Linear Relationships Among the Hand and Clubhead Motion Characteristics in Golf Driving in Skilled Male Golfers.

The purpose of this study was to investigate the linear relationships among the hand/clubhead motion characteristics in golf driving in skilled male golfers (n = 66; handicap ≤ 3). The hand motion plane (HMP) and functional swing plane (FSP) angles, the HMP-FSP angle gaps, the planarity characteristics of the off-plane motion of the clubhead, and the attack angles were computed from the drives captured by an optical motion capture system. The HMP angles were identified as the key variables, as the HMP and FSP angles were intercorrelated, but the plane angle gaps, the planarity bias, and the attack angles showed correlations to the HMP angles primarily. Three main swing pattern clusters were identified. The parallel HMP-FSP alignment pattern with a small direction gap was associated with neutral planarity and planar swing pattern. The inward alignment pattern with a large inward direction gap was characterized by flat planes, follow-through-centric planarity, spiral swing pattern, and inward/downward impact. The outward alignment pattern with a large outward direction gap was associated with steep planes, downswing-centric planarity, reverse spiral swing, and outward/upward impact. The findings suggest that practical drills targeting the hand motion pattern can be effective in holistically reprogramming the swing pattern.

Predicting vertical ground reaction force during running using novel piezoresponsive sensors and accelerometry.

Running is a common exercise with numerous health benefits. Vertical ground reaction force (vGRF) influences running injury risk and running performance. Measurement of vGRF during running is now primarily constrained to a laboratory setting. The purpose of this study was to evaluate a new approach to measuring vGRF during running. This approach can be used outside of the laboratory and involves running shoes instrumented with novel piezoresponsive sensors and a standard accelerometer. Thirty-one individuals ran at three different speeds on a force-instrumented treadmill while wearing the instrumented running shoes. vGRF was predicted using data collected from the instrumented shoes, and predicted vGRF were compared to vGRF measured via the treadmill. Per cent error of the resulting predictions varied depending upon the predicted vGRF characteristic. Per cent error was relatively low for predicted vGRF impulse (2-7%), active peak vGRF (3-7%), and ground contact time (3-6%), but relatively high for predicted vGRF load rates (22-29%). These errors should decrease with future iterations of the instrumented shoes and collection of additional data from a more diverse sample. The novel technology described herein might become a feasible way to collect large amounts of vGRF data outside of the traditional biomechanics laboratory.

Estimation of 3D Ground Reaction Force Using Nanocomposite Piezo-Responsive Foam Sensors During Walking.

This paper describes a method for the estimation of the 3D ground reaction force (GRF) during human walking using novel nanocomposite piezo-responsive foam (NCPF) sensors. Nine subjects (5 male, 4 female) walked on a force-instrumented treadmill at 1.34 m/s for 120 s each while wearing a shoe that was instrumented with four NCPF sensors. GRF data, measured via the treadmill, and sensor data, measured via the NCPF inserts, were used in a tenfold cross validation process to calibrate a separate model for each individual. The calibration model estimated average anterior-posterior, mediolateral and vertical GRF with mean average errors (MAE) of 6.52 N (2.14%), 4.79 N (6.34%), and 15.4 N (2.15%), respectively. Two additional models were created using the sensor data from all subjects and subject demographics. A tenfold cross validation process for this combined data set resulted in models that estimated average anterior-posterior, mediolateral and vertical GRF with less than 8.16 N (2.41%), 6.63 N (7.37%), and 19.4 N (2.31%) errors, respectively. Intra-subject estimates based on the model had a higher accuracy than inter-subject estimates, likely due to the relatively small subject cohort used in creating the model. The novel NCPF sensors demonstrate the ability to accurately estimate 3D GRF during human movement outside of the traditional biomechanics laboratory setting.