Background: The ability to jump has been related to muscle strength and power, speed and amplitude of the lower limbs movements, and specifically for the elderly, the vertical jump has been shown to be a good predictor of functional capacity and risk of falling. The use of a mobile application (App) which can measure the vertical jump (i.e., iPhone App My Jump) has recently emerged as a simple, cheap and very practical tool for evaluation of jump ability. However, the validity of this tool for the elderly population has not been tested yet. The elderly usually perform very low jumps and therefore the signal-to-noise ratio may compromise the validity and reliability of this method. Thus, the aim of the current study was to verify the validity and reliability of the iPhone App “My Jump” for the evaluation of countermovement jump (CMJ) height within an elderly population. Methods: After familiarization, 41 participants performed three CMJs assessed via a contact mat and the My Jump App. The intraclass correlation coefficient (ICC) was used to verify the relative reliability, while the coefficient of variation (CV%) and the typical error of measurement (TEM) were used to verify the absolute reliability. Pearson’s correlation coefficient was used to verify the strength of the relationship between methods (i.e., concurrent validity), a Bland–Altman plot to show their agreement, and the Student’s t-test to identify systematic bias between them. For reliability analyses, all jumps were considered (i.e., 123). All jumps (i.e., 123), the average height of each attempt (i.e., 41), and the highest jump, were considered for validity analyses. Results: The CMJ height of the highest jump was 10.78 ± 5.23 cm with contact mat, and 10.87 ± 5.32 with My Jump App, with an identified systematic bias of 0.096 cm (P = 0.007). There was a nearly perfect correlation between methods (r = 0.999; P = 0.000, in all cases) with a very good agreement observed (0.3255 to −0.5177 cm, 0.2797 to −0.5594 cm, and 0.3466 to −0.6264 cm, for highest jump height, average jump height, and all jump heights, respectively). The ICC of the My Jump App was 0.948, the TEM was 1.150 cm, and the CV was 10.10%. Conclusion: Our results suggest that the My Jump App is a valid and reliable tool compared to the contact mat for evaluating vertical jump performance in the elderly. Therefore, it allows a simple and practical assessment of lower limbs’ power in this population. For the elderly, as well as for other populations with low jumping heights, the highest jump height and the average jump height could be used indistinctly.

The root mean square of successive differences (RMSSD) of R‐R intervals, the most robust vagal modulation parameter of heart rate variability (HRV), has been proposed as a marker of global health and training adaptations. The weekly averaging of RMSSD and its natural logarithm (LnRMSSD) has been adopted to enhance detection of training‐induced adaptations. We assessed measures of aerobic fitness, body composition, objective physical activity (PA), and daily LnRMSSD recordings during different conditions, such as supine rest, seated rest, standing and walking at 5 km/h, over a week in 34 healthy young individuals of both sexes (age: 22 ± 4 yr; body fatness: 20 ± 8%; estimated VO₂max: 40 ± 8 mL·kg⁻¹·min⁻¹). The day‐to‐day reliability and agreement among LnRMSSD averages over 5, 4, 3, 2 and a single‐day value per condition were assessed, while correlations between LnRMSSD, aerobic fitness, body composition, and PA were also examined. Poor to good day‐to‐day reliability, and moderate to excellent agreement were observed for LnRMSSD recordings for diverse conditions with a minimum of two daily recordings in the supine condition, and three in the other conditions achieving excellent agreement for weekly HRV assessment. Several correlations between LnRMSSD, aerobic fitness, body composition, and PA were revealed, with stronger observed associations during walking. Utilisation of weekly HRV (average of 2–3 daily recordings), as described in the current study, may provide practitioners with a tool to assess weekly vagal modulations for health and performance purposes. Walking HRV recordings may be a practical alternative to other conditions for the investigation of cardiac autonomic function.

Background: The association between heart rate variability (HRV), training load (TL), and performance is poorly understood. Methods: A middle-aged recreational female runner was monitored during a competitive 20-wk macrocycle divided into first (M1) and second mesocycle (M2) in which best performances over 10 km and 21 km were recorded. Volume (km), session rating of perceived exertion (sRPE), TL, and monotony (mean TL/SD TL) were the workload parameters recorded. The root mean square of the successive differences in R-R intervals (RMSSD), its coefficient of variation (RMSSDcv), and the RMSSD:RR ratio were the HRV parameters monitored. Results: During M2, RMSSD (p = 0.006) and RMSSD:RR (p = 0.002) were significantly increased, while RR was significantly reduced (p = 0.017). Significant correlations were identified between monotony and volume (r = 0.552; p = 0.012), RR (r = 0.447; p = 0.048), and RMSSD:RR (r = −0.458; p = 0.042). A sudden reduction in RMSSD (from 40.31 to 24.34 ms) was observed the day before the first symptoms of an influenza. Conclusions: The current results confirm the practicality of concurrent HRV and sRPE monitoring in recreational runners, with the RMSSD:RR ratio indicative of specific adaptations. Excessive training volume may be associated to both elevated monotony and reduced RMSSD:RR. Identification of mesocycle patterns is recommended for better individualization of the periodization used.

Background: Depression is associated with a decreased cardiorespiratory fitness, and physical activity [PA] levels, higher rates of obesity, and dysfunction in autonomic control of heart rate [HR]. However, these parameters were mostly recorded with indirect methods. Thus, the aim of the current study was to investigate the relationships between depression scores and objective measures of body fatness, autonomic indices (i.e. HRV and HRR), cardiorespiratory fitness and PA levels; and subsequently to present the best predictive models of depression scores for this population, based on these variables. Methods: Thirty-five non-exercising women (26–43 years; maximal oxygen consumption [VO₂max] ~ 17.4–38.3 mL/kg/min) volunteered for participation in this study. All participants responded to the Beck Depression Inventory [DBI] and were evaluated for body mass index [BMI], percentage of body fat, sum of skinfolds, and VO₂max. Subsequently, over four consecutive days, an orthostatic test and a submaximal exercise on a cycle ergometer were performed to record HRV and HRR, respectively. In addition, incidental PA was recorded during 5 consecutive days using accelerometers. Results: depression scores were related to VO₂max (r = −0.446, p = 0.007) and the sum of skinfolds (r = 0.434, p = 0.009). Several stepwise multiple linear regression models were performed and only VO₂max was revealed as an independent predictor of the Beck scores (ß = −0.446, R² = 0.199, p = 0.007). Conclusion: The present study revealed that VO₂max and the sum of skinfolds were moderately related to depression scores, while VO₂max was the only independent predictor of depression scores in female workers.