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Implementation of a Wearable Ultrasound Device for the Overnight Monitoring of Tongue Base Deformation during Obstructive Sleep Apnea Events
Ultrasound in Med. & Biol., Vol. 43, No. 8, pp. 1639–1650, 2017 Ó 2017 World Federation for Ultrasound in Medicine & Biology Printed in the USA. All rights reserved 0301-5629/$ - see front matter
http://dx.doi.org/10.1016/j.ultrasmedbio.2017.04.004
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Original Contribution IMPLEMENTATION OF A WEARABLE ULTRASOUND DEVICE FOR THE OVERNIGHT MONITORING OF TONGUE BASE DEFORMATION DURING OBSTRUCTIVE SLEEP APNEA EVENTS CHI-KAI WENG,* JENG-WEN CHEN,yz PO-YANG LEE,* and CHIH-CHUNG HUANG* * Department of Biomedical Engineering, National Cheng Kung University, Tainan, Taiwan; y Department of Otolaryngology-Head and Neck Surgery, Cardinal Tien Hospital, New Taipei City, Taiwan; and z School of Medicine, Fu-Jen Catholic University, New Taipei City, Taiwan (Received 12 October 2016; revised 17 March 2017; in final form 5 April 2017)
Abstract—Obstructive sleep apnea (OSA) is a breathing disorder characterized by the repeated collapse of the pharyngeal airway during sleep. Previous studies have reported that tongue base deformation may be a major contributing factor. However, overnight monitoring of tongue motion in patients with OSA has previously been impracticable. We developed a wearable ultrasound device for prolonged recording during natural sleep of the changes in tongue base thickness (TBT) in patients with OSA. The maximum TBT was fed into a polysomnography system so that physiologic signals and TBT data were simultaneously monitored. Subject trials revealed that TBT increased significantly during snoring, hypopnea and apnea events during natural sleep in patients with OSA. Moreover, the data revealed that the location of the maximum TBT during normal breathing was significantly different compared with the location during obstructive respiratory events, which implies a posterior or inferior displacement of the tongue base during sleep apnea. (E-mail: [email protected]) Ó 2017 World Federation for Ultrasound in Medicine & Biology. Key Words: Obstructive sleep apnea, Wearable device, Medical ultrasound, Tongue base thickness.
Overnight polysomnography (PSG) is currently the gold standard for diagnosing OSA. During PSG, an apnea event is defined as a complete cessation of airflow or a decrease of more than 90% in the peak thermal sensor signal for at least 10 s. A hypopnea event is defined as a decrease of more than 50% in the nasal pressure signal for at least 10 s and simultaneous arousal or oxyhemoglobin desaturation of more than 3%. The apnea–hypopnea index (AHI) is calculated using the total number of apnea and hypopnea events per hour of sleep. AHI is generally accepted as a reference that categorizes the severity of the OSA. AHI scores ,5 are normal. Mild, moderate and severe OSA are defined by the following scores: #AHI ,15, 15 #AHI ,30 and AHI $30, respectively. Although PSG measures a patient’s physiologic signals, it cannot pinpoint the sites of upper airway (UA) occlusion. Thus, additional methods for evaluation of UA anatomy and function are necessary. Several medical imaging methods have been applied to assess UA anatomy of patients with OSA, including magnetic resonance imaging (MRI), computed tomography (CT), endoscopy and ultrasonography, each of which has specific advantages and limitations (Stuck and Maurer 2008).
INTRODUCTION Sleep apnea is a sleep-related breathing disorder comprising central sleep apnea and obstructive sleep apnea (OSA). OSA involves recurring episodes of partial or complete obstruction of the pharyngeal airway during sleep and may cause intermittent hypoxemia, frequent arousal and fragmented sleep (American Academy of Sleep Medicine [AASM] Task Force 1999). It is associated with risk for hypertension, heart failure, myocardial infarction and stroke. A strong correlation between sleep apnea and traffic accident risk has also been proven (Teran-Santos et al. 1999). Prior studies have indicated that anatomic factors such as craniofacial anomalies, obesity and adenotonsillar hypertrophy contribute to the occurrence of OSA (Arens and Marcus 2004).
Address correspondence to: Chih-Chung Huang, Department of Biomedical Engineering, National Cheng Kung University, Tainan, Taiwan, No 1, University Road, Tainan City 701, Taiwan. E-mail: [email protected] Conflict of Interest Disclosure: The authors declare that they have no conflicts of interest. 1639
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Magnetic resonance imaging and CT scanning have been used to detect the narrowing of the UA in patients while they are awake (AASM Task Force 1999). CT scanning offers favorable contrast between soft tissue and bony structures. Several studies have suggested that the UA is smaller (especially in the retropalatal region) in OSA patients compared with healthy control patients (Bohlman et al. 1983). Specifically, the dimensions of the soft palate and tongue, as well as the cross-sectional areas, are considered important indicators that OSA may be diagnosed. Yucel et al. (2005) investigated the cross-sectional areas of the UA using CT scanning. They reported that patients with severe OSA had narrower cross-sectional areas and a thickened soft palate at the velopharyngeal level. However, CT scanning is not suitable for monitoring dynamic UA changes in patients with OSA, especially when they are asleep. Cine MRI has been used to visualize the dynamics of the UA in patients with OSA and identify the severity of UA obstruction. Static and dynamic MRI methods have improved understanding of the biomechanics and pathophysiology underlying OSA (Ciscar et al. 2001). Nonetheless, cine MRI is not universally available and is unsuitable for prolonged observations. Also, many people are unable to fall asleep during MRI scanning because of the noise made by the device. Most patients are given a sedative before an MRI scan, and the induced sleep that results may not accurately reflect the true respiratory condition during natural sleep. Cephalometric analysis is used to investigate skeletal craniofacial morphology (Partinen et al. 1988), and can be used to identify any craniofacial characteristics associated with OSA. However, real-time evaluation is not possible, and it is challenging to distinguish between soft tissues. Video endoscopy assesses the dynamics of the UA for precise pre-operative analysis (Ko and Su 2008). Obstruction of the UA can be observed and recorded during the M€uller maneuver (MM) using endoscopy. The MM is a simple examination that has been widely applied to simulate the pathophysiologic condition of OSA during wakefulness. However, the sites that are obstructed while the MM is performed are not the real sites obstructed during normal sleep (Terris et al. 2000). Ultrasonography has the advantages of being noninvasive, radiation free, portable and inexpensive, which have led to its use in OSA diagnosis. Liu et al. (2007) measured the lateral parapharyngeal wall (LPW) thickness using ultrasound to assess the soft tissue structure of OSA patients. The transducer was placed vertically on the side of the neck, and LPW thickness was measured from the internal carotid artery to the lateral pharyngeal wall. The results indicated that LPW thickness was independently associated with OSA. However, the area between the oropharynx and laryngopharynx is the most
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common anatomic location of airway collapse (Horner et al. 1989). OSA causes posterior migration of the tongue base on the laryngeal aperture and marked narrowing of the pharyngeal airway (Davidson 2003). Many studies have reported that deformation of the tongue is a major contributing factor in OSA (Chen et al. 2014; Lahav et al. 2009; Remijn et al. 2015). These findings indicate that measuring the deformation of the tongue base is also a reliable method for assessing airway collapse. In our previous study, we reported tongue base thickness (TBT) was an effective index for differentiating between people with and without OSA (Chen et al. 2014). Forty patients (20 patients with OSA and 20 control patients with an AHI ,5) were recruited for that study. Compared with the control group, the OSA patients had a significantly greater TBT during eupneic breathing and the MM and a significant difference between their TBT when the MM was use and that when it was not used. Most studies have measured the deformation of the tongue base in OSA patients only at the moment they awaken or by asking patients to perform the MM to simulate UA obstruction, neither of which is a realistic condition during an OSA patient’s natural sleep. Unfortunately, MRI and CT scanning are not suitable for use across the patient’s total daily sleep duration, and PSG cannot provide UA anatomic information. Overnight measurements of tongue base deformation during sleep have not previously been performed on patients with OSA or otherwise, but ultrasound imaging is an excellent option for achieving this objective. The purpose of this study was to develop a wearable ultrasound device for overnight monitoring during sleep of the TBT of patients with OSA. Because it is impossible for an operator to hold the ultrasound transducer for an overnight measurement, we designed a wearable transducer that did not need to be held. Hardware based on a field programmable gate array (FPGA) core unit was developed to constantly measure the tongue base deformation. Data measured using the ultrasound device were integrated with those from PSG to assess patients with OSA. Feasibility tests were performed in both healthy volunteers and patients with OSA, and the information obtained was used to generate hypotheses on the underlying mechanisms of OSA and tailor-made multimodality OSA management techniques that can be tested in subsequent studies. METHODS Custom-designed ultrasound transducer Figure 1(a) illustrates the position of the transducer relative to the neck, which allowed the submental midline sagittal section of the surrounding UA and tongue base to
