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Characteristics of pulse-waveform and laser-Doppler indices in frozen-shoulder patients
Biomedical Signal Processing and Control 56 (2020) 101718
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Biomedical Signal Processing and Control journal homepage: www.elsevier.com/locate/bspc
Characteristics of pulse-waveform and laser-Doppler indices in frozen-shoulder patients Feng-Cheng Lin a , Hsin Hsiu b,c,∗ , Han-Si Chiu b , Chao-Tsung Chen d,e,f , Chung-Hua Hsu e,g a
Department of Rehabilitation, Taipei City Hospital RenAi Branch, Taipei, Taiwan Graduate Institute of Biomedical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan Biomedical Engineering Research Center, National Defense Medical Center, Taipei, Taiwan d Department of Traditional Chinese Medicine, Taipei City Hospital RenAi Branch, Taipei, Taiwan e Institute of Traditional Medicine, National Yang-Ming University, Taipei, Taiwan f General Education Center, University of Taipei, Taipei, Taiwan g Branch of Linsen and Chinese Medicine, Taipei City Hospital, Taipei, Taiwan b c
a r t i c l e
i n f o
Article history: Received 21 August 2019 Received in revised form 1 October 2019 Accepted 10 October 2019 Keywords: Frozen shoulder Blood flow Laser doppler Pulse Photoplethysmography Spectral analysis
a b s t r a c t This study tested the hypothesis that measuring and analyzing the arterial pulse waveform and the skinsurface blood flow makes it possible to noninvasively discriminate the different microcirculatory states of patients with frozen shoulder (FS). Radial blood pressure waveform (BPW), finger photoplethysmography (PPG), and skin-surface laser Doppler flowmetry (LDF) signals were measured noninvasively on the back of the hand in 25 FS and 18 control subjects. Beat-to-beat, spectral, and variability analyses were applied to the 3-minute-long recorded signals. Significant intergroup differences were found in the BPW, PPG, and LDF indices. For example, the amplitude indices of the predominant (lower-frequency) BPW components were significantly larger in FS subjects than controls. Some of the PPG phase-angle variability indices were significantly larger on the diseased side than on the contralateral side. The present results illustrate that LDF indices can be used to evaluate the blood-flow-perfusion responses and their regulation, and that pulse-waveform indices can help to evaluate changes in the arterial pulse-wave transmission condition and its regulation in FS. Moreover, the trends in the changes in certain spectral pulse-waveform indices were similar for the wrist BPW and finger PPG signals. These findings could facilitate the development of a rapid, inexpensive, and objective technique for evaluating the blood-flow responses induced by FS. © 2019 Published by Elsevier Ltd.
1. Introduction Frozen shoulder (FS) is a common clinical condition characterized by severe pain and a reduced range of motion in the shoulder, but its etiology is unknown [1,2]. Previous pathological studies have documented chronic inflammation or fibrosis in the synovium and capsule in patients with FS [3]. Providing optimal treatment requires the accurate and timely diagnosis of FS, but few noninvasive means of scrutinizing the properties of the synovium and capsule in FS have been reported [4]. FS can induce or be associated with several types of changes in the local blood-flow perfusion or vascular properties. For example, an abnormal vasoconstrictor response in the skin over the shoul-
∗ Corresponding author at: No.43, Section 4, Keelung Road, Graduate Institute of Biomedical Engineering, National Taiwan University of Science and Technology, Taipei, 10607, Taiwan. E-mail address: [email protected] (H. Hsiu). https://doi.org/10.1016/j.bspc.2019.101718 1746-8094/© 2019 Published by Elsevier Ltd.
der has been noted in FS patients, which reduces the cutaneous blood flow [1]. Many studies have found evidence of increased vascularity in the capsular tissue in FS patients. Research studies of the association between FS-related pain and blood flow have also been reported on. The underlying mechanisms may include higher expression levels of neuronal markers, and abnormal blood vessels and accompanying nerves at the joints might be sources of pain [4]. Changes in the blood-flow perfusion or vascular elastic properties of local vessels could affect the amplitude and speed of arterial pulse-wave transmission, and thus change the arterial pulse waveform [5,6]. Previous studies have found differences in waveform indices calculated from the radial arterial blood pressure waveform (BPW) and finger photoplethysmography (PPG) signals between control subjects and patients with various kinds of diseases, including stroke [7], metabolic syndrome [8], polycystic-ovary syndrome [9], and breast cancer [10]. Similarly, since FS can be accompanied with changes in the local blood flow or vascular properties, it might also affect the pulse-wave transmission and thus the waveform indices. Furthermore, the blood-flow perfusion condition at
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Table 1 Characteristics of subjects.
Subject number Gender (male/female) Age (years) disease
SPADI score shoulder flexion (degree) shoulder extension (degree) shoulder abduction (degree) shoulder internal rotation (degree) shoulder external rotation (degree)
Control
frozen shoulder
25 11/14 53.8 ± 7.5
18 8/10 58.1 ± 8.2 chronic lymphocytic thyroiditis: 3 hypertension: 2 diabetes: 1 fibrocystic breast: 1 colorectal cancer: 1 coronary artery bypass: 1 mitral valve prolapse: 1 84.7 ± 24.1 121.6 ± 34.3 42.7 ± 16.5 96.4 ± 40.8 44.6 ± 27.9 60.2 ± 25.2
the downstream extremity (e.g., around the hand) can also be affected by changes in the altered pulse-wave transmission. Previous studies have used laser Doppler flowmetry (LDF) to measure changes in the cutaneous blood flow, and LDF waveform indices have also been shown to be useful for discriminating differences in the skin-surface blood-flow perfusion condition between patients and control subjects [11–14]. These previous findings illustrate that using noninvasive measurement techniques has the potential to identify disease-induced hemodynamic changes. The aim of the present study was to determine the effectiveness of using arterial pulse-wave and LDF measurements in discriminating between FS patients and control subjects. Arterial pulse waveforms were acquired by mechanical measurements (using strain-gauge sensors to measure the BPW) and optical measurements (in PPG), while the skin-surface microcirculatory blood-flow perfusion was measured by LDF. The analyses focused on the time-domain beat-to-beat and frequencydomain spectral changes in the BPW, PPG, and LDF waveform. The obtained knowledge could be used in the development of a noninvasive and easy-to-use measurement technique for detecting the FS-induced changes in blood perfusion. 2. Materials and methods 2.1. Measurements Details of experimental setup and the signal processing were described previously [7,8,14]. The subject descriptions are listed in Table 1. The FS and control subjects were recruited in the Department of Rehabilitation, Taipei City Hospital RenAi Branch. The inclusion criteria included patients aged between 40 and 70 years with 1-side shoulder attacked; experiencing shoulder pain and motion limitation at least 2 months before the study. Informed consent was obtained from the study participants or their legal designates (approved by the Review Board of Taipei City Hospital; TCHIRB-10606115-E-F). Patients were excluded if they did not agree to participate or continue the study; patients with osteoarthritis, rheumatoid arthritis, cervical radiculopathy, thoracic outlet syndrome, or stroke were also excluded. Bilateral (diseased and contralateral sides) BPW, PPG and LDF signals were simultaneously and noninvasively measured for FS subjects; measurements were performed on the right side of control subjects. Before the measurements, the subjects were relaxed and rested for 20 min, and the range of motion (ROM) was measured by a goniometer (including passive and active; in directions); shoulder pain and disability index (SPADI) was calculated for the FS patients. For each experiment, the subjects were sitting on a
