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|a Rastgaar Aagaah, Mohammad
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|a Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
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|a Massachusetts Institute of Technology. Department of Mechanical Engineering
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|a Rastgaar Aagaah, Mohammad
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|a Ho, Patrick
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|a Lee, Hyunglae
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|a Krebs, Hermano I
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|a Hogan, Neville
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|a Ho, Patrick
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|a Lee, Hyunglae
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|a Krebs, Hermano I
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|a Hogan, Neville
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|a Stochastic Estimation of the Multi-Variable Mechanical Impedance of the Human Ankle With Active Muscles
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|b ASME International,
|c 2018-12-03T16:25:01Z.
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|z Get fulltext
|u http://hdl.handle.net/1721.1/119384
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|a This article compares stochastic estimates of multi-variable human ankle mechanical impedance when ankle muscles were fully relaxed, actively generating ankle torque or co-contracting antagonistically. We employed Anklebot, a rehabilitation robot for the ankle, to provide torque perturbations. Muscle activation levels were monitored electromyographically and these EMG signals were displayed to subjects who attempted to maintain them constant. Time histories of ankle torques and angles in the Dorsi-Plantar flexion (DP) and Inversion-Eversion (IE) directions were recorded. Linear time-invariant transfer functions between the measured torques and angles were estimated for the Anklebot alone and when it was worn by a human subject, the difference between these functions providing an estimate of ankle mechanical impedance. High coherence was observed over a frequency range up to 30 Hz. The main effect of muscle activation was to increase the magnitude of ankle mechanical impedance in both DP and IE directions.
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|a Toyota Motor Corporation. Partner Robot Division
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|a Samsung Fellowship
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|a Article
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|t ASME 2010 Dynamic Systems and Control Conference, Volume 1
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