Editorial for the Special Issue on Sensors and Wearable Technologies in Sports Biomechanics.

Sport biomechanics is a subfield of biomechanics that studies mechanics to improve performance and reduce injury during exercise and sports competitions in abled-bodied people and people with disabilities [...].

The relationship between cardiovagal baroreflex and cerebral autoregulation in postural orthostatic tachycardia disorder using advanced cross-correlation function.

Postural orthostatic tachycardia syndrome (POTS) presents excessive orthostatic tachycardia and orthostatic intolerance. POTS is a common and therapeutically challenging condition affecting numerous people worldwide. As many disease entities can be confused with POTS, it becomes critical to identify this syndrome. Moreover, unbalanced autonomic nervous activity can induce cardiovascular diseases and influence the bio-feedback mechanism: Baroreflex (BR) and cerebral autoregulation (CA). BR and CA are important bio-mechanisms that maintain a stable circulatory system via the autonomic nervous system. Therefore, an impaired autonomic nervous system would lead to imbalanced BRS and CA. Consequently, we propose an advanced cross-correlation function (ACCF) time-domain approach to analyze baroreflex and cerebral autoregulation using physiological signals. This study assesses relation changes in BR and CA using ACCF in POTS for early clinical detection and diagnosis. The ACCF analysis results has thresholds that reveal that the BR of healthy and POTS groups present significantly different maximum CCF values (p < 0.05). The complete CCF index shows that the BR phase changes significantly into phase lag in the POTS group. Although CA analysis using the maximum CCF index was mildly weak, it did not differ in the POTS group. Thus, POTS only affects BR. An increasing sympathetic activity might induce an unbalanced baroreflex effect and increase cerebral vasomotor tone with CA. Maximum CCF value correlation coefficients between BR and CA indicated positive in POTS groups and negative in the healthy group. It could be speculated that the sympathetic nervous system compensates to improve BR function, which remains CA function. The advantage of this ACCF algorithm is that it helps observe BR and CA for early detection.

Effect of different inner pressures of air insoles and walking durations on plantar pressure time integral.

Air insoles have provided insights for reducing the risk of diabetic foot ulcers (DFU). The pressure time integral (PTI) is an effective assessment that considers the time effect in various physical activities. We investigated the interactions between three different insole inner pressures (80, 160, and 240 mmHg) and two walking durations (10 and 20 min). The big toe (T1), first metatarsal head (M1), and second metatarsal head (M2) were investigated in 13 healthy participants. One-way analysis of variance (ANOVA) showed that the effects of each insole inner pressure significantly differed (P < 0.05) with a 10 min walking duration. The PTI values resulting from 80 mmHg in M2 (38.4 ± 3.8, P = 0.002) and 160 mmHg in M1 (44.3 ± 4.3, P = 0.027) were lower than those from 240 mmHg. Additionally, the paired t test showed that the effects of each walking duration were also considerably different at 160 mmHg. The PTI at 10 min was lower than that at 20 min in M1 (44.31 ± 4.31, P = 0.015) and M2 (47.14 ± 5.27, P = 0.047). Thus, we suggest that walking with a pressure of 160 mmHg for 10 min has a lower risk of DFU.

Effect of negative pressure therapy on the treatment response to scar thickness and viscoelasticity.

Patients with scars face a grave threat to their mental and physical health. Negative pressure has been used for scar therapy in medical care and provides a microenvironment conducive to scar healing while stimulating cell regeneration. Negative pressure may disrupt scar tissue regeneration when the pressure is too high or too low, so finding a suitable negative pressure is important. We hypothesized that different negative pressure magnitudes would affect scar tissue properties differently. This research aimed to provide practical recommendations for scar therapy. This study used three negative pressures (-105 mmHg, -125 mmHg, and -145 mmHg) to compare scar material properties. We measured scar tissue thickness and viscoelasticity with a motor-driven ultrasound indentation system. According to the results of this study, scar thickness is most effectively reduced at a negative pressure of -105 mmHg. In comparison, scar viscoelasticity continuously increases at a negative pressure of -125 mmHg. Negative pressure therapy can be recommended to scar care clinics based on the results of this study.

