Validation of an open-source ambulatory assessment system in support of replicable activity studies

Abstract

Purpose: Inertial-based trackers have become a common tool in data capture for ambulatory studies that aim at characterizing physical activity. Many systems that perform remote recording of accelerometer data use commercial trackers and black-box aggregation algorithms, often resulting in data that are locked into proprietary formats and metrics that make later replication or comparison difficult. Methods: The primary purpose of this manuscript is to validate an open-source ambulatory assessment system that consists of hardware devices, algorithms, and software components of our approach. We report on two validation experiments, one lab-based treadmill study on a convenience sample of 16 volunteers and one ’in vivo’ study with 28 volunteers suffering from diabetes or cardiovascular disease. Results: A comparison between data from ActiGraph GT9X trackers and our proposed system reveals that the original inertial sensor signals at the wrist strongly correlate (Pearson correlation coefficients for raw inertial sensor signals of 0.97 in the controlled treadmill-walking setting) and that estimated steps from an open-source wrist-based detection approach correlate with the hip-worn ActiGraph output (average Pearson correlation coefficients of 0.81 for minute-wise comparisons of detected steps) in day-long ambulatory data. Conclusion: Recording inertial sensor data in a standardized form and relying on open-source algorithms on these data form a promising methodology that ensures that datasets can be replicated or enriched long after the wearable trackers have been decommissioned.