An EMG-CT method using multiple surface electrodes in the forearm |
| |
| Affiliation: | 1. Industrial Research Institute, Hokkaido Research Organization, Kita 19-jo, Nishi 11-chome, Kita-ku, Sapporo, Hokkaido 060-0819, Japan;2. Division of Human Mechanical Systems and Design, Faculty of Engineering, Hokkaido University, Kita 13-jo, Nishi 8-chome, Kita-ku, Sapporo, Hokkaido 060-8628, Japan;1. Department of Rehabilitation, Sagamihara Chuo Hospital, 6-4-20, Fujimi, Chuo-ku, Sagamihara, Kanagawa, Japan;2. Department of Rehabilitation, Toho University Omori Medical Center, 6-11-1, Omori-Nishi, Ota-ku, Tokyo, Japan;3. Department of Exercise Physiology and Biomechanics, Faculty of Medicine, School of Medicine, Toho University, 5-21-16, Omori-Nishi, Ota-ku, Tokyo, Japan;4. Department of Physical Therapy, Tokyo University of Technology, 5-23-22, Nishi-Kamata, Ota-ku, Tokyo, Japan;5. Department of Exercise Physiology, School of Pharmacy, Tokyo University of Pharmacy and Life Sciences, 1432-1, Horinouchi, Hachioji, Tokyo, Japan;6. Department of Rehabilitation, School of Allied Health Science, Kitasato University, 1-15-1, Kitasato, Minami-ku, Sagamihara, Kanagawa, Japan;1. Departments of Neurology, School of Medicine, University of Patras, Patras, Greece;2. Departments of Spinal Cord Lesions Rehabilitation, School of Medicine, University of Patras, Patras, Greece;3. Departments of Medical Physics, School of Medicine, University of Patras, Patras, Greece;1. Department of Biomechanics, Medicine and Rehabilitation of the Locomotor System, Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, SP, Brazil;2. Faculty of Electrical Engineering, Biomedical Engineering Lab, Federal University of Uberlândia, Uberlândia, MG, Brazil |
| |
| Abstract: | Electromyography computed tomography (EMG-CT) method is proposed for visualizing the individual muscle activities in the human forearm. An EMG conduction model was formulated for reverse-estimation of muscle activities using EMG signals obtained with multi surface electrodes. The optimization process was calculated using sequential quadratic programming by comparing the estimated EMG values from the model with the measured values. The individual muscle activities in the deep region were estimated and used to produce an EMG tomographic image. For validation of the method, isometric contractions of finger muscles were examined for three subjects, applying a flexion load (4.9, 7.4 and 9.8 N) to the proximal interphalangeal joint of the middle finger. EMG signals in the forearm were recorded during the tasks using multiple surface electrodes, which were bound around the subject’s forearm. The EMG-CT method illustrates the distribution of muscle activities within the forearm. The change in amplitude and area of activated muscles can be observed. The normalized muscle activities of all three subjects appear to increase monotonically with increases in the load. Kinesiologically, this method was able to estimate individual muscle activation values and could provide a novel tool for studying hand function and development of an examination for evaluating rehabilitation. |
| |
| Keywords: | Forearm Surface electromyography Muscle activity Optimization Conductive model |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