Plantar pressure gradient and pressure gradient angle are affected by inner pressure of air insole.

Clinically, air insoles may be applied to shoes to decrease plantar pressure gradient (PPG) and increase plantar gradient angle (PGA) to reduce foot ulcers. PPG and PGA may cause skin breakdown. The effects of different inner pressures of inflatable air insoles on dynamic PPG and PGA distributions are largely unknown in non-diabetics and people with diabetes. This study aimed to explore the impact of varying inner air insole pressures on PPG and PGA to establish early mitigation strategies for people at risk of foot ulcers. A repeated measures study design, including three air insoles (80 mmHg, 160 mmHg, and 240 mmHg) and two walking durations (10 and 20 min) for a total of six walking protocols, was tested on 13 healthy participants (height, 165.8 ± 8.4 cm; age, 27.0 ± 7.3 years; and weight, 56.0 ± 7.9 kg, BMI: 20.3 ± 1.7 kg/m^2) over three consecutive weeks. PPG, a measurement of the spatial variation in plantar pressure around the peak plantar pressure (PPP) and PGA, a variation in the gradient direction values at the three plantar regions, big toe (T1), first metatarsal head (M1), and second metatarsal head (M2), were calculated. This study indicated that PPG was lower at 80 mmHg air insoles after 20 min of walking in the M1 region (p = 0.010). The PGA in the M2 increased at an air insole of 80 mmHg compared to 240 mmHg (p = 0.015). Compared to 20 min, the 10 min walking duration at 240 mmHg of air insole had the lowest PPG in the M1 (p = 0.015) and M2 (p = 0.034) regions. The 80 mmHg air insole significantly lowered the PPG compared to a 160 mmHg and 240 mmHg air insole. Moreover, the 80 mmHg air insole significantly decreased PPP and increased PGA compared to the 160 mmHg and 240 mmHg air insole. A shorter walking period (10 min) significantly lowered PPG. The findings of this study suggest that people with a higher risk of foot ulcers should wear softer air insoles to have a lower PPG, as well as an increased PGA.

Using cross-correlation analysis of multi-channel near infrared spectroscopy to assess the hemodynamic response to cupping therapy.

Cupping therapy is a common intervention for the management of musculoskeletal impairment. Previous studies have demonstrated that cupping therapy can improve muscle hemodynamic responses using single-channel near-infrared spectroscopy (NIRS). However, the effects of cupping therapy on spatial hemodynamic responses as well as the correlation between oxyhemoglobin and deoxy-hemoglobin are largely unknown. The cross-correlation function (CCF) algorithm was used to determine the correlation between time-series NIRS signals from inside and outside the cup as well as time-series oxyhemoglobin and deoxy-hemoglobin under 4 cupping intensities, including -225 and -300 mmHg for 5 and 10 min. The main finding was that the maximum CCF values of oxyhemoglobin was significantly higher than those in deoxy-hemoglobin (p < 0.05). Furthermore, it was found that there was a correlation between deoxy-hemoglobin with a longer duration and a larger magnitude of negative pressure. This is the first study investigating time-series hemodynamic responses after cupping therapy using cross-correlation function analysis of multi-channel NIRS signals.

The effects of different inner pressures of air insoles and walking durations on peak plantar pressure.

