2026-09-20T00:27:01Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1450652022-08-30T04:04:55Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Hogan, Neville
Sugimoto Dimitrova, Rika
Massachusetts Institute of Technology. Department of Mechanical Engineering
2022-08-29T16:30:35Z
2022-08-29T16:30:35Z
2022-05
2022-06-23T14:10:32.138Z
https://hdl.handle.net/1721.1/145065
0000-0001-7055-0196
Balance disorders affect millions in the United States alone. Despite the large body of literature in the field, we do not yet fully understand the neuromuscular control of balance. A method to estimate natural, unperturbed standing balance dynamics would provide a necessary tool to examine the apparent control mechanisms employed by healthy individuals, and lead to insight and inspiration for developing effective rehabilitation and assistive technologies for those with balance impairments.
In this thesis, a correlation-based system identification method has been investigated as a candidate for perturbation-free identification of human standing balance. The method was tested in simulation to understand its strengths and limitations, and was successfully validated on a hardware system. However, existing human quiet standing data revealed that the posture control process cannot be modelled by a stationary process at the time scales of interest, as required by the system identification method. Accordingly, the perturbation-free system identification of balance dynamics and control remains an area for ongoing research.
S.M.
Massachusetts Institute of Technology
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http://rightsstatements.org/page/InC-EDU/1.0/
Towards Perturbation-free Identification of Human Standing Balance
Thesis
application/pdf
Master
Master of Science in Mechanical Engineering
Publication
unknown
unknown
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<Abstract>Balance disorders affect millions in the United States alone. Despite the large body of literature in the field, we do not yet fully understand the neuromuscular control of balance. A method to estimate natural, unperturbed standing balance dynamics would provide a necessary tool to examine the apparent control mechanisms employed by healthy individuals, and lead to insight and inspiration for developing effective rehabilitation and assistive technologies for those with balance impairments.
In this thesis, a correlation-based system identification method has been investigated as a candidate for perturbation-free identification of human standing balance. The method was tested in simulation to understand its strengths and limitations, and was successfully validated on a hardware system. However, existing human quiet standing data revealed that the posture control process cannot be modelled by a stationary process at the time scales of interest, as required by the system identification method. Accordingly, the perturbation-free system identification of balance dynamics and control remains an area for ongoing research.</Abstract>
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