Thumb-tip force estimation from sEMG and a musculoskeletal model for real-time finger prosthesis
- Resource Type
- Conference
- Authors
- Park, Won-Il; Sun-Cheol Kwon; Hae-Dong Lee; Jung Kim
- Source
- 2009 IEEE International Conference on Rehabilitation Robotics Rehabilitation Robotics, 2009. ICORR 2009. IEEE International Conference on. :305-310 Jun, 2009
- Subject
- Bioengineering
Robotics and Control Systems
Musculoskeletal system
Fingers
Prosthetics
Muscles
Force measurement
Force control
Artificial neural networks
Thumb
Software packages
Real time systems
- Language
- ISSN
- 1945-7898
1945-7901
Due to the difficulties in measurement of muscle activities and the complex musculoskeletal structure, estimations of the thumb-tip force in real time have been a challenge for controlling artificial prosthesis naturally. This study describes an isometric thumb-tip force estimation technique based on phenomenological muscle model named Hill's model. The surface electromyogram (sEMG) signals of the muscles near surface were measured and converted to muscle activation information. The activations of deep muscles were inferred from the ratios of muscle activations from earlier study. The muscle length of each contributed muscle was obtained by using motion capture system and musculoskeletal modeling software packages. Once muscle forces were calculated, thumb-tip force was estimated based on mapping model from the muscle force to thumb-tip force. The proposed method was evaluated in comparisons with an artificial neural network (ANN) under four different thumb configurations to investigate the potential for estimations under conditions in which the thumb configuration changes. The results seem to be promising and the proposed method could be applied to predict finger-tip forces from non-invasive neurosignals with a real-time prosthesis control system.