chair, and we recorded a 3-minute data sequence. The BPW signals were acquired by pressure transducers (KFG-2-120-D111, Kyowa) held onto the skin surface above the radial artery 2 cm from the wrist [7,10]. The PPG signals from a 940-nmwavelength infrared LED penetrating the middle finger tissue were acquired by photodiodes [8]. Moor VMS-LDF (VP1 probe; MBF3, Moor Instruments, UK) was used to measure the skinsurface temperature and the MBF flux between the thumb and the index finger on the back of the hand [13,14]. These signals were sampled at 1024 Hz. Before the measurement, the heart rate (HR), brachial systolic blood pressure (BP) and diastolic BP were measured by using a sphygmomanometer (MG150f, Rossmax). 2.2. Signal analysis Spikes that deviated by more than 30% from the mean flux value of the two adjacent data points were smoothed and replaced by their average value, since this implied the presence of obvious motion artifacts. For time-domain BPW and LDF signals, foot-delay time (FDT), flux-rising time (FRT) pulse width (PW), and their coefficient of variation (FDT CV, FRT CV, and PW CV), were calculated by beat-to-beat waveform analysis [13,14]. The two neighboring minimal points were used to identify the cut points in the BPW, PPG, and LDF flux signals to define each pulse. The foot delay time (FDT) was defined as the time interval between the ECG R-peak and the cut point in the foot, and the flow rise time (FRT) was defined as the time interval between the foot point and the maximal point of the LDF or BPW signals. The pulse width (PW) was defined as the time interval between those points at which the flux value was 80% of the pulse peak on the rising and falling edges, respectively. Values of the coefficient of variance of FDT, FRT, and PW for all the pulses within a 3-minute data sequence were then calculated to evaluate the beat-to-beat parameters (indicated by the “CV” suffix) [13,14]. For BPW and PPG signals, harmonic indices including amplitude proportion (Cn ), coefficient of variations of Cn (CVn ), phase angle (Pn ), and SD of Pn were calculated by frequency-domain analysis. (between foot points) can be represented Each individual pulse by the following finite series [10]:
x(t) =
A0 +{ An cos nωts + Bn sin nwts } 2 k/2
k/2
n=1
n=1
The Fourier coefficients (An calculated by
and
Bn) of the pulse can be
2 k xs cos nωts (forn = 0, 1, ..., ) 2 k k
An =
s=0 k
2 k Bn = xs sin nωts (forn = 0, 1, ..., ) 2 k s=0
Where ω is the angular frequency and ts is the sampling time interval. The amplitude (Ampn ) and phase angle (Pn ) of each harmonic of the pulse harmonic spectrum can then be calculated by
Ampn = A2n + Bn2 and Pn = arctan(Bn /An ), respectively. The amplitude proportions (Cn ) were calculated according to Ampn /Amp0 ×100% for n = 1–10. Signal processing was performed with MATLAB (MathWorks). The differences were tested with two-tailed t-test and were considered significant when p < 0.05; all
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p-values were two-sided hypotheses. Power analysis revealed that the power of the present analysis were all larger than 0.8.
3. Results The characteristics of the study subjects are listed in Table 1. Fig. 1 compares the beat-to-beat parameters of BPW and LDF signals. Regarding BPW indices, FDT was significantly shorter and PW was significantly smaller on the diseased side than controls, while FDT CV was significantly larger. Regarding LDF indices, FDT and FRT were significantly longer while PW CV was significantly larger on the diseased side than controls. Figs. 2 and 3 compare the spectral indices of the BPW and PPG waveforms. Regarding BPW indices, C1 –C4 were significantly larger on the diseased and contralateral sides than controls. P1 was significantly larger while P2 –P8 were significantly smaller on the diseased side than controls. Regarding PPG indices, C1 –C4 and P1 –P4 were significantly smaller on the diseased and contralateral sides than controls. Regarding BPW indices, the BPW and PPG variability indices showed similar trends between FS patients and control subjects (Figs. 2 and 3), with CV of C1 and SD of P1 –P10 being significantly larger on the diseased side than controls. Regarding PPG indices, CV of C1 –C10 and SD of P3 –P10 were significantly larger on the diseased side than controls, while CV of C1 –C3 and SD of P1 –P7 were significantly larger on the diseased side than on the contralateral side. Fig. 4 compares the post-to-pre harmonic ratios [defined as (kth harmonic)/((k – 1)th harmonic) for k = 2–10] between the BPW and PPG waveforms for identifying any possible relationships. The changing trends and significant correlations (p < 0.05 by the F-test) for the nine post-to-pre harmonic ratios were similar in the BPW and PPG waveforms.
Fig. 1. Comparisons of BPW and LDF beat-to-beat parameters. ” indicates p < 0.05. The diseased side (A); the contralateral side (B); Controls (C). “
4. Discussion This study found significant differences in the BPW, PPG, and LDF indices between FS patients and control subjects, indicating that these indices can be used to identify FS.
Fig. 2. Comparisons of BPW harmonic indices: amplitude proportion (Cn ), CVn , phase angle (Pn ), and SD of Pn . C5 –C10 values have been multiplied by 5 to make the differences clearer. “ ” indicates p < 0.05. The diseased side (A); the contralateral side (B); Controls (C).
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Fig. 3. Comparisons of PPG harmonic indices: amplitude proportion (Cn ), CVn , phase angle (Pn ), and SD of Pn . C5 –C10 values have been multiplied by 5 to make the differences clearer. “ ” indicates p < 0.05. The diseased side (A); the contralateral side (B); Controls (C).
4.1. Beat-to-beat waveform indices Fig.1 reveals that the differences in several beat-to-beat BPW indices between the control and FS subjects were more prominent on the diseased side than the contralateral side. BPW FDT was shorter than the control value both on the diseased and contralateral sides (significant on the diseased side). This parameter refers to the time taken for the arterial pulse to travel from the heart to the radial artery. Two main changes may lead to BPW FDT decreasing: an increased arterial BP and stiffening of the artery. The present subjects included only a few hypertension patients (as listed in Table 1), and so the main underlying mechanism could have been stiffening of the artery accompanying FS. It has been reported that artery stiffening could be related to a disease associated with FS, such as diabetes or hypothyroidism. However, few of the present subjects had diabetes. FS can induce or be associated with several types of changes in the local blood-flow perfusion and vascular properties. The possible mechanisms underlying FS-induced hemodynamic changes include changes in vascularity, vessel elastic properties, and inflammation, as described below. (1) Vascularity Angiogenesis is the growth and remodeling process via which an initial vascular system is modified to form a complex branched network. This multistep process involves the degradation, proliferation, survival, migration, and anastomosis of the endothelial extracellular matrix [15]. FS patients in the early phase exhibit abnormal blood flow and the genesis of neovessels around the superior and inferior glenohumeral joints [4,15]. Pain that occurs in FS has also been suggested to be associated with angiogenesis, such as inflammatory changes in the inferior glenohumeral joint triggering pain during exercise [4].
