Estimating mechanical parameters of leg segments in individuals with and without physical disabilities

Stein, Richard B.; Zehr, E. Paul; Lebiedowska, Maria K.; Popović, Dejan B.; Scheiner, Avram; Chizeck, H.J.

doi:10.1109/86.536776

Cited by 104 publications

(66 citation statements)

References 33 publications

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“…The anthropometric parameters m, J K and l are estimated by measuring the height and weight of the subject and using regression equations (Stein et al, 1996). A passive pendulum trial is performed to obtain stiffness and damping parameters.…”

Section: Passive Viscous-elastic Characteristics and Equation Of Motionmentioning

confidence: 99%

Online identification and nonlinear control of the electrically stimulated quadriceps muscle

Schauer

Negard

Previdi

et al. 2005

Control Engineering Practice

124

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A new approach for estimating nonlinear models of the electrically stimulated quadriceps muscle group under non-isometric conditions is investigated. The model can be used for designing controlled neuro-prostheses. In order to identify the muscle dynamics (stimulation pulsewidth -active knee moment relation) from discrete-time angle measurements only, a hybrid model structure is postulated for the shankquadriceps dynamics. The model consists of a relatively well known time-invariant passive component and an uncertain time-variant active component. Rigid body dynamics, described by the Equation of Motion (EoM), and passive joint properties form the time-invariant part. The actuator, i.e. the electrically stimulated muscle group, represents the uncertain time-varying section. A recursive algorithm is outlined for identifying online the stimulated quadriceps muscle group. The algorithm requires EoM and passive joint characteristics to be known a priori. The muscle dynamics represent the product of a continuous-time nonlinear activation dynamics and a nonlinear static contraction function described by a Normalised Radial Basis Function (NRBF) network which has knee-joint angle and angular velocity as input arguments. An Extended Kalman Filter (EKF) approach is chosen to estimate muscle dynamics parameters and to obtain full state estimates of the shank-quadriceps dynamics simultaneously. The latter is important for implementing state feedback controllers. A nonlinear state feedback controller using the backstepping method is Preprint submitted to Control Engineering Practice 16 July 2004explicitly designed whereas the model was identified a priori using the developed identification procedure.

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Section: Passive Viscous-elastic Characteristics and Equation Of Motionmentioning

confidence: 99%

Online identification and nonlinear control of the electrically stimulated quadriceps muscle

Schauer

Negard

Previdi

et al. 2005

Control Engineering Practice

124

View full text Add to dashboard Cite

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“…Another physiologic cause may be a large thixotropic effect of knee muscle. (26) All gravity (G) parameters of the stroke patients were smaller then normal.…”

Section: Discussionmentioning

confidence: 99%

“…The spastic torque from the stretch reflex was added to the model as a velocity-dependent one, which caused the trajectory to deviate from a normal pendular appearance. The early researchers attempted to generate the abnormal stretch reflex responses through the variation of mechanical parameters4, (18), (26) or the addition of pulse-shaped spastic torque at the EMG onset times. (29) These methods are useful in demonstrating how the abnormal stretch reflex responses could produce abnormal mechanical behavior in spastic patients.…”

Section: Introductionmentioning

confidence: 99%

Modeling and Identification of Mechanical and Reflex Properties related to Spasticity in Stroke Patients using Multiple Pendulum Tests

Kim

Eom

Hase

2011

JBSE

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We propose a method for the comprehensive identification of spastic and intrinsic properties of spastic knee joints using multiple pendulum tests. The stretch reflex system was modeled as a velocity feedback loop where the key component was the muscle spindle model generating the afferent signals with a constant threshold and gain of the lengthening velocity. For the comprehensive identification, multiple trajectories from one session of pendulum trials with different release angles were used as the reference trajectories that the model must reproduce. The identification was successful based on the results that the identified model represented the various features of pendulum trajectories and the simulated spastic torque closely matched the experimental EMG. The identified velocity threshold showed a remarkable correlation with the EMG duration and peak. The session-based method was effective in the identification of the spastic musculoskeletal system and the velocity threshold of the stretch reflex was suggested as a reliable and intuitive indicator of spastic severity.

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“…However, these authors used a more qualitative assessment of stiffness based on the number of swings that occurred and the shape of the oscillation. Stein et al 14 used a method similar to our approach and found no difference in stiffness and damping coefficients in 9 neurologically impaired individuals, as compared to 9 neurologically intact subjects. However, the authors did not match gender for all subjects in the 2 groups, which is likely to have affected the comparisons.…”

Section: Discussionmentioning

confidence: 99%

Knee Joint Stiffness in Individuals With and Without Knee Osteoarthritis: A Preliminary Study

Oatis¹,

Wolff²,

Lennon³

2006

J Orthop Sports Phys Ther

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Study Design: Descriptive, case-matched comparison. Objectives: To compare the knee joint stiffness and damping coefficients of individuals with knee osteoarthritis (KOA) to those of age-and gender-matched individuals without KOA. A secondary purpose was to investigate relationships between these coefficients and complaints of stiffness in individuals with KOA. Background: KOA is a leading cause of disability, and stiffness is a common complaint in individuals with KOA. Yet the most common method of assessing knee joint stiffness is through a self-report questionnaire. Methods and Measures: Stiffness and damping coefficients at the knee were calculated in 10 volunteers (mean age ± SD, 64.1 ± 15.5 years) with KOA and compared to coefficients from ageand gender-matched individuals without KOA, collected in a previous study (mean age ± SD, 62.1 ± 13.9 years). Stiffness and damping coefficients were calculated from the angular motion of the knee during a relaxed oscillation. Spearman correlation coefficients were calculated between stiffness and damping coefficients and WOMAC (Western Ontario and McMaster Universities Osteoarthritis Index) scores for subjects with KOA. Results: Independent 2-tailed t tests revealed significantly larger damping coefficients (P = .035) among those with KOA (95% CI, 0.10-2.32 Nm s/rad). Spearman rank correlations revealed a significant positive relationship (r = .85, P = .003) between the damping coefficient and the stiffness subscore of the WOMAC. Conclusion: This study offers preliminary data demonstrating the feasibility of measuring stiffness and damping coefficients in individuals with KOA. Additionally, the damping coefficient is increased in people with KOA when compared to age-and gender-matched individuals without KOA. The damping coefficient appears to be associated with the complaints of stiffness reported by the WOMAC.

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Estimating mechanical parameters of leg segments in individuals with and without physical disabilities

Cited by 104 publications

References 33 publications

Online identification and nonlinear control of the electrically stimulated quadriceps muscle

Online identification and nonlinear control of the electrically stimulated quadriceps muscle

Modeling and Identification of Mechanical and Reflex Properties related to Spasticity in Stroke Patients using Multiple Pendulum Tests

Knee Joint Stiffness in Individuals With and Without Knee Osteoarthritis: A Preliminary Study

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