Merrill D. Funk

Tennis forehand kinematics change as post-impact ball speed is altered

Peak joint angles and joint angular velocities were evaluated for varying speed forehands in an attempt to better understand what kinematic variables are most closely related to increases in post-impact ball velocity above 50% of maximal effort. High-speed video was used to measure three-dimensional motion for 12 highly skilled tennis players who performed forehands at three different post-impact ball speeds: fast (42.7 ± 3.8 m/s), medium (32.1 ± 2.9 m/s), and slow (21.4 ± 2.0 m/s). Several dominant-side peak joint angles (prior to ball impact) increased as post-impact ball speed increased from slow to fast: wrist extension (16%), trunk rotation (28%), hip flexion (38%), knee flexion (27%), and dorsiflexion (5%). Between the aforementioned peak joint angles and ball impact, dominant-side peak angular velocities increased as ball speed increased from slow to fast: peak wrist flexion (118%), elbow flexion (176%), trunk rotation (99%), hip extension (143%), knee extension (56%), and plantarflexion (87%). Most kinematic variables changed as forehand ball speed changed; however, some variables changed more than others, indicating that range of motion and angular velocity for some joints may be more closely related to post-impact ball speed than for other joints.

Comparison of Smartphone Pedometer Apps on a Treadmill versus Outdoors: 1755 Board #6 June 1 1

Previous research has focused on the accuracy of smartphone pedometer apps in laboratory settings, however less information is available in outdoor (free living) environments. PURPOSE: Determine the accuracy of 5 smartphone apps at recording steps at a walking speed in a laboratory versus an outdoor setting. METHODS: Twenty-three healthy college students consented (Mean±SD; 22±3.8yrs; BMI 24.9±4.13kg/m2) to participate in 2 separate visits. During the first visit participants walked 500 steps at 3mph on a treadmill while wearing a pedometer and a smartphone placed in the pocket using 5 pedometer apps concurrently (Moves, Google Fit (G-Fit), Runtastic, Accupedo, S-Health). During the second visit, participants walked 400 meters at 3mph on a sidewalk outside. Actual steps for each visit were recorded using a hand tally counter device. Zero and negative values were replaced with the mean value for that trial. Statistical analyses were performed using IBM SPSS 23.0. Mean bias scores were calculated between the step count for each app and the respective tally count for each trial. Mean bias scores were correlated between trials for each app using Pearson correlations and significance was set at p<0.05. Mean Absolute Percent Error (MAPE) values were also calculated for each app for both trials. RESULTS: G-Fit recorded 2 zero values and 2 negative values and Moves recorded 1 zero value. Mean bias scores were significantly correlated between the indoor and outdoor protocols for the pedometer (r=0.67, p<0.01) and S-Health (r=0.46, p<0.5). The remaining apps were not correlated between protocols. The outdoor protocol producing a greater mean bias for the outdoor protocol for G-Fit, Runtastic, and Accupedo (mean bias ± SD indoor, outdoor; -4.3±53.1, -19.3±120.0; -10.7±63.3, -33.4±118.7; 16.0±143.6, 79.0±75.0; respectively) and a greater mean bias for the indoor protocol for the pedometer, Moves, and SHealth (mean bias indoor, outdoor; -1.4±41.5, 0.0±34.1; -117.4±196.7, -42.2±209.6; 11.3±28.4, 0.0±58.7; respectively). MAPE was below 5% for the pedometer and S-Health for both trials. CONCLUSION: Apps with the lowest error in a controlled setting may be less affected when used in other settings, while apps with greater variation in a controlled setting may be affected when used in a different environment.

