EMG based classification for continuous thumb angle and force prediction
Human hand functions range from precise-minute handling to heavy and robust movements. Remarkably, 50 percent of all hand functions are made possible by the thumb. Therefore, developing an artificial thumb which can mimic the actions of a real thumb precisely is a majo...
Main Authors: | Siddiqi, Abdul Rahman, Sidek, Shahrul Na'im, Roslan, Muhammad Rozaidi |
---|---|
Format: | Conference or Workshop Item |
Language: | English |
Published: |
IEEE
2015
|
Subjects: | |
Online Access: | http://irep.iium.edu.my/47317/ http://irep.iium.edu.my/47317/ http://irep.iium.edu.my/47317/ http://irep.iium.edu.my/47317/4/47317.pdf |
Similar Items
-
Signal processing of EMG signal for continuous thumb-angle estimation
by: Siddiqi, Abdul Rahman, et al.
Published: (2015) -
Estimation of continuous thumb angle and force using electromyogram classification
by: Siddiqi, Abdul Rahman, et al.
Published: (2016) -
EMG based classification of thumb posture using portable thumb training system
by: Roslan, Muhammad Rozaidi, et al.
Published: (2017) -
Investigation of thumb-tip force prediction based on Hill's Muscle model using noninvasive electromyography and ultrasound signals
by: Sidek, Shahrul Na'im
Published: (2017) -
Measurement system to study the relationship between forearm EMG signals and hand grip force
by: Sidek, Shahrul Naim, et al.
Published: (2012)