METHODS: Fifty-one participants performed the standard incremental treadmill exercise in a controlled laboratory setting with 12-lead ECG attached to the patient's body and wearing wrist-worn PPG trackers.

RESULTS: At each stage, the absolute percentage error of the PPG was within 10% of the standard acceptable range. Further analysis using a linear mixed model, which accounts for individual variations, revealed that PPG yielded the best performance at the baseline low-intensity exercise. As the stages progressed, heart rate validity decreased but was regained during recovery. The reliability was moderate to excellent.

METHODS: A pragmatic randomised controlled trial was conducted on 29 healthy sedentary adults (seven males and 22 females) in a 12-week exercise program. They were randomly assigned to group A (75 min/week, N.=15) or group B (150 min/week, N.=14) of moderate intensity aerobic exercise groups. HRR at 1-minute (HRR1), HRR at 2-minute (HRR2), and peak oxygen uptake (VO2peak) were measured pre- and post-intervention.

RESULTS: The improvements of HRR1 and HRR2 were seen in both groups but was only significant (P<0.05) for group A with HRR1, -4.07 bpm (post 24.47±6.42 - pre 20.40±5.51, P=0.018) and HHR2, -3.93 bpm (post 43.40±13.61 - pre 39.47±10.68, P=0.046). Group B showed increment of HRR1, -1.14 bpm (post 21.14±5.35 - pre 20.00±6.30, P=0.286) and HRR2, -2.5 bpm, (post 39.36±8.01 - pre 36.86±9.57, P=0.221). Improvement of the VO2peak was only significant in group B with an increment of 1.52±2.61 (P=0.049).

OBJECTIVE: The present study introduces an approach for assessing athlete physical fitness in training environments: the Internet of Things (IoT) and CPS-based Physical Fitness Evaluation Method (IoT-CPS-PFEM).

METHODS: The IoT-CPS-PFEM employs a range of IoT-connected sensors and devices to observe and assess the physical fitness of athletes. The proposed methodology gathers information on diverse fitness parameters, including heart rate, body temperature, and oxygen saturation. It employs machine learning algorithms to scrutinize and furnish feedback on the athlete's physical fitness status.

RESULTS: The simulation findings illustrate the efficacy of the proposed IoT-CPS-PFEM in identifying the physical fitness levels of athletes, with an average precision of 93%. The method under consideration aims to tackle the existing obstacles of conventional physical fitness assessment techniques, including imprecisions, time lags, and manual data-gathering requirements. The approach of IoT-CPS-PFEM provides the benefits of real-time monitoring, precision, and automation, thereby enhancing an athlete's physical fitness and overall performance to a considerable extent.

METHODS: We reviewed 22 previous studies that (1) empirically manipulated social support in a stressful situation, (2) measured CVR, and (3) tested a moderator of social support effects on CVR.

RESULTS: Although a majority of studies reported a CVR-mitigating effect of social support resulting in an overall significant combined p-value, we found that there were different effects of social support on CVR when we considered high- and low-engagement contexts. That is, compared to control conditions, social support lowered CVR in more engaging situations but had no significant effect on CVR in less engaging situations.

METHODS: Thirty healthy Muslim men participated in the study. Their electrocardiograms and EEGs were continuously recorded before, during, and after salat practice with a computer-based data acquisition system (MP150, BIOPAC Systems Inc., Camino Goleta, California). Power spectral analysis was conducted to extract the RPα and HRV components.

METHODS: In the Malaysian Health and Adolescents Longitudinal Research Team (MyHEART) study, 1071 healthy secondary school students, aged 13 years old, participated in the step test. Parameters for body composition measures were body mass index z-score, body fat percentage, waist circumference, and waist height ratio. The step test was conducted by using a modified Harvard step test. Heart rate recovery of 1 minute (HRR1min) and heart rate recovery of 2 minutes (HRR2min) were calculated by the difference between the peak pulse rate during exercise and the resting pulse rate at 1 and 2 minutes, respectively. Analysis was done separately based on gender. Pearson correlation analysis was used to determine the association between the HRR parameters with body composition measures, while multiple regression analysis was used to determine which body composition measures was the strongest predictor for HRR.

RESULTS: For both gender groups, all body composition measures were inversely correlated with HRR1min. In girls, all body composition measures were inversely correlated with HRR2min, while in boys all body composition measures, except BMI z-score, were associated with HRR2min. In multiple regression, only waist circumference was inversely associated with HRR2min (p=0.024) in boys, while in girls it was body fat percentage for HRR2min (p=0.008).

METHODS: Ninety-six adults (59.4 ± 9.1 years; 84% female; BMI 22.7 ± 1.6 kg/m2) with hypertension were randomized into one of four groups: Breathing Exercise (BE), High-Intensity Bodyweight Interval Training (HIBIT), Combined Exercise (CE), or a Non-Exercise Control (CON) group. The intervention lasted 10 weeks, with all exercise groups having the same total training time of 3 days per week (BE: 30 min/day; HIBIT: 60 min/day; CE: BE 30 min/day plus HIBIT 60 min/day). Resting heart rate, resting blood pressure, hand grip strength, cardiorespiratory fitness assessed using 6-Minute Walking Test (6MWT) and blood lipids were measured pre- and post-intervention.

RESULTS: The BE group showed the greatest reduction in systolic blood pressure (SBP) compared to CON, although differences among the exercise groups were not statistically significant. The increase in 6MWT values in the combined exercise group differed significantly compared to the other three groups (p = 0.000 and effect size = 0.296). The combined exercise group showed significant reductions in total cholesterol, LDL and triglyceride levels compared to the control group. The average reduction in total cholesterol levels was 20.8 mg/dL (95% C: -41.9 - 0.4) with an effect size of 0.103. Meanwhile, the decrease in LDL and triglyceride levels was 20.1 mg/dL (95% CI: -37.6--2.5; p = 0.014) and -40.4 mg/dL (95% CI: -82.1-1.3; p = 0.04) with effect sizes of 0.118 and 0.101.

CONCLUSIONS: In conclusion combined exercise for 10 weeks could lower systolic and diastolic blood pressure, increase CRF, and improved lipid profile. As a clinical implication, the results of this study can be an alternative or complementary approach to treatment for hypertension, potentially reducing the need for medications and their associated side effects.

TRIAL REGISTRATION: TCTR20230707003 ( http://www.

METHODS: GBS patients were consecutively recruited and the results were compared to age- and gender-matched healthy controls. A series of autonomic function tests including computation-dependent tests (power spectrum analysis of HRV and BRS at rest) and challenge maneuvers (deep breathing, eyeball compression, active standing, the Valsalva maneuver, sustained handgrip, and the cold pressor test) were performed.

RESULTS: Ten GBS patients (six men; mean age = 40.1 ± 13.9 years) and ten gender- and age-matched healthy controls were recruited. The mean GBS functional grading scale at disease plateau was 3.4 ± 1.0. No patients required intensive care unit admission or mechanical ventilation. Low-frequency HRV (p = 0.027), high-frequency HRV (p = 0.008), and the total power spectral density of HRV (p = 0.015) were significantly reduced in patients compared to controls. The mean up slope (p = 0.034), down slope (p = 0.011), and total slope (p = 0.024) BRS were significantly lower in GBS patients. The diastolic rise in blood pressure in the cold pressor test was significantly lower in GBS patients compared to controls (p = 0.008).