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be seen in the ultrasound images. Figure 1(b) is a typical ultrasound image of the tongue base obtained using a commercial ultrasound system (Terason T3000, Teratech, Burlington, MA, USA) with a 2- to 5-MHz curved array transducer (5C2A, Teratech). Because there is a large mismatch in the acoustic impedance at the boundary between the tongue base and airway, stronger echogenic signals are easily observed in the ultrasound image, which means that the tongue base deformation can be monitored using gray-scale real-time ultrasound imaging during natural sleep. However, a conventional transducer could not be used for overnight measurements because it was impossible for an operator to hold the transducer in the same position over an extended period, and the subject would likely have felt uncomfortable. Therefore, we designed a wearable custom-designed 16-channel curvilinear array ultrasound transducer (Broadsound, Hsinchu, Taiwan), illustrated in Figure 2(a,b). Because the boundary between the tongue base and airway is a smooth curve, a 16-channel array was sufficient for characterizing the deformation of the tongue base. The miniaturized transducer (3.6 3 1.6 3 3.5 cm3) allowed the OSA patient to wear it overnight for continuous measurement. The center frequency of the transducer was 3 MHz, which allowed the acoustic waves propagated 8 cm in depth to reach the air–mucosa interface of tongue. Figure 2(c) illustrates the pulse-echo response of one element, and the transducer specifications are listed in Figure 2(d). The transducer scanned the midline sagittal plane of the submental skin, and changes in the relative positions and morphology of the tongue base along the sagittal axis of the UA were recorded. System implementation Figure 3 is a block diagram of the ultrasound device designed. The system comprised a custom transducer, system hardware, computer and PSG device. The main
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circuits were a transmit/receive switch, high-voltage (HV) bipolar ultrasound transmitter, pre-amplifier, variable-gain amplifier (VGA), analogue-to-digital converter (ADC), DC-to-DC power module, universal asynchronous receiver/transmitter (UART) interface, generalpurpose input/output (GPIO) interface and FPGA unit. The FPGA unit (Altera FPGA development board, DE2-115, Terasic Technologies, Hsinchu, Taiwan) was the core of the device, and included a pulse repetition frequency (PRF) timing controller and signal processor. The timing controller provided the control signal to the HV bipolar ultrasound transmitter, and this transmitter generated the 3-MHz bipolar pulse that drove the transducer. Figure 4(a) illustrates the timing sequences of the timing controller. A 50-MHz crystal oscillator was used to generate a stable clock on the FPGA development board. A 6-MHz rectangular clock (trace A) and a PRF pulse (trace B) were obtained by dividing the 50-MHz clock by a 12-bit counter using Verilog. The on time of the PRF pulse was set to 1 ms. Two logic control inputs (traces C and D) were needed for the bipolar transmitter, which was constructed using pairs of high-speed HV metal-oxide-semiconductor field-effect transistors (MOSFETs) (HV7350, Supertex, San Jose, CA, USA). The transmitter excited the ultrasound transducer through an expander (SMBD7000, Infineon Technologies, Munich, Germany) to reduce the noise signal from the transmitter to the transducer or from the electronic components in the receiver. This noise inhibition avoided the generation of undesirable jitters in the ultrasound devices (Huang et al. 2012). The output of the bipolar transmitter drove a 50-U load, and the maximum output peak-to-peak voltage was 100 V. The 26-dB bandwidth of the bipolar signal was approximately 40%. In this system, a signal with a PRF of 160 Hz with one cycle was fed to the bipolar transmitter. To ensure that a high-performance bipolar-pulse waveform was produced (trace E), the supply voltage bypass capacitors and MOSFET coupling capacitors had
Fig. 1. (a) Schematic of the relative positions of the ultrasound transducer and neck. The transducer was placed on the submental midline of the neck. (b) Typical B-mode ultrasound image of the tongue base.
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Fig. 2. (a,b) Top (a) and side (b) views of the wearable 16-channel ultrasound array transducer. (c) Pulse-echo response of one channel. (d) Specifications of the transducer.
to be as close as possible to the pins of the chip. This arrangement reduced noise and prevented resonance by the inclusion of a ferrite bead in the lead from the power supply to the capacitors. Because the transducer had 16 channels, switching was used to excite each channel
sequentially. A linear sequence switch (MAX14803, Maxim Integrated, San Jose, CA, USA) was controlled by the FPGA unit in a 16-bit serial–shift register arrangement. The switching sequence was synchronized with the PRF pulse, indicated by traces F and B in Figure 4(a).
Fig. 3. Block diagram of the designed ultrasound device. FPGA 5 field programmable gate array; GPIO 5 general-purpose input/output interface; PSG 5 polysomnography system; T/R 5 transmitter/receiver; UART 5 universal asynchronous receiver/transmitter.
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Fig. 4. (a) Timing controller sequences of the field programmable gate array (FPGA). (b) Flowchart of the signal processing procedure in the FPGA. CORDIC 5 coordinate rotation digital computer; GPIO 5 general-purpose input/ output interface; PSG 5 polysomnography system; TBT 5 tongue base thickness; UART 5 universal asynchronous receiver/transmitter.
The echo signals from the tissue were received via a limiter (SMBD7000, Infineon Technologies) and then fed to a preamplifier (Gali-741, Mini-Circuits, Brooklyn, NY, USA) and a VGA (MAX2077, Maxim Integrated). A gain of 45 dB was used in this study. A limiter was placed in front of the pre-amplifier to ensure that the input amplifier was not affected by the large excitation signal. The echo signals were then digitized by an ADC board (AD/DA data conversion card, Terasic Technologies) with 14-bit resolution and a 50-MHz sampling rate. The system included three low-drop voltage regulators (LD1117, STMicroelectronics, Geneva, Switzerland) that provided 3- and 5-V supplies to all components. Two miniature and ultralow-ripple high-voltage DC-to-DC converters (PCS01-05 N050 and PCS01-05 P050, 3 Gold Electronics, Hsinchu, Taiwan) were used to supply the bipolar transmitter’s high voltage (100 Vpp). Figure 4(b) is a flowchart depicting how tongue base deformation is measured with the FPGA unit. After the echo signals were digitized and fed into the FPGA, a buffer was created to capture the data. Because the air–mucosa interface exhibits a hyper-echoic raphe in a B-mode image, a clear echo signal was obtained in the A-line signal from each scan line. The position of this stronger echo represented the TBT measured by each channel, and was determined with a peak-detection method. A multiplier and adder in the FPGA then determined the depth of the air–mucosa interface, and a register stored the maximum positions from all 16 channels. Because the wearable transducer was a curved array, it was necessary to transform polar coordinates into Cartesian coordinates, which was achieved using a multiplier and look-up table to implement the coordinate rotation digital computer (CORDIC) algorithm in the FPGA. The maximum depths from the 16 channels were placed in a TBT register to
represent the boundary of the air–mucosa interface. The measured data in the FPGA were then transmitted to the computer and PSG device via the UART and GPIO interfaces, respectively. Because the PSG device had only a single analogue input channel, the TBT data stored in the FPGA were transformed into a clock signal (in which the number of cycles represented the TBT) that was then fed to the PSG device. This design allowed all the TBT and other PSG data to be recorded synchronously during the measurements. The system could detect TBTs within the range 44–80 mm. The TBT data were recorded at a sampling rate of 1 Hz because of the PSG device specifications. Today, FPGA is becoming powerful for many kinds of data transmission interfaces and signal processing. In addition to the signal processing unit, an ultrasound system is needed to integrate some I/O interfaces, such as LVDS, USB and SPI. FPGA provides the solution for these two purposes in the present system. Patients The ethics committee of Cardinal Tien Hospital approved this study, and written informed consent was obtained from all participants. Two healthy volunteers without OSA were enrolled to verify the feasibility of using the ultrasound system used in this study. OSA patients were recruited from the Center for Sleep Disorders at the Cardinal Tien Hospital, Taiwan. Exclusion criteria included refusal to participate, age ,20 y and a history of conditions: syndromal craniofacial abnormalities (e.g., Down syndrome); oral cavity, oropharyngeal or laryngeal masses; craniofacial surgery; burns, trauma or radiotherapy involving the head and neck region; neurologic disorders other than OSA; active inflammation in the head and neck region; or cervical rigidity that limited neck flexion and head extension.
