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WBAN Path Loss Based Approach For Human Activity Recognition With Machine Learning Techniques | IEEE Conference Publication | IEEE Xplore

WBAN Path Loss Based Approach For Human Activity Recognition With Machine Learning Techniques


Abstract:

Wireless Body Area Networks are nowadays attracting both academic and industrial worlds. Combining collected data related to patient context with original health measurem...Show More

Abstract:

Wireless Body Area Networks are nowadays attracting both academic and industrial worlds. Combining collected data related to patient context with original health measurement can enhance the general health state monitoring and help to better understand the patient disease evolution. Daily activity is one of the important features that may influence the patient health state. Thus, recognizing the user activity can be a useful way for improving quality of health services. Relying on supervised learning, we study the feasibility of extracting and classifying the human activities from channel gain measures, which is an important feature that characterizes the WBAN channel links.
Date of Conference: 25-29 June 2018
Date Added to IEEE Xplore: 30 August 2018
ISBN Information:
Electronic ISSN: 2376-6506
Conference Location: Limassol, Cyprus

References

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