BACKGROUND: Exercise reduces chronic complications in individuals with diabetes and peripheral vascular diseases. In clinical practice, the use of air insole may reduce peak plantar pressure (PPP), and risk for diabetic foot ulcers (DFUs). However, there is no guideline on selecting air insole pressure for effectively reducing PPP. Therefore, this study aimed to investigate the effects of different air insole pressure on PPP at different walking durations. METHODS: We tested 13 participants using repeated measures study design, including 3 air insole pressures (80, 160, and 240 mm Hg) and 2 walking durations (10 and 20 minutes) for 6 walking conditions. PPP values at the first toe, first metatarsal head, and second metatarsal head were calculated. RESULTS: The one-way ANOVA showed significant pairwise differences of PPP at 20 minutes duration in the first metatarsal head between 80 and 240 mm Hg (P = .007) and between 160 and 240 mm Hg (P = .038); in the second metatarsal head between 80 and 240 mm Hg (P = .043). The paired t test confirmed that walking duration significantly has lower PPP at 10 minutes than 20 minutes with 240 mm Hg air insole in the first metatarsal head (P = .012) and the second metatarsal head (P = .027). CONCLUSION: People at risk of foot ulcers are suggested to wear shoes with 80 mm Hg of air insole for reducing PPP in the first metatarsal head and the second metatarsal head. Moreover, people may avoid wearing the stiffer insole (240 mm Hg) for more than 20 minutes.

An approach to the diagnosis of lumbar disc herniation using deep learning models.

Background: In magnetic resonance imaging (MRI), lumbar disc herniation (LDH) detection is challenging due to the various shapes, sizes, angles, and regions associated with bulges, protrusions, extrusions, and sequestrations. Lumbar abnormalities in MRI can be detected automatically by using deep learning methods. As deep learning models gain recognition, they may assist in diagnosing LDH with MRI images and provide initial interpretation in clinical settings. YOU ONLY LOOK ONCE (YOLO) model series are often used to train deep learning algorithms for real-time biomedical image detection and prediction. This study aims to confirm which YOLO models (YOLOv5, YOLOv6, and YOLOv7) perform well in detecting LDH in different regions of the lumbar intervertebral disc. Materials and methods: The methodology involves several steps, including converting DICOM images to JPEG, reviewing and selecting MRI slices for labeling and augmentation using ROBOFLOW, and constructing YOLOv5x, YOLOv6, and YOLOv7 models based on the dataset. The training dataset was combined with the radiologist's labeling and annotation, and then the deep learning models were trained using the training/validation dataset. Results: Our result showed that the 550-dataset with augmentation (AUG) or without augmentation (non-AUG) in YOLOv5x generates satisfactory training performance in LDH detection. The AUG dataset overall performance provides slightly higher accuracy than the non-AUG. YOLOv5x showed the highest performance with 89.30% mAP compared to YOLOv6, and YOLOv7. Also, YOLOv5x in non-AUG dataset showed the balance LDH region detections in L2-L3, L3-L4, L4-L5, and L5-S1 with above 90%. And this illustrates the competitiveness of using non-AUG dataset to detect LDH. Conclusion: Using YOLOv5x and the 550 augmented dataset, LDH can be detected with promising both in non-AUG and AUG dataset. By utilizing the most appropriate YOLO model, clinicians have a greater chance of diagnosing LDH early and preventing adverse effects for their patients.

Effects of walking speeds and durations on the plantar pressure gradient and pressure gradient angle.