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Polysomnography Participants with OSA underwent overnight ultrasound scanning with a standard attended PSG device (Embla N7000, Medcare, Reykjavik, Iceland) in the Center for Sleep Disorders. Ultrasound and PSG examinations took place over approximately 6 h. The PSG included continuous recording of the electroencephalogram, left and right electro-oculogram, chin and anterior tibia electromyogram, electrocardiogram, scoring of breathing variables based on a flow trace from a nasal cannula and thermistor, thoraco-abdominal motion and sleep position using chest and abdominal bands and a position monitor and oxyhemoglobin saturation with a finger pulse oximeter. The PSG data were scored by a registered sleep technician and reviewed by certified sleep physicians according to the criteria of Rechtschaffen and Kales (1968) and the updated scoring guidelines of the American Academy of Sleep Medicine. The sleep technicians and physicians were blinded to the ultrasound results. OSA was defined as the complete cessation of airflow or a decrease of $90% in the peak thermal sensor signal for at least 10 s, whereas a hypopnea event was defined as a decrease $50% in the nasal pressure signal for at least 10 s and simultaneous arousal or oxyhemoglobin desaturation of $3% (AASM Task Force 1999). Statistical analysis We compared the distribution of the recorded channels of the maximum TBT between normal breathing and other obstructive respiratory events, namely, snoring, hypopnea and apnea, using a goodness-of-fit test for each patient with OSA. Data analysis was conducted using Statistical Analysis System software, Version 9.3 (SAS Institute, Cary, NC, USA). Statistical significance was accepted at p 5 0.05.
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hyoid bones and covering as much as the entire surface of the tongue. The acoustic beam profile of one element (middle one) from the array transducer was measured with a calibrated hydrophone (HNP-0200, Onda, Sunnyvale, CA, USA) in a water tank (45 3 30 3 20 cm3), as illustrated in Figure 6. The transducer was fixed on a holder, and the hydrophone was attached to a motor platform to allow 2D mechanical scanning to obtain beam profiles of the element. A square plane with an area of 10 3 10 mm2 was scanned at a distance of 45 mm to obtain the 2-D map of the acoustic pressure. The 26-dB axial and lateral beam profiles as functions of distance are provided in Figure 7. The 2-D mapping of the acoustic pressure from one element at a depth of 45 mm is seen in Figure 8. The near field of the element is about 45 mm in depth. The lateral resolutions of the element from 45 to 80 mm in depth are between about 4.2 and 5.0 mm. Total exposed length from 16 elements at the air–mucosa interface is 4.5 3 16 5 72 mm, which is between 60 and 80 mm. Therefore, this wearable custom-designed 16-channel curvilinear array ultrasound transducer is sufficient for detecting tongue deformation. System specifications Figure 9(a) illustrates the layout of the printed circuit board (PCB) at the hardware front end, which includes all analogue electronics for the ultrasound device, such as the HV bipolar transmitter, channel switcher, amplifier, DC
RESULTS AND DISCUSSION Transducer specifications We reviewed 237 patients (144 female, 93 male) who had previously undergone a neck CT scan for indications other than OSA. The midline sagittal section of the CT scan was viewed and measured using OsiriX software. Figure 5 is a typical CT image of the midline sagittal section. The average distance between the mandible and hyoid bone was 32 6 8 mm, the average distance of the submandibular skin between the mandible and hyoid bone was 26 6 7 mm, the average maximum distance between skin and tongue surface was 67 6 9 mm and the length of the air–mucosa interface was between 60 and 80 mm. The miniature transducer (3.6 3 1.6 3 3.5 cm3) should be fitted into the small area of the submentum, avoiding the mandible and the
Fig. 5. Typical computed tomography image of the midline sagittal section for a patient with obstructive sleep apnea.
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Fig. 6. Schematic of the system for measuring the acoustic beam profiles and the 2-D acoustic pressure map.
Fig. 7. Axial and lateral profiles of one element on the array transducer.
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Fig. 8. Two-dimensional mapping of the acoustic pressure from one element (at 45-mm depth).
power module and transducer socket. The aforementioned four-layer PCB was designed to optimize the ground coupling and power distribution. Ferrite beads and capacitors were placed as close as possible to the power pins of the chips, and all signal sources were well shielded and impedance matched. Figure 9(b) illustrates a prototype of the portable ultrasound device, comprising a wearable
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ultrasound transducer, Altera FPGA development board, analogue front end, ADC board and AC power source. The size of the device (25 3 40 3 15 cm3) made it suitable for bedside use. Figure 9(c) compares the pulse-echo tests of the transducer (one channel) in our device with those of a commercial pulser-receiver (5072 PR, Olympus, Waltham, MA, USA). The bipolar transmitter provided a 3-MHz one-cycle pulse that drove a 50-U load. The two devices exhibited similar sensitivity to the echo signals, with the amplitude of the echo waveform from our transmitter being 0.7 dB higher than that of the commercial device. The system specifications are summarized in Figure 9(d). This system is an element-per-element beam system. Sixteen elements were fired individually and sequentially during measurement. The acoustic output pressure of the ultrasound transducer was measured using a calibrated hydrophone (NH0500, Precision Acoustic, Dorset, UK). The measured spatial peak temporal average intensity was 1.4 mW/cm, the spatial peak pulse average intensity was 52 mW/cm2 and the mechanical index was 0.005 when the transducer was excited by the transmitter at a peak-to-peak amplitude of 100 V. Ultrasound measurements Figure 10(a) is a schematic of an ultrasound measurement. The surface of the transducer was covered
Fig. 9. (a,b) Photographs of (a) the system front end and (b) the ultrasound device. (c) Results from pulse-echo tests of the proposed device and a commercial pulser-receiver. (d) Specifications of the ultrasound device.