(2) Vessel elastic properties FS can affect not only the distribution of vessel density but also the vascular elastic properties, such as fibrosis inducing the stiffening of local tissue. This may suppress the nearby arteries, and thus increase the vascular elastic modulus. Moreover, FS patients may tend to use muscles on the diseased side less (either intentionally or nonintentionally) due to the pain or the limited range of motion [16,17], which might also reduce the blood supply to nearby vessels. Local changes in the vessel elastic properties may further affect the arterial pulse-wave transmission in the downstream vessels. (3) Inflammation Inflammation in local tissue is another important mechanism that can contribute to hemodynamic changes in local vascular beds. Inflammation is a complex process that involves distinct cell types and factors acting in a coordinated manner to protect tissues against pathogenic, traumatic, or toxic damage [15]. Persistent chronic inflammatory conditions have been found to mediate a wide variety of diseases, including psoriasis, rheumatoid arthritis, osteoarthritis, metabolic-syndrome-associated disorders, and cancer [15]. It is now considered that capsular inflammation is a predominant pathological feature of the early stage of FS [4]. FS pathogenesis has been suggested to involve inflammatory cells and increased levels of growth factors and cytokines in the synovium, which subsequently induces reactive capsular fibrosis [2]. The pathological process has been described as inflammatory thickening of the articular capsule or the development of intra-articular or extra-articular synovial inflammation [4]. Moreover, angiogenesis and inflammation are often closely integrated, since inflammatory mediators can stimulate angiogenesis and angiogenesis can facilitate inflammation [2]. Hypoxia is a common stimulus for both of these processes, resulting in the accumulation of macrophages and
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more effort might be required for the blood flow to overcome the resistance through arteriolar openings, making FRT useful when evaluating the perfusion condition of the blood flow. Therefore, the longer LDF FRT on the FS-diseased side (Fig.1) implied the presence of a larger resistance to blood-flow perfusion through the arteriolar openings. 4.2. Variability indices
Fig. 4. Comparisons of post-to-pre harmonic ratios of spectral indices [amplitude proportion (Cn +1 )/(Cn )] between the BPW and PPG waveforms on the FS-diseased side. The changing trends and significant correlations (p < 0.05 by the F-test) for the nine post-to-pre harmonic ratios [defined as (kth harmonic)/((k – 1)th harmonic) for k = 2–10] in the BPW and PPG waveforms.
other immune cells, as well as the increased production of growth factors [15]. Regarding the LDF beat-to-beat waveform indices, Fig. 1 shows that FDT and FRT were significantly longer on the FS-diseased side than controls. It is worth noting that BPW FDT was significantly shorter whereas LDF FDT was significantly longer on the FS-diseased side. These opposite changes in the direction of FDT could be attributed to the cardiovascular system being measured at different levels: BPW relates to the pulse waveform in the main artery, whereas LDF relates to the blood-flow waveform in the microcirculation. Different from BPW FDT, LDF FDT has been suggested to be correlated with the time taken for blood to fill the vascular beds prior to the arteriolar openings [13]. It is possible that FS-induced arterial stiffening leads to a mismatch of the elastic properties of upstream and downstream arteries, which could reduce the transmission efficiency of the arterial pulse. This may in turn reduce the driving force for blood flow, reduce the blood-filling ability, and thus lengthen the time taken for blood to accumulate in the local vascular beds. This would further result in a later onset of the opening of the arteriolar openings, and thus lengthen the FDT of the LDF waveform. The significantly longer LDF FRT on the FS-diseased side indicated a longer time to reach the peak blood flow. This implies that
Many of the present BPW FDT CV values, BPW spectral variability indices, and LDF PW CV values were larger in FS patients (either on the diseased or contralateral side) than in the controls, with some of these differences being statistically significant. The cardiovascular system can adjust the vessel or blood-flow properties according to the blood-supply condition to keep the blood perfusion stable and sufficient. HR, BP, and MBF variability indices can therefore be used to evaluate the extent of cardiovascular regulatory activities [18,19]. When FS patients are experiencing changes in their local shoulder tissues (either an abnormal blood supply or vessel elasticity) on the diseased side, this could result in the regulatory activities increasing, thus leading to increased CV indices for both the main artery (BPW spectral variability indices) and local vessels (LDF PW CV). For example, changes in the BPW spectral variability indices might be correlated with changes in the arterial pulse-wave transmission condition. Since PW corresponds to the LDF pulse width, it can be used to evaluate the time duration of blood-flow perfusion. Although PW itself did not differ significantly between FS patients and control subjects, its variability index (i.e., PW CV) can still be used to evaluate the regulatory activity acting on the arteriolar openings. However, for the control subjects there were no such prominent changes in local shoulder tissue, and hence the values of the variability indices were smaller. Since FS patients can experience pain or a reduced range of motion on the diseased side, their blood supply might be more influenced than for the controls. Similarly, this condition can lead to BPW FDT CV on the diseased side also being increased more prominently, possibly with the aim of regulating the blood-supply perfusion condition. Furthermore, some of the CV indices on the diseased side were both increased for the BPW and LDF signals in the present FS patients. This illustrates that the FS-induced changes in local tissue can lead to similar cardiovascular regulatory activity acting on both the upstream radial artery and the downstream vascular beds. 4.3. Spectral BPW and PPG indices The pulse pressure plays an important role in driving the perfusion of the blood flow, and knowledge of the spectral distribution of the pulse waveform might facilitate the understanding of the pulse-wave transmission condition and thus evaluations of the blood-flow supply condition [8,10]. Fig. 2a illustrates that there were larger amplitude contributions from the lower-frequency Cn components (C1 –C4 ) in the BPW, and smaller contributions from the higher-frequency components. It is possible that the efficiency of transmitting the pulse wave along the artery is reduced in FS patients due to the changed vascular elastic properties or bloodflow perfusion condition in the local tissue. The smaller amplitudes of the higher-frequency components might make them more likely to become insignificant during the transmission of the pulse wave compared to the lower-frequency components (which dominate the amplitude distribution of the pulse waveform). This results in the lower-frequency Cn components making a larger contribution in FS patients than in controls, as revealed in Fig. 2a. The comparison of PPG waveforms in Fig. 3a reveals that the Cn contribution for lower-frequency components (C1 –C4 ) was smaller for FS patients than controls. The PPG measurements were performed at the finger, which is downstream of where BPW is