BACKGROUND: Walking exercise has been demonstrated to improve health in people with diabetes. However, it is largely unknown the influences of various walking intensities such as walking speeds and durations on dynamic plantar pressure distributions in non-diabetics and diabetics. Traditional methods ignoring time-series changes of plantar pressure patterns may not fully capture the effect of walking intensities on plantar tissues. The purpose of this study was to investigate the effect of various walking intensities on the dynamic plantar pressure distributions. In this study, we introduced the peak pressure gradient (PPG) and its dynamic patterns defined as the pressure gradient angle (PGA) to quantify dynamic changes of plantar pressure distributions during walking at various intensities. METHODS: Twelve healthy participants (5 males and 7 females) were recruited in this study. The demographic data were: age, 27.1 ± 5.8 years; height, 1.7 ± 0.1 m; and weight, 63.5 ± 13.5 kg (mean ± standard deviation). An insole plantar pressure measurement system was used to measure plantar pressures during walking at three walking speeds (slow walking 1.8 mph, brisk walking 3.6 mph, and slow running 5.4 mph) for two durations (10 and 20 min). The gradient at a location is defined as the unique vector field in the two-dimensional Cartesian coordinate system with a Euclidean metric. PGA was calculated by quantifying the directional variation of the instantaneous peak gradient vector during stance phase of walking. PPG and PGA were calculated in the plantar regions of the first toe, first metatarsal head, second metatarsal head, and heel at higher risk for foot ulcers. Two-way ANOVA with Fisher's post-hoc analysis was used to examine the speed and duration factors on PPG and PGA. RESULTS: The results showed that the walking speeds significantly affect PPG (P < 0.05) and PGA (P < 0.05), and the walking durations does not. No interaction between the walking duration and speed was observed. PPG in the first toe region after 5.4 mph for either 10 or 20 min was significantly higher than 1.8 mph. Meanwhile, after 3.6 mph for 20 min, PPG in the heel region was significantly higher than 1.8 mph. Results also indicate that PGA in the forefoot region after 3.6 mph for 20 min was significantly narrower than 1.8 mph. CONCLUSIONS: Our findings indicate that people may walk at a slow speed at 1.8 mph for reducing PPG and preventing PGA concentrated over a small area compared to brisk walking at 3.6 mph and slow running at 5.4 mph.

Advanced Cross-Correlation Function Application to Identify Arterial Baroreflex Sensitivity Variations From Healthy to Diabetes Mellitus.

Diabetes mellitus (DM) is a chronic disease characterized by elevated blood glucose levels, which leads over time to serious damage to the heart, blood vessels, eyes, kidneys, and nerves. DM is of two types-types 1 or 2. In type 1, there is a problem with insulin secretion, and in type 2-insulin resistance. About 463 million people worldwide have diabetes, and 80% of the majority live in low- and middle-income countries, and 1.5 million deaths are directly attributed to diabetes each year. Autonomic neuropathy (AN) is one of the common diabetic complications, leading to failure in blood pressure (BP) control and causing cardiovascular disease. Therefore, early detection of AN becomes crucial to optimize treatment. We propose an advanced cross-correlation function (ACCF) between BP and heart rate with suitable threshold parameters to analyze and detect early changes in baroreflex sensitivity (BRS) in DM with AN (DM+). We studied heart rate (HR) and systolic BP responses during tilt in 16 patients with diabetes mellitus only (DM-), 19 diabetes mellitus with autonomic dysfunction (DM+), and 10 healthy subjects. The ACCF analysis revealed that the healthy and DM groups had different filtered percentages of significant maximum cross-correlation function (CCF) value (p < 0.05), and the maximum CCF value after thresholds was significantly reduced during tilt in the DM+ group (p < 0.05). The maximum CCF index, a parameter for the phase between HR and BP, separated the healthy group from the DM groups (p < 0.05). Due to the maximum CCF index in DM groups being located in the positive range and significantly different from healthy ones, it could be speculated that BRS dysfunction in DM and AN could cause a phase change from lead to lag. ACCF could detect and separate DM+ from DM groups. This fact could represent an advantage of the ACCF algorithm. A common cross-correlation analysis was not easy to distinguish between DM- and DM+. This pilot study demonstrates that ACCF analysis with suitable threshold parameters could explore hidden changes in baroreflex control in DM+ and DM-. Furthermore, the superiority of this ACCF algorithm is useful in distinguishing whether AN is present or not in DM.

A Deep Learning Method for Foot Progression Angle Detection in Plantar Pressure Images.

