Subject-Independent sEMG Pattern Recognition by Using a Muscle Source Activation Model

• Published in: IEEE robotics and automation letters Vol. 5; no. 4; pp. 5175 - 5180
• Main Authors: Kim, Minjae, Chung, Wan Kyun, Kim, Keehoon
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.10.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Activation; Classifiers; Computational modeling; Electrodes; Gesture recognition; Indexing; Mathematical model; Microsoft Windows; Muscles; Noise reduction; Pattern recognition; prosthetics and exoskeletons; Rehabilitation robotics; Wrist

The interpretation of surface electromyographic (sEMG) signals facilitates intuitive gesture recognition. However, sEMG signals are highly dependent on measurement conditions. The relationship between sEMG signals and gestures identified from a specific subject cannot be applied to other subjects ow...