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measured around the wrist. From the wave-transmission point of view, the (PPG Cn )/(BPW Cn ) ratio can be used to evaluate the transmission efficiency for specific harmonic components of the pulse wave. Comparing Figs. 2 and 3 reveals that this ratio for the main frequency components (C1 –C4 ) was decreased in the FS patients. It is possible that the present BPW and PPG results implied the presence of abnormal pulse-wave transmission efficiency, possibly due to the vascular or blood-flow changes in local tissues in FS. This results in the main components decreasing more rapidly, thus leading to the decreased C1 –C4 in the PPG waveforms in the FS patients. Fig. 2 also illustrates that there were significant differences between the FS patients and controls in the phase-angle indices. Similar to the BPW amplitude indices, the differences compared the control values in many BPW phase-angle indices were more prominent on the diseased side (significantly smaller for P1 –P8 and significantly larger for the SD of P1 –P10 ) than the contralateral side. The phase-angle indices represent the time delays of individual frequency components within the arterial pulse waveform, and therefore can also be used to evaluate the pulse-wave transmission condition. A larger phase angle indicates a lead condition of pulsewave transmission, and so the larger BPW phase angles for control subjects might indicate better transmission efficiency for the arterial pulse. The pulse-wave transmission condition in the FS patients can be affected by changes in the local vascular tissues. It is possible that the pulse-wave transmission efficiency could be affected, and hence influence the local blood-supply perfusion condition on the diseased side. Changes in the phase-angle SD indices potentially provide further support for the above conjecture. It has been suggested that cardiovascular variability indices are correlated with the regulatory activities influencing the perfusion condition of the blood supply [14,18,19]. A sufficient and stable blood supply will make it easier for the cardiovascular regulatory activity to fulfill the tissue requirements. However, the changes in the perfusion condition of blood flow on the FS-diseased side could increase the cardiovascular regulatory efforts needed to adjust the local perfusion condition, which would increase the values of the BPW phase-angle SD indices. The changing trends of the PPG waveforms were similar to those of the BPW spectral phase-angle indices, with several of the phaseangle indices being significantly smaller and several phase-angle SD indices being significantly larger in FS patients than controls. Furthermore, the changing trends of variability indices were similar for the beat-to-beat LDF indices, beat-to-beat BPW indices, spectral BPW indices, and spectral PPG indices, with many of them being larger in FS patients than controls. These observations further support the above conjecture that the BPW, PPG, and LDF signals acquired at different levels of cardiovascular system may be under similar regulatory control. 4.4. Comparison of BPW and PPG spectral indices Figs. 2 and 3 reveal that were some similarities in the changing trends of the BPW and PPG spectral indices. For example, compared to the controls, on the diseased side of FS patients there were significantly larger CV values for Cn , significantly smaller Pn values, and significantly larger SD values for Pn for several harmonic components for both the BPW and PPG waveforms. These observations could be attributed to the BPW referring to BP changes (using mechanical measurements) inside the vessel, and PPG referring to volume changes (using optical measurements) of the artery during pulsation—they both originate from the driving force of the heartbeat and the arterial pulse-wave transmission. Since the BPW and PPG waveforms originate from the same mechanism, many previous researchers had tried to connect indices between these
two waveforms with the aim of facilitating noninvasive measurements of the arterial pulse waveform, as implemented in wearable biosignal measurement devices. Based on the above conjecture, we used another method to further test the similarity between these two waveforms. Fig. 4 illustrates that comparing the Cn /Cn–1 values (for n = 2–10) between the BPW and PPG waveforms reveals similar changing trends either for the amplitude ratio or the correlation scatter plot. This further indicates the similarities in the BPW and PPG waveforms. The present findings implied the reliability of the transfer function for the spectral indices between these two waveforms, which is similar to the conclusion we drew based on the results obtained in one of our previous studies [20]. 4.5. Limitations The present study was limited by its relatively small sample. The responses of indices may have been biased by different disease subtypes or locations, and the smallness of the sample made it difficult to further divide subjects into subgroups. Future studies should therefore include larger samples. Another important limitation of the present study was not accounting for the possibility of interference effects on the indices induced by other diseases. Future studies should investigate possible differences of the effects of these interference factors on the measured index values. 5. Conclusion This study found significant differences in blood-flow and pulsewaveform indices between FS patients and control subjects. The present findings indicate that LDF can be used to evaluate the responses of the blood-flow perfusion and its regulatory activities in FS patients. Measuring pulse-waveform indices such as the beatto-beat variability, spectral amplitude, spectral phase angle, and spectral variability indices can facilitate evaluations of the changes in the arterial pulse-wave transmission condition and its regulatory activities in FS. Based on the present findings, the best parameters include: C1-C4, P1-P8, and SD of P1-P10 of BPW; C1-C4, CV1-CV10, P1P8, and SD of P1-P10 of PPG; FDT of LDF. It has been revealed that different diseases have different patterns in the BPW and PPG indices distribution. For example, stroke patients had larger CVn values in BPW than in control [7], whereas there was only significantly larger C1 than in control in the present FS patients. In polycystic-ovary-syndrome subjects, C1 of BPW was significantly larger, and C4 and C5 were significantly smaller compared with controls [9]. In BPW of breast-cancer subjects, C1 and C2 were significantly larger, and CV2 and CV3 were significantly smaller in the cancer group than in control [10]. These illustrated different diseases may induce different characteristic patterns in spectral BPW indices. In future analysis, using machine-learning analysis techniques on these parameters may help to provide suggestion of FS condition for doctors and users. The changing trends of some of the spectral pulse-waveform indices were similar in the wrist BPW and finger PPG signals. Since these signals are easy to measure noninvasively, they could facilitate the development of a rapid, inexpensive, and objective device for evaluating the blood-flow responses induced by FS. Funding This work was partly supported by Ministry of Science and Technology (MOST 108-2221-E-011-112-), and Taipei City Hospital.
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Informed consent Informed consent was obtained from all individual participants included in the study. Acknowledgements The authors would like to thank the Ministry of Science and Technology (MOST 108-2221-E-011-112-) and Taipei City Hospital for partial support of this work. Declaration of Competing Interest The authors declare no conflict of interest. References [1] R. Mani, C. Cooper, B.L. Kidd, J.D. Cole, M.I. Cawley, Use of laser Doppler flowmetry and transcutaneous oxygen tension electrodes to assess local autonomic dysfunction in patients with frozen shoulder, J. R. Soc. Med. 82 (9) (1989) 536–538. [2] Y. Xu, F. Bonar, G.A. Murrell, Enhanced expression of neuronal proteins in idiopathic frozen shoulder, J. Shoulder Elbow Surg. 21 (2012) 1391–1397. [3] K. Tamai, M. Yamato, Abnormal synovium in the frozen shoulder: a preliminary report with dynamic magnetic resonance imaging, J. Shoulder Elbow Surg. 6 (6) (1997) 534–543. [4] H. Sasanuma, H. Sugimoto, A. Fujita, Y. Kanaya, Y. Iijima, T. Saito, K. Takeshita, Characteristics of dynamic magnetic resonance imaging of idiopathic severe frozen shoulder, J. Shoulder Elbow Surg. 26 (2) (2017) e52–e57. [5] M.F. O’Rourke, A. Adji, M.E. Safar, Structure and function of systemic arteries: reflections on the arterial pulse, Am. J. Hypertens. 31 (8) (2018) 934–940. [6] B. Hametner, S. Wassertheurer, Pulse waveform analysis: is it ready for prime time? Curr. Hypertens. Rep. 19 (9) (2017) 73. [7] H. Hsiu, C.L. Hsu, C.T. Chen, W.C. Hsu, F.C. Lin, Effects of acupuncture on the harmonic components of the radial arterial blood-pressure waveform in stroke patients, Biorheology 50 (1–2) (2013) 69–81.
