Breath-by-breath O(2) uptake (VO2, L min(-1)) and blood lactate concentration were measured before, during exercise, and recovery in six kata and six kumite karate Word Champions performing a simulated competition. VO2max, maximal anaerobic alactic, and lactic power were also assessed. The total energy cost (VO2TOT mL kg(-1) above resting) of each simulated competition was calculated and subdivided into aerobic, lactic, and alactic fractions. Results showed that (a) no differences between kata and kumite groups in VO2max, height of vertical jump, and Wingate test were found; (b) VO2TOT were 87.8 +/- 6.6 and 82.3 +/- 12.3 mL kg(-1) in kata male and female with a performance time of 138 +/- 4 and 158 +/- 14 s, respectively; 189.0 +/- 14.6 mL kg(-1) in kumite male and 155.8 +/- 38.4 mL kg(-1) in kumite female with a predetermined performance time of 240 +/- 0 and 180 +/- 0 s, respectively; (c) the metabolic power was significantly higher in kumite than in kata athletes (p < or = 0.05 in both gender); (d) aerobic and anaerobic alactic sources, in percentage of the total, were significantly different between gender and disciplines (p < 0.05), while the lactic source was similar; (e) HR ranged between 174 and 187 b min(-1) during simulated competition. In conclusion, kumite appears to require a much higher metabolic power than kata, being the energy source with the aerobic contribution predominant.

Total and segmental body composition (fat mass, FM; fat-free mass, FFM; bone mineral density, BMD) were evaluated in 13 sedentary spinal cord injury (SCI) subjects and in 13 able-bodied healthy males (control, C) using dual X-ray absorptiometry (DXA) and skinfold methods. In the SCI group, total FM was significantly higher (31.1+/-8.2 vs. 20.8+/-6.9%) and total FFM was significantly lower (62.2+/-8.9 vs. 73.5+/-6.4%) than in C subjects. Total BMD did not differ between the SCI and C groups (1.20+/-0.11 vs. 1.30+/-0.11 g/cm(2)). In the SCI group, segmental FM was higher in the legs and trunk, whereas BMD was lower in legs only. The skinfold method significantly underestimated FM in the SCI group. Body composition is severely modified in paralyzed segments. The predictive equations developed for healthy populations appear to be inapplicable to SCI subjects.

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Background Wearable devices hold great promise, particularly for data generation for cutting-edge health research, and their demand has risen substantially in recent years. However, there is a shortage of aggregated insights into how wearables have been used in health research. Objective In this review, we aim to broadly overview and categorize the current research conducted with affordable wearable devices for health research. Methods We performed a scoping review to understand the use of affordable, consumer-grade wearables for health research from a population health perspective using the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) framework. A total of 7499 articles were found in 4 medical databases (PubMed, Ovid, Web of Science, and CINAHL). Studies were eligible if they used noninvasive wearables: worn on the wrist, arm, hip, and chest; measured vital signs; and analyzed the collected data quantitatively. We excluded studies that did not use wearables for outcome assessment and prototype studies, devices that cost >€500 (US $570), or obtrusive smart clothing. Results We included 179 studies using 189 wearable devices covering 10,835,733 participants. Most studies were observational (128/179, 71.5%), conducted in 2020 (56/179, 31.3%) and in North America (94/179, 52.5%), and 93% (10,104,217/10,835,733) of the participants were part of global health studies. The most popular wearables were fitness trackers (86/189, 45.5%) and accelerometer wearables, which primarily measure movement (49/189, 25.9%). Typical measurements included steps (95/179, 53.1%), heart rate (HR; 55/179, 30.7%), and sleep duration (51/179, 28.5%). Other devices measured blood pressure (3/179, 1.7%), skin temperature (3/179, 1.7%), oximetry (3/179, 1.7%), or respiratory rate (2/179, 1.1%). The wearables were mostly worn on the wrist (138/189, 73%) and cost <€200 (US $228; 120/189, 63.5%). The aims and approaches of all 179 studies revealed six prominent uses for wearables, comprising correlations—wearable and other physiological data (40/179, 22.3%), method evaluations (with subgroups; 40/179, 22.3%), population-based research (31/179, 17.3%), experimental outcome assessment (30/179, 16.8%), prognostic forecasting (28/179, 15.6%), and explorative analysis of big data sets (10/179, 5.6%). The most frequent strengths of affordable wearables were validation, accuracy, and clinical certification (104/179, 58.1%). Conclusions Wearables showed an increasingly diverse field of application such as COVID-19 prediction, fertility tracking, heat-related illness, drug effects, and psychological interventions; they also included underrepresented populations, such as individuals with rare diseases. There is a lack of research on wearable devices in low-resource contexts. Fueled by the COVID-19 pandemic, we see a shift toward more large-sized, web-based studies where wearables increased insights into the developing pandemic, including forecasting models and the effects of the pandemic. Some studies have indicated that big data extracted from wearables may potentially transform the understanding of population health dynamics and the ability to forecast health trends.