Wrist-worn Accelerometry for Runners: Objective Quantification of Training Load

Purpose This study aimed to apply open-source analysis code to raw habitual physical activity data from wrist-worn monitors to: 1) objectively, unobtrusively, and accurately discriminate between running and nonrunning days; and 2) develop and compare simple accelerometer-derived metrics of external training load with existing self-report measures. Methods Seven-day wrist-worn accelerometer (GENEActiv; Activinsights Ltd, Kimbolton, UK) data obtained from 35 experienced runners (age, 41.9 11.4 yr; height, 1.72 0.08 m; mass, 68.5 +/- 9.7 kg; body mass index, 23.2 +/- 2.2 kgm(-2); 19 [54%] women) every other week over 9 to 18 wk were date-matched with self-reported training log data. Receiver operating characteristic analyses were applied to accelerometer metrics (Average Acceleration, Most Active-30mins, Mins400 mg) to discriminate between running and nonrunning days and cross-validated (leave one out cross-validation). Variance explained in training log criterion metrics (miles, duration, training load) by accelerometer metrics (Mins400 mg, workload (WL) 400-4000 mg) was examined using linear regression with leave one out cross-validation. Results Most Active-30mins and Mins400 mg had >94% accuracy for correctly classifying running and nonrunning days, with validation indicating robustness. Variance explained in miles, duration, and training load by Mins400 mg (67%-76%) and WL400-4000 mg (55%-69%) was high, with validation indicating robustness. Conclusions Wrist-worn accelerometer metrics can be used to objectively, unobtrusively, and accurately identify running training days in runners, reducing the need for training logs or user input in future prospective research or commercial activity tracking. The high percentage of variance explained in existing self-reported measures of training load by simple, accelerometer-derived metrics of external training load supports the future use of accelerometry for prospective, preventative, and prescriptive monitoring purposes in runners.