Can an Inertial Measurement Unit, Combined with Machine Learning, Accurately Measure Ground Reaction Forces in Cricket Fast Bowling? - McGrath, Joseph W; Neville, Jonathon; Stewart, Tom; Lamb, Matt; Alway, Peter; King, Mark; Cronin, John (Taylor and Francis Group, 2023)
This study examined whether an inertial measurement unit (IMU) could measure ground reaction force (GRF) during a cricket fast bowling delivery. Eighteen male fast bowlers had IMUs attached to their upper back and bowling wrist. Each participant bowled 36 deliveries, split into three different intensity zones: low = 70% of maximum perceived bowling effort, medium = 85%, and high = 100%. A force plate was embedded into the bowling crease to measure the ground truth GRF. Three machine learning models were used to estimate GRF from the IMU data. The best results from all models showed a mean absolute percentage error of 22.1% body weights (BW) for vertical and horizontal peak force, 24.1% for vertical impulse, 32.6% and 33.6% for vertical and horizontal loading rates, respectively. The linear support vector machine model had the most consistent results. Although results were similar to other papers that have estimated GRF, the error would likely prevent its use in individual monitoring. However, due to the large differences in raw GRFs between participants, researchers may be able to help identify links among GRF, injury, and performance by categorising values into levels (i.e., low and high).
Keywords: IMU; injury prevention; performance enhancement; sports technology; wearable sensors; IMU; injury prevention; performance enhancement; sports technology; wearable sensors; 42 Health Sciences; 4207 Sports Science and Exercise; 0913 Mechanical Engineering; 1106 Human Movement and Sports Sciences; 1303 Specialist Studies in Education; Sport Sciences; 3202 Clinical sciences; 4207 Sports science and exercise