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with gel and placed on the submental skin of the neck between the mandible and the hyoid bones. Figure 10(b) illustrates typical measured 16-channel A-line signals. The red arrows indicate the echo from the boundary between the tongue base and airway, and the distances between the submental skin and the air–mucosa interface were taken as the TBTs. Variation in transducer location may influence the reproducibility of measurement. Therefore, we used these two bones to locate the position of the transducer during measurement. To verify the performance of the system in measuring the dynamic deformations of the tongue base, two control patients wore the transducer, and their tongue base deformation was obtained as they performed the MM (in which the participant was asked to take a breath with the mouth closed and the nose pinched). The negative pressure generated by the MM caused a posterior and inferior displacement of the tongue toward the pharyngeal airway. Figure 11 graphs the measured tongue base deformations in the two patients as they began the MM and illustrates that variations in the TBT before and after the MM could clearly be distinguished using our novel ultrasound device. The tongue base displaced posteriorly and inferiorly because of the negative pressure generated by the MM, resulting in an increased TBT in both cases. The curves in Figure 11 correspond to the stronger echogenic signals in the B-mode images, an example of which is provided in Figure 1(b). Even though only 16 channels were used in this system, the air–mucosa interface of the tongue was clearly identified. Also, the portion of the tongue base that most commonly collapses during OSA was visualized with the ultrasound device. Submental ultrasound measurement of the tongue base with the MM is an alternative objective clinical method for the easy and tolerable evaluation of the
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severity of UA obstruction severity in OSA patients when they are awake. However, overnight measurement of tongue base collapse is more crucial in understanding the underlying mechanism in patients with OSA. Experiments with OSA patients Two OSA patients were enrolled for an overnight sleep study. Figure 12(a) is a photograph of the experimental environment in the Center for Sleep Disorders. Patients were asked to sleep overnight for at least 6 h. Both the ultrasound and PSG devices were placed at the bedside, and sensors for measuring physiologic signals were attached to the patient. The midline sagittal plane of the tongue base was scanned by the transducer placed on the submental skin of the neck. Also seen in Figure 12(a) is the custom-designed headband that held the transducer in place on the neck. The transducer was fastened around the head of the subject and secured using a Velcro band. To make the patients more comfortable, we placed two sponges on each side of the transducer. The size of the headband could be adjusted freely depending on head size. Neither subject exhibited signs of skin allergy or reported any sensation of heat after the ultrasound examination. Additionally, wearing this transducer only minimally disturbed their natural sleeping patterns. Therefore, we confirmed that this transducer was appropriate for overnight monitoring of tongue base deformation during natural sleep. The ultrasound device was integrated with PSG (Embla N7000, Medcare), and dedicated software was used to display PSG signals and ultrasound recordings simultaneously, as illustrated in Figure 12(b). The bottom traces are the measured TBTs and their corresponding positions as determined by the maximum depth of the tongue base over 16 channels. The blue line is the original
Fig. 10. (a) Schematic diagram of an ultrasound measurement. Stronger echogenic signals are reflected from the air–mucosa interface. (b) Typical measured 16-channel A-line signals. The red arrows indicate the echo from the boundary between the tongue base and airway.
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Fig. 11. (a,b) Results of measurement of tongue base deformation in two patients as they began the M€ uller maneuver. The circles (eupnea) and squares (M€uller maneuver) represent the actual 16 positions of the air–mucosa interface from the 16 A-line signals. TBT 5 tongue base thickness.
analogue signal from the FPGA, which represents the maximum TBT. Because the PSG device had only one analogue input channel, the TBT data stored in the FPGA were transformed into a clock signal (blue line in
Fig. 12 [bottom traces]), in which the number of cycles represents the TBT, which was then fed to the PSG device. After the software counted the number of cycles, the values and red line were plotted in Figure 12(b). TBTs
Fig. 12. (a) Photographs of the experimental environment. Ultrasound measurements could be performed while subjects were sleeping on their back or side. (b) Physiologic polysomnography signals and the measured tongue base thicknesses (TBTs) from the ultrasound device and their corresponding positions.
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were represented as a red line in the PSG software, and the numbers displayed along the TBT curve are channel numbers. The technicians identified snoring, hypopnea and apnea events as they occurred based on the PSG signals, and airway collapse was measured using the ultrasound device. For example, during rapid eye movement (REM) sleep, motor neurons throughout the body undergo hyperpolarization, which results in the need for greater stimulation to excite the dilator muscles of the UA. An increase in TBT occurs because of genioglossus muscle relaxation accompanied by the posterior motion of the tongue base into the UA. The PSG results revealed that the TBT increased a few seconds before apnea events, as illustrated in Figure 12(b). In addition to monitoring the dynamic motion of the tongue base during natural sleep, our novel ultrasound device also registered the location on the tongue base where
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the maximum TBT was recorded. For example, one patient had 141 hypopnea events and 65 apnea events during the 6-h measurement period. As every event occurred, the ultrasound device detected which portions of the tongue base had collapsed. In Figure 13 are bar charts of these results, in which the x-axis represents channel number, and the y-axis represents the number of recorded events. Events were sorted into two groups: normal breathing and snoring and hypopnea plus apnea. Using a goodness-of-fit test, we found a significant difference (p , 0.0001) between the recorded channel distribution of the maximum TBT during eupnea and that recorded during other respiratory events for both patients with OSA. Channel 16, the closest channel closest to the base of the tongue, recorded the most maximum TBTs when respiratory events occurred. This implied that during obstructive respiratory events, the posterior and
Fig. 13. Overnight measurements of events and their collapse positions for patients (a) and (b). Channel 16 was close to the underside of the tongue base, and channel 1 was close to the tongue tip. OSA 5 obstructive sleep apnea; TBT 5 tongue base thickness.
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inferior parts of the tongue descend and block the UA. On average, an increase in TBT of 6.1 mm was associated with obstructive respiratory events. Diagnostic UA evaluations continue to evolve. No method is yet available that adequately addresses the simultaneous structural and physiologic contributions to UA obstruction during natural sleep. In this study, we developed a wearable ultrasound device for the automatic detection and quantification of TBT. The ability to detect potential patterns and severity of UA obstructions would provide invaluable insight for sleep physicians who are evaluating patients with OSA. Combining this novel ultrasound device with PSG to monitor the retroglossal airways of OSA patients yields vital information on UA behavior during natural sleep, which is essential for planning, applying and measuring the effectiveness of tailormade treatments. CONCLUSIONS Awearable 3-MHz 16-channel custom-designed ultrasound transducer was designed to monitor tongue base deformation during normal sleep. The electronic circuitry required to implement the device was described. Ultrasound data were integrated with a commercial PSG system to observe physiologic signals and tongue base data simultaneously. Most patients who tested the device did not feel uncomfortable and were not disturbed by the experimental measurements being performed while they slept. This novel approach for monitoring the anatomic and functional changes of the tongue under real sleep conditions is particularly useful for patients with OSA. The recorded TBT increased and remained elevated for the few seconds before the onset of hypopnea and apnea events. Because the 16-channel curved array transducer was long enough to measure the thickness of the full tongue length, the collapsed portions of the tongue were detected in real time. Tongue collapse was discovered to occur close to the tongue base during hypopnea and apnea events in both OSA patients. TBT increased by an average of 6.1 mm during these events. Future studies could use this ultrasound device to identify the portions of the UA that collapse during OSA events, to help clinical physicians determine tailor-made treatment strategies and to develop and test hypotheses of the mechanisms underlying OSA. Acknowledgments—This work was supported by the Ministry of Science and Technology of Taiwan under Grant MOST 102-2628B-006-016-MY3 and, in part, by Cardinal Tien Hospital under Grant CTH-101-1-2 B04.