Foot progression angle (FPA) analysis is one of the core methods to detect gait pathologies as basic information to prevent foot injury from excessive in-toeing and out-toeing. Deep learning-based object detection can assist in measuring the FPA through plantar pressure images. This study aims to establish a precision model for determining the FPA. The precision detection of FPA can provide information with in-toeing, out-toeing, and rearfoot kinematics to evaluate the effect of physical therapy programs on knee pain and knee osteoarthritis. We analyzed a total of 1424 plantar images with three different You Only Look Once (YOLO) networks: YOLO v3, v4, and v5x, to obtain a suitable model for FPA detection. YOLOv4 showed higher performance of the profile-box, with average precision in the left foot of 100.00% and the right foot of 99.78%, respectively. Besides, in detecting the foot angle-box, the ground-truth has similar results with YOLOv4 (5.58 ± 0.10° vs. 5.86 ± 0.09°, p = 0.013). In contrast, there was a significant difference in FPA between ground-truth vs. YOLOv3 (5.58 ± 0.10° vs. 6.07 ± 0.06°, p < 0.001), and ground-truth vs. YOLOv5x (5.58 ± 0.10° vs. 6.75 ± 0.06°, p < 0.001). This result implies that deep learning with YOLOv4 can enhance the detection of FPA.

Effectiveness of self-management of dry and wet cupping therapy for low back pain: A systematic review and meta-analysis.

BACKGROUND: Low back pain (LBP) can significantly affect a person's quality of life. Cupping has been used to treat LBP. However, various cupping methods are typically included in evaluating the efficacy of cupping therapy. Therefore, the objectives of this study were to evaluate the evidence from the literature regarding the effects of dry and wet cupping therapy on LBP in adults. Dry and wet cupping therapy are analyzed categorically in this study. METHODS: We searched for randomized clinical trials with cupping in LBP published between 2008 and 2022. In dry or wet cupping clinical studies, pain intensity was assessed using the Visual Analogue Scale and present pain intensity, and the quality of life intensity was measured using the Oswestry disability index. RESULTS: The 656 studies were identified, of which 10 studies for 690 patients with LBP were included in the meta-analysis. There was a significant reduction in the pain intensity score with present pain intensity using wet cupping therapy (P < .01). In addition, both cupping therapy groups displayed significant Oswestry disability index score reduction compared to the control group (both P < .01). The patients with LBP have a substantial reduction by using wet cupping but have not shown a considerable decrease by using dry cupping (P = .19). In addition, only wet cupping therapy groups displayed a significantly improved quality of life compared to the control group. The study had a very high heterogeneity (I2 > 50%). It means there is no standardization in the treatment protocol in randomized clinical trials. In the meta-regression, there was statistically significant evidence that the number of treatment times and intercepts were related (P < .01). CONCLUSION: The present meta-analysis shows that wet cupping therapy effectively reduces the pain intensity of LBP. Furthermore, both dry wet cupping therapy improved patients with LBP quality of life.

Hypertension and Stroke Cardiovascular Control Evaluation by Analyzing Blood Pressure, Cerebral Blood Flow, Blood Vessel Resistance and Baroreflex.

Cardiovascular diseases have been the leading causes of mortality in Taiwan and the world at large for decades. The composition of cardiovascular and cerebrovascular systems is quite complicated. Therefore, it is difficult to detect or trace the related signs of cardiovascular and cerebrovascular diseases. The characteristics and changes in cardiopulmonary system disease can be used to track cardiovascular and cerebrovascular disease prevention and diagnosis. This can effectively reduce the occurrence of cardiovascular and cerebrovascular diseases. This study analyzes the variability in blood pressure, cerebral blood flow velocity and the interaction characteristics using linear and nonlinear approaches in stroke, hypertension and healthy groups to identify the differences in cardiovascular control in these groups. The results showed that the blood pressure and cerebral blood flow of stroke patients and hypertensive patients were significantly higher than those of healthy people (statistical differences (p < 0.05). The cerebrovascular resistance (CVR) shows that the CVR of hypertensive patients is higher than that of healthy people and stroke patients (p < 0.1), indicating that the cerebral vascular resistance of hypertensive patients is slightly higher. From the patient's blood flow and vascular characteristics, it can be observed that the cardiovascular system is different from those in healthy people. Baroreflex sensitivity (BRS) decreased in stroke patients (p < 0.05). Chaotic analysis revealed that the blood pressure disturbance in hypertensive patients has a higher chaotic behavior change and the difference in initial state sensitivity. Cross-correlation (CCF) analysis shows that as the course of healthy→hypertension→stroke progresses, the maximum CCF value decreases significantly (p < 0.05). That means that blood pressure and cerebral blood flow are gradually not well controlled by the self-regulation mechanism. In conclusion, cardiovascular control performance in hypertensive and stroke patients displays greater variation. This can be observed by the bio-signal analysis. This analysis could identify a measure for detecting and preventing the risk for hypertension and stroke in clinical practice. This is a pilot study to analyze cardiovascular control variation in healthy, hypertensive and stroke groups.

