University of Bahrain
Scientific Journals

Real-Time Wearable-Device Based Activity recognition Using Machine Learning Methods

Show simple item record Thu, Nguyen Thi Dao, To-Hieu Quoc, Bao Bo Tran, Duc-Nghia Thanh, Pham Van Tran, Duc-Tan 2022-03-09T12:39:03Z 2022-03-09T12:39:03Z 2022-03-09
dc.identifier.issn 2210-142X
dc.description.abstract Classification of activities from body-worn accelerometer data to help monitor and take care of health attracts much attention from the research community. This paper proposed to design a real-time monitoring device that can identify people's actions from the accelerometer's data worn on the waist with five activities, including lying, sitting, standing, walking, and jogging. From the collected acceleration data, it is necessary to extract suitable features for real-time classification with high performance. These features are trained with machine learning algorithms that improve the efficiency of action classification. Consequently, a decision tree algorithm was embedded in the microcontroller. This programmed waist-mounted device was connected to the monitoring system via WiFi protocol. Users could monitor activities and managed data on a computer, a website, or a smartphone. The results were optimistic when the overall accuracy for the activities dataset reached 99.3% when training and classifying the activities on the computer. When experimenting with real-time wearable devices, the overall accuracy when classifying activities decreased but was still very good, reaching over 90%. en_US
dc.language.iso en en_US
dc.publisher University of Bahrain en_US
dc.subject Human activity en_US
dc.subject classification en_US
dc.subject machine learning en_US
dc.subject decision tree en_US
dc.subject webserver en_US
dc.subject accelerometer en_US
dc.title Real-Time Wearable-Device Based Activity recognition Using Machine Learning Methods en_US
dc.volume 11 en_US
dc.issue 1 en_US
dc.pagestart XXXX en_US
dc.pageend XXXX en_US
dc.contributor.authoraffiliation Hanoi University of Industry, Ha Noi 11307, Vietnam en_US
dc.contributor.authoraffiliation Thai Nguyen University, University of Information And Communication Technology, Thai Nguyen 24119, Viet Nam en_US
dc.contributor.authoraffiliation Vietnam Academy of Science and Technology, Ha Noi 11307, Vietnam en_US
dc.contributor.authoraffiliation Institute of Information Technology, Vietnam Academy of Science and Technology, Ha Noi 11307, Viet Nam en_US
dc.contributor.authoraffiliation University of Fire Prevention and Fighting, Hanoi, Vietnam en_US
dc.contributor.authoraffiliation Faculty of Electrical and Electronic Engineering, Phenikaa University, Ha Noi 12116, Viet Nam en_US
dc.source.title International Journal of Computing and Digital Systems en_US
dc.abbreviatedsourcetitle IJCDS en_US

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