are easily set by the user through the software interface of the ANScovery System. The only requirement is that the product of these two factors remains constant. Moreover, the instrument allows the input ranges to be set according to the external monitor set-up, being the optimal solution to integrate products with different technical specifications. The AD converter is serial connected with a Microsoft Windows-based PC with dedicated software for visualization, storage and analysis. The software is built with Microsoft Visual Studio based on
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NET Framework SDK and will combine signals from the AD converter with additional signals directly acquired from the PC (i.e. video recordings). HR is calculated in real time and a tachogram channel is added and visualized together with the other signals. Systolic (SBP) and diastolic BP (DBP) values are shown throughout the procedure.
2.3 Video recorder
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The video and audio recording system is integrated into the PC and comprises an internal interface (MORPHIS MATROX EVO), an external camera (PANASONIC VIDEOCAMERA mod. WV-
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CS580/G for acquisition of high-resolution video clips at 25fps, and joystick Videotec mod. DCJ for the remote control of the video camera) and a high sensitivity microphone to record ambient
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sounds. A secondary monitor has been added to the PC for better video display. The video interface is directly driven by the AD converter to guarantee a simultaneous start-up.
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Since the timing of the electronic components used for video and signals acquisition is intrinsically variable, the ANScovery system also implemented a software synchronization protocol: after a fixed time, depending on the settled sampling rate, the numbers of buffered samples is compared to
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the acquired frames. In case of incongruity, a correction is made. Given that the AD converter has an internal clock at 20kHz and the typical sampling rates used for signal acquisition are 500/100Hz,
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the timing errors of the analogical signals due to clock variability is 20/40 times less than the
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sampling rate. When the timing discrepancy between the frame rate and the sampled data becomes equal to the sampling period, a sample is added or erased from the buffered data. Since the video frame rate is lower than the AD sampling rate, errors in video acquisition are rare. In case of undersampling, each lost frame is compensated by an additional one equal to the last frame correctly acquired, thereby always maintaining the frame rate equal to 25fps. Thus, the signals and video are realigned in real time and any time lags kept shorter than one sampling period, irrespective of the procedure duration.
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2.4 Tutor monitor A PC-based tutor monitor (TM) was designed and built to guide and support patients during execution of the ANS tests by means of visual and acoustic feedback (time, event mark, test parameters). The beginning and end of each manoeuvre are automatically marked and a marker channel is added and acquired together with the other parameters. This channel is important for automatic
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recognition of the manoeuvre and for software analysis. A dedicated pressure module (composed of two pressure sensors) is connected to the monitor to acquire the pressure generated by the patient
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during VM and IE. A mouthpiece is connected to one pressure sensor and an armcuff is connected with an air hose to the other. TM shows these pressure signals in real time, providing positive
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feedback to patients and helping them perform the manoeuvres. For example, during the VM the patient’s expiratory pressure is shown as an incremental green bar. A threshold mark is set by the
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operator (red mark) and is clearly visible on the screen. The manoeuvre starts when the green bar crosses the threshold and stops after 15s.
The start and stop time instants are stored and automatically sent to the AD unit as marker signals.
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Correct manoeuvre identification is fundamental for procedure analysis and clinical evaluation. For
manoeuvres.
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each manoeuvre, the TM shows different frames (figure 2) guiding the patient through the
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The clinical set-up in the ANS laboratory is completed by a tilting bed (MFTT tilt-bed) to change the patient’s position from clinostatism to orthostatism depending on the procedure [2, 3].
2.5 Clinical protocol for ANS evaluation
The standard clinical protocol for ANS analysis comprises a sequence of cardiovascular tests that can be customized depending on the patient’s condition and the correct execution of manoeuvres. The ANScovery System can manage the following tests: HUTT, VM, DB, CF, CP, right and left
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sinus massage, standing, IE (or hand grip), mental stress and hyperventilation. The standard sequence of tests performed in the University of Bologna ANS laboratory [14] includes: 1) Head-up tilt test (HUTT); 2) Three repetitions of the Valsalva manoeuvre (VM); 3) Deep breathing (DB); 4) Cold face (CF);
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Tests are executed and evaluated following standard procedures [2-4, 6, 9, 15].
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5) Isometric exercise (IE) or hand grip.
2.6 Software analysis
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ANScovery software manages the visualization and storage of real-time signals and video recordings. Visualization can be customized by the user and some basic analysis procedures can be
time and amplitude measurements, marking events).
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applied both in real time and in the post-processing phase (i.e. digital filtering, tachogram creation,
To date, the ANScovery System has fully analysed and correlated HR and BP during the different
• Detection of events;
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tests [3, 5]. At the end of acquisition, the analysis software follows four steps:
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• Association between event and manoeuvre according to standard protocols;
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• Manoeuvre analysis with subsequent visualization of the sequences or identified points (SBP, DBP, HR) following the criteria explained below;
• Final report (Microsoft Word format) including the results of the parameters evaluated for each manoeuvre and concurrent data dispatch to the web database.
The user is able to check and correct each step of the analysis. Some more analysis algorithms have been implemented such as frequency analysis (Fast Fourier Transform and autoregression), HR variability, baroreceptor sensitivity and other simple calculations like signal derivative, integrals, and digital filtration (low-pass, high-pass, band-pass, notch).
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To guarantee the compatibility between ANScovery software and other commercial stand-alone devices able to acquire at least pressure and ECG (FMS Finometer, Portapres and Finapress) data and beat-to-beat files exported from the different machines can be read allowing the same ANS analysis.
2.7 Database
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ANScovery software can be connected to a web-server database (ANS Web-application) to store the parameters of interest of all patients. The patient’s case history and clinical data (diagnosis,
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drugs, etc.) must be inserted directly by the physician, whereas physiological values related to ANS
evaluation are directly stored in the database by the ANScovery software. All data are encrypted
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and stored in a safe server according to current regulations concerning privacy and data protection. Figure 6 (a) shows two database screenshots related to general patient information (a) and VM
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analysis (b).
The whole software package, including the acquisition and analysis modules, TM and remote database, was developed following the requirements of the IEC 62304. As a final step, during
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clinical and technical validation, the ANScovery System was CE-marked according to the medical
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devices EU directives (93/42/CEE and 2007/47).