: 1363 Board #38 June 1 9

Numerous physical activity monitors exist and are used to track and improve fitness levels. Due to the increasing popularity of these devices, newer products have been developed that measure heart rate (HR) at the wrist. Little is known about how accurate these devices are at measuring HR at the wrist and how they compare to each other. PURPOSE: To determine how accurately HR was measured by three different wrist-worn physical activity monitors. METHODS: Recreationally active men (n=9) and women (n=3) participated in this study. The average age and weight of participants was 22 ± 3 years and 73.9 ± 12 kg. TomTom Cardio (TT), Fitbit Surge (FB) and Microsoft Band (MB) physical activity monitors were used. The TT, FB, and MB were randomly assigned to the right or left wrist for each participant. The testing procedure included speeds of 2, 3, 4, 5, and 6 mph with each speed lasting three minutes. HR was measured by electrocardiography (ECG) using standard limb lead II and by the three different physical activity monitors. HR was recorded from each device every minute throughout the duration of the procedure. Pearson product moment correlations and bias between electrocardiography (ECG) and physical activity monitors with 95% limits of agreement (Bland-Altman analysis) were calculated. Repeated measures ANOVA [Speed x Device] were also calculated. Statistical significance was set at p<0.05. RESULTS: At 2 mph and 3 mph, only TT HR was significantly correlated with ECG heart rate (r=0.693, p=0.012 and r=0.592, p=0.043). At 4 mph and 6 mph TT was significantly correlated with ECG (r=0.911, p<0.001 and r=0.853, p<0.001). Significant correlations were calculated between FB and ECG at 4 mph (r=0.691, p=0.013), 5 mph (r=0.953, p<0.001) and 6 mph (r=0.924, p<0.001). Only FB had a significantly different HR than the ECG at 2 mph (99 vs 85 bpm, p=0.037). The largest mean bias was found between ECG and FB at 2 mph [-13 bpm ± 24 bpm (95% limits of agreement)], while the smallest mean bias was found between TT and ECG [-2 bpm ± 12 bpm (95% limits of agreement)]. CONCLUSION: With increasing speeds, physical activity monitors more accurately measure HR but individuals should be aware that these devices may overestimate HR during slower walking speeds.

Accuracy of Fitbit Charge 2 Worn at Different Wrist Locations During Exercise: 1360 Board #35 June 1 9

Many newly released activity monitors use heart rate measured at the wrist to estimate exercise intensity, however, where the device is placed on the wrist may affect accuracy of the measurement. PURPOSE: To determine whether the Pure Pulse technology on the Fitbit Charge 2 will show different heart rate readings when placed on the recommended exercise position compared to the all-day wear position at various exercise intensities. METHODS: Thirty-five participants (MEAN ± SD; 22.0 ± 2.9yrs; 23.9 ± 2.6kg/m2; 18 male) consented to participate in a single visit where two Fitbit Charge 2 devices were placed on the non-dominant wrist. Fitbit A was placed 2-3 fingers above the wrist bone. Fitbit B was placed directly above the wrist bone. The treadmill was set at 3 mph with 0% grade. Participants remained at this speed for 4 minutes. Heart rate measurements were taken at the last 10 seconds of each stage from both Fitbits and a polar heart rate monitor (chest strap). The same procedure was followed for 5 and 6 mph. Statistical analyses were performed using IBM SPSS 23.0. A Two-way (speed x location) Repeated Measures ANOVA was used to examine mean differences. Pairwise comparisons with Bonferroni correction were used in post-hoc analysis. Pearson correlations and mean bias between polar heart rate monitor and activity monitors were also calculated for each speed. RESULTS: Repeated Measures ANOVA found significant differences between speeds (p<0.01) and location (p<0.01), but not for the interaction (p=0.234). Pairwise comparisons indicated significant differences between each speed (p<0.01) and between the polar monitor and Fitbit B (p<0.05), but not between the polar monitor and Fitbit A (p=0.608). Pearson correlations indicated strong correlations between each Fitbit and the polar monitor (r= .58-.91; all p<0.01). Mean bias decreased as speed increased for Fitbit A (mean bias BPM ± SD; -1.1 ± 5.4; -1.9 ± 9.5; -0.4 ± 6.9; -0.3 ± 7.3 for resting, 3mph, 5mph, 6mph respectively) while mean bias for Fitbit B increased as speed increased (-2.8 ± 8.8; -3.1 ± 11.1; -3.9 ± 14.6; 6.7 ± 14.3 for resting, 3mph, 5mph, 6mph respectively). CONCLUSION: Wrist-worn heart rate monitors appear to provide values adequate for recreational use, however, following recommended guidelines on wear-position may impact heart rate readings.