DocumentCode :
1791967
Title :
Development of a bilateral rehabilitation training system using the haptic device and inertia sensors
Author :
Songyuan Zhang ; Shuxiang Guo ; Mohan Qu ; Muye Pang
Author_Institution :
Grad. Sch. of Eng., Kagawa Univ., Takamatsu, Japan
fYear :
2014
fDate :
3-6 Aug. 2014
Firstpage :
606
Lastpage :
611
Abstract :
According to the neuro-rehabilitation theory, passive, resistance and bilateral training are commonly applied for recovering the motor-function of stroke patient. Among them, bilateral training is proved to be an effective method for the hemiparesis that occupies most part of stroke patients. In this article, a novel system is proposed for providing the bilateral training with coordinative motion of two limbs. This system is developed for the elbow function recovery and the motion of two limbs is detected with two inertia sensors. A commercial haptic device (Phantom Premium) is adopted for providing a feedback with information of errors and how to correct them. