Accelerometry-based recognition of the placement sites of a wearable sensor

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...

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Bibliographic Details
Published in:Pervasive and mobile computing Vol. 21; pp. 62 - 74
Main Authors: Mannini, Andrea, Sabatini, Angelo M., Intille, Stephen S.
Format: Journal Article
Language:English
Published: Netherlands Elsevier B.V 01.08.2015
Subjects:
Accelerometer
Activity recognition
Body location
Walking detection
Wearable sensors
Accelerometer
Activity recognition
Body location
Wearable sensors
Walking detection
body location
walking detection
accelerometer
activity recognition
ISSN:1574-1192, 1873-1589
Online Access:Get full text
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Summary: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.
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ISSN:1574-1192
1873-1589
DOI:10.1016/j.pmcj.2015.06.003