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Biomedical Signal Processing and Control journal homepage: www.elsevier.com/locate/bspc
Characteristics of pulse-waveform and laser-Doppler indices in frozen-shoulder patients Feng-Cheng Lin a , Hsin Hsiu b,c,∗ , Han-Si Chiu b , Chao-Tsung Chen d,e,f , Chung-Hua Hsu e,g a
Department of Rehabilitation, Taipei City Hospital RenAi Branch, Taipei, Taiwan Graduate Institute of Biomedical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan Biomedical Engineering Research Center, National Defense Medical Center, Taipei, Taiwan d Department of Traditional Chinese Medicine, Taipei City Hospital RenAi Branch, Taipei, Taiwan e Institute of Traditional Medicine, National Yang-Ming University, Taipei, Taiwan f General Education Center, University of Taipei, Taipei, Taiwan g Branch of Linsen and Chinese Medicine, Taipei City Hospital, Taipei, Taiwan b c
a r t i c l e
i n f o
Article history: Received 21 August 2019 Received in revised form 1 October 2019 Accepted 10 October 2019 Keywords: Frozen shoulder Blood flow Laser doppler Pulse Photoplethysmography Spectral analysis
a b s t r a c t This study tested the hypothesis that measuring and analyzing the arterial pulse waveform and the skinsurface blood flow makes it possible to noninvasively discriminate the different microcirculatory states of patients with frozen shoulder (FS). Radial blood pressure waveform (BPW), finger photoplethysmography (PPG), and skin-surface laser Doppler flowmetry (LDF) signals were measured noninvasively on the back of the hand in 25 FS and 18 control subjects. Beat-to-beat, spectral, and variability analyses were applied to the 3-minute-long recorded signals. Significant intergroup differences were found in the BPW, PPG, and LDF indices. For example, the amplitude indices of the predominant (lower-frequency) BPW components were significantly larger in FS subjects than controls. Some of the PPG phase-angle variability indices were significantly larger on the diseased side than on the contralateral side. The present results illustrate that LDF indices can be used to evaluate the blood-flow-perfusion responses and their regulation, and that pulse-waveform indices can help to evaluate changes in the arterial pulse-wave transmission condition and its regulation in FS. Moreover, the trends in the changes in certain spectral pulse-waveform indices were similar for the wrist BPW and finger PPG signals. These findings could facilitate the development of a rapid, inexpensive, and objective technique for evaluating the blood-flow responses induced by FS. © 2019 Published by Elsevier Ltd.
1. Introduction Frozen shoulder (FS) is a common clinical condition characterized by severe pain and a reduced range of motion in the shoulder, but its etiology is unknown [1,2]. Previous pathological studies have documented chronic inflammation or fibrosis in the synovium and capsule in patients with FS [3]. Providing optimal treatment requires the accurate and timely diagnosis of FS, but few noninvasive means of scrutinizing the properties of the synovium and capsule in FS have been reported [4]. FS can induce or be associated with several types of changes in the local blood-flow perfusion or vascular properties. For example, an abnormal vasoconstrictor response in the skin over the shoul-
∗ Corresponding author at: No.43, Section 4, Keelung Road, Graduate Institute of Biomedical Engineering, National Taiwan University of Science and Technology, Taipei, 10607, Taiwan. E-mail address: [email protected] (H. Hsiu). https://doi.org/10.1016/j.bspc.2019.101718 1746-8094/© 2019 Published by Elsevier Ltd.
der has been noted in FS patients, which reduces the cutaneous blood flow [1]. Many studies have found evidence of increased vascularity in the capsular tissue in FS patients. Research studies of the association between FS-related pain and blood flow have also been reported on. The underlying mechanisms may include higher expression levels of neuronal markers, and abnormal blood vessels and accompanying nerves at the joints might be sources of pain [4]. Changes in the blood-flow perfusion or vascular elastic properties of local vessels could affect the amplitude and speed of arterial pulse-wave transmission, and thus change the arterial pulse waveform [5,6]. Previous studies have found differences in waveform indices calculated from the radial arterial blood pressure waveform (BPW) and finger photoplethysmography (PPG) signals between control subjects and patients with various kinds of diseases, including stroke [7], metabolic syndrome [8], polycystic-ovary syndrome [9], and breast cancer [10]. Similarly, since FS can be accompanied with changes in the local blood flow or vascular properties, it might also affect the pulse-wave transmission and thus the waveform indices. Furthermore, the blood-flow perfusion condition at
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Table 1 Characteristics of subjects.
Subject number Gender (male/female) Age (years) disease
SPADI score shoulder flexion (degree) shoulder extension (degree) shoulder abduction (degree) shoulder internal rotation (degree) shoulder external rotation (degree)
Control
frozen shoulder
25 11/14 53.8 ± 7.5
18 8/10 58.1 ± 8.2 chronic lymphocytic thyroiditis: 3 hypertension: 2 diabetes: 1 fibrocystic breast: 1 colorectal cancer: 1 coronary artery bypass: 1 mitral valve prolapse: 1 84.7 ± 24.1 121.6 ± 34.3 42.7 ± 16.5 96.4 ± 40.8 44.6 ± 27.9 60.2 ± 25.2
the downstream extremity (e.g., around the hand) can also be affected by changes in the altered pulse-wave transmission. Previous studies have used laser Doppler flowmetry (LDF) to measure changes in the cutaneous blood flow, and LDF waveform indices have also been shown to be useful for discriminating differences in the skin-surface blood-flow perfusion condition between patients and control subjects [11–14]. These previous findings illustrate that using noninvasive measurement techniques has the potential to identify disease-induced hemodynamic changes. The aim of the present study was to determine the effectiveness of using arterial pulse-wave and LDF measurements in discriminating between FS patients and control subjects. Arterial pulse waveforms were acquired by mechanical measurements (using strain-gauge sensors to measure the BPW) and optical measurements (in PPG), while the skin-surface microcirculatory blood-flow perfusion was measured by LDF. The analyses focused on the time-domain beat-to-beat and frequencydomain spectral changes in the BPW, PPG, and LDF waveform. The obtained knowledge could be used in the development of a noninvasive and easy-to-use measurement technique for detecting the FS-induced changes in blood perfusion. 2. Materials and methods 2.1. Measurements Details of experimental setup and the signal processing were described previously [7,8,14]. The subject descriptions are listed in Table 1. The FS and control subjects were recruited in the Department of Rehabilitation, Taipei City Hospital RenAi Branch. The inclusion criteria included patients aged between 40 and 70 years with 1-side shoulder attacked; experiencing shoulder pain and motion limitation at least 2 months before the study. Informed consent was obtained from the study participants or their legal designates (approved by the Review Board of Taipei City Hospital; TCHIRB-10606115-E-F). Patients were excluded if they did not agree to participate or continue the study; patients with osteoarthritis, rheumatoid arthritis, cervical radiculopathy, thoracic outlet syndrome, or stroke were also excluded. Bilateral (diseased and contralateral sides) BPW, PPG and LDF signals were simultaneously and noninvasively measured for FS subjects; measurements were performed on the right side of control subjects. Before the measurements, the subjects were relaxed and rested for 20 min, and the range of motion (ROM) was measured by a goniometer (including passive and active; in directions); shoulder pain and disability index (SPADI) was calculated for the FS patients. For each experiment, the subjects were sitting on a
