An Exploratory Study on the Use of Concentric Velocities in the Back Squat as a Monitoring Tool

Abstract available in the 9th Annual Coaches and Sport Science College

Utilizing Weightlifting for Cycling Performance

Abstract available in the 9th Annual Coaches and Sport Science College

Ideal Combinations of Acceleration-Based Intensity Metrics and Sensor Positions to Monitor Exercise Intensity under Different Types of Sports

This study quantified the strength of the relationship between the percentage of heart rate reserve (%HRR) and two acceleration-based intensity metrics (AIMs) at three sensor-positions during three sport types (running, basketball, and badminton) under three intensity conditions (locomotion speeds). Fourteen participants (age: 24.9 ± 2.4 years) wore a chest strap HR monitor and placed three accelerometers at the left wrist (non-dominant), trunk, and right shank, respectively. The %HRR and two different AIMs (Player Load per minute [PL/min] and mean amplitude deviation [MAD]) during exercise were calculated. During running, both AIMs at the shank and PL at the wrist had strong correlations (r = 0.777–0.778) with %HRR; while other combinations were negligible to moderate (r = 0.065–0.451). For basketball, both AIMs at the shank had stronger correlations (r = 0.604–0.628) with %HRR than at wrist (r = 0.536–0.603) and trunk (r = 0.403–0.463) with %HRR. During badminton exercise, both AIMs at shank had stronger correlations (r = 0.782–0.793) with %HRR than those at wrist (r = 0.587–0.621) and MAD at trunk (r = 0.608) and trunk (r = 0.314). Wearing the sensor on the shank is an ideal position for both AIMs to monitor external intensity in running, basketball, and badminton, while the wrist and using PL-derived AIM seems to be the second ideal combination

The Validity and Reliability of a Tire Pressure-Based Power Meter for Indoor Cycling

The purpose of this study was to evaluate the validity and reliability of a tire pressure sensor (TPS) cycling power meter against a gold standard (SRM) during indoor cycling. Twelve recreationally active participants completed eight trials of 90 s of cycling at different pedaling and gearing combinations on an indoor hybrid roller. Power output (PO) was simultaneously calculated via TPS and SRM. The analysis compared the paired 1 s PO and 1 min average PO per trial between devices. Agreement was assessed by correlation, linear regression, inferential statistics, effect size, and Bland–Altman LoA. Reliability was assessed by ICC and CV comparison. TPS showed near-perfect correlation with SRM in 1 s (r(s) = 0.97, p < 0.001) and 1-min data (r(s) = 0.99, p < 0.001). Differences in paired 1 s data were statistically significant (p = 0.04), but of a trivial magnitude (d = 0.05). There was no significant main effect for device (F(1,9) = 0.05, p = 0.83, [Formula: see text] = 0.97) in 1 min data and no statistical differences between devices by trial in post hoc analysis (p < 0.01–0.98; d < 0.01–0.93). Bias and LoA were −0.21 ± 16.77 W for the 1 min data. Mean TPS bias ranged from 3.37% to 7.81% of the measured SRM mean PO per trial. Linear regression SEE was 7.55 W for 1 min TPS prediction of SRM. ICC(3,1) across trials was 0.96. No statistical difference (p = 0.09–0.11) in TPS CV (3.6–5.0%) and SRM CV (4.3–4.7%). The TPS is a valid and reliable power meter for estimating average indoor PO for time periods equal to or greater than 1 min and may have acceptable sensitivity to detect changes under less stringent criteria (±5%)