Journal
PERVASIVE AND MOBILE COMPUTING
Volume 21, Issue -, Pages 62-74Publisher
ELSEVIER
DOI: 10.1016/j.pmcj.2015.06.003
Keywords
Wearable sensors; Accelerometer; Activity recognition; Body location; Walking detection
Funding
- National Heart, Lung and Blood Institute, National Institutes of Health [5UO1HL091737]
- Italian Ministry of Education and Research [2010R277FT]
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This work describes an automatic method to recognize the position of an accelerometer worn on five different parts of the body ankle, thigh, hip, arm and wrist from raw accelerometer data. Automatic detection of body position of a wearable sensor would enable systems that allow users to wear sensors flexibly on different body parts or permit systems that need to automatically verify sensor placement. The two-stage location detection algorithm works by first detecting time periods during which candidates are walking (regardless of where the sensor is positioned). Then, assuming that the data refer to walking, the algorithm detects the position of the sensor. Algorithms were validated on a dataset that is substantially larger than in prior work, using a leave-one-subject-out cross-validation approach. Correct walking and placement recognition were obtained for 97.4% and 91.2% of classified data windows, respectively. (C) 2015 Elsevier B.V. All rights reserved.
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