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In order to demonstrate the feasibility of the ANScovery System, we extracted from our database two groups of subjects who underwent the standard battery of tests performed in our laboratories: 37 healthy subjects (age: 63±8 years, 24 males and 13 females) and 33 patients (age: 64±7 years, 27 males and 6 females) with a diagnosis of autonomic neuropathy. Each subject was submitted to a standard battery of tests as reported in paragraph 2.5. The duration of tilt test was 10 minutes. Table 2 shows the parameters evaluated for each manoeuvre [3, 5] with its description.
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Test
Description response to HUTT as the difference (∆) between values at 3 min and basal values of SBP as the mean value of the last 5 min of supine rest preceding HUTT
∆DBP (mmHg)
response to HUTT as the difference (∆) between values at 3 min and basal values of DBP as the mean value of the last 5 min of supine rest preceding HUTT
∆HR (bpm)
response to HUTT as the difference (∆) between values at 3 min and basal values of HR as the mean value of the last 5 min of supine rest preceding HUTT
VR
Valsalva ratio as the ratio between the highest HR reached in phase II and the lowest HR of phase IV reflex bradycardia
∆BP IV (mmHg)
∆ BP IV as difference (∆) between max SBP phase IV and basal values of SBP as the mean value of the last 10 beats preceding Valsalva manoeuvre
Deep breathing
∆IE (bpm)
Sinus arrhythmia during DB as average of the 10 shortest R-R intervals during inspiration – average of the 10 longest R-R during expiration
Cold face
∆SBP (mmHg)
Response to CF as the difference (∆) between the highest value reached during test and basal values of SBP as the mean value of the last 20 beats preceding the test
∆DBP (mmHg)
Response to CF as the difference (∆) between the highest value reached during test and basal values of DBP as the mean value of the last 20 beats preceding the test
∆HR (bpm)
Response to CF as the difference (∆) between the lowest value reached during test and basal values of HR as the mean value of the last 20 beats preceding the test
∆SBP (mmHg)
Response to HG as the difference (∆) between values after 5 min of isometric effort and basal values of SBP as the mean value of the last 3 min preceding isometric effort
∆DBP (mmHg)
Response to HG as the difference (∆) between values after 5 min of isometric effort and basal values of DBP as the mean value of the last 3 min preceding isometric effort
∆HR (bpm)
Response to HG as the difference (∆) between values after 5 min of isometric effort and basal values of HR as the mean value of the last 3 min preceding isometric effort
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Handgrip
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Valsalva manoeuvre
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∆SBP (mmHg)
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Head-up tilt test
Evaluated parameter
The Kolgomorov-Smirnov test was used to verify the normal distribution of data; then a parametric Student t-test was performed to compare the results of the two groups. A p value <0.05 was accepted for rejection of the null hypothesis.
3. Results
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The daily clinical use of the ANScovery System in the University of Bologna ANS laboratory has demonstrated it is a versatile easy to use instrument. The possibility to integrate different AM for different physiologic parameters allowed us to create a powerful system for ANS evaluation. The laboratory is shown in figure 3. The different sensors used to acquire signals are well-tolerated by the patients who appreciate the usefulness of the TM. Standardization of the manoeuvres and step-by-step guidance throughout the
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procedure has shortened its duration and avoided repetitions. Figure 4 shows an example of parameters acquired during a normal HUTT, and software appearance after analysis (display speed:
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1mm/s). The table shows the different parameters inserted in the final report. All the signals of
interest are visible during the real-time acquisition helping the technician to evaluate the correctness
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of test execution. Some examples are plotted in figure 5. Figure 6 shows an example of the final report generated by the software and fully customizable by the user.
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Table 3 shows the results of the tests for normal and pathological subjects. The between groups comparison highlights significant statistically differences for all the parameters of interest. The only
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exception is ∆HR during HUTT. This result is in agreement with the physiology of the test. [3, 5] Autonomic Neuropathy
Control
n=33
n=37
SD
Mean
SD
64.03
6.93
62.57
8.49
-60.21
20.26
11.59
11.46
<0.05
-28.39
12.14
10.49
6.74
<0.05
∆HR (bpm)
6.70
13.14
10.62
5.11
ns
VR
1.11
0.15
1.74
0.35
<0.05
∆BP IV (mmHg)
-24.48
16.90
46.74
18.57
<0.05
Deep breathing
∆IE (bpm)
6.03
4.59
15.40
5.07
<0.05
Cold face
∆SBP (mmHg)
11.34
5.77
34.00
16.49
<0.05
4.91
4.28
17.26
14.41
<0.05
age
∆SBP (mmHg) ∆DBP (mmHg)
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Head-up tilt test
yrs
d
Mean
Valsalva manoeuvre
∆DBP (mmHg)
p
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(mmHg)
Handgrip
∆SBP (mmHg) ∆DBP (mmHg) ∆HR (bpm)
-2.88
7.69
-7.00
5.34
<0.05
-3.31
18.65
45.50
20.10
<0.05
-0.56
8.91
23.53
9.57
<0.05
7.03
10.06
15.19
7.48
<0.05
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∆HR (bpm)
4. Discussion
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The ANScovery System is the result of ten years’ research by neurologists and technicians in an
ANS laboratory. The project stemmed from the need to standardize the procedures and analysis
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undertaken in different institutions. [10] Our goals were to: (a) build a modular solution to integrate devices already present on the market; (b) design and build a device able to guide the patient
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through the execution of manoeuvres; (c) implement powerful software for simple clinical evaluation and more complex procedures for research purposes. The “modular” approach was successful and guarantees the possibility to improve the ANScovery System in the future.
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Our integrated solution allows autonomic tests to acquire all the signals of interest simultaneously, with the possibility of adding new signals if required. Automatic analysis of ECG and BP signals is
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a powerful tool for daily use in a clinical ANS laboratory. The integration of different information
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could lead to a more complete evaluation of the ANS and hence improve diagnostic accuracy. Moreover, acquiring parameters of interest with different methods minimizes the errors intrinsic to physiological models or procedures.