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REFERENCES American Academy of Sleep Medicine (AASM) Task Force. Sleeprelated breathing disorders in adults: Recommendations for syndrome definition and measurement techniques in clinical research. The Report of an American Academy of Sleep Medicine Task Force. Sleep 1999;22:667–689. Arens R, Marcus CL. Pathophysiology of upper airway obstruction: A developmental perspective. Sleep 2004;27:997–1019. Bohlman ME, Haponik EF, Smith PL, Allen RP, Bleecker ER, Goldman SM. CT demonstration of pharyngeal narrowing in adult obstructive sleep apnea. AJR Am J Roentgenol 1983;140:543–548. Chen JW, Chang CH, Wang SJ, Chang YT, Huang CC. Submental ultrasound measurement of dynamic tongue base thickness in patients with obstructive sleep apnea. Ultrasound Med Biol 2014;40: 2590–2598. Ciscar MA, Juan G, Martinez V, Ramon M, Lloret T, Minguez J, Armengot M, Marin J, Basterra J. Magnetic resonance imaging of the pharynx in OSA patients and healthy subjects. Eur Respir J 2001;17:79–86. Davidson TM. The great leap forward: The anatomic basis for the acquisition of speech and obstructive sleep apnea. Sleep Med 2003;4: 185–194. Horner RL, Mohiaddin RH, Lowell DG, Shea SA, Burman ED, Longmore DB, Guz A. Sites and sizes of fat deposits around the pharynx in obese patients with obstructive sleep apnoea and weight matched controls. Eur Respir J 1989;2:613–622. Huang CC, Lee PY, Chen PY, Liu TY. Design and implementation of a smartphone-based portable ultrasound pulsed-wave Doppler device for blood flow measurement. IEEE Trans Ultrason Ferroelectr Freq Control 2012;59:182–188. Ko MT, Su CY. Computer-assisted quantitative evaluation of obstructive sleep apnea using digitalized endoscopic imaging with Muller maneuver. Laryngoscope 2008;118:909–914. Lahav Y, Rosenzweig E, Heyman Z, Doljansky J, Green A, Dagan Y. Tongue base ultrasound: A diagnostic tool for predicting obstructive sleep apnea. Ann Otol Rhinol Laryngol 2009;118:179–184. Liu KH, Chu WC, To KW, Ko FW, Tong MW, Chan JW, Hui DS. Sonographic measurement of lateral parapharyngeal wall thickness in patients with obstructive sleep apnea. Sleep 2007;30: 1503–1508. Partinen M, Guilleminault C, Quera-Salva MA, Jamieson A. Obstructive sleep apnea and cephalometric roentgenograms: The role of anatomic upper airway abnormalities in the definition of abnormal breathing during sleep. Chest 1988;93:1199–1205. Rechtschaffen A, Kales A. A manual of standardized terminology, techniques and scoring system for sleep stages of human subjects. Washington, DC: U.S. Government Printing Office; 1968. Remijn L, Weijers G, Nijhuis-van der Sanden MW, Groen BE, de Korte CL. Ultrasound imaging for analyzing lateral tongue movements during mastication in adults with cerebral palsy compared with adults without oral motor disabilities. Ultrasound Med Biol 2015;41:1784–1793. Stuck BA, Maurer JT. Airway evaluation in obstructive sleep apnea. Sleep Med Rev 2008;12:411–436. Teran-Santos J, Jimenez-Gomez A, Cordero-Guevara J. The association between sleep apnea and the risk of traffic accidents. Cooperative Group Burgos-Santander. N Engl J Med 1999;340:847–851. Terris DJ, Hanasono MM, Liu YC. Reliability of the Muller maneuver and its association with sleep-disordered breathing. Laryngoscope 2000;110:1819–1823. Yucel A, Unlu M, Haktanir A, Acar M, Fidan F. Evaluation of the upper airway cross-sectional area changes in different degrees of severity of obstructive sleep apnea syndrome: Cephalometric and dynamic CT study. AJNR Am J Neuroradiol 2005;26:2624–2629.
http://dx.doi.org/10.1016/j.ultrasmedbio.2017.04.004
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Original Contribution IMPLEMENTATION OF A WEARABLE ULTRASOUND DEVICE FOR THE OVERNIGHT MONITORING OF TONGUE BASE DEFORMATION DURING OBSTRUCTIVE SLEEP APNEA EVENTS CHI-KAI WENG,* JENG-WEN CHEN,yz PO-YANG LEE,* and CHIH-CHUNG HUANG* * Department of Biomedical Engineering, National Cheng Kung University, Tainan, Taiwan; y Department of Otolaryngology-Head and Neck Surgery, Cardinal Tien Hospital, New Taipei City, Taiwan; and z School of Medicine, Fu-Jen Catholic University, New Taipei City, Taiwan (Received 12 October 2016; revised 17 March 2017; in final form 5 April 2017)
Abstract—Obstructive sleep apnea (OSA) is a breathing disorder characterized by the repeated collapse of the pharyngeal airway during sleep. Previous studies have reported that tongue base deformation may be a major contributing factor. However, overnight monitoring of tongue motion in patients with OSA has previously been impracticable. We developed a wearable ultrasound device for prolonged recording during natural sleep of the changes in tongue base thickness (TBT) in patients with OSA. The maximum TBT was fed into a polysomnography system so that physiologic signals and TBT data were simultaneously monitored. Subject trials revealed that TBT increased significantly during snoring, hypopnea and apnea events during natural sleep in patients with OSA. Moreover, the data revealed that the location of the maximum TBT during normal breathing was significantly different compared with the location during obstructive respiratory events, which implies a posterior or inferior displacement of the tongue base during sleep apnea. (E-mail: [email protected]) Ó 2017 World Federation for Ultrasound in Medicine & Biology. Key Words: Obstructive sleep apnea, Wearable device, Medical ultrasound, Tongue base thickness.
Overnight polysomnography (PSG) is currently the gold standard for diagnosing OSA. During PSG, an apnea event is defined as a complete cessation of airflow or a decrease of more than 90% in the peak thermal sensor signal for at least 10 s. A hypopnea event is defined as a decrease of more than 50% in the nasal pressure signal for at least 10 s and simultaneous arousal or oxyhemoglobin desaturation of more than 3%. The apnea–hypopnea index (AHI) is calculated using the total number of apnea and hypopnea events per hour of sleep. AHI is generally accepted as a reference that categorizes the severity of the OSA. AHI scores ,5 are normal. Mild, moderate and severe OSA are defined by the following scores: #AHI ,15, 15 #AHI ,30 and AHI $30, respectively. Although PSG measures a patient’s physiologic signals, it cannot pinpoint the sites of upper airway (UA) occlusion. Thus, additional methods for evaluation of UA anatomy and function are necessary. Several medical imaging methods have been applied to assess UA anatomy of patients with OSA, including magnetic resonance imaging (MRI), computed tomography (CT), endoscopy and ultrasonography, each of which has specific advantages and limitations (Stuck and Maurer 2008).
INTRODUCTION Sleep apnea is a sleep-related breathing disorder comprising central sleep apnea and obstructive sleep apnea (OSA). OSA involves recurring episodes of partial or complete obstruction of the pharyngeal airway during sleep and may cause intermittent hypoxemia, frequent arousal and fragmented sleep (American Academy of Sleep Medicine [AASM] Task Force 1999). It is associated with risk for hypertension, heart failure, myocardial infarction and stroke. A strong correlation between sleep apnea and traffic accident risk has also been proven (Teran-Santos et al. 1999). Prior studies have indicated that anatomic factors such as craniofacial anomalies, obesity and adenotonsillar hypertrophy contribute to the occurrence of OSA (Arens and Marcus 2004).
