Validity of a Non-Proprietary Algorithm for Identifying Lying Down Using Raw Data from Thigh-Worn Triaxial Accelerometers.
Body postural allocation during daily life is important for health, and can be assessed with thigh-worn accelerometers. An algorithm based on sedentary bouts from the proprietary ActivePAL software can detect lying down from a single thigh-worn accelerometer using rotations of the thigh. However, it is not usable across brands of accelerometers. This algorithm has the potential to be refined. Aim: To refine and assess the validity of an algorithm to detect lying down from raw data of thigh-worn accelerometers. Axivity-AX3 accelerometers were placed on the thigh and upper back (reference) on adults in a development dataset (n = 50) and a validation dataset (n = 47) for 7 days. Sedentary time from the open Acti4-algorithm was used as input to the algorithm. In addition to the thigh-rotation criterion in the existing algorithm, two criteria based on standard deviation of acceleration and a time duration criterion of sedentary bouts were added. The mean difference (95% agreement-limits) between the total identified lying time/day, between the refined algorithm and the reference was +2.9 (-135,141) min in the development dataset and +6.5 (-145,159) min in the validation dataset. The refined algorithm can be used to estimate lying time in studies using different accelerometer brands.
['Hettiarachchi|Pasan|P|0000-0003-1377-1923', 'Aili|Katarina|K|', 'Holtermann|Andreas|A|0000-0003-4825-5697', 'Stamatakis|Emmanuel|E|0000-0001-7323-3225', 'Svartengren|Magnus|M|0000-0002-8165-7236', 'Palm|Peter|P|0000-0001-9354-6704']
D061725:Accelerometry D000328:Adult D000465:Algorithms D005260:Female D006801:Humans D011187:Posture D057185:Sedentary Behavior D013848:Thigh
posture ProPASS accuracy bedtime daily activity objective measurement physical activity physical behaviour sedentary behaviour