Different all-in-one commercial devices are used in most ANS laboratories. Although they are powerful systems (e.g. Task Force Monitor, CNSystem Medizintechnik, Graz, Austria), they cannot be integrated with other signals and specific software analysis is often lacking or incomplete. Our system represents a comprehensive solution for ANS evaluation: it is user-adjustable both for hardware and software and guarantees standardized procedures. The possibility to share data with
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different centres through the web-based database is a major improvement for both clinical and research purposes. The TM does not substitute the technician but facilitates the execution of cardiovascular tests and provides immediate feedback on the clinical parameters. Moreover, it helps to standardize the execution of manoeuvres by guiding the patient throughout the cardiovascular tests with a potential improvement in duration and related costs (personnel, etc.).
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Video and audio recordings are of primary importance to relate events and body movements, identify artifacts and avoid losing any important information provided by the patient vocally during
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the tests.
The software represents a real innovation, analysing all the data in a short time-span and printing
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the final numerical report in a few seconds. The algorithms for manoeuvre analysis are not superimposed by an external manufacturer but developed directly in the laboratory, based on the
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experience of technicians and physicians and applied to real cases recorded during the last ten years. All the new requirements arising in daily clinical and research experience have been implemented and integrated in the ANScovery System. The approach adopted was always modular
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and the philosophy was “to integrate” and not “to rebuild”. Hence, the same algorithms used for the analysis of data recorded by the ANScovery System are now applicable to signals exported from
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other commercial devices. This means the software and database can be used as stand-alone
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devices, but in this case, manoeuvres cannot be standardized with the TM that represents the only device of its kind on the market.
The web-server database allows patients’ physiological data to be collected for intra-patient and inter-patient analysis. Since the database is web stored, it is remotely accessible by client computers in other hospitals and research centres, thereby enhancing cooperation and research among different groups.
The results of clinical evaluation performed with ANScovery are in agreement with the existing scientific literature. The example reported in this paper shows significant statistically differences
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between healthy subjects and autonomic patients. The standard battery of cardiovascular tests implemented in our system is powerful and represents a good solution for clinical evaluation of a patient. The possibility to improve this standard sequence with the other tests provided by ANScovery gives the physician a further chance to enhance the diagnosis. Our solution standardizes procedures for daily clinical investigation of the ANS and the analysis
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can be improved and customized for research purposes.
5. Acknowledgements
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We thank SparkBio SRL (Bologna, Italy) for fundamental technical support. Moreover we are grateful to GRASS TECHNOLOGIES and FMS for their help in integrating their sensors with the
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ANScovery System.
All authors certify that there is no actual or potential conflict of interest in relation to this article and
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that no external funding was obtained to conduct this research.
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6. References
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[1] Freeman R., Chapleau M.W., Testing the autonomic nervous system, Handb Clin Neurol 115 115-36. [2] Freeman R., Assessment of cardiovascular autonomic function, Clin Neurophysiol 117 (2006) 716-30. [3] Mathias C.J., Autonomic diseases: clinical features and laboratory evaluation, J Neurol Neurosurg Psychiatry 74 Suppl 3 (2003) iii31-41. [4] Spallone V., Bellavere F., Scionti L., Maule S., Quadri R., Bax G., et al., Recommendations for the use of cardiovascular tests in diagnosing diabetic autonomic neuropathy, Nutr Metab Cardiovasc Dis 21 (2011) 69-78. [5] Weimer L.H., Autonomic testing: common techniques and clinical applications, Neurologist 16 (2010) 215-22. [6] Ewing D.J., Clarke B.F., Diagnosis and management of diabetic autonomic neuropathy, Br Med J (Clin Res Ed) 285 (1982) 916-8. [7] Goldstein D.S., Differential responses of components of the autonomic nervous system, Handb Clin Neurol 117 13-22. [8] Guyenet P.G., The sympathetic control of blood pressure, Nat Rev Neurosci 7 (2006) 33546. [9] Lahrmann H., Cortelli P., Hilz M., Mathias C.J., Struhal W., Tassinari M., EFNS guidelines on the diagnosis and management of orthostatic hypotension, Eur J Neurol 13 (2006) 930-6.
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[10] Lahrmann H., Magnifico F., Haensch C.A., Cortelli P., Autonomic nervous system laboratories: a European survey, Eur J Neurol 12 (2005) 375-9. [11] Machado C., Estevez M., Rodriguez R., Perez-Nellar J., Chinchilla M., Defina P., et al., Zolpidem Arousing Effect In Persistent Vegetative State Patients: Autonomic, Eeg And Behavioral Assessment, Curr Pharm Des (2012). [12] Subhani A.R., Likun X., Saeed Malik A., Association of autonomic nervous system and EEG scalp potential during playing 2D Grand Turismo 5, Conf Proc IEEE Eng Med Biol Soc 2012 3420-3. [13] van Dijk J.G., Thijs R.D., van Zwet E., Tannemaat M.R., van Niekerk J., Benditt D.G., et al., The semiology of tilt-induced reflex syncope in relation to electroencephalographic changes, Brain 137 576-85. [14] Grimaldi D., Pierangeli G., Barletta G., Terlizzi R., Plazzi G., Cevoli S., et al., Spectral analysis of heart rate variability reveals an enhanced sympathetic activity in narcolepsy with cataplexy, Clin Neurophysiol 121 (2010) 1142-7. [15] Ewing D.J., Irving J.B., Kerr F., Wildsmith J.A., Clarke B.F., Cardiovascular responses to sustained handgrip in normal subjects and in patients with diabetes mellitus: a test of autonomic function, Clin Sci Mol Med 46 (1974) 295-306.
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Figure 1: Schematic representation of the ANScovery System. Figure 2: Example of manoeuvre windows. Figure 3: University of Bologna ANS laboratory. Left: the ANScovery System; right: the tutor monitor; middle: the tilting bed. Figure 4: Example of signals during HUTT. Red and green markers refer to the beats of interest used for the analysis. The table shows the parameters extrapolated after software analysis inserted in the final report. Figure 5: (a) Example of Valsalva manoeuvre. Blue, red and green vertical markers highlight the beats of
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interest: the patient’s forced expiration pressure is wrong (20mmHg) and the manoeuvre is not significant. (b) The manoeuvre is performed correctly (pressure=40mmHg, according to the protocol). A “blinded”
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analysis of the test, without a verification of the correctness of execution, leads to wrong results: Overshoot=18mmHg instead of 30mmHg; VR=0.96 instead of 1.94; Max Bradi=84bpm instead of 66 bpm.
