Wearable networked sensing for human mobility and activity analytics: A systems study

Author

Dong, Bo ; Biswas, Subir

Author_Institution

Electr. & Comput. Eng., Michigan State Univ., East Lansing, MI, USA

fYear

2012

fDate

3-7 Jan. 2012

Firstpage

1

Lastpage

6

Abstract

This paper presents implementation details, system characterization, and the performance of a wearable sensor network that was designed for human activity analysis. Specific machine learning mechanisms are implemented for recognizing a target set of activities with both out-of-body and on-body processing arrangements. Impacts of energy consumption by the on-body sensors are analyzed in terms of activity detection accuracy for out-of-body processing. Impacts of limited processing abilities in the on-body scenario are also characterized in terms of detection accuracy, by varying the background processing load in the sensor units. Through a rigorous systems study, it is shown that an efficient human activity analytics system can be designed and operated even under energy and processing constraints of tiny on-body wearable sensors.

Keywords

body sensor networks; mobile radio; activity detection accuracy; energy consumption; human activity analytics; human mobility analytics; on-body processing arrangements; on-body wearable sensors; out-of-body processing arrangements; sensor units; wearable sensor network; Acceleration; Accuracy; Decision trees; Entropy; Sensor systems; Wearable sensors; Activity Analytics; Machine Learning; Neural Network; On-body Processing; Wearable Sensor Network;

fLanguage

English

Publisher

ieee

Conference_Titel

Communication Systems and Networks (COMSNETS), 2012 Fourth International Conference on

Conference_Location

Bangalore

Print_ISBN

978-1-4673-0296-8

Electronic_ISBN

978-1-4673-0297-5

Type

conf

DOI

10.1109/COMSNETS.2012.6151376

Filename

6151376