| Project/Area Number |
15360219
|
|---|
| Research Category |
Grant-in-Aid for Scientific Research (B)
|
| Allocation Type | Single-year Grants |
|---|
| Section | 一般 |
|---|
| Research Field |
Measurement engineering
|
|---|
| Research Institution | National Institute of Information and Communications Technology (2004)
Kobe University (2003) |
|---|
Principal Investigator |
MAEKAWA Satoshi (2004) National Institute of Information and Communications Technology, Information and Network Systems Department, Senior Researcher, 情報通信部門ユニバーサル端末グループ, 主任研究員 (60358893)
小谷 学 (2003) 神戸大学, 工学部, 助教授 (30215272)
|
|---|
| Co-Investigator(Kenkyū-buntansha) |
OZAWA Seiichi Kobe University, Graduate School of Science and Technology, Associate Professor, 自然科学研究科, 助教授 (70214129)
KOTANI Manabu Kobe University, Faculty of Engineering, Associate Professor (30215272)
前川 聡 通信総合研究所, けいはんな情報通信融合研究センター, 主任研究員 (60358893)
|
|---|
| Project Period (FY) |
2003 – 2004
|
| Project Status |
Completed (Fiscal Year 2004)
|
| Budget Amount *help |
¥12,500,000 (Direct Cost: ¥12,500,000)
Fiscal Year 2004: ¥6,500,000 (Direct Cost: ¥6,500,000)
Fiscal Year 2003: ¥6,000,000 (Direct Cost: ¥6,000,000)
|
|---|
| Keywords | Surface EMG / Motor Unit / Visualization / Independent Component Analysis / Blind Deconvolution / Overcomplete / Current Source Estimation / boosting KDA / 筋電図 / 電流源 |
|---|
| Research Abstract |
This research was executed for the motor unit decomposition and making the activity visible from the surface electromyogram as follows.
A)Improvement of motor unit decomposition technique
We proposed a new motor unit decomposition technique with overcomplete bases to introduce the statistical model. It was confirmed that this technique was applied to the real measurement surface EMG signals, and it had the decomposition performance equal with blind deconvolution. Moreover, it was confirmed that each motor unit activity might be separable even if the number of observation channels were less than the number of active motor units.
B)Examination of effectiveness of recognition technique using statistical model
We proposed the recognition system using both KDA and boosting mechanism and confirmed that it's recognition performance was just like an existing technique such as SVM. In general, to maximize generalization performance, parameter tuning process such as cross validation, whose computati
… More
on cost is very expensive, is needed. To solve this problem, we proposed new index value for parameter selection, and with this index, appropriate parameters can be selected without so expensive computation cost.
C)The three dimensional position estimation of each decomposed motor unit
The 3D position of the depolarization of individual motor unit was estimated by using the 3D finite element method from the potential distribution on the skin surface which was estimated with motor unit decomposition technique from surface EMG signals. As a result, it was confirmed that 3D position and dynamics of dopolarization of individual motor unit might be estimated. Moreover, the size of innervation zone and temporal dynamics of current intensity of depolarization could be estimated.
In addition, this study had been started in 2003 fiscal year under Dr.Kotani head researcher, Assistant Professor of Kobe University. However he died in May, 2004, so the head was changed suddenly. I write down that contribution of Dr.Kotani covers the whole of the above results. Less
|