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The signal at the bottom of the windows represents the patient’s expiration pressure: the difference between the two tests is clear and it is immediately possible to discriminate between them. (b) Example of deep
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breathing in a normal patient and in a patient with autonomic failure. The morphology of the breath channel guarantees the correctness of procedure execution. Tachogram morphology clearly shows the difference
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Figure 6: Example of a final report.
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between normal and pathologic subjects.
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S0169-2607(14)00304-6 http://dx.doi.org/doi:10.1016/j.cmpb.2014.08.002 COMM 3843
To appear in:
Computer Methods and Programs in Biomedicine
Received date: Revised date: Accepted date:
4-3-2014 15-7-2014 5-8-2014
Please cite this article as: I. Corazza, G. Barletta, P. Guaraldi, A. Cecere, G. CalandraBuonaura, E. Altini, R. Zannoli, P. Cortelli, A new integrated instrumental approach to autonomic nervous system assessment., Computer Methods and Programs in Biomedicine (2014), http://dx.doi.org/10.1016/j.cmpb.2014.08.002 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
A new integrated instrumental approach to autonomic nervous system assessment I Corazza1*, G Barletta2,3*, P Guaraldi2,3, A Cecere2,3,G Calandra-Buonaura2,3, E Altini1, R Zannoli1 and P Cortelli2,3 (1) Experimental, Diagnostic and Specialty Medicine Department, University of Bologna, Italy
(3) IRCCS, Institute of Neurological Sciences of Bologna, Bologna, Italy
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* These authors contributed equally to this work
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Corresponding author: Ivan Corazza
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DIMES – University of Bologna Via Massarenti, 9
Phone: +390516363588
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40138 Bologna Italy
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(2) Department of Biomedical and Neuromotor Sciences, University of Bologna, Italy
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Email: [email protected]
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Abstract Background and Objectives The autonomic nervous system (ANS) regulates involuntary body functions and is commonly evaluated by measuring reflex responses of systolic and diastolic blood pressure (BP) and heart rate (HR) to physiological and pharmacological stimuli. However, BP and HR values may not sufficient
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be to explain specific ANS events and other parameters like the electrocardiogram (ECG), BP waves, the respiratory rate and the electroencephalogram (EEG) are mandatory. Although ANS
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behaviour and its response to stimuli are well-known, their clinical evaluation is often based on individual medical training and experience. As a result, ANS laboratories have been customized,
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making it impossible to standardize procedures and share results with colleagues.
The aim of our study was to build a powerful versatile instrument easy-to-use in clinical practice to
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standardize procedures and allow a cross-analysis of all the parameters of interest for ANS evaluation. Methods
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The new ANScovery System developed by neurologists and technicians is a two-step device: 1) integrating physiological information from different already existing commercial modules, making
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it possible to cross-analyse, store and share data; 2) standardizing procedures by an innovative tutor
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monitor able to guide the patient throughout ANS testing. Results and Conclusions
The daily use of the new ANScovery System in clinical practice has proved it is a versatile easy to use instrument. Standardization of the manoeuvres and step-by-step guidance throughout the procedure avoid repetitions and allow intra and inter-patient data comparison.
Keywords: autonomic nervous system, cardiovascular reflexes, integrated solution, signal analysis
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1. Introduction The ANS consists of several interconnected areas distributed throughout the neuraxis and known as the central autonomic network (CAN). The CAN is involved in tonic, reflex and adaptive control of autonomic functions receiving visceroceptive, humoral and exteroceptive information and modulating sympathetic and parasympathetic neuronal outputs of the CAN. [1]
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Because the anatomical location of the ANS renders it inaccessible to simple and direct physiological testing, a series of clinical tests assessing autonomic function and dysfunction have
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been developed to overcome this problem by measuring the end-organ responses to various physiological perturbations. [2-5]
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In 1982, Ewing and Clarke advocated a battery of five tests suitable for bedside autonomic function testing. These tests provided an assessment of both sympathetic and parasympathetic nervous
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system function. With some modifications, this test battery still forms the core of the cardiovascular autonomic evaluation performed by many autonomic laboratories. [6]
The background physiology of these cardiovascular tests includes parasympathetic cardiac control
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and sympathetic cardiovascular control. The preganglionic parasympathetic nerves are located in the nucleus ambiguus and the dorsal motor nucleus of the vagus in the medulla oblongata of the
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brain stem and project to the heart via vagus nerves terminating in cardiac ganglia that innervate the
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sino-atrial node, right and left atria, and atrio-ventricular node, where the neurotransmitter acetylcholine binds to muscarinic receptors to decrease heart rate (HR), atrial contractility, and A-V nodal conduction. Inputs from the arterial baroreflex, arterial chemoreflex, and cardiopulmonary receptors mediate cardiovascular reflexes that alter cardiovagal nerve activity. The activity of the sympathetic nervous system influences mean arterial pressure through many mechanisms, including effects on total peripheral vascular resistance, HR, myocardial contractility, venous vascular tone, and blood volume. The tonic excitatory drive to preganglionic sympathetic neurons located in the intermediolateral column of the thoracolumbar spinal cord originates primarily in premotor neurons
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in the rostral ventrolateral medulla, with other central nervous system sites such as the hypothalamic paraventricular nucleus contributing to variable degrees depending on the physiological and pathological state. Preganglionic sympathetic neurons project to sympathetic ganglia where they release acetylcholine as the primary neurotransmitter and they provide widespread innervation of arterial and venous systems, visceral organs and adrenal glands. The arterial baroreflex, arterial chemoreflex, and cardiopulmonary receptors mediate cardiovascular
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reflexes that also alter blood pressure. In addition, neural activity originating within the CAN associated with various behaviours (stress, anxiety, and/or fear) may trigger changes in sympathetic
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output that influence cardiovascular control. [7, 8]
Autonomic function in health and disease is now widely assessed myriad disciplines (neurology,
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cardiology, psychology, psychophysiology, obstetrics, anaesthesiology, and psychiatry) and ANS laboratories are increasingly required to disclose autonomic dysfunction, determine the anatomic
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and physiologic distribution of the deficit, grade its severity, and monitor the patient’s response to therapy. [2]
According to the well-known physiology of cardiovascular reflex tests the BP responses to head-up
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tilt test (HUTT), Valsalva manoeuvre (VM), and isometric exercise (IE) are considered a good estimate of sympathetic function while the HR response to deep breathing (DB), and VM are
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considered a good estimate of cardiovagal function. [2-5]
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In order to understand and analyse the beat-to-beat changes in BP and HR induced by the manoeuvres and to check the correctness of the procedure ECG and pressures waves must be acquired in real time [9] with instrumentation such as the Finometer (FMS, Amsterdam, The Netherlands) or Nexfin System (Edwards Lifesciences, Irvine, CA, USA; NIBP100D, Biopac, Goleta, CA, USA). [10]
However, measuring only BP and HR without real-time monitoring and simultaneous measurement of the respiratory rate and EEG signals with video recordings may lead to the wrong diagnosis (i.e.