chair, and we recorded a 3-minute data sequence. The BPW signals were acquired by pressure transducers (KFG-2-120-D111, Kyowa) held onto the skin surface above the radial artery 2 cm from the wrist [7,10]. The PPG signals from a 940-nmwavelength infrared LED penetrating the middle finger tissue were acquired by photodiodes [8]. Moor VMS-LDF (VP1 probe; MBF3, Moor Instruments, UK) was used to measure the skinsurface temperature and the MBF flux between the thumb and the index finger on the back of the hand [13,14]. These signals were sampled at 1024 Hz. Before the measurement, the heart rate (HR), brachial systolic blood pressure (BP) and diastolic BP were measured by using a sphygmomanometer (MG150f, Rossmax). 2.2. Signal analysis Spikes that deviated by more than 30% from the mean flux value of the two adjacent data points were smoothed and replaced by their average value, since this implied the presence of obvious motion artifacts. For time-domain BPW and LDF signals, foot-delay time (FDT), flux-rising time (FRT) pulse width (PW), and their coefficient of variation (FDT CV, FRT CV, and PW CV), were calculated by beat-to-beat waveform analysis [13,14]. The two neighboring minimal points were used to identify the cut points in the BPW, PPG, and LDF flux signals to define each pulse. The foot delay time (FDT) was defined as the time interval between the ECG R-peak and the cut point in the foot, and the flow rise time (FRT) was defined as the time interval between the foot point and the maximal point of the LDF or BPW signals. The pulse width (PW) was defined as the time interval between those points at which the flux value was 80% of the pulse peak on the rising and falling edges, respectively. Values of the coefficient of variance of FDT, FRT, and PW for all the pulses within a 3-minute data sequence were then calculated to evaluate the beat-to-beat parameters (indicated by the “CV” suffix) [13,14]. For BPW and PPG signals, harmonic indices including amplitude proportion (Cn ), coefficient of variations of Cn (CVn ), phase angle (Pn ), and SD of Pn were calculated by frequency-domain analysis. (between foot points) can be represented Each individual pulse by the following finite series [10]:
x(t) =
A0 +{ An cos nωts + Bn sin nwts } 2 k/2
k/2
n=1
n=1
The Fourier coefficients (An calculated by
and
Bn) of the pulse can be
2 k xs cos nωts (forn = 0, 1, ..., ) 2 k k
An =
s=0 k
2 k Bn = xs sin nωts (forn = 0, 1, ..., ) 2 k s=0
Where ω is the angular frequency and ts is the sampling time interval. The amplitude (Ampn ) and phase angle (Pn ) of each harmonic of the pulse harmonic spectrum can then be calculated by
Ampn = A2n + Bn2 and Pn = arctan(Bn /An ), respectively. The amplitude proportions (Cn ) were calculated according to Ampn /Amp0 ×100% for n = 1–10. Signal processing was performed with MATLAB (MathWorks). The differences were tested with two-tailed t-test and were considered significant when p < 0.05; all
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p-values were two-sided hypotheses. Power analysis revealed that the power of the present analysis were all larger than 0.8.
3. Results The characteristics of the study subjects are listed in Table 1. Fig. 1 compares the beat-to-beat parameters of BPW and LDF signals. Regarding BPW indices, FDT was significantly shorter and PW was significantly smaller on the diseased side than controls, while FDT CV was significantly larger. Regarding LDF indices, FDT and FRT were significantly longer while PW CV was significantly larger on the diseased side than controls. Figs. 2 and 3 compare the spectral indices of the BPW and PPG waveforms. Regarding BPW indices, C1 –C4 were significantly larger on the diseased and contralateral sides than controls. P1 was significantly larger while P2 –P8 were significantly smaller on the diseased side than controls. Regarding PPG indices, C1 –C4 and P1 –P4 were significantly smaller on the diseased and contralateral sides than controls. Regarding BPW indices, the BPW and PPG variability indices showed similar trends between FS patients and control subjects (Figs. 2 and 3), with CV of C1 and SD of P1 –P10 being significantly larger on the diseased side than controls. Regarding PPG indices, CV of C1 –C10 and SD of P3 –P10 were significantly larger on the diseased side than controls, while CV of C1 –C3 and SD of P1 –P7 were significantly larger on the diseased side than on the contralateral side. Fig. 4 compares the post-to-pre harmonic ratios [defined as (kth harmonic)/((k – 1)th harmonic) for k = 2–10] between the BPW and PPG waveforms for identifying any possible relationships. The changing trends and significant correlations (p < 0.05 by the F-test) for the nine post-to-pre harmonic ratios were similar in the BPW and PPG waveforms.
Fig. 1. Comparisons of BPW and LDF beat-to-beat parameters. ” indicates p < 0.05. The diseased side (A); the contralateral side (B); Controls (C). “
4. Discussion This study found significant differences in the BPW, PPG, and LDF indices between FS patients and control subjects, indicating that these indices can be used to identify FS.
Fig. 2. Comparisons of BPW harmonic indices: amplitude proportion (Cn ), CVn , phase angle (Pn ), and SD of Pn . C5 –C10 values have been multiplied by 5 to make the differences clearer. “ ” indicates p < 0.05. The diseased side (A); the contralateral side (B); Controls (C).
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Fig. 3. Comparisons of PPG harmonic indices: amplitude proportion (Cn ), CVn , phase angle (Pn ), and SD of Pn . C5 –C10 values have been multiplied by 5 to make the differences clearer. “ ” indicates p < 0.05. The diseased side (A); the contralateral side (B); Controls (C).
4.1. Beat-to-beat waveform indices Fig.1 reveals that the differences in several beat-to-beat BPW indices between the control and FS subjects were more prominent on the diseased side than the contralateral side. BPW FDT was shorter than the control value both on the diseased and contralateral sides (significant on the diseased side). This parameter refers to the time taken for the arterial pulse to travel from the heart to the radial artery. Two main changes may lead to BPW FDT decreasing: an increased arterial BP and stiffening of the artery. The present subjects included only a few hypertension patients (as listed in Table 1), and so the main underlying mechanism could have been stiffening of the artery accompanying FS. It has been reported that artery stiffening could be related to a disease associated with FS, such as diabetes or hypothyroidism. However, few of the present subjects had diabetes. FS can induce or be associated with several types of changes in the local blood-flow perfusion and vascular properties. The possible mechanisms underlying FS-induced hemodynamic changes include changes in vascularity, vessel elastic properties, and inflammation, as described below. (1) Vascularity Angiogenesis is the growth and remodeling process via which an initial vascular system is modified to form a complex branched network. This multistep process involves the degradation, proliferation, survival, migration, and anastomosis of the endothelial extracellular matrix [15]. FS patients in the early phase exhibit abnormal blood flow and the genesis of neovessels around the superior and inferior glenohumeral joints [4,15]. Pain that occurs in FS has also been suggested to be associated with angiogenesis, such as inflammatory changes in the inferior glenohumeral joint triggering pain during exercise [4].