Address correspondence to: Chih-Chung Huang, Department of Biomedical Engineering, National Cheng Kung University, Tainan, Taiwan, No 1, University Road, Tainan City 701, Taiwan. E-mail: [email protected] Conflict of Interest Disclosure: The authors declare that they have no conflicts of interest. 1639
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Magnetic resonance imaging and CT scanning have been used to detect the narrowing of the UA in patients while they are awake (AASM Task Force 1999). CT scanning offers favorable contrast between soft tissue and bony structures. Several studies have suggested that the UA is smaller (especially in the retropalatal region) in OSA patients compared with healthy control patients (Bohlman et al. 1983). Specifically, the dimensions of the soft palate and tongue, as well as the cross-sectional areas, are considered important indicators that OSA may be diagnosed. Yucel et al. (2005) investigated the cross-sectional areas of the UA using CT scanning. They reported that patients with severe OSA had narrower cross-sectional areas and a thickened soft palate at the velopharyngeal level. However, CT scanning is not suitable for monitoring dynamic UA changes in patients with OSA, especially when they are asleep. Cine MRI has been used to visualize the dynamics of the UA in patients with OSA and identify the severity of UA obstruction. Static and dynamic MRI methods have improved understanding of the biomechanics and pathophysiology underlying OSA (Ciscar et al. 2001). Nonetheless, cine MRI is not universally available and is unsuitable for prolonged observations. Also, many people are unable to fall asleep during MRI scanning because of the noise made by the device. Most patients are given a sedative before an MRI scan, and the induced sleep that results may not accurately reflect the true respiratory condition during natural sleep. Cephalometric analysis is used to investigate skeletal craniofacial morphology (Partinen et al. 1988), and can be used to identify any craniofacial characteristics associated with OSA. However, real-time evaluation is not possible, and it is challenging to distinguish between soft tissues. Video endoscopy assesses the dynamics of the UA for precise pre-operative analysis (Ko and Su 2008). Obstruction of the UA can be observed and recorded during the M€uller maneuver (MM) using endoscopy. The MM is a simple examination that has been widely applied to simulate the pathophysiologic condition of OSA during wakefulness. However, the sites that are obstructed while the MM is performed are not the real sites obstructed during normal sleep (Terris et al. 2000). Ultrasonography has the advantages of being noninvasive, radiation free, portable and inexpensive, which have led to its use in OSA diagnosis. Liu et al. (2007) measured the lateral parapharyngeal wall (LPW) thickness using ultrasound to assess the soft tissue structure of OSA patients. The transducer was placed vertically on the side of the neck, and LPW thickness was measured from the internal carotid artery to the lateral pharyngeal wall. The results indicated that LPW thickness was independently associated with OSA. However, the area between the oropharynx and laryngopharynx is the most
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common anatomic location of airway collapse (Horner et al. 1989). OSA causes posterior migration of the tongue base on the laryngeal aperture and marked narrowing of the pharyngeal airway (Davidson 2003). Many studies have reported that deformation of the tongue is a major contributing factor in OSA (Chen et al. 2014; Lahav et al. 2009; Remijn et al. 2015). These findings indicate that measuring the deformation of the tongue base is also a reliable method for assessing airway collapse. In our previous study, we reported tongue base thickness (TBT) was an effective index for differentiating between people with and without OSA (Chen et al. 2014). Forty patients (20 patients with OSA and 20 control patients with an AHI ,5) were recruited for that study. Compared with the control group, the OSA patients had a significantly greater TBT during eupneic breathing and the MM and a significant difference between their TBT when the MM was use and that when it was not used. Most studies have measured the deformation of the tongue base in OSA patients only at the moment they awaken or by asking patients to perform the MM to simulate UA obstruction, neither of which is a realistic condition during an OSA patient’s natural sleep. Unfortunately, MRI and CT scanning are not suitable for use across the patient’s total daily sleep duration, and PSG cannot provide UA anatomic information. Overnight measurements of tongue base deformation during sleep have not previously been performed on patients with OSA or otherwise, but ultrasound imaging is an excellent option for achieving this objective. The purpose of this study was to develop a wearable ultrasound device for overnight monitoring during sleep of the TBT of patients with OSA. Because it is impossible for an operator to hold the ultrasound transducer for an overnight measurement, we designed a wearable transducer that did not need to be held. Hardware based on a field programmable gate array (FPGA) core unit was developed to constantly measure the tongue base deformation. Data measured using the ultrasound device were integrated with those from PSG to assess patients with OSA. Feasibility tests were performed in both healthy volunteers and patients with OSA, and the information obtained was used to generate hypotheses on the underlying mechanisms of OSA and tailor-made multimodality OSA management techniques that can be tested in subsequent studies. METHODS Custom-designed ultrasound transducer Figure 1(a) illustrates the position of the transducer relative to the neck, which allowed the submental midline sagittal section of the surrounding UA and tongue base to
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be seen in the ultrasound images. Figure 1(b) is a typical ultrasound image of the tongue base obtained using a commercial ultrasound system (Terason T3000, Teratech, Burlington, MA, USA) with a 2- to 5-MHz curved array transducer (5C2A, Teratech). Because there is a large mismatch in the acoustic impedance at the boundary between the tongue base and airway, stronger echogenic signals are easily observed in the ultrasound image, which means that the tongue base deformation can be monitored using gray-scale real-time ultrasound imaging during natural sleep. However, a conventional transducer could not be used for overnight measurements because it was impossible for an operator to hold the transducer in the same position over an extended period, and the subject would likely have felt uncomfortable. Therefore, we designed a wearable custom-designed 16-channel curvilinear array ultrasound transducer (Broadsound, Hsinchu, Taiwan), illustrated in Figure 2(a,b). Because the boundary between the tongue base and airway is a smooth curve, a 16-channel array was sufficient for characterizing the deformation of the tongue base. The miniaturized transducer (3.6 3 1.6 3 3.5 cm3) allowed the OSA patient to wear it overnight for continuous measurement. The center frequency of the transducer was 3 MHz, which allowed the acoustic waves propagated 8 cm in depth to reach the air–mucosa interface of tongue. Figure 2(c) illustrates the pulse-echo response of one element, and the transducer specifications are listed in Figure 2(d). The transducer scanned the midline sagittal plane of the submental skin, and changes in the relative positions and morphology of the tongue base along the sagittal axis of the UA were recorded. System implementation Figure 3 is a block diagram of the ultrasound device designed. The system comprised a custom transducer, system hardware, computer and PSG device. The main
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circuits were a transmit/receive switch, high-voltage (HV) bipolar ultrasound transmitter, pre-amplifier, variable-gain amplifier (VGA), analogue-to-digital converter (ADC), DC-to-DC power module, universal asynchronous receiver/transmitter (UART) interface, generalpurpose input/output (GPIO) interface and FPGA unit. The FPGA unit (Altera FPGA development board, DE2-115, Terasic Technologies, Hsinchu, Taiwan) was the core of the device, and included a pulse repetition frequency (PRF) timing controller and signal processor. The timing controller provided the control signal to the HV bipolar ultrasound transmitter, and this transmitter generated the 3-MHz bipolar pulse that drove the transducer. Figure 4(a) illustrates the timing sequences of the timing controller. A 50-MHz crystal oscillator was used to generate a stable clock on the FPGA development board. A 6-MHz rectangular clock (trace A) and a PRF pulse (trace B) were obtained by dividing the 50-MHz clock by a 12-bit counter using Verilog. The on time of the PRF pulse was set to 1 ms. Two logic control inputs (traces C and D) were needed for the bipolar transmitter, which was constructed using pairs of high-speed HV metal-oxide-semiconductor field-effect transistors (MOSFETs) (HV7350, Supertex, San Jose, CA, USA). The transmitter excited the ultrasound transducer through an expander (SMBD7000, Infineon Technologies, Munich, Germany) to reduce the noise signal from the transmitter to the transducer or from the electronic components in the receiver. This noise inhibition avoided the generation of undesirable jitters in the ultrasound devices (Huang et al. 2012). The output of the bipolar transmitter drove a 50-U load, and the maximum output peak-to-peak voltage was 100 V. The 26-dB bandwidth of the bipolar signal was approximately 40%. In this system, a signal with a PRF of 160 Hz with one cycle was fed to the bipolar transmitter. To ensure that a high-performance bipolar-pulse waveform was produced (trace E), the supply voltage bypass capacitors and MOSFET coupling capacitors had
Fig. 1. (a) Schematic of the relative positions of the ultrasound transducer and neck. The transducer was placed on the submental midline of the neck. (b) Typical B-mode ultrasound image of the tongue base.
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Fig. 2. (a,b) Top (a) and side (b) views of the wearable 16-channel ultrasound array transducer. (c) Pulse-echo response of one channel. (d) Specifications of the transducer.
to be as close as possible to the pins of the chip. This arrangement reduced noise and prevented resonance by the inclusion of a ferrite bead in the lead from the power supply to the capacitors. Because the transducer had 16 channels, switching was used to excite each channel
sequentially. A linear sequence switch (MAX14803, Maxim Integrated, San Jose, CA, USA) was controlled by the FPGA unit in a 16-bit serial–shift register arrangement. The switching sequence was synchronized with the PRF pulse, indicated by traces F and B in Figure 4(a).
Fig. 3. Block diagram of the designed ultrasound device. FPGA 5 field programmable gate array; GPIO 5 general-purpose input/output interface; PSG 5 polysomnography system; T/R 5 transmitter/receiver; UART 5 universal asynchronous receiver/transmitter.
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Fig. 4. (a) Timing controller sequences of the field programmable gate array (FPGA). (b) Flowchart of the signal processing procedure in the FPGA. CORDIC 5 coordinate rotation digital computer; GPIO 5 general-purpose input/ output interface; PSG 5 polysomnography system; TBT 5 tongue base thickness; UART 5 universal asynchronous receiver/transmitter.
