Development and validation of a tool to measure physical activity, posture and sleep – ActiPASS
The aim of this project is to develop and validate algorithms and software tools that uses raw data from thigh worn accelerometers to identify physical activity, postures and sleep.
Small body worn accelerometers can easily be worn day and night on participant’s thigh for several days to capture movements. With an existing algorithm “Acti-4”, the raw acelerometer signals can be processed to give information about time in sedentary, standing, walking, running, bicycling, and stair walking. In this project we have implemented the Acti4- algorithm in a software for automatic processing of large amount of raw- thigh accelerometer data. We have also further developed and validated the Acti-4 algorithm to also differentiate lying down from sitting and identifying sleep. This work is done in close collaboration with Det Nationale Forskningscenter for Arbejdsmiljø (NFA) in Denmark and with an international Consortium, The Prospective Physical Activity, Sitting and Sleep consortium (ProPASS).
Physical activity, postures and sleep are important determinants for health. Objective measurements are needed, both in large observational studies and for risk assessments at work places, to assess different aspects of physical activity, postures and sleep.
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Hettiarachchi P, Aili K, Holtermann A, Stamatakis E, Svartengren M, Palm P. Validity of a Non-Proprietary Algorithm for Identifying Lying Down Using Raw Data from Thigh-Worn Triaxial Accelerometers. Sensors. 2021 Jan;21(3):904.
Höjvall C. Detection of physical behavior from thigh worn accelerometer: Validation of a new data processing software that automatically compensates for minor variations in the placement of the accelerometer. Stockholm: KTH Royal Institute Of Technoclogy School Of Engineering Sciences In Chemistry, Biotechnology And Health; 2020. (Degree Project Technology and Health). Available from: http://kth.diva-portal.org/smash/get/diva2:1509359/FULLTEXT01.pdf