JICCE (한국정보통신학회)
Current Result Document :
| 한글제목(Korean Title) |
Modeling and Posture Control of Lower Limb Prosthesis Using Neural Networks |
| 영문제목(English Title) |
Modeling and Posture Control of Lower Limb Prosthesis Using Neural Networks |
| 저자(Author) |
Ju-Won Lee
Gun-Ki Lee
|
| 원문수록처(Citation) |
VOL 02 NO. 02 PP. 0110 ~ 0115 (2004. 06) |
한글내용
(Korean Abstract) |
|
영문내용
(English Abstract) |
The prosthesis of current commercialized apparatus has considerable problems, requiring improvement. Especially, LLP(Lower Limb Prosthesis)-related problems have improved, but it cannot provide normal walking because, mainly, the gait control of the LLP does not fit with patient's gait manner. To solve this problem, HCI((Human Computer Interaction) that adapts and controls LLP postures according to patient's gait manner more effectively is studied in this research. The proposed control technique has 2 steps: 1) the multilayer neural network forecasts angles of gait of LLP by using the angle of normal side of lower limbs; and 2) the adaptive neural controller manages the postures of the LLP based on the predicted joint angles. According to the experiment data, the prediction error of hip angles was 0.32[deg.], and the predicted error of knee angles was 0.12[deg.] for the estimated posture angles for the LLP. The performance data was obtained by applying the reference inputs of the LLP controller while walking. Accordingly, the control performance of the hip prosthesis improved by 80% due to the control postures of the LLP using the reference input when comparing with LQR controller. |
| 키워드(Keyword) |
Lower Limb Prosthesis
Neural Net-works
Gait Control
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| 파일첨부 |
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