Arrhythmia is one kind of diseases that gives rise to the death and possibly forms the immedicable danger. The most common cardiac arrhythmia is the ventricular premature beat. The main purpose of this study is to develop an efficient arrhythmia detection algorithm based on the morphology characteristics of arrhythmias using correlation coefficient in ECG signal. Subjects for experiments included normal subjects, patients with atrial premature contraction (APC), and patients with ventricular premature contraction (PVC). So and Chan's algorithm was used to find the locations of QRS complexes. When the QRS complexes were detected, the correlation coefficient and RR-interval were utilized to calculate the similarity of arrhythmias. The algorithm was tested using MIT-BIH arrhythmia database and every QRS complex was classified in the database

This study investigated the therapeutic effect of the far-infrared ray-emitting belt (FIRB) in the management of primary dysmenorrhea in female patients. Forty adolescent females with primary dysmenorrhea were enrolled in the study. Quantitative measurements were taken during the menstruation. Several parameters were measured and compared, including temperature, abdominal blood flow, heart rate variability, and pain assessment. Statistical analysis shows that treatment with FIRB had significant efficiency in increasing regional surface temperature and abdominal blood flow, widening standard deviation of normal-to-normal RR intervals, and reducing VRS and NRS pain scores. The application of an FIRB appears to alleviate dysmenorrhea.

Exercise has been demonstrated to improve health in people with diabetes. However, exercise may increase risk for foot ulcers because of increased plantar pressure during most weight-bearing physical activities. To date, there is no study investigating the effect of various walking speeds and durations (i.e., the most common form of exercise in daily living) on the plantar foot. The objective of this study was to investigate the effect of various walking intensities on plantar tissue stiffness. A 3 × 2 factorial design, including three walking speeds (1.8, 3.6 and 5.4 mph) and two durations (10 and 20 min), was tested in 12 healthy participants. B-mode and elastographic ultrasound images were measured from the first metatarsal head to quantify plantar tissue stiffness after walking. Two-way ANOVA was used to examine the results. Our results showed that the walking speed factor caused a significant main effect of planar stiffness of the superficial layers (p = 0.007 and 0.003, respectively). However, the walking duration factor did not significantly affect the plantar stiffness. There was no interaction between the speed and duration factors on plantar tissue stiffness. Regarding the walking speed effect, there was a significant difference in the plantar stiffness between 1.8 and 3.6 mph (56.8 ± 0.8% vs. 53.6 ± 0.9%, p = 0.017) under 20 min walking duration. This finding is significant because moderate-to-fast walking speed (3.6 mph) can decrease plantar stiffness compared to slow walking speed (1.8 mph). This study suggests people at risk for foot ulcers walk at a preferred or fast speed (3.6 mph) rather than walk slowly (1.8 mph).

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.

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.

Cerebral autoregulation (CA) was assessed by chaotic analysis based on mean arterial blood pressure (MABP) and mean cerebral blood flow velocity (MCBFV) in 19 diabetics with autonomic neuropathy (AN) and 11 age-matched normal subjects. MABP in diabetics dropped significantly in response to tilting (91.6 +/- 14.9 vs. 74.1 +/- 13.4 mmHg, P < 0.05). Valsalva ratio of heart rate was reduced in diabetics compared to normal (1.1 +/- 0.1 vs. 1.5 +/- 0.2, P < 0.05). It indicated AN affects the vasomotor tone of peripheral vessels and baroreflex. Nonlinear results showed higher correlation dimension values of MABP and MCBFV in diabetics compared to normal, especially MABP (3.7 +/- 2.3 vs. 2.0 +/- 0.8, P < 0.05). It indicated CA is more complicated in diabetics. The lower Lyapunov exponent and the higher Kolmogorov entropy values in diabetics indicated less predictable behavior and higher chaotic degree. This study suggests impaired autoregulation would be more chaotic and less predictable.

: Participation in various physical activities requires successful postural control in response to the changes in position of our body. It is important to assess postural control for early detection of falls and foot injuries. Walking at various speeds and for various durations is essential in daily physical activities. The purpose of this study was to evaluate the changes in complexity of the center of pressure (COP) during walking at different speeds and for different durations. In this study, a total of 12 participants were recruited for walking at two speeds (slow at 3 km/h and moderate at 6 km/h) for two durations (10 and 20 minutes). An insole-type plantar pressure measurement system was used to measure and calculate COP as participants walked on a treadmill. Multiscale entropy (MSE) was used to quantify the complexity of COP. Our results showed that the complexity of COP significantly decreased (p < 0.05) after 20 min of walking (complexity index, CI = −3.51) compared to 10 min of walking (CI = −3.20) while walking at 3 km/h, but not at 6 km/h. Our results also showed that the complexity index of COP indicated a significant difference (p < 0.05) between walking at speeds of 3 km/h (CI = −3.2) and 6 km/h (CI = −3.6) at the walking duration of 10 minutes, but not at 20 minutes. This study demonstrated an interaction between walking speeds and walking durations on the complexity of COP.

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