Estimation of Various Walking Intensities Based on Wearable Plantar Pressure Sensors Using Artificial Neural Networks.

Walking has been demonstrated to improve health in people with diabetes and peripheral arterial disease. However, continuous walking can produce repeated stress on the plantar foot and cause a high risk of foot ulcers. In addition, a higher walking intensity (i.e., including different speeds and durations) will increase the risk. Therefore, quantifying the walking intensity is essential for rehabilitation interventions to indicate suitable walking exercise. This study proposed a machine learning model to classify the walking speed and duration using plantar region pressure images. A wearable plantar pressure measurement system was used to measure plantar pressures during walking. An Artificial Neural Network (ANN) was adopted to develop a model for walking intensity classification using different plantar region pressure images, including the first toe (T1), the first metatarsal head (M1), the second metatarsal head (M2), and the heel (HL). The classification consisted of three walking speeds (i.e., slow at 0.8 m/s, moderate at 1.6 m/s, and fast at 2.4 m/s) and two walking durations (i.e., 10 min and 20 min). Of the 12 participants, 10 participants (720 images) were randomly selected to train the classification model, and 2 participants (144 images) were utilized to evaluate the model performance. Experimental evaluation indicated that the ANN model effectively classified different walking speeds and durations based on the plantar region pressure images. Each plantar region pressure image (i.e., T1, M1, M2, and HL) generates different accuracies of the classification model. Higher performance was achieved when classifying walking speeds (0.8 m/s, 1.6 m/s, and 2.4 m/s) and 10 min walking duration in the T1 region, evidenced by an F1-score of 0.94. The dataset T1 could be an essential variable in machine learning to classify the walking intensity at different speeds and durations.

Effects of various walking intensities on leg muscle fatigue and plantar pressure distributions.

BACKGROUND: Physical activity may benefit health and reduce risk for chronic complications in normal and people with diabetes and peripheral vascular diseases. However, it is unclear whether leg muscle fatigue after weight-bearing physical activities, such as brisk walking, may increase risk for plantar tissue injury. In the literature, there is no evidence on the effect of muscle fatigue on plantar pressure after various walking intensities. The objectives of this study were to investigate the effects of various walking intensities on leg muscle fatigue and plantar pressure patterns. METHODS: A 3 × 2 factorial design, including 3 walking speeds (1.8 (slow and normal walking), 3.6 (brisk walking), and 5.4 (slow running) mph) and 2 walking durations (10 and 20 min) for a total of 6 walking intensities, was tested in 12 healthy participants in 3 consecutive weeks. The median frequency and complexity of electromyographic (EMG) signals of tibialis anterior (TA) and gastrocnemius medialis (GM) were used to quantify muscle fatigue. Fourier transform was used to compute the median frequency and multiscale entropy was used to calculate complexity of EMG signals. Peak plantar pressure (PPP) values at the 4 plantar regions (big toe, first metatarsal head, second metatarsal head, and heel) were calculated. RESULTS: Two-way ANOVA showed that the walking speed (at 1.8, 3.6, 5.4 mph) significantly affected leg muscle fatigue, and the duration factor (at 10 and 20 min) did not. The one-way ANOVA showed that there were four significant pairwise differences of the median frequency of TA, including walking speed of 1.8 and 3.6 mph (185.7 ± 6.1 vs. 164.9 ± 3.0 Hz, P = 0.006) and 1.8 and 5.4 mph (185.7 ± 6.1 vs. 164.5 ± 5.5 Hz, P = 0.006) for the 10-min duration; and walking speed of 1.8 and 3.6 mph (180.0 ± 5.9 vs. 163.1 ± 4.4 Hz, P = 0.024) and 1.8 and 5.4 mph (180.0 ± 5.9 vs. 162.8 ± 4.9 Hz, P = 0.023) for the 20-min duration. The complexity of TA showed a similar trend with the median frequency of TA. The median frequency of TA has a significant negative correlation with PPP on the big toe ( r = -0.954, P = 0.003) and the first metatarsal head ( r = -0.896, P = 0.016). CONCLUSIONS: This study demonstrated that brisk walking and slow running speeds (3.6 and 5.4 mph) cause an increase in muscle fatigue of TA compared to slow walking speed (1.8 mph); and the increased muscle fatigue is significantly related to a higher PPP.

