The purpose of the study was to determine allometric exponents for scaling grip strength in children that effectively control for body mass (BM) and stature (Ht) and to develop normative grip strength data for Hawaiian children. One thousand, four hundred thirty-seven students (754 boys) from a rural community in Hawaii participated in this 5-year study, resulting in 2,567 data points. Handgrip strength, BM, and Ht were collected every year. Multiple log-linear regression was used to determine allometric exponents for BM and Ht. Appropriateness of the allometric model was assessed through regression diagnostics, including normality of residuals and homoscedasticity. Allometrically scaled, ratio-scaled, and unscaled grip strength were then correlated with BM and Ht to examine the effectiveness of the procedure in controlling for body size. Allometric exponents for BM and Ht were calculated separately for each age group of boys and girls to satisfy the common exponent and group difference principles described by Vanderburgh. Unscaled grip strength had moderate to strong positive correlations with BM and Ht (p ≤ 0.05 for all) for all age groups. Ratio-scaled handgrip strength had significant moderate to strong negative correlations with BM (p ≤ 0.05 for all) and, to a lesser extent, Ht (p ≤ 0.05 for 8- to 12-year-old boys; p ≤ 0.05 for 8- to 12- and 14-year-old girls). Correlations between allometrically scaled handgrip strength and BM and Ht were not significant and approached zero. This study was the first to allometrically scale handgrip strength for BM and Ht in Hawaiian children. Allometric scaling applied to grip strength provides a useful expression of grip strength free of the confounding influence of body size.

The movements of the torso due to normal breathing could be harvested as an alternative, and renewable power source for an ultra-low power electronic device. The same output signal could also be recorded as a physiological signal containing information about breathing, thus enabling self-powered wearable biosensors/harvesters. In this paper, the selection criteria for such a biosensor, optimization procedure, trade-offs, and challenges as a sensor and harvester are presented. The empirical data obtained from testing different modules on a mechanical torso and a human subject demonstrated that an electromagnetic generator could be used as an unobtrusive self-powered medical sensor by harvesting more power, offering reasonable amount of output voltage for rectification purposes, and detecting respiratory effort.

Remote health monitoring is increasingly recognized as a valuable tool in chronic disease management. Continuous respiratory monitoring could be a powerful tool in managing chronic diseases, however it is infrequently performed because of obtrusiveness and inconvenience of the existing methods. The movements of the chest wall and abdominal area during normal breathing can be monitored and harvested to enable self-powered wearable biosensors for continuous remote monitoring. This paper presents human testing results of a light-weight (30 g), wearable respiratory effort energy harvesting sensor. The harvester output voltage, power, and its metabolic burden, are measured on twenty subjects in two resting and exercise conditions each lasting 5 min. The system includes two off-the-shelf miniature electromagnetic generators harvesting and sensing thoracic and abdominal movements. Modules can be placed in series to increase the output voltage for rectification purposes. Electromagnetic respiratory effort harvester/sensor system can produce up to 1.4 V, 6.44 mW, and harvests 30.4 mJ during a 5-min exercise stage. A statistical paired t-test analysis of the calculated EE confirmed there is no significant change ( P > 0.05 ) in the metabolic rate of subjects wearing the electromagnetic harvester and biosensor.

Background Non-exercise (N-EX) questionnaires have been developed to determine maximal oxygen consumption (VO2max) in healthy populations. There are limited reliable and validated N-EX questionnaires for the HIV+ population that provide estimates of habitual physical activity and not VO2max. Objectives To determine how well regression equations developed previously on healthy populations, including N-EX prediction equations for VO2max and age-predicted maximal heart rates (APMHR), worked on an HIV+ population; and to develop a specific N-EX prediction equation for VO2max and APMHR for HIV+ individuals. Methods Sixty-six HIV+ participants on stable HAART completed 4 N-EX questionnaires and performed a maximal graded exercise test. Results Sixty males and 6 females were included; mean (SD) age was 49.2 (8.2) years; CD4 count was 516.0 ± 253.0 cells·mn−3; and 92% had undetectable HIV PCR. Mean VO2max was 29.2 ± 7.6 (range, 14.4–49.4) mL·kg−1·min−1. Despite positive correlations with VO2max, previously published N-EX VO2max equations produced results significantly different than actual VO2 scores (P < .0001). An HIV+ specific N-EX equation was developed and produced similar mean VO2max values, R = 0.71, when compared to achieved VO2max (P = .53). Conclusion HIV+ individuals tend to be sedentary and unfit, putting them at increased risk for the development of chronic diseases associated with a sedentary lifestyle. Based on the level of error associated with utilizing APMHR and N-EX VO2max equations with HIV+ individuals, neither should be used in this population for exercise prescription.

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