Quantitative Characterization of Steady-State Ankle Impedance With Muscle Activation

Lee, Hyunglae; Ho, Patrick; Rastgaar, Mo; Krebs, Hermano Igo; Hogan, Neville

doi:10.1115/dscc2010-4062

Cited by 20 publications

(12 citation statements)

References 6 publications

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“…The average break frequencies were 9.1Hz and 6.4 Hz for passive and active tests, respectively. This break frequency was consistent with the 90° phase crossing and showed similar behavior as IE and DP impedances [3]. On average, the impedance observed at frequencies below the break frequency for the contraction test was 96% higher with values of 28.6 dB (27 Nm/rad) and 22.8 dB (13.8 Nm/rad) for the active and passive tests, respectively.…”

Section: Resultssupporting

confidence: 78%

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Stochastic Estimation of Human Ankle Mechanical Impedance in Lateral/Medial Rotation

Ficanha

Rastgaar

2014

Volume 2: Dynamic Modeling and Diagnostics in Biomedical Systems; Dynamics and Control of Wind Energy Systems; Vehicle Energy M

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This article compares stochastic estimates of human ankle mechanical impedance when ankle muscles were fully relaxed and co-contracting antagonistically. We employed Anklebot, a rehabilitation robot for the ankle to provide torque perturbations. Surface electromyography (EMG) was used to monitor muscle activation levels and these EMG signals were displayed to subjects who attempted to maintain them constant. Time histories of ankle torques and angles in the lateral/medial (LM) directions were recorded. The results also compared with the ankle impedance in inversion-eversion (IE) and dorsiflexion-plantarflexion (DP). Linear time-invariant transfer functions between the measured torques and angles were estimated for the Anklebot alone and when a human subject wore it; the difference between these functions provided 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 all degrees of freedom of ankle.

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Section: Resultssupporting

confidence: 78%

“…Previous work estimated the multivariable mechanical impedance of ankle in IE and DP, when the muscles connected to the ankle joint were relaxed and in co-contraction [1][2][3]. Ankle impedance during muscle contraction is important since most activities are performed with varying levels of muscle activation.…”

Section: Introductionmentioning

confidence: 99%

Stochastic Estimation of Human Ankle Mechanical Impedance in Lateral/Medial Rotation

Ficanha

Rastgaar

2014

Volume 2: Dynamic Modeling and Diagnostics in Biomedical Systems; Dynamics and Control of Wind Energy Systems; Vehicle Energy M

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“…During the tests, each actuator received a command voltage with a bandwidth of 100 Hz, equivalent to peak torque perturbations of 23 Nm in DP and 15 Nm in IE (Iqbal and Roy 2009;Lee et al 2010). The sum and difference of the Anklebot actuator forces perturbed the ankle in the DP and IE directions, respectively.…”

Section: Methodsmentioning

confidence: 99%

Estimating the multivariable human ankle impedance in dorsi-plantarflexion and inversion-eversion directions using EMG signals and artificial neural networks

Dallali

Knop

Castelino

et al. 2017

Int J Intell Robot Appl

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The use of a suitably designed ankle-foot prosthesis is essential for transtibial amputees to regain lost mobility. A desired ankle-foot prosthesis must be able to replicate the function of a healthy human ankle by transferring the ground reaction forces to the body, absorbing shock during contact, and providing propulsion. During the swing phase of walking, the human ankle is soft and relaxed; however, it hardens as it bears the body weight and provides force for push-off. The stiffness is one of the components of the mechanical impedance, and it varies with muscle activation (Stochastic estimation of human ankle mechanical impedance in medial-lateral direction, 2014, Stochastic estimation of the multivariable mechanical impedance of the human ankle with active muscles, 2010). This study defines the relationship between ankle impedance and the lower extremity muscle activations using artificial neural networks (ANN). We used the Anklebot, a highly backdrivable, safe, and therapeutic robot to apply stochastic position perturbations to the human ankle in the sagittal and frontal planes. A previously proposed system identification method was used to estimate the target ankle impedance to train the ANN. The ankle impedance was estimated with relaxed muscles and with lower leg muscle activations at 10 and 20% of the maximum voluntary contraction (MVC) of each individual subject. Given the root mean squared (rms) of the electromyography (EMG) signals, the proposed ANN effectively predicted the ankle impedance with mean accuracy of 89.8 ± 6.1% in DP and mean accuracy of 88.3 ± 5.7% in IE, averaged across three muscle activation levels and all subjects.

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“…However, when cocontracted muscle activation is not spring-like, it includes nonzero rotational components (Lee et al 2010). If the nonconservative curl is zero while intermuscular feedback is nonzero, then the feedback gains must be exactly balanced; a dorsiplantar flexion torque evoked by an inversion-eversion displacement must be identical to the inversion-eversion torque evoked by a comparable dorsiplantar flexion displacement.…”

Section: Abnormal Joint Stiffness May Also Be a Consequence Of Distormentioning

confidence: 99%

Measurement of passive ankle stiffness in subjects with chronic hemiparesis using a novel ankle robot

Roy¹,

Krebs²,

Bever³

et al. 2011

Journal of Neurophysiology

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Quantitative Characterization of Steady-State Ankle Impedance With Muscle Activation

Cited by 20 publications

References 6 publications

Stochastic Estimation of Human Ankle Mechanical Impedance in Lateral/Medial Rotation

Stochastic Estimation of Human Ankle Mechanical Impedance in Lateral/Medial Rotation

Estimating the multivariable human ankle impedance in dorsi-plantarflexion and inversion-eversion directions using EMG signals and artificial neural networks

Measurement of passive ankle stiffness in subjects with chronic hemiparesis using a novel ankle robot

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