Compliant grasp in a myoelectric hand prosthesis

Okuno, Ryuhei; Yoshida, Masaki; Akazawa, Kenzo

doi:10.1109/memb.2005.1463396

Cited by 18 publications

(9 citation statements)

References 24 publications

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“…For decades, many works have been done in the use of myoelectric signals as a control signal to operate prosthetic devices [1]- [4] for arm amputees. Currently, the clinically available myoelectric prosthesis uses the amplitudes of surface electromyography (sEMG) signals from the forearm flexors and extensors to control hand opening and closing.…”

Section: Introductionmentioning

confidence: 99%

Effect of upper-limb positions on motion pattern recognition using electromyography

Chen

Geng

2011

2011 4th International Congress on Image and Signal Processing

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Previous studies of electromyographic (EMG) pattern recognition for neural prosthesis control mainly focused on the estimation of offline classification accuracy. Factors that may affect the performance in operating prosthesis in practice were rarely considered. In the preliminary study we investigated effects of the variation of limb positions on classification performance. Eight channels of myoelectric signals and a LDA classifier were used to identify seven classes of forearm movements in five transradial amputees. Our pilot results showed that the classification error of inter-position was about 4 times more than that of single position across the five transradial amputees (p<0.02), indicating the significant effect of limb position variation on classification performance. We further attempted to reduce the limb position effect by training the classifier with EMG from multiple EMG recording positions, and the classification performance was compared with that of single position training. It was found multiple positions training method could decrease the classification error as more positions involved, which reached its minimum value 11.25% when all five positions were included.

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Section: Introductionmentioning

confidence: 99%

Effect of upper-limb positions on motion pattern recognition using electromyography

Chen

Geng

2011

2011 4th International Congress on Image and Signal Processing

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“…The stretch re ex or co-contraction of antagonistic muscles has been used to construct a stable motor system [19]. Using these mechanisms, we have already developed a novel control design of a myoelectric prosthetic hand for compliant grasping [20]. It was found that fatigue of forearm muscles developed when the subject continued to control the nger position with EMG signals of the muscles.…”

Section: Discussionmentioning

confidence: 99%

A Mathematical Model of the Dynamic Force–length Relationship of Skeletal Muscle Operating on Ascending and Descending Limbs

Akazawa

2019

ABE

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A new Hill-type model of skeletal muscle contraction referred to as the SL/ST model is proposed based on recent physiological ndings: intact human skeletal muscles operate on the ascending limb (hereinafter referred to as the as-limb) and the descending limb (ds-limb) of the isometric force-length relationship; and stretch-evoked force enhancement (ST-enhancement) is found on the ds-limb. Dynamic behaviors differ remarkably between the two limbs. The model has two modes: a sliding lament mode (SL mode) and a stretch-evoked force enhancement mode (ST mode). The SL mode operates on the as-limb, and on the ds-limb when the muscle is shortening, while the ST mode operates when ST-enhancement occurs in the ds-limb. Transient force responses of the model to length perturbations were similar to those of frog semitendinosus muscles in vitro. Length responses to step change in load of the model suggest that the muscle is unstable and not static in SL mode on the ds-limb, while it is stable and static in SL mode on the as-limb and in ST mode on the ds-limb.

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“…Las prótesis mioeléctricas son en la actualidad una de las de mayor aplicación en el mundo, ya que brindan un mayor grado de estética y un elevado porcentaje de precisión y fuerza, basándose en la obtención de señales musculares [9] [27] [28] las mismas que son obtenidas mediante el uso de electrodos que permiten la extracción de la señal que es amplificada, procesada y filtrada al control para el manejo de la prótesis [3] [22] [29]. En la Figura 5 tenemos las partes de la prótesis mioeléctrica.…”

Section: Prótesis Mioeléctricasunclassified

Estudio del estado del arte de las prótesis de mano

Brito

Quinde

Cusco

et al. 2013

ings

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Recibido: 20-05-2013, Aprobado tras revisión: 03-06-2013. Forma sugerida de citación: Brito, J.; Quinde, X.; Cusco, D. y Calle, J. (2013). "Estudio del estado del arte de las prótesis de mano". Ingenius. N.• 9, (Enero-Junio). pp. 57-64. ISSN: 1390-650X. Resumen AbstractEn este artículo se hace una revisión de los tipos de prótesis de mano que se han desarrollado con diferentes tipos de tecnologías, incluyendo ventajas y desventajas de su utilización. Se presenta la evolución tecnológica de las prótesis de mano durante estos últi-mos años. Finalmente se hace referencia a las nuevas tendencias en la utilización de materiales inteligentes para la construcción de prótesis de mano.This article is a review of the types of prosthetic hands have been developed with different technologies, including advantages and disadvantages of their use. We present the technological evolution of prosthetic hands in recent years. Finally, reference is made to the new trends in the use of smart materials for the construction of prosthetic hand.Palabras clave: Prótesis de mano, control, grados de libertad, mioeléctrica, materiales inteligentes.

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Compliant grasp in a myoelectric hand prosthesis

Cited by 18 publications

References 24 publications

Effect of upper-limb positions on motion pattern recognition using electromyography

Effect of upper-limb positions on motion pattern recognition using electromyography

A Mathematical Model of the Dynamic Force–length Relationship of Skeletal Muscle Operating on Ascending and Descending Limbs

Estudio del estado del arte de las prótesis de mano

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