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mistaking a seizure or the effects of hyperventilation for syncope). EEG monitoring provides dynamic information on brain function, disclosing early changes in neurologic status and a possible correlation between the central nervous system and the ANS [11-13]. Respiratory rate assessment is fundamental to evaluate physiological sinus arrhythmia and the possible effects of hyperventilation, apnoeas or breath-holding on cardiovascular parameters [6]. Video recording is crucial during the post-processing phase to relate the patient’s physiological responses to the accuracy of manoeuvres,
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evaluating any extraneous body movements and artifacts. Unfortunately, few ANS laboratories use standard procedures and new acquisition modules (AM)
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are usually added to those already present without the possibility to interconnect; other laboratories
adopt all-in-one solutions, allowing the integration and cross-analysis of some but not all
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parameters depending on the manufacturer. [10]
The wide variety of instrumentation and the lack of standardization in today’s ANS laboratories are
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critical shortcomings for diagnosis, results comparison and clinical advances. Since the cost of equipment is high and health system budgets are limited, it is unrealistic to think that standardization could be achieved with a powerful but expensive all-in-one system. For this reason,
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a good solution to the problem could be a modular system able to interface the AM already present in an ANS laboratory and open to improvement with new devices.
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The aim of our study was to build a powerful versatile instrument to guide the patient through test
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procedures and cross-analyse all the cardiovascular parameters of interest for ANS evaluation. Our solution was designed and built in the ANS laboratory of the University of Bologna (Bologna, Italy) based on the clinical and research experience of ANS specialists. [14] Our approach was to collect signals from commercial AM by means of a specific analogue-to-digital (AD) converter and dedicated open software to visualize, store and analyse the clinical information and generate a final report with the results. This guarantees standardization of the procedures, simultaneous acquisition of all the parameters required, the addition of any new AM to upgrade the system, and storage of all patient data in only one repository for statistical analysis and research purposes. Standard protocols
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were followed for each clinical procedure. [2-4, 6, 15] An example is reported of the results obtained by applying a standard battery of tests to two groups of healthy and pathological subjects.
2. Material and methods The core of our proposal was the possibility to integrate physiological information from different commercial modules during ANS evaluation in order to cross-analyse and store data. The solution
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was based on an analogue-digital approach and comprises four main blocks: 1) Commercial AM with analogue outputs;
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2) Multipurpose AD converter connected with a medical grade personal computer (PC) to integrate, analyse and store all the signals of interest;
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3) Video recorder directly interfaced to the PC; 4) Centralized web-based database to store data.
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To complete the proposal, an external device (tutor monitor, TM) was developed and interfaced to the system to guide the patient through test procedures, standardizing execution of the manoeuvres.
2.1 Commercial AM
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A schematic view of our system (ANScovery) is shown in figure 1.
For ANS evaluation acquiring all the parameters of interest (BP, ECG, EEG, nasal and abdominal
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breathing), the following commercial AM were used:
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Model 15LT (GRASS TECHNOLOGIES, Quincy, MA) polygraph amplifiers for: - ECG: Lead II with foam, wet, gel, ECG Electrodes ( Kendall™); - BREATH: Abdominal or chest respiration motions with piezo-crystal respiration effort sensor (SleepSense) and respiratory airflow with thermal flow sensor (SleepSense);
- PERIPHERAL VASOMOTOR TONE: with finger photoelectric transducer (51P35H GRASS TECHNOLOGIES):
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- EEG: two or four bipolar leads derived from Ag/AgCl disk electrodes positioned on the scalp according to the10/20 international system; - Finometer MIDI (Finapres Medical Systems, Amsterdam) for continuous beat-to-beat BP measurement.
ch
ECG
Model 15 LT 15A54
3
EEG
Model 15 LT 15A54
2
BREATH
Model 15 LT 15A94
2
Model 15 LT 15A12
1
VASOMOTOR TONE Finometer Midi
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BLOOD PRESSURE
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PERIPHERAL
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Monitoring device
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Parameter
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Table 1 shows the technical number of channels for each parameter.
Table 1. Clinical parameters, acquisition module and number of channels (ch) for each device.
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2.2 Data acquisition (multipurpose AD converter)
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The AD unit was designed and built in collaboration with SparkBio Srl (Bologna, Italy) and acquires up to 16 analogical signals at a sample rate of 500 Hz with a resolution of 12 bits. The sampling rate and number of channels are easily set by the user through the software interface of the ANScovery System. The only requirement is that the product of these two factors remains constant. Moreover, the instrument allows the input ranges to be set according to the external monitor set-up, being the optimal solution to integrate products with different technical specifications. The AD converter is serial connected with a Microsoft Windows-based PC with dedicated software for visualization, storage and analysis. The software is built with Microsoft Visual Studio based on
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NET Framework SDK and will combine signals from the AD converter with additional signals directly acquired from the PC (i.e. video recordings). HR is calculated in real time and a tachogram channel is added and visualized together with the other signals. Systolic (SBP) and diastolic BP (DBP) values are shown throughout the procedure.