Using Bidimensional Multiscale Entropy Analysis of Ultrasound Images to Assess the Effect of Various Walking Intensities on Plantar Soft Tissues.

Walking performance is usually assessed by linear analysis of walking outcome measures. However, human movements consist of both linear and nonlinear complexity components. The purpose of this study was to use bidimensional multiscale entropy analysis of ultrasound images to evaluate the effects of various walking intensities on plantar soft tissues. Twelve participants were recruited to perform six walking protocols, consisting of three speeds (slow at 1.8 mph, moderate at 3.6 mph, and fast at 5.4 mph) for two durations (10 and 20 min). A B-mode ultrasound was used to assess plantar soft tissues before and after six walking protocols. Bidimensional multiscale entropy (MSE2D) and the Complexity Index (CI) were used to quantify the changes in irregularity of the ultrasound images of the plantar soft tissues. The results showed that the CI of ultrasound images after 20 min walking increased when compared to before walking (CI4: 0.39 vs. 0.35; CI5: 0.48 vs. 0.43, p < 0.05). When comparing 20 and 10 min walking protocols at 3.6 mph, the CI was higher after 20 min walking than after 10 min walking (CI4: 0.39 vs. 0.36, p < 0.05; and CI5: 0.48 vs. 0.44, p < 0.05). This is the first study to use bidimensional multiscale entropy analysis of ultrasound images to assess plantar soft tissues after various walking intensities.

Dynamic changes in seating pressure gradient in wheelchair users with spinal cord injury.

Pressure ulcer interventions are commonly assessed with measures of seating interface pressure, such as peak pressure gradients (PPGs). Decreases in PPG magnitudes may reduce pressure ulcer risk by decreasing tissue deformation and increasing tissue perfusion of at-risk weight-bearing tissues. Changes in PPG directions, which have previously been overlooked in the seating pressure literature, may provide a transient increase in blood flow to at-risk tissues, even if the PPG magnitude and location remain the same. The purpose of this study was to assess both PPG components in response to combinations of wheelchair tilt and recline angles. Thirteen power wheelchair users were recruited into the study. Six combinations of wheelchair tilt (15°, 25°, and 35°) and recline (10° and 30°) were tested in random order. Each combination was tested with 5-min upright sitting, 5-min tilt and recline, and 5-min maximal pressure relief recovery. Changes in PPG magnitudes and PPG directions under the left ischial tuberosity were computed for the six angle combinations. The findings in this study suggested that when combining wheelchair tilt and recline, the recline function may be particularly useful in reducing PPG magnitudes, while the tilt function may be particularly useful in manipulating PPG directions.

Evaluating the Far-Infrared Radiation Bioeffects on Micro Vascular Dysfunction, Nervous System, and Plantar Pressure in Diabetes Mellitus.