The echo signals from the tissue were received via a limiter (SMBD7000, Infineon Technologies) and then fed to a preamplifier (Gali-741, Mini-Circuits, Brooklyn, NY, USA) and a VGA (MAX2077, Maxim Integrated). A gain of 45 dB was used in this study. A limiter was placed in front of the pre-amplifier to ensure that the input amplifier was not affected by the large excitation signal. The echo signals were then digitized by an ADC board (AD/DA data conversion card, Terasic Technologies) with 14-bit resolution and a 50-MHz sampling rate. The system included three low-drop voltage regulators (LD1117, STMicroelectronics, Geneva, Switzerland) that provided 3- and 5-V supplies to all components. Two miniature and ultralow-ripple high-voltage DC-to-DC converters (PCS01-05 N050 and PCS01-05 P050, 3 Gold Electronics, Hsinchu, Taiwan) were used to supply the bipolar transmitter’s high voltage (100 Vpp). Figure 4(b) is a flowchart depicting how tongue base deformation is measured with the FPGA unit. After the echo signals were digitized and fed into the FPGA, a buffer was created to capture the data. Because the air–mucosa interface exhibits a hyper-echoic raphe in a B-mode image, a clear echo signal was obtained in the A-line signal from each scan line. The position of this stronger echo represented the TBT measured by each channel, and was determined with a peak-detection method. A multiplier and adder in the FPGA then determined the depth of the air–mucosa interface, and a register stored the maximum positions from all 16 channels. Because the wearable transducer was a curved array, it was necessary to transform polar coordinates into Cartesian coordinates, which was achieved using a multiplier and look-up table to implement the coordinate rotation digital computer (CORDIC) algorithm in the FPGA. The maximum depths from the 16 channels were placed in a TBT register to
represent the boundary of the air–mucosa interface. The measured data in the FPGA were then transmitted to the computer and PSG device via the UART and GPIO interfaces, respectively. Because the PSG device had only a single analogue input channel, the TBT data stored in the FPGA were transformed into a clock signal (in which the number of cycles represented the TBT) that was then fed to the PSG device. This design allowed all the TBT and other PSG data to be recorded synchronously during the measurements. The system could detect TBTs within the range 44–80 mm. The TBT data were recorded at a sampling rate of 1 Hz because of the PSG device specifications. Today, FPGA is becoming powerful for many kinds of data transmission interfaces and signal processing. In addition to the signal processing unit, an ultrasound system is needed to integrate some I/O interfaces, such as LVDS, USB and SPI. FPGA provides the solution for these two purposes in the present system. Patients The ethics committee of Cardinal Tien Hospital approved this study, and written informed consent was obtained from all participants. Two healthy volunteers without OSA were enrolled to verify the feasibility of using the ultrasound system used in this study. OSA patients were recruited from the Center for Sleep Disorders at the Cardinal Tien Hospital, Taiwan. Exclusion criteria included refusal to participate, age ,20 y and a history of conditions: syndromal craniofacial abnormalities (e.g., Down syndrome); oral cavity, oropharyngeal or laryngeal masses; craniofacial surgery; burns, trauma or radiotherapy involving the head and neck region; neurologic disorders other than OSA; active inflammation in the head and neck region; or cervical rigidity that limited neck flexion and head extension.
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Polysomnography Participants with OSA underwent overnight ultrasound scanning with a standard attended PSG device (Embla N7000, Medcare, Reykjavik, Iceland) in the Center for Sleep Disorders. Ultrasound and PSG examinations took place over approximately 6 h. The PSG included continuous recording of the electroencephalogram, left and right electro-oculogram, chin and anterior tibia electromyogram, electrocardiogram, scoring of breathing variables based on a flow trace from a nasal cannula and thermistor, thoraco-abdominal motion and sleep position using chest and abdominal bands and a position monitor and oxyhemoglobin saturation with a finger pulse oximeter. The PSG data were scored by a registered sleep technician and reviewed by certified sleep physicians according to the criteria of Rechtschaffen and Kales (1968) and the updated scoring guidelines of the American Academy of Sleep Medicine. The sleep technicians and physicians were blinded to the ultrasound results. OSA was defined as the complete cessation of airflow or a decrease of $90% in the peak thermal sensor signal for at least 10 s, whereas a hypopnea event was defined as a decrease $50% in the nasal pressure signal for at least 10 s and simultaneous arousal or oxyhemoglobin desaturation of $3% (AASM Task Force 1999). Statistical analysis We compared the distribution of the recorded channels of the maximum TBT between normal breathing and other obstructive respiratory events, namely, snoring, hypopnea and apnea, using a goodness-of-fit test for each patient with OSA. Data analysis was conducted using Statistical Analysis System software, Version 9.3 (SAS Institute, Cary, NC, USA). Statistical significance was accepted at p 5 0.05.
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hyoid bones and covering as much as the entire surface of the tongue. The acoustic beam profile of one element (middle one) from the array transducer was measured with a calibrated hydrophone (HNP-0200, Onda, Sunnyvale, CA, USA) in a water tank (45 3 30 3 20 cm3), as illustrated in Figure 6. The transducer was fixed on a holder, and the hydrophone was attached to a motor platform to allow 2D mechanical scanning to obtain beam profiles of the element. A square plane with an area of 10 3 10 mm2 was scanned at a distance of 45 mm to obtain the 2-D map of the acoustic pressure. The 26-dB axial and lateral beam profiles as functions of distance are provided in Figure 7. The 2-D mapping of the acoustic pressure from one element at a depth of 45 mm is seen in Figure 8. The near field of the element is about 45 mm in depth. The lateral resolutions of the element from 45 to 80 mm in depth are between about 4.2 and 5.0 mm. Total exposed length from 16 elements at the air–mucosa interface is 4.5 3 16 5 72 mm, which is between 60 and 80 mm. Therefore, this wearable custom-designed 16-channel curvilinear array ultrasound transducer is sufficient for detecting tongue deformation. System specifications Figure 9(a) illustrates the layout of the printed circuit board (PCB) at the hardware front end, which includes all analogue electronics for the ultrasound device, such as the HV bipolar transmitter, channel switcher, amplifier, DC
RESULTS AND DISCUSSION Transducer specifications We reviewed 237 patients (144 female, 93 male) who had previously undergone a neck CT scan for indications other than OSA. The midline sagittal section of the CT scan was viewed and measured using OsiriX software. Figure 5 is a typical CT image of the midline sagittal section. The average distance between the mandible and hyoid bone was 32 6 8 mm, the average distance of the submandibular skin between the mandible and hyoid bone was 26 6 7 mm, the average maximum distance between skin and tongue surface was 67 6 9 mm and the length of the air–mucosa interface was between 60 and 80 mm. The miniature transducer (3.6 3 1.6 3 3.5 cm3) should be fitted into the small area of the submentum, avoiding the mandible and the
Fig. 5. Typical computed tomography image of the midline sagittal section for a patient with obstructive sleep apnea.
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Fig. 6. Schematic of the system for measuring the acoustic beam profiles and the 2-D acoustic pressure map.
Fig. 7. Axial and lateral profiles of one element on the array transducer.
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Fig. 8. Two-dimensional mapping of the acoustic pressure from one element (at 45-mm depth).
power module and transducer socket. The aforementioned four-layer PCB was designed to optimize the ground coupling and power distribution. Ferrite beads and capacitors were placed as close as possible to the power pins of the chips, and all signal sources were well shielded and impedance matched. Figure 9(b) illustrates a prototype of the portable ultrasound device, comprising a wearable
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ultrasound transducer, Altera FPGA development board, analogue front end, ADC board and AC power source. The size of the device (25 3 40 3 15 cm3) made it suitable for bedside use. Figure 9(c) compares the pulse-echo tests of the transducer (one channel) in our device with those of a commercial pulser-receiver (5072 PR, Olympus, Waltham, MA, USA). The bipolar transmitter provided a 3-MHz one-cycle pulse that drove a 50-U load. The two devices exhibited similar sensitivity to the echo signals, with the amplitude of the echo waveform from our transmitter being 0.7 dB higher than that of the commercial device. The system specifications are summarized in Figure 9(d). This system is an element-per-element beam system. Sixteen elements were fired individually and sequentially during measurement. The acoustic output pressure of the ultrasound transducer was measured using a calibrated hydrophone (NH0500, Precision Acoustic, Dorset, UK). The measured spatial peak temporal average intensity was 1.4 mW/cm, the spatial peak pulse average intensity was 52 mW/cm2 and the mechanical index was 0.005 when the transducer was excited by the transmitter at a peak-to-peak amplitude of 100 V. Ultrasound measurements Figure 10(a) is a schematic of an ultrasound measurement. The surface of the transducer was covered
Fig. 9. (a,b) Photographs of (a) the system front end and (b) the ultrasound device. (c) Results from pulse-echo tests of the proposed device and a commercial pulser-receiver. (d) Specifications of the ultrasound device.
