This paper presents a robust control approach to control the movement of a prosthetic hand based on an estimation of the finger angles using surface electromyographic (sEMG) signals. All the available prosthesis uses the motion control strategy which is pre-programmed get initiated when some threshold value of the measured sEMG signal is reached for a particular motion set. Here we use a novel approach to model the finger angle which utilizes System Identification (SI) techniques. The dynamic model obtained allows the instantaneous control for the finger motions. sEMG data is acquired using an array of nine sensors and the corresponding finger angle is acquired using a finger angle measuring device and a data glove. A nonlinear Teager–Kaiser Energy (TKE) operator based nonlinear spatial filter is used to filter sEMG data whereas the angle data is filtered using a Chebyshev type-II filters. An EMG-angle estimation model is proposed then the estimated angles are used to control to control movement of a prosthetic hand using a robust approach which can deal with modeling uncertainty. The overall performance of the prosthetic hand are measured based on numerical simulation. The resulting fusion based output of this approach plus the robust controller gives improved the prosthetic hand motion control.

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Категория: Научные статьи | 1 Комментарий »

Taking care of older adults is among the major challenges currently faced by ageing populations. Researchers, designers, and engineers have proposed socially assistive robots as one way of helping elderly people stay in their homes longer. In a systematic literature review, this paper wants to investigate if and how evaluations of the acceptance of socially assistive robots by older people take into account sociodemographic factors. The results indicate that this only holds true for a few studies. Research that incorporates age, gender, education, and so forth; clearly shows that these key factors have a significant impact. However, the relations are complex and experience with technology mitigates the influence of sociodemographic factors on acceptance. Assistive devices should be adaptable to individual needs to be able to consider all these factors.

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Категория: Научные статьи | 1 Комментарий »

В исследовательской лаборатории в недрах коридоров Etcheverry Hall, 22-летний Остин Уитни (Austin Whitney) облачается в роботизированный костюм и делает практически невозможное. Парализованный ниже пояса после автомобильной аварии в 2007 году, Уитни снова учится ходить.

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Категория: Austin | 2 комментария »

Реабилитация инсультных больных часто требует 3-6 многочасовых сеансов в неделю с врачом-физиотерапевтом.Кроме того, пациенты имеют проблемы с неинтересными многочисленными упражнениями, которые им назначают на дом.

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Бен Фарлей провел лето, работая в лаборатории Bionics Lab при Калифорнийском университете, Санта Круз, под руководством Джейкоба Розена.

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