Human movement detection algorithm using 3-axis accelerometer sensor based on low-power management scheme for mobile health care system

Authors:
Jaewan Shin;Dongkyoo Shin;Dongil Shin;Sungmin Her;Soohan Kim;Myungsoo Lee
Affiliations:
Department of Computer Engineering, Sejong University, Seoul, Republic Of Korea;Department of Computer Engineering, Sejong University, Seoul, Republic Of Korea;Department of Computer Engineering, Sejong University, Seoul, Republic Of Korea;SevenCore Co., Ltd, Seoul, Republic Of Korea;Samsung Eletronics Co., Ltd, Republic Of Korea;Samsung Eletronics Co., Ltd, Republic Of Korea
Venue:
GPC'10 Proceedings of the 5th international conference on Advances in Grid and Pervasive Computing
Year:
2010

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Implementation of a real-time human movement classifier using a triaxial accelerometer for ambulatory monitoring

IEEE Transactions on Information Technology in Biomedicine

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Abstract

Phone and PDA mobile devices that recognize a user's movements and biometric information that can be utilized in a sensor system have been generating interest among users This paper proposes a low-power management scheme that uses the baseband processor installed in a portable communications device to limit the electric power consumed by the device, along with a human movement detection algorithm that records and predicts the movement of the mobile user in a low-power mode In addition, a mobile healthcare system is developed to use the proposed scheme and algorithm This system uses 3-axis accelerometer sensors on an Android platform and calculates the amount of human movement from the sensor output The user's uphill, downhill, flat area, climbing stairs, going down stairs, and jogging movements were measured with accuracies of 93.2%, 97.4%, 97.6%, 98.8%, 92.2%, and 90.8%, respectively.