A Personalized Classifier for Human Motion Activities With Semi-Supervised Learning

• Published in: IEEE transactions on consumer electronics Vol. 66; no. 4; pp. 346 - 355
• Main Authors: Singh, Ghanapriya, Chowdhary, Mahesh, Kumar, Arun, Bahl, Rajendar
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.11.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Accuracy; Classification algorithms; Classifiers; Customization; Gait; generalized classifier; Human motion; Information theoretic criteria; Information theory; Mobile handsets; mobile or wearable device; motion activities; Motion perception; Performance evaluation; personalized classifier; Semi-supervised learning; Semisupervised learning; Sensors; Wearable computers; Wearable technology

The motion activities performed by a mobile or wearable device user are characteristic of the user and the accuracy of detection of motion activity context can be improved by incorporating personalized samples of motion activity. But obtaining personalized samples of motion activity from device user...