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with gel and placed on the submental skin of the neck between the mandible and the hyoid bones. Figure 10(b) illustrates typical measured 16-channel A-line signals. The red arrows indicate the echo from the boundary between the tongue base and airway, and the distances between the submental skin and the air–mucosa interface were taken as the TBTs. Variation in transducer location may influence the reproducibility of measurement. Therefore, we used these two bones to locate the position of the transducer during measurement. To verify the performance of the system in measuring the dynamic deformations of the tongue base, two control patients wore the transducer, and their tongue base deformation was obtained as they performed the MM (in which the participant was asked to take a breath with the mouth closed and the nose pinched). The negative pressure generated by the MM caused a posterior and inferior displacement of the tongue toward the pharyngeal airway. Figure 11 graphs the measured tongue base deformations in the two patients as they began the MM and illustrates that variations in the TBT before and after the MM could clearly be distinguished using our novel ultrasound device. The tongue base displaced posteriorly and inferiorly because of the negative pressure generated by the MM, resulting in an increased TBT in both cases. The curves in Figure 11 correspond to the stronger echogenic signals in the B-mode images, an example of which is provided in Figure 1(b). Even though only 16 channels were used in this system, the air–mucosa interface of the tongue was clearly identified. Also, the portion of the tongue base that most commonly collapses during OSA was visualized with the ultrasound device. Submental ultrasound measurement of the tongue base with the MM is an alternative objective clinical method for the easy and tolerable evaluation of the
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severity of UA obstruction severity in OSA patients when they are awake. However, overnight measurement of tongue base collapse is more crucial in understanding the underlying mechanism in patients with OSA. Experiments with OSA patients Two OSA patients were enrolled for an overnight sleep study. Figure 12(a) is a photograph of the experimental environment in the Center for Sleep Disorders. Patients were asked to sleep overnight for at least 6 h. Both the ultrasound and PSG devices were placed at the bedside, and sensors for measuring physiologic signals were attached to the patient. The midline sagittal plane of the tongue base was scanned by the transducer placed on the submental skin of the neck. Also seen in Figure 12(a) is the custom-designed headband that held the transducer in place on the neck. The transducer was fastened around the head of the subject and secured using a Velcro band. To make the patients more comfortable, we placed two sponges on each side of the transducer. The size of the headband could be adjusted freely depending on head size. Neither subject exhibited signs of skin allergy or reported any sensation of heat after the ultrasound examination. Additionally, wearing this transducer only minimally disturbed their natural sleeping patterns. Therefore, we confirmed that this transducer was appropriate for overnight monitoring of tongue base deformation during natural sleep. The ultrasound device was integrated with PSG (Embla N7000, Medcare), and dedicated software was used to display PSG signals and ultrasound recordings simultaneously, as illustrated in Figure 12(b). The bottom traces are the measured TBTs and their corresponding positions as determined by the maximum depth of the tongue base over 16 channels. The blue line is the original
Fig. 10. (a) Schematic diagram of an ultrasound measurement. Stronger echogenic signals are reflected from the air–mucosa interface. (b) Typical measured 16-channel A-line signals. The red arrows indicate the echo from the boundary between the tongue base and airway.
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Fig. 11. (a,b) Results of measurement of tongue base deformation in two patients as they began the M€ uller maneuver. The circles (eupnea) and squares (M€uller maneuver) represent the actual 16 positions of the air–mucosa interface from the 16 A-line signals. TBT 5 tongue base thickness.
analogue signal from the FPGA, which represents the maximum TBT. Because the PSG device had only one analogue input channel, the TBT data stored in the FPGA were transformed into a clock signal (blue line in
Fig. 12 [bottom traces]), in which the number of cycles represents the TBT, which was then fed to the PSG device. After the software counted the number of cycles, the values and red line were plotted in Figure 12(b). TBTs
Fig. 12. (a) Photographs of the experimental environment. Ultrasound measurements could be performed while subjects were sleeping on their back or side. (b) Physiologic polysomnography signals and the measured tongue base thicknesses (TBTs) from the ultrasound device and their corresponding positions.
Wearable US device for obstructive sleep apnea d C.-K. WENG et al.
were represented as a red line in the PSG software, and the numbers displayed along the TBT curve are channel numbers. The technicians identified snoring, hypopnea and apnea events as they occurred based on the PSG signals, and airway collapse was measured using the ultrasound device. For example, during rapid eye movement (REM) sleep, motor neurons throughout the body undergo hyperpolarization, which results in the need for greater stimulation to excite the dilator muscles of the UA. An increase in TBT occurs because of genioglossus muscle relaxation accompanied by the posterior motion of the tongue base into the UA. The PSG results revealed that the TBT increased a few seconds before apnea events, as illustrated in Figure 12(b). In addition to monitoring the dynamic motion of the tongue base during natural sleep, our novel ultrasound device also registered the location on the tongue base where
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the maximum TBT was recorded. For example, one patient had 141 hypopnea events and 65 apnea events during the 6-h measurement period. As every event occurred, the ultrasound device detected which portions of the tongue base had collapsed. In Figure 13 are bar charts of these results, in which the x-axis represents channel number, and the y-axis represents the number of recorded events. Events were sorted into two groups: normal breathing and snoring and hypopnea plus apnea. Using a goodness-of-fit test, we found a significant difference (p , 0.0001) between the recorded channel distribution of the maximum TBT during eupnea and that recorded during other respiratory events for both patients with OSA. Channel 16, the closest channel closest to the base of the tongue, recorded the most maximum TBTs when respiratory events occurred. This implied that during obstructive respiratory events, the posterior and
Fig. 13. Overnight measurements of events and their collapse positions for patients (a) and (b). Channel 16 was close to the underside of the tongue base, and channel 1 was close to the tongue tip. OSA 5 obstructive sleep apnea; TBT 5 tongue base thickness.
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inferior parts of the tongue descend and block the UA. On average, an increase in TBT of 6.1 mm was associated with obstructive respiratory events. Diagnostic UA evaluations continue to evolve. No method is yet available that adequately addresses the simultaneous structural and physiologic contributions to UA obstruction during natural sleep. In this study, we developed a wearable ultrasound device for the automatic detection and quantification of TBT. The ability to detect potential patterns and severity of UA obstructions would provide invaluable insight for sleep physicians who are evaluating patients with OSA. Combining this novel ultrasound device with PSG to monitor the retroglossal airways of OSA patients yields vital information on UA behavior during natural sleep, which is essential for planning, applying and measuring the effectiveness of tailormade treatments. CONCLUSIONS Awearable 3-MHz 16-channel custom-designed ultrasound transducer was designed to monitor tongue base deformation during normal sleep. The electronic circuitry required to implement the device was described. Ultrasound data were integrated with a commercial PSG system to observe physiologic signals and tongue base data simultaneously. Most patients who tested the device did not feel uncomfortable and were not disturbed by the experimental measurements being performed while they slept. This novel approach for monitoring the anatomic and functional changes of the tongue under real sleep conditions is particularly useful for patients with OSA. The recorded TBT increased and remained elevated for the few seconds before the onset of hypopnea and apnea events. Because the 16-channel curved array transducer was long enough to measure the thickness of the full tongue length, the collapsed portions of the tongue were detected in real time. Tongue collapse was discovered to occur close to the tongue base during hypopnea and apnea events in both OSA patients. TBT increased by an average of 6.1 mm during these events. Future studies could use this ultrasound device to identify the portions of the UA that collapse during OSA events, to help clinical physicians determine tailor-made treatment strategies and to develop and test hypotheses of the mechanisms underlying OSA. Acknowledgments—This work was supported by the Ministry of Science and Technology of Taiwan under Grant MOST 102-2628B-006-016-MY3 and, in part, by Cardinal Tien Hospital under Grant CTH-101-1-2 B04.
Volume 43, Number 8, 2017
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