Classifier Level Fusion of Accelerometer and sEMG Signals for Automatic Fitness Activity Diarization

• Published in: Sensors (Basel, Switzerland) Vol. 18; no. 9; p. 2850
• Main Authors: Biagetti, Giorgio, Crippa, Paolo, Falaschetti, Laura, Turchetti, Claudio
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 29.08.2018; MDPI
• Subjects: accelerometer; Accelerometers; Accelerometry - methods; activity diarization; classifier level fusion; data fusion; Digitization; Electrodes; electromiography; Electromyography; Electromyography - methods; Exercise - physiology; Humans; Pattern recognition; Physical fitness; Physical Fitness - physiology; sEMG; Sensors; Smartphones; Wearable Electronic Devices; wearable system; activity diarization; data fusion; electromiography; classifier level fusion; accelerometer; wearable system; sEMG
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s18092850

The human activity diarization using wearable technologies is one of the most important supporting techniques for ambient assisted living, sport and fitness activities, healthcare of elderly people. The activity diarization is performed in two steps: the acquisition of body signals and the classification of activities being performed. This paper presents a technique for data fusion at classifier level of accelerometer and sEMG signals acquired by using a low-cost wearable wireless system for monitoring the human activity when performing sport and fitness activities, as well as in healthcare applications. To demonstrate the capability of the system of diarizing the user’s activities, data recorded from a few subjects were used to train and test the automatic classifier for recognizing the type of exercise being performed.