This paper presents an upper limb exoskeleton that allows cognitive(through electromyography signals)and physical user interaction(through load cells sensors)for passive and active exercises that can activate neuropla...This paper presents an upper limb exoskeleton that allows cognitive(through electromyography signals)and physical user interaction(through load cells sensors)for passive and active exercises that can activate neuroplasticity in the rehabilitation process of people who suffer from a neurological injury.For the exoskeleton to be easily accepted by patients who suffer from a neurological injury,we used the ISO9241-210:2010 as a methodology design process.As the first steps of the design process,design requirements were collected from previous usability tests and literature.Then,as a second step,a technological solution is proposed,and as a third step,the system was evaluated through performance and user testing.As part of the technological solution and to allow patient participation during the rehabilitation process,we have proposed a hybrid admittance control whose input is load cell or electromyography signals.The hybrid admittance control is intended for active therapy exercises,is easily implemented,and does not need musculoskeletal modeling to work.Furthermore,electromyography signals classification models and features were evaluated to identify the best settings for the cognitive human–robot interaction.展开更多
文摘This paper presents an upper limb exoskeleton that allows cognitive(through electromyography signals)and physical user interaction(through load cells sensors)for passive and active exercises that can activate neuroplasticity in the rehabilitation process of people who suffer from a neurological injury.For the exoskeleton to be easily accepted by patients who suffer from a neurological injury,we used the ISO9241-210:2010 as a methodology design process.As the first steps of the design process,design requirements were collected from previous usability tests and literature.Then,as a second step,a technological solution is proposed,and as a third step,the system was evaluated through performance and user testing.As part of the technological solution and to allow patient participation during the rehabilitation process,we have proposed a hybrid admittance control whose input is load cell or electromyography signals.The hybrid admittance control is intended for active therapy exercises,is easily implemented,and does not need musculoskeletal modeling to work.Furthermore,electromyography signals classification models and features were evaluated to identify the best settings for the cognitive human–robot interaction.