The most frequent clinical complication is diabetes. Diabetes is characterized by elevated blood glucose levels resulting in sensory nerve damage or lesions. Diabetic foot wounds are often slow to heal and require medical attention and monitoring. This study evaluates the effect of far-infrared radiation on the microcirculation and plantar pressure in the diabetic foot. Ten diabetics and 4 nondiabetics were recruited in this study. The diabetic group was examined before and after the intervention in each month for 3 consecutive months. Four nondiabetic groups were also measured before and after the intervention for 2 weeks in each month. The surface temperature and blood flow in the diabetic foot was significantly improved (temperature: 32.1 ± 2.3°C vs 33.5 ± 2.2°C, P < .05; blood flow image: 118.3 ± 58.1 PU [perfusion unit] vs 50.4 ± 4.3 PU, P < .05). The sympathetic nerve activity index LF also increased from 40.8 ± 18.6% to 61.8 ± 13.5% (P = .07) in the second month. Plantar pressure tended to increase in the third month. This might indicate that far-infrared radiation could affect the mechanical properties of the plantar foot soft tissue. These results indicated that the effects of far-infrared radiation would improve blood circulation and change the soft tissue properties in the diabetic foot.

Using local scale exponent to characterize heart rate variability in response to postural changes in people with spinal cord injury.

Heart rate variability (HRV) is a promising marker for evaluating the remaining autonomic function in people with spinal cord injury (SCI). HRV is commonly assessed by spectral analysis and detrended fluctuation analysis (DFA). This study aimed to investigate whether local scale exponent α(t) can reveal new features of HRV that cannot be reflected by spectral measures and DFA coefficients. We studied 12 participants with SCI and 15 healthy able-bodied controls. ECG signals were continually recorded during 10 min sitting and 10 min prone postures. α(t) was calculated for scales between 4 and 60 s. Because α(t) could be overestimated at small scales, we developed an approach for correcting α(t) based on previous studies. The simulation results on simulated monofractal time series with α between 0.5 and 1.3 showed that the proposed method can yield improved estimation of α(t). We applied the proposed method to raw RR interval series. The results showed that α(t) in healthy controls monotonically decreased with scale at scales between 4 and 12 s (0.083-0.25 Hz) in both the sitting and prone postures, whereas in participants with SCI, α(t) slowly decreased at almost all scales. The sharp decreasing trend in α(t) in controls suggests a more complex dynamics of HRV in controls. α(t) at scales between 4 (0.25 Hz) and around 7 s (0.143 Hz) was lower in subjects with SCI than in controls in the sitting posture; α(t) at a narrow range of scales around 12 s (0.083 Hz) was higher in participants with SCI than in controls in the prone posture. However, none of normalized low frequency (0.04-0.15 Hz) power, the ratio of low frequency power to high frequency (0.15-0.4 Hz) power and long-term (>11 beats) DFA coefficient showed significant difference between healthy controls and subjects with SCI in the prone posture. Our results suggest that α(t) can reveal more detailed information in comparison to spectral measures and the standard DFA parameters.

A Parallel-Arm Randomized Controlled Trial to Assess the Effects of a Far-Infrared-Emitting Collar on Neck Disorder.

The purpose of this study is to assess the beneficial effects of a far-infrared-emitting collar (FIRC) on the management of neck disorders. A neck disorder is generalized as neck muscle pain and its relative mental disorders because the etiologies of the neck's multidimensional syndrome are either muscle impairment or psychiatric distress. This is the first study to determine the efficacy of a FIRC by evaluating objective physical evidence and psychometric self-reports using a parallel-arm randomized sham-controlled and single-blinded design. In this trial, 60 participants with neck disorders were observed at baseline and post-intervention. Compared to the placebo group after a 30-min intervention, the FIRC demonstrated a statistically significant biological effect in elevating skin temperature and promoting blood circulation with p-values 0.003 and 0.020, respectively. In addition, FIRC application significantly reduced neck muscle tension, relieved pain, ameliorated fatigue, improved depression, and decreased anxiety. The FIRC could therefore be a potential treatment for neck disorders.