2.3 Video recorder
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The video and audio recording system is integrated into the PC and comprises an internal interface (MORPHIS MATROX EVO), an external camera (PANASONIC VIDEOCAMERA mod. WV-
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CS580/G for acquisition of high-resolution video clips at 25fps, and joystick Videotec mod. DCJ for the remote control of the video camera) and a high sensitivity microphone to record ambient
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sounds. A secondary monitor has been added to the PC for better video display. The video interface is directly driven by the AD converter to guarantee a simultaneous start-up.
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Since the timing of the electronic components used for video and signals acquisition is intrinsically variable, the ANScovery system also implemented a software synchronization protocol: after a fixed time, depending on the settled sampling rate, the numbers of buffered samples is compared to
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the acquired frames. In case of incongruity, a correction is made. Given that the AD converter has an internal clock at 20kHz and the typical sampling rates used for signal acquisition are 500/100Hz,
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the timing errors of the analogical signals due to clock variability is 20/40 times less than the
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sampling rate. When the timing discrepancy between the frame rate and the sampled data becomes equal to the sampling period, a sample is added or erased from the buffered data. Since the video frame rate is lower than the AD sampling rate, errors in video acquisition are rare. In case of undersampling, each lost frame is compensated by an additional one equal to the last frame correctly acquired, thereby always maintaining the frame rate equal to 25fps. Thus, the signals and video are realigned in real time and any time lags kept shorter than one sampling period, irrespective of the procedure duration.
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2.4 Tutor monitor A PC-based tutor monitor (TM) was designed and built to guide and support patients during execution of the ANS tests by means of visual and acoustic feedback (time, event mark, test parameters). The beginning and end of each manoeuvre are automatically marked and a marker channel is added and acquired together with the other parameters. This channel is important for automatic
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recognition of the manoeuvre and for software analysis. A dedicated pressure module (composed of two pressure sensors) is connected to the monitor to acquire the pressure generated by the patient
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during VM and IE. A mouthpiece is connected to one pressure sensor and an armcuff is connected with an air hose to the other. TM shows these pressure signals in real time, providing positive
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feedback to patients and helping them perform the manoeuvres. For example, during the VM the patient’s expiratory pressure is shown as an incremental green bar. A threshold mark is set by the
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operator (red mark) and is clearly visible on the screen. The manoeuvre starts when the green bar crosses the threshold and stops after 15s.
The start and stop time instants are stored and automatically sent to the AD unit as marker signals.
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Correct manoeuvre identification is fundamental for procedure analysis and clinical evaluation. For
manoeuvres.
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each manoeuvre, the TM shows different frames (figure 2) guiding the patient through the
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The clinical set-up in the ANS laboratory is completed by a tilting bed (MFTT tilt-bed) to change the patient’s position from clinostatism to orthostatism depending on the procedure [2, 3].
2.5 Clinical protocol for ANS evaluation
The standard clinical protocol for ANS analysis comprises a sequence of cardiovascular tests that can be customized depending on the patient’s condition and the correct execution of manoeuvres. The ANScovery System can manage the following tests: HUTT, VM, DB, CF, CP, right and left
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sinus massage, standing, IE (or hand grip), mental stress and hyperventilation. The standard sequence of tests performed in the University of Bologna ANS laboratory [14] includes: 1) Head-up tilt test (HUTT); 2) Three repetitions of the Valsalva manoeuvre (VM); 3) Deep breathing (DB); 4) Cold face (CF);
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Tests are executed and evaluated following standard procedures [2-4, 6, 9, 15].
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5) Isometric exercise (IE) or hand grip.
2.6 Software analysis
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ANScovery software manages the visualization and storage of real-time signals and video recordings. Visualization can be customized by the user and some basic analysis procedures can be
time and amplitude measurements, marking events).
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applied both in real time and in the post-processing phase (i.e. digital filtering, tachogram creation,
To date, the ANScovery System has fully analysed and correlated HR and BP during the different
• Detection of events;
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tests [3, 5]. At the end of acquisition, the analysis software follows four steps:
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• Association between event and manoeuvre according to standard protocols;
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• Manoeuvre analysis with subsequent visualization of the sequences or identified points (SBP, DBP, HR) following the criteria explained below;
• Final report (Microsoft Word format) including the results of the parameters evaluated for each manoeuvre and concurrent data dispatch to the web database.
The user is able to check and correct each step of the analysis. Some more analysis algorithms have been implemented such as frequency analysis (Fast Fourier Transform and autoregression), HR variability, baroreceptor sensitivity and other simple calculations like signal derivative, integrals, and digital filtration (low-pass, high-pass, band-pass, notch).
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To guarantee the compatibility between ANScovery software and other commercial stand-alone devices able to acquire at least pressure and ECG (FMS Finometer, Portapres and Finapress) data and beat-to-beat files exported from the different machines can be read allowing the same ANS analysis.
2.7 Database
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ANScovery software can be connected to a web-server database (ANS Web-application) to store the parameters of interest of all patients. The patient’s case history and clinical data (diagnosis,
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drugs, etc.) must be inserted directly by the physician, whereas physiological values related to ANS
evaluation are directly stored in the database by the ANScovery software. All data are encrypted
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and stored in a safe server according to current regulations concerning privacy and data protection. Figure 6 (a) shows two database screenshots related to general patient information (a) and VM
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analysis (b).
The whole software package, including the acquisition and analysis modules, TM and remote database, was developed following the requirements of the IEC 62304. As a final step, during
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clinical and technical validation, the ANScovery System was CE-marked according to the medical
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devices EU directives (93/42/CEE and 2007/47).
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In order to demonstrate the feasibility of the ANScovery System, we extracted from our database two groups of subjects who underwent the standard battery of tests performed in our laboratories: 37 healthy subjects (age: 63±8 years, 24 males and 13 females) and 33 patients (age: 64±7 years, 27 males and 6 females) with a diagnosis of autonomic neuropathy. Each subject was submitted to a standard battery of tests as reported in paragraph 2.5. The duration of tilt test was 10 minutes. Table 2 shows the parameters evaluated for each manoeuvre [3, 5] with its description.
