Feature Selection and Activity Recognition System Using a Single Triaxial Accelerometer

• Published in: IEEE transactions on biomedical engineering Vol. 61; no. 6; pp. 1780 - 1786
• Main Authors: Gupta, Piyush, Dallas, Tim
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.06.2014; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Acceleration; Accelerometer; Accelerometers; Accelerometry - instrumentation; Accuracy; Activities of Daily Living - classification; activity recognition; Adult; Algorithms; Bayes Theorem; Classification; detrended fluctuation analysis (DFA); error estimates; feature selection; Female; Fluctuations; Humans; k -nearest neighbor ( k -NN) classifier; leave-one-person-out (LOO) error; Legged locomotion; Male; Monitoring; Monitoring, Ambulatory - instrumentation; Monitoring, Ambulatory - methods; Motor Activity - physiology; Naïve Bayes classifier; Neural Networks (Computer); Patients; Position (location); Recognition; Relief-F algorithm; Searching; sequential forward floating search (SFFS) wrapper algorithm; Time series analysis; Young Adult

Activity recognition is required in various applications such as medical monitoring and rehabilitation. Previously developed activity recognition systems utilizing triaxial accelerometers have provided mixed results, with subject-to-subject variability. This paper presents an accurate activity recog...