A Subspace Approach to the Structural Decomposition and Identification of Ankle Joint Dynamic Stiffness

Jalaleddini, Kian; Tehrani, Ehsan Sobhani; Kearney, Robert E.

doi:10.1109/tbme.2016.2604293

Cited by 31 publications

(24 citation statements)

References 48 publications

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“…with muscle afferentation). This is critical in understanding the mechanisms of muscle function, for instance, the choice of muscle model in replicating nonlinear properties of joint impedance [49] or in stability of the joint in response to perturbations or in voluntary movement. Therefore, the selection of the muscle model is a known and unavoidable limitation of this work that merits further investigation by a systematic comparison for a variety of muscle models proposed in the literature — whose behavior when coupled with a closed-loop neuromorphic system remains unknown [50].…”

Section: Discussionmentioning

confidence: 99%

Neuromorphic meets neuromechanics, part II: the role of fusimotor drive

et al. 2017

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Objective We studied the fundamentals of muscle afferentation by building a neuro-mechano-morphic system actuating a cadaveric finger. This system is a faithful implementation of the stretch reflex circuitry. It allowed the systematic exploration of the effects of different fusimotor drives to the muscle spindle on the closed-loop stretch reflex response. Approach As in Part I of this work, sensory neurons conveyed proprioceptive information from muscle spindles (with static and dynamic fusimotor drive) to populations of α-motor neurons (with recruitment and rate coding properties). The motor commands were transformed into tendon forces by a Hill-type muscle model (with activation-contraction dynamics) via brushless DC motors. Two independent afferented muscles emulated the forces of flexor digitorum profundus and the extensor indicis proprius muscles, forming an antagonist pair at the metacarpophalangeal joint of a cadaveric index finger. We measured the physical response to repetitions of bidirectional ramp-and-hold rotational perturbations for 81 combinations of static and dynamic fusimotor drives, across four ramp velocities, and three levels of constant cortical drive to the α-motor neuron pool. Results We found that this system produced responses compatible with the physiological literature. Fusimotor and cortical drives had nonlinear effects on the reflex forces. In particular, only cortical drive affected the sensitivity of reflex forces to static fusimotor drive. In contrast, both static fusimotor and cortical drives reduced the sensitivity to dynamic fusimotor drive. Interestingly, realistic signal-dependent motor noise emerged naturally in our system without having been explicitly modeled. Significance We demonstrate that these fundamental features of spinal afferentation sufficed to produce muscle function. As such, our neuro-mechano-morphic system is a viable platform to study the spinal mechanisms for healthy muscle function — and its pathologies such as dystonia and spasticity. In addition, it is a working prototype of a robust biomorphic controller for compliant robotic limbs and exoskeletons.

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Section: Discussionmentioning

confidence: 99%

Neuromorphic meets neuromechanics, part II: the role of fusimotor drive

et al. 2017

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“…All parameter and nominal values of simulation model were selected based on experimental results reported in literature (Mirbagheri et al, 2000; Jalaleddini et al, 2016). …”

Section: Simulation Studymentioning

confidence: 99%

Linear Parameter Varying Identification of Dynamic Joint Stiffness during Time-Varying Voluntary Contractions

Golkar

Tehrani

Kearney

2017

Front. Comput. Neurosci.

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Dynamic joint stiffness is a dynamic, nonlinear relationship between the position of a joint and the torque acting about it, which can be used to describe the biomechanics of the joint and associated limb(s). This paper models and quantifies changes in ankle dynamic stiffness and its individual elements, intrinsic and reflex stiffness, in healthy human subjects during isometric, time-varying (TV) contractions of the ankle plantarflexor muscles. A subspace, linear parameter varying, parallel-cascade (LPV-PC) algorithm was used to identify the model from measured input position perturbations and output torque data using voluntary torque as the LPV scheduling variable (SV). Monte-Carlo simulations demonstrated that the algorithm is accurate, precise, and robust to colored measurement noise. The algorithm was then used to examine stiffness changes associated with TV isometric contractions. The SV was estimated from the Soleus EMG using a Hammerstein model of EMG-torque dynamics identified from unperturbed trials. The LPV-PC algorithm identified (i) a non-parametric LPV impulse response function (LPV IRF) for intrinsic stiffness and (ii) a LPV-Hammerstein model for reflex stiffness consisting of a LPV static nonlinearity followed by a time-invariant state-space model of reflex dynamics. The results demonstrated that: (a) intrinsic stiffness, in particular ankle elasticity, increased significantly and monotonically with activation level; (b) the gain of the reflex pathway increased from rest to around 10–20% of subject's MVC and then declined; and (c) the reflex dynamics were second order. These findings suggest that in healthy human ankle, reflex stiffness contributes most at low muscle contraction levels, whereas, intrinsic contributions monotonically increase with activation level.

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“…Combined efforts from prosthetic care providers, including engineers and practitioners, to restore functional outcomes of individuals with lower limb amputation could be supported by in-depth biomechanical understanding of healthy joints. [1,2] For instance, Drevelle et al (2014) indicated that "The stiffness related to flexion movement has been proposed to characterise the functioning of the healthy ankle and to define realistic targets for prosthesis design". [3] This pointed out the importance of the ankle stiffness of a prosthetic foot in restoring functions.…”

Section: Introductionmentioning

confidence: 99%

Automated Characterization of Anthropomorphicity of Prosthetic Feet Fitted to Bone-Anchored Transtibial Prosthesis

Frossard

Leech²,

Pitkin

2019

IEEE Trans. Biomed. Eng.

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A Subspace Approach to the Structural Decomposition and Identification of Ankle Joint Dynamic Stiffness

Abstract: SDSS will be a valuable tool for studying joint stiffness under functionally important conditions. It has important clinical implications for the diagnosis, assessment, objective quantification, and monitoring of neuromuscular diseases that change the muscle tone.

Cited by 31 publications

References 48 publications

Neuromorphic meets neuromechanics, part II: the role of fusimotor drive

Neuromorphic meets neuromechanics, part II: the role of fusimotor drive

Linear Parameter Varying Identification of Dynamic Joint Stiffness during Time-Varying Voluntary Contractions

Automated Characterization of Anthropomorphicity of Prosthetic Feet Fitted to Bone-Anchored Transtibial Prosthesis

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