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Test
Description response to HUTT as the difference (∆) between values at 3 min and basal values of SBP as the mean value of the last 5 min of supine rest preceding HUTT
∆DBP (mmHg)
response to HUTT as the difference (∆) between values at 3 min and basal values of DBP as the mean value of the last 5 min of supine rest preceding HUTT
∆HR (bpm)
response to HUTT as the difference (∆) between values at 3 min and basal values of HR as the mean value of the last 5 min of supine rest preceding HUTT
VR
Valsalva ratio as the ratio between the highest HR reached in phase II and the lowest HR of phase IV reflex bradycardia
∆BP IV (mmHg)
∆ BP IV as difference (∆) between max SBP phase IV and basal values of SBP as the mean value of the last 10 beats preceding Valsalva manoeuvre
Deep breathing
∆IE (bpm)
Sinus arrhythmia during DB as average of the 10 shortest R-R intervals during inspiration – average of the 10 longest R-R during expiration
Cold face
∆SBP (mmHg)
Response to CF as the difference (∆) between the highest value reached during test and basal values of SBP as the mean value of the last 20 beats preceding the test
∆DBP (mmHg)
Response to CF as the difference (∆) between the highest value reached during test and basal values of DBP as the mean value of the last 20 beats preceding the test
∆HR (bpm)
Response to CF as the difference (∆) between the lowest value reached during test and basal values of HR as the mean value of the last 20 beats preceding the test
∆SBP (mmHg)
Response to HG as the difference (∆) between values after 5 min of isometric effort and basal values of SBP as the mean value of the last 3 min preceding isometric effort
∆DBP (mmHg)
Response to HG as the difference (∆) between values after 5 min of isometric effort and basal values of DBP as the mean value of the last 3 min preceding isometric effort
∆HR (bpm)
Response to HG as the difference (∆) between values after 5 min of isometric effort and basal values of HR as the mean value of the last 3 min preceding isometric effort
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Handgrip
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Valsalva manoeuvre
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∆SBP (mmHg)
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Head-up tilt test
Evaluated parameter
The Kolgomorov-Smirnov test was used to verify the normal distribution of data; then a parametric Student t-test was performed to compare the results of the two groups. A p value <0.05 was accepted for rejection of the null hypothesis.
3. Results
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The daily clinical use of the ANScovery System in the University of Bologna ANS laboratory has demonstrated it is a versatile easy to use instrument. The possibility to integrate different AM for different physiologic parameters allowed us to create a powerful system for ANS evaluation. The laboratory is shown in figure 3. The different sensors used to acquire signals are well-tolerated by the patients who appreciate the usefulness of the TM. Standardization of the manoeuvres and step-by-step guidance throughout the
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procedure has shortened its duration and avoided repetitions. Figure 4 shows an example of parameters acquired during a normal HUTT, and software appearance after analysis (display speed:
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1mm/s). The table shows the different parameters inserted in the final report. All the signals of
interest are visible during the real-time acquisition helping the technician to evaluate the correctness
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of test execution. Some examples are plotted in figure 5. Figure 6 shows an example of the final report generated by the software and fully customizable by the user.
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Table 3 shows the results of the tests for normal and pathological subjects. The between groups comparison highlights significant statistically differences for all the parameters of interest. The only
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exception is ∆HR during HUTT. This result is in agreement with the physiology of the test. [3, 5] Autonomic Neuropathy
Control
n=33
n=37
SD
Mean
SD
64.03
6.93
62.57
8.49
-60.21
20.26
11.59
11.46
<0.05
-28.39
12.14
10.49
6.74
<0.05
∆HR (bpm)
6.70
13.14
10.62
5.11
ns
VR
1.11
0.15
1.74
0.35
<0.05
∆BP IV (mmHg)
-24.48
16.90
46.74
18.57
<0.05
Deep breathing
∆IE (bpm)
6.03
4.59
15.40
5.07
<0.05
Cold face
∆SBP (mmHg)
11.34
5.77
34.00
16.49
<0.05
4.91
4.28
17.26
14.41
<0.05
age
∆SBP (mmHg) ∆DBP (mmHg)
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Head-up tilt test
yrs
d
Mean
Valsalva manoeuvre
∆DBP (mmHg)
p
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(mmHg)
Handgrip
∆SBP (mmHg) ∆DBP (mmHg) ∆HR (bpm)
-2.88
7.69
-7.00
5.34
<0.05
-3.31
18.65
45.50
20.10
<0.05
-0.56
8.91
23.53
9.57
<0.05
7.03
10.06
15.19
7.48
<0.05
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∆HR (bpm)
4. Discussion
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The ANScovery System is the result of ten years’ research by neurologists and technicians in an
ANS laboratory. The project stemmed from the need to standardize the procedures and analysis
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undertaken in different institutions. [10] Our goals were to: (a) build a modular solution to integrate devices already present on the market; (b) design and build a device able to guide the patient
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through the execution of manoeuvres; (c) implement powerful software for simple clinical evaluation and more complex procedures for research purposes. The “modular” approach was successful and guarantees the possibility to improve the ANScovery System in the future.
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Our integrated solution allows autonomic tests to acquire all the signals of interest simultaneously, with the possibility of adding new signals if required. Automatic analysis of ECG and BP signals is
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a powerful tool for daily use in a clinical ANS laboratory. The integration of different information
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could lead to a more complete evaluation of the ANS and hence improve diagnostic accuracy. Moreover, acquiring parameters of interest with different methods minimizes the errors intrinsic to physiological models or procedures.
Different all-in-one commercial devices are used in most ANS laboratories. Although they are powerful systems (e.g. Task Force Monitor, CNSystem Medizintechnik, Graz, Austria), they cannot be integrated with other signals and specific software analysis is often lacking or incomplete. Our system represents a comprehensive solution for ANS evaluation: it is user-adjustable both for hardware and software and guarantees standardized procedures. The possibility to share data with
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different centres through the web-based database is a major improvement for both clinical and research purposes. The TM does not substitute the technician but facilitates the execution of cardiovascular tests and provides immediate feedback on the clinical parameters. Moreover, it helps to standardize the execution of manoeuvres by guiding the patient throughout the cardiovascular tests with a potential improvement in duration and related costs (personnel, etc.).
