Physical activity monitoring based on accelerometry: validation and comparison with video observation

• Published in: Medical & biological engineering & computing Vol. 37; no. 3; pp. 304 - 308
• Main Authors: Aminian, K., Robert, Ph, Buchser, E. E., Rutschmann, B., Hayoz, D., Depairon, M.
• Format: Journal Article
• Language: English
• Published: Heidelberg Springer 01.05.1999; Springer Nature B.V
• Subjects: Acceleration measurement; Accelerometers; Activities of Daily Living; Algorithms; Biological and medical sciences; Feasibility studies; Fundamental and applied biological sciences. Psychology; Humans; Monitoring, Physiologic - instrumentation; Monitoring, Physiologic - methods; Movement - physiology; Neural Networks (Computer); Reproducibility of Results; Vertebrates: body movement. Posture. Locomotion. Flight. Swimming. Physical exercise. Rest. Sports; Physical exercise; Human; Validation; Video technique; Feasibility; Ambulatory; Accelerometry; Comparative study; Monitoring
• ISSN: 0140-0118; 1741-0444
• DOI: 10.1007/BF02513304

The objective of this feasibility study is to evaluate the use of the 'Physilog' device, an ambulatory physical-activity recorder based on acceleration measurement, for the monitoring of daily physical activities. Accelerations measured at the level of the chest and the thigh are recorded by Physilog over a period of 1 h in five normal subjects. A specially designed studio-like room allowing the performance of most usual activities of everyday life is used. A video film synchronised with the Physilog is obtained for each subject to check the accuracy of the data derived from Physilog. Based on the analysis on the average and the deviation of the acceleration signal, an algorithm is developed to classify the activities in four categories, i.e. lying, sitting, standing and locomotion. Compared with the video observations, the results from the algorithm show an overall misclassification of 10.7%, which is mainly due to confusion between dynamic activities and the standing posture. In contrast, the misclassification between postures is negligible. It is concluded that Physilog can be used in the clinical setting for the reliable measurement and long-term recording of most usual physical activities.