(2) Vessel elastic properties FS can affect not only the distribution of vessel density but also the vascular elastic properties, such as fibrosis inducing the stiffening of local tissue. This may suppress the nearby arteries, and thus increase the vascular elastic modulus. Moreover, FS patients may tend to use muscles on the diseased side less (either intentionally or nonintentionally) due to the pain or the limited range of motion [16,17], which might also reduce the blood supply to nearby vessels. Local changes in the vessel elastic properties may further affect the arterial pulse-wave transmission in the downstream vessels. (3) Inflammation Inflammation in local tissue is another important mechanism that can contribute to hemodynamic changes in local vascular beds. Inflammation is a complex process that involves distinct cell types and factors acting in a coordinated manner to protect tissues against pathogenic, traumatic, or toxic damage [15]. Persistent chronic inflammatory conditions have been found to mediate a wide variety of diseases, including psoriasis, rheumatoid arthritis, osteoarthritis, metabolic-syndrome-associated disorders, and cancer [15]. It is now considered that capsular inflammation is a predominant pathological feature of the early stage of FS [4]. FS pathogenesis has been suggested to involve inflammatory cells and increased levels of growth factors and cytokines in the synovium, which subsequently induces reactive capsular fibrosis [2]. The pathological process has been described as inflammatory thickening of the articular capsule or the development of intra-articular or extra-articular synovial inflammation [4]. Moreover, angiogenesis and inflammation are often closely integrated, since inflammatory mediators can stimulate angiogenesis and angiogenesis can facilitate inflammation [2]. Hypoxia is a common stimulus for both of these processes, resulting in the accumulation of macrophages and
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more effort might be required for the blood flow to overcome the resistance through arteriolar openings, making FRT useful when evaluating the perfusion condition of the blood flow. Therefore, the longer LDF FRT on the FS-diseased side (Fig.1) implied the presence of a larger resistance to blood-flow perfusion through the arteriolar openings. 4.2. Variability indices
Fig. 4. Comparisons of post-to-pre harmonic ratios of spectral indices [amplitude proportion (Cn +1 )/(Cn )] between the BPW and PPG waveforms on the FS-diseased side. The changing trends and significant correlations (p < 0.05 by the F-test) for the nine post-to-pre harmonic ratios [defined as (kth harmonic)/((k – 1)th harmonic) for k = 2–10] in the BPW and PPG waveforms.
other immune cells, as well as the increased production of growth factors [15]. Regarding the LDF beat-to-beat waveform indices, Fig. 1 shows that FDT and FRT were significantly longer on the FS-diseased side than controls. It is worth noting that BPW FDT was significantly shorter whereas LDF FDT was significantly longer on the FS-diseased side. These opposite changes in the direction of FDT could be attributed to the cardiovascular system being measured at different levels: BPW relates to the pulse waveform in the main artery, whereas LDF relates to the blood-flow waveform in the microcirculation. Different from BPW FDT, LDF FDT has been suggested to be correlated with the time taken for blood to fill the vascular beds prior to the arteriolar openings [13]. It is possible that FS-induced arterial stiffening leads to a mismatch of the elastic properties of upstream and downstream arteries, which could reduce the transmission efficiency of the arterial pulse. This may in turn reduce the driving force for blood flow, reduce the blood-filling ability, and thus lengthen the time taken for blood to accumulate in the local vascular beds. This would further result in a later onset of the opening of the arteriolar openings, and thus lengthen the FDT of the LDF waveform. The significantly longer LDF FRT on the FS-diseased side indicated a longer time to reach the peak blood flow. This implies that
Many of the present BPW FDT CV values, BPW spectral variability indices, and LDF PW CV values were larger in FS patients (either on the diseased or contralateral side) than in the controls, with some of these differences being statistically significant. The cardiovascular system can adjust the vessel or blood-flow properties according to the blood-supply condition to keep the blood perfusion stable and sufficient. HR, BP, and MBF variability indices can therefore be used to evaluate the extent of cardiovascular regulatory activities [18,19]. When FS patients are experiencing changes in their local shoulder tissues (either an abnormal blood supply or vessel elasticity) on the diseased side, this could result in the regulatory activities increasing, thus leading to increased CV indices for both the main artery (BPW spectral variability indices) and local vessels (LDF PW CV). For example, changes in the BPW spectral variability indices might be correlated with changes in the arterial pulse-wave transmission condition. Since PW corresponds to the LDF pulse width, it can be used to evaluate the time duration of blood-flow perfusion. Although PW itself did not differ significantly between FS patients and control subjects, its variability index (i.e., PW CV) can still be used to evaluate the regulatory activity acting on the arteriolar openings. However, for the control subjects there were no such prominent changes in local shoulder tissue, and hence the values of the variability indices were smaller. Since FS patients can experience pain or a reduced range of motion on the diseased side, their blood supply might be more influenced than for the controls. Similarly, this condition can lead to BPW FDT CV on the diseased side also being increased more prominently, possibly with the aim of regulating the blood-supply perfusion condition. Furthermore, some of the CV indices on the diseased side were both increased for the BPW and LDF signals in the present FS patients. This illustrates that the FS-induced changes in local tissue can lead to similar cardiovascular regulatory activity acting on both the upstream radial artery and the downstream vascular beds. 4.3. Spectral BPW and PPG indices The pulse pressure plays an important role in driving the perfusion of the blood flow, and knowledge of the spectral distribution of the pulse waveform might facilitate the understanding of the pulse-wave transmission condition and thus evaluations of the blood-flow supply condition [8,10]. Fig. 2a illustrates that there were larger amplitude contributions from the lower-frequency Cn components (C1 –C4 ) in the BPW, and smaller contributions from the higher-frequency components. It is possible that the efficiency of transmitting the pulse wave along the artery is reduced in FS patients due to the changed vascular elastic properties or bloodflow perfusion condition in the local tissue. The smaller amplitudes of the higher-frequency components might make them more likely to become insignificant during the transmission of the pulse wave compared to the lower-frequency components (which dominate the amplitude distribution of the pulse waveform). This results in the lower-frequency Cn components making a larger contribution in FS patients than in controls, as revealed in Fig. 2a. The comparison of PPG waveforms in Fig. 3a reveals that the Cn contribution for lower-frequency components (C1 –C4 ) was smaller for FS patients than controls. The PPG measurements were performed at the finger, which is downstream of where BPW is