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Video and audio recordings are of primary importance to relate events and body movements, identify artifacts and avoid losing any important information provided by the patient vocally during
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the tests.
The software represents a real innovation, analysing all the data in a short time-span and printing
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the final numerical report in a few seconds. The algorithms for manoeuvre analysis are not superimposed by an external manufacturer but developed directly in the laboratory, based on the
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experience of technicians and physicians and applied to real cases recorded during the last ten years. All the new requirements arising in daily clinical and research experience have been implemented and integrated in the ANScovery System. The approach adopted was always modular
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and the philosophy was “to integrate” and not “to rebuild”. Hence, the same algorithms used for the analysis of data recorded by the ANScovery System are now applicable to signals exported from
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other commercial devices. This means the software and database can be used as stand-alone
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devices, but in this case, manoeuvres cannot be standardized with the TM that represents the only device of its kind on the market.
The web-server database allows patients’ physiological data to be collected for intra-patient and inter-patient analysis. Since the database is web stored, it is remotely accessible by client computers in other hospitals and research centres, thereby enhancing cooperation and research among different groups.
The results of clinical evaluation performed with ANScovery are in agreement with the existing scientific literature. The example reported in this paper shows significant statistically differences
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between healthy subjects and autonomic patients. The standard battery of cardiovascular tests implemented in our system is powerful and represents a good solution for clinical evaluation of a patient. The possibility to improve this standard sequence with the other tests provided by ANScovery gives the physician a further chance to enhance the diagnosis. Our solution standardizes procedures for daily clinical investigation of the ANS and the analysis
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can be improved and customized for research purposes.
5. Acknowledgements
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We thank SparkBio SRL (Bologna, Italy) for fundamental technical support. Moreover we are grateful to GRASS TECHNOLOGIES and FMS for their help in integrating their sensors with the
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ANScovery System.
All authors certify that there is no actual or potential conflict of interest in relation to this article and
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that no external funding was obtained to conduct this research.
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6. References
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[1] Freeman R., Chapleau M.W., Testing the autonomic nervous system, Handb Clin Neurol 115 115-36. [2] Freeman R., Assessment of cardiovascular autonomic function, Clin Neurophysiol 117 (2006) 716-30. [3] Mathias C.J., Autonomic diseases: clinical features and laboratory evaluation, J Neurol Neurosurg Psychiatry 74 Suppl 3 (2003) iii31-41. [4] Spallone V., Bellavere F., Scionti L., Maule S., Quadri R., Bax G., et al., Recommendations for the use of cardiovascular tests in diagnosing diabetic autonomic neuropathy, Nutr Metab Cardiovasc Dis 21 (2011) 69-78. [5] Weimer L.H., Autonomic testing: common techniques and clinical applications, Neurologist 16 (2010) 215-22. [6] Ewing D.J., Clarke B.F., Diagnosis and management of diabetic autonomic neuropathy, Br Med J (Clin Res Ed) 285 (1982) 916-8. [7] Goldstein D.S., Differential responses of components of the autonomic nervous system, Handb Clin Neurol 117 13-22. [8] Guyenet P.G., The sympathetic control of blood pressure, Nat Rev Neurosci 7 (2006) 33546. [9] Lahrmann H., Cortelli P., Hilz M., Mathias C.J., Struhal W., Tassinari M., EFNS guidelines on the diagnosis and management of orthostatic hypotension, Eur J Neurol 13 (2006) 930-6.
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[10] Lahrmann H., Magnifico F., Haensch C.A., Cortelli P., Autonomic nervous system laboratories: a European survey, Eur J Neurol 12 (2005) 375-9. [11] Machado C., Estevez M., Rodriguez R., Perez-Nellar J., Chinchilla M., Defina P., et al., Zolpidem Arousing Effect In Persistent Vegetative State Patients: Autonomic, Eeg And Behavioral Assessment, Curr Pharm Des (2012). [12] Subhani A.R., Likun X., Saeed Malik A., Association of autonomic nervous system and EEG scalp potential during playing 2D Grand Turismo 5, Conf Proc IEEE Eng Med Biol Soc 2012 3420-3. [13] van Dijk J.G., Thijs R.D., van Zwet E., Tannemaat M.R., van Niekerk J., Benditt D.G., et al., The semiology of tilt-induced reflex syncope in relation to electroencephalographic changes, Brain 137 576-85. [14] Grimaldi D., Pierangeli G., Barletta G., Terlizzi R., Plazzi G., Cevoli S., et al., Spectral analysis of heart rate variability reveals an enhanced sympathetic activity in narcolepsy with cataplexy, Clin Neurophysiol 121 (2010) 1142-7. [15] Ewing D.J., Irving J.B., Kerr F., Wildsmith J.A., Clarke B.F., Cardiovascular responses to sustained handgrip in normal subjects and in patients with diabetes mellitus: a test of autonomic function, Clin Sci Mol Med 46 (1974) 295-306.
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Figure 1: Schematic representation of the ANScovery System. Figure 2: Example of manoeuvre windows. Figure 3: University of Bologna ANS laboratory. Left: the ANScovery System; right: the tutor monitor; middle: the tilting bed. Figure 4: Example of signals during HUTT. Red and green markers refer to the beats of interest used for the analysis. The table shows the parameters extrapolated after software analysis inserted in the final report. Figure 5: (a) Example of Valsalva manoeuvre. Blue, red and green vertical markers highlight the beats of
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interest: the patient’s forced expiration pressure is wrong (20mmHg) and the manoeuvre is not significant. (b) The manoeuvre is performed correctly (pressure=40mmHg, according to the protocol). A “blinded”
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analysis of the test, without a verification of the correctness of execution, leads to wrong results: Overshoot=18mmHg instead of 30mmHg; VR=0.96 instead of 1.94; Max Bradi=84bpm instead of 66 bpm.
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The signal at the bottom of the windows represents the patient’s expiration pressure: the difference between the two tests is clear and it is immediately possible to discriminate between them. (b) Example of deep
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breathing in a normal patient and in a patient with autonomic failure. The morphology of the breath channel guarantees the correctness of procedure execution. Tachogram morphology clearly shows the difference
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Figure 6: Example of a final report.
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between normal and pathologic subjects.
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