A method to compare new and traditional accelerometry data in physical activity monitoring

Abstract

The accelerometer devices as traditionally used in the epidemiological field for physical activity monitoring (e.g. Actigraph, Actical, and RT3) provide manufacturer-dependent output values called counts that are computed by obscure and proprietary signal processing techniques. This lack of transparency poses a challenge for comparison of historical accelerometer data in counts with data collected using raw accelerometry in S.I. units — m/s2. The purpose of this study was to develop a method that facilitates the compatibility between both methods through conversion of raw accelerometer output data collected with inertial acceleration sensors into Actigraph counts — the most widely used (de facto standard) device brand in epidemiological studies. The basics of the conversion algorithm were captured from the technical specifications of the Actigraph GT1M. Fine-tuning of the algorithm was achieved empirically under controlled conditions using a mechanical shaker device. A pilot evaluation was carried out through physical activity monitoring in free-living scenarios of 19 adult participants (age: 47 ± 11 yrs, BMI: 25.2 ± 4.1 kg-m−2) wearing both devices. The results show that Actigraph counts estimated by the proposed method explain 94.2% of the variation in Actigraph counts (p < 0.001). The concordance correlation coefficient was 0.93 (p < 0.05). The sensitivity for classifying intensity ranged from 93.4% for light physical activity to 70.7% for moderate physical activity.