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measured around the wrist. From the wave-transmission point of view, the (PPG Cn )/(BPW Cn ) ratio can be used to evaluate the transmission efficiency for specific harmonic components of the pulse wave. Comparing Figs. 2 and 3 reveals that this ratio for the main frequency components (C1 –C4 ) was decreased in the FS patients. It is possible that the present BPW and PPG results implied the presence of abnormal pulse-wave transmission efficiency, possibly due to the vascular or blood-flow changes in local tissues in FS. This results in the main components decreasing more rapidly, thus leading to the decreased C1 –C4 in the PPG waveforms in the FS patients. Fig. 2 also illustrates that there were significant differences between the FS patients and controls in the phase-angle indices. Similar to the BPW amplitude indices, the differences compared the control values in many BPW phase-angle indices were more prominent on the diseased side (significantly smaller for P1 –P8 and significantly larger for the SD of P1 –P10 ) than the contralateral side. The phase-angle indices represent the time delays of individual frequency components within the arterial pulse waveform, and therefore can also be used to evaluate the pulse-wave transmission condition. A larger phase angle indicates a lead condition of pulsewave transmission, and so the larger BPW phase angles for control subjects might indicate better transmission efficiency for the arterial pulse. The pulse-wave transmission condition in the FS patients can be affected by changes in the local vascular tissues. It is possible that the pulse-wave transmission efficiency could be affected, and hence influence the local blood-supply perfusion condition on the diseased side. Changes in the phase-angle SD indices potentially provide further support for the above conjecture. It has been suggested that cardiovascular variability indices are correlated with the regulatory activities influencing the perfusion condition of the blood supply [14,18,19]. A sufficient and stable blood supply will make it easier for the cardiovascular regulatory activity to fulfill the tissue requirements. However, the changes in the perfusion condition of blood flow on the FS-diseased side could increase the cardiovascular regulatory efforts needed to adjust the local perfusion condition, which would increase the values of the BPW phase-angle SD indices. The changing trends of the PPG waveforms were similar to those of the BPW spectral phase-angle indices, with several of the phaseangle indices being significantly smaller and several phase-angle SD indices being significantly larger in FS patients than controls. Furthermore, the changing trends of variability indices were similar for the beat-to-beat LDF indices, beat-to-beat BPW indices, spectral BPW indices, and spectral PPG indices, with many of them being larger in FS patients than controls. These observations further support the above conjecture that the BPW, PPG, and LDF signals acquired at different levels of cardiovascular system may be under similar regulatory control. 4.4. Comparison of BPW and PPG spectral indices Figs. 2 and 3 reveal that were some similarities in the changing trends of the BPW and PPG spectral indices. For example, compared to the controls, on the diseased side of FS patients there were significantly larger CV values for Cn , significantly smaller Pn values, and significantly larger SD values for Pn for several harmonic components for both the BPW and PPG waveforms. These observations could be attributed to the BPW referring to BP changes (using mechanical measurements) inside the vessel, and PPG referring to volume changes (using optical measurements) of the artery during pulsation—they both originate from the driving force of the heartbeat and the arterial pulse-wave transmission. Since the BPW and PPG waveforms originate from the same mechanism, many previous researchers had tried to connect indices between these
two waveforms with the aim of facilitating noninvasive measurements of the arterial pulse waveform, as implemented in wearable biosignal measurement devices. Based on the above conjecture, we used another method to further test the similarity between these two waveforms. Fig. 4 illustrates that comparing the Cn /Cn–1 values (for n = 2–10) between the BPW and PPG waveforms reveals similar changing trends either for the amplitude ratio or the correlation scatter plot. This further indicates the similarities in the BPW and PPG waveforms. The present findings implied the reliability of the transfer function for the spectral indices between these two waveforms, which is similar to the conclusion we drew based on the results obtained in one of our previous studies [20]. 4.5. Limitations The present study was limited by its relatively small sample. The responses of indices may have been biased by different disease subtypes or locations, and the smallness of the sample made it difficult to further divide subjects into subgroups. Future studies should therefore include larger samples. Another important limitation of the present study was not accounting for the possibility of interference effects on the indices induced by other diseases. Future studies should investigate possible differences of the effects of these interference factors on the measured index values. 5. Conclusion This study found significant differences in blood-flow and pulsewaveform indices between FS patients and control subjects. The present findings indicate that LDF can be used to evaluate the responses of the blood-flow perfusion and its regulatory activities in FS patients. Measuring pulse-waveform indices such as the beatto-beat variability, spectral amplitude, spectral phase angle, and spectral variability indices can facilitate evaluations of the changes in the arterial pulse-wave transmission condition and its regulatory activities in FS. Based on the present findings, the best parameters include: C1-C4, P1-P8, and SD of P1-P10 of BPW; C1-C4, CV1-CV10, P1P8, and SD of P1-P10 of PPG; FDT of LDF. It has been revealed that different diseases have different patterns in the BPW and PPG indices distribution. For example, stroke patients had larger CVn values in BPW than in control [7], whereas there was only significantly larger C1 than in control in the present FS patients. In polycystic-ovary-syndrome subjects, C1 of BPW was significantly larger, and C4 and C5 were significantly smaller compared with controls [9]. In BPW of breast-cancer subjects, C1 and C2 were significantly larger, and CV2 and CV3 were significantly smaller in the cancer group than in control [10]. These illustrated different diseases may induce different characteristic patterns in spectral BPW indices. In future analysis, using machine-learning analysis techniques on these parameters may help to provide suggestion of FS condition for doctors and users. The changing trends of some of the spectral pulse-waveform indices were similar in the wrist BPW and finger PPG signals. Since these signals are easy to measure noninvasively, they could facilitate the development of a rapid, inexpensive, and objective device for evaluating the blood-flow responses induced by FS. Funding This work was partly supported by Ministry of Science and Technology (MOST 108-2221-E-011-112-), and Taipei City Hospital.
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Informed consent Informed consent was obtained from all individual participants included in the study. Acknowledgements The authors would like to thank the Ministry of Science and Technology (MOST 108-2221-E-011-112-) and Taipei City Hospital for partial support of this work. Declaration of Competing Interest The authors declare no conflict of interest. References [1] R. Mani, C. Cooper, B.L. Kidd, J.D. Cole, M.I. Cawley, Use of laser Doppler flowmetry and transcutaneous oxygen tension electrodes to assess local autonomic dysfunction in patients with frozen shoulder, J. R. Soc. Med. 82 (9) (1989) 536–538. [2] Y. Xu, F. Bonar, G.A. Murrell, Enhanced expression of neuronal proteins in idiopathic frozen shoulder, J. Shoulder Elbow Surg. 21 (2012) 1391–1397. [3] K. Tamai, M. Yamato, Abnormal synovium in the frozen shoulder: a preliminary report with dynamic magnetic resonance imaging, J. Shoulder Elbow Surg. 6 (6) (1997) 534–543. [4] H. Sasanuma, H. Sugimoto, A. Fujita, Y. Kanaya, Y. Iijima, T. Saito, K. Takeshita, Characteristics of dynamic magnetic resonance imaging of idiopathic severe frozen shoulder, J. Shoulder Elbow Surg. 26 (2) (2017) e52–e57. [5] M.F. O’Rourke, A. Adji, M.E. Safar, Structure and function of systemic arteries: reflections on the arterial pulse, Am. J. Hypertens. 31 (8) (2018) 934–940. [6] B. Hametner, S. Wassertheurer, Pulse waveform analysis: is it ready for prime time? Curr. Hypertens. Rep. 19 (9) (2017) 73. [7] H. Hsiu, C.L. Hsu, C.T. Chen, W.C. Hsu, F.C. Lin, Effects of acupuncture on the harmonic components of the radial arterial blood-pressure waveform in stroke patients, Biorheology 50 (1–2) (2013) 69–81.
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