2026-09-19T07:05:29Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/761102022-01-13T07:54:13Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Hugh Herr and Ed Boyden.
Wang, Jing, M. Eng. Massachusetts Institute of Technology
Massachusetts Institute of Technology. Dept. of Biological Engineering.
Massachusetts Institute of Technology. Department of Biological Engineering
2013-01-07T21:21:37Z
2013-01-07T21:21:37Z
2011
2011
http://hdl.handle.net/1721.1/76110
820554551
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Biological Engineering, 2011.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 59-60).
Similar to biological human ankle, today's commercially available powered ankle-foot prostheses can vary impedance and deliver net positive ankle work. These commercially available prostheses are intrinsically controlled. Users cannot intuitively change ankle controller's behavior to perform movements that are not part of the repetitive walking gait cycle. For example, when transition from level ground walking to descending stairs, user cannot intuitively initiate or control the amount of ankle angle deflexion for a more normative stair descent gait pattern. This paper presents a hybrid controller that adds myoelectric control functionality to an existing intrinsic controller. The system employs input from both mechanical sensors on the ankle as well as myoelectric signals from gastrocnemius muscle of the user. This control scheme lets the user to modulate the gain of command ankle torque upon push off during level ground walking and stair ascent. It also allows the user to interrupt level ground walking control cycle and initiate ankle plantar flexion during stair descent. As a preliminary study, ankle characteristics such as ankle angle and torque were measured and compared to biological ankle characteristics. Results show that the proposed hybrid controller can maintain existing controller's biomimetic characteristics. In addition, it can also recognize to a qualitative extent the intended command torque for ankle push off and user's desire to switch between control modalities for different terrains. The study shows that it is possible and desirable to use neural signals as control signals for prosthetic leg controllers. Keyword: Myoelectric control, powered prosthesis, proportional torque control
by Jing Wang.
M.Eng.
60 p.
eng
Massachusetts Institute of Technology
MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.
http://dspace.mit.edu/handle/1721.1/7582
Biological Engineering.
EMG control of prosthetic ankle plantar flexion
Thesis
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<Abstract>Similar to biological human ankle, today's commercially available powered ankle-foot prostheses can vary impedance and deliver net positive ankle work. These commercially available prostheses are intrinsically controlled. Users cannot intuitively change ankle controller's behavior to perform movements that are not part of the repetitive walking gait cycle. For example, when transition from level ground walking to descending stairs, user cannot intuitively initiate or control the amount of ankle angle deflexion for a more normative stair descent gait pattern. This paper presents a hybrid controller that adds myoelectric control functionality to an existing intrinsic controller. The system employs input from both mechanical sensors on the ankle as well as myoelectric signals from gastrocnemius muscle of the user. This control scheme lets the user to modulate the gain of command ankle torque upon push off during level ground walking and stair ascent. It also allows the user to interrupt level ground walking control cycle and initiate ankle plantar flexion during stair descent. As a preliminary study, ankle characteristics such as ankle angle and torque were measured and compared to biological ankle characteristics. Results show that the proposed hybrid controller can maintain existing controller's biomimetic characteristics. In addition, it can also recognize to a qualitative extent the intended command torque for ankle push off and user's desire to switch between control modalities for different terrains. The study shows that it is possible and desirable to use neural signals as control signals for prosthetic leg controllers. Keyword: Myoelectric control, powered prosthesis, proportional torque control</Abstract>
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