A Dynamic Model of Electrically Stimulated Knee Muscles in Healthy and Paraplegics

Ferrarin, Maurizio; Iacuone, P; Mingrino, A.; Frigo, C.; Pedotti, A.

doi:10.1007/978-3-642-80211-9_11

Cited by 9 publications

(2 citation statements)

References 7 publications

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“…The passive pendulum test [28] is often used to determine damping characteristics of the limbs. In this test adopted for the upper limb, the subject is asked to lie face down and hang his/her forearm over the edge of the bench.…”

Section: ) Viscous Effectsmentioning

confidence: 99%

EEG controlled neuromuscular electrical stimulation of the upper limb for stroke patients

Tan

Shee

Kong

et al. 2011

Front. Mech. Eng. China

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This paper describes the Brain Computer Interface (BCI) system and the experiments to allow post-acute ( < 3 months) stroke patients to use electroencephalogram (EEG) to trigger neuromuscular electrical stimulation (NMES)-assisted extension of the wrist/ fingers, which are essential pre-requisites for useful hand function. EEG was recorded while subjects performed motor imagery of their paretic limb, and then analyzed to determine the optimal frequency range within the murhythm, with the greatest attenuation. Aided by visual feedback, subjects then trained to regulate their mu-rhythm EEG to operate the BCI to trigger NMES of the wrist/ finger. 6 post-acute stroke patients successfully completed the training, with 4 able to learn to control and use the BCI to initiate NMES. This result is consistent with the reported BCI literacy rate of healthy subjects. Thereafter, without the loss of generality, the controller of the NMES is developed and is based on a model of the upper limb muscle (biceps/triceps) groups to determine the intensity of NMES required to flex or extend the forearm by a specific angle. The muscle model is based on a phenomenological approach, with parameters that are easily measured and conveniently implemented.

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Section: ) Viscous Effectsmentioning

confidence: 99%

EEG controlled neuromuscular electrical stimulation of the upper limb for stroke patients

Tan

Shee

Kong

et al. 2011

Front. Mech. Eng. China

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show abstract

“…The passive pendulum test [Ferrarin 1996] is often used to determine damping characteristics of the limbs. In this test adopted for the upper limb, the subject is asked to lie face down and hang hislher forearm over the edge of the bench.…”

Section: Passive Viscous Characteristicsmentioning

confidence: 99%

Brain-computer interface controlled neuromuscular electrical stimulation of the upper limb for stroke patients

Tan¹

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Experimental parameter identification of a multi-scale musculoskeletal model controlled by electrical stimulation: application to patients with spinal cord injury

Benoussaad

Poignet

Hayashibe

et al. 2013

Med Biol Eng Comput

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We investigated the parameter identification of a multi-scale physiological model of skeletal muscle, based on Huxley's formulation. We focused particularly on the knee joint controlled by quadriceps muscles under electrical stimulation (ES) in subjects with a complete spinal cord injury. A noninvasive and in vivo identification protocol was thus applied through surface stimulation in nine subjects and through neural stimulation in one ES-implanted subject. The identification protocol included initial identification steps, which are adaptations of existing identification techniques to estimate most of the parameters of our model. Then we applied an original and safer identification protocol in dynamic conditions, which required resolution of a nonlinear programming (NLP) problem to identify the serial element stiffness of quadriceps. Each identification step and cross validation of the estimated model in dynamic condition were evaluated through a quadratic error criterion. The results highlighted good accuracy, the efficiency of the identification protocol and the ability of the estimated model to predict the subject-specific behavior of the musculoskeletal system. From the comparison of parameter values between subjects, we discussed and explored the inter-subject variability of parameters in order to select parameters that have to be identified in each patient.

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A Dynamic Model of Electrically Stimulated Knee Muscles in Healthy and Paraplegics

Cited by 9 publications

References 7 publications

EEG controlled neuromuscular electrical stimulation of the upper limb for stroke patients

EEG controlled neuromuscular electrical stimulation of the upper limb for stroke patients

Brain-computer interface controlled neuromuscular electrical stimulation of the upper limb for stroke patients

Experimental parameter identification of a multi-scale musculoskeletal model controlled by electrical stimulation: application to patients with spinal cord injury

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