Volume 11, Issue 1, 2018, Pages 238 - 247
Thumb-tip Force Prediction Based on Hill’s Muscle Model using Electromyogram and Ultrasound Signal
Authors
Shahrul Naim Sidek1, snaim@iium.edu.my, Muhammad Rozaidi Roslan1, rozaidiroslan21@gmail.com, Sabrilhakim Sidek2, sabrilhakim@salam.uitm.edu.my, Mohd Shukry Mohd Khalid2, shooke937@yahoo.com
1Mechatronics Engineering Department, Kulliyyah of Engineering, IIUM, Jalan Gombak, Kuala Lumpur 53100, Malaysia
2Medical Imaging Unit, Faculty of Medicine, Universiti Teknologi MARA, Sg. Buloh Campus, Jalan Hospital, Sg. Buloh, Selangor, 47000, Malaysia
Received 26 April 2017, Accepted 28 October 2017, Available Online 1 January 2018.
- DOI
- 10.2991/ijcis.11.1.18How to use a DOI?
- Keywords
- Thumb-tip force; electromyography; thumb training system; muscle model
- Abstract
The use of prostheses is necessary to restore lost limbs to a level of functionality to enable activity of daily living. Many prostheses are now using myoelectric based control techniques to operate. However, to develop a model based controller for the system remains a challenge as accurate model is necessary. This study investigates the use of electromyogram and ultrasound signal to predict thumb tip force based on Hill’s Muscle model. The results obtained has shown a significant improvement in the prediction of thumb tip force as much as 31.45% of average RMSE over the benchmark model that leverages on biomechanics model and active marker to characterize the muscle.
- Copyright
- © 2018, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article under the CC BY-NC license (http://creativecommons.org/licences/by-nc/4.0/).
Download article (PDF)
View full text (HTML)
Cite this article
TY - JOUR AU - Shahrul Naim Sidek AU - Muhammad Rozaidi Roslan AU - Sabrilhakim Sidek AU - Mohd Shukry Mohd Khalid PY - 2018 DA - 2018/01/01 TI - Thumb-tip Force Prediction Based on Hill’s Muscle Model using Electromyogram and Ultrasound Signal JO - International Journal of Computational Intelligence Systems SP - 238 EP - 247 VL - 11 IS - 1 SN - 1875-6883 UR - https://doi.org/10.2991/ijcis.11.1.18 DO - 10.2991/ijcis.11.1.18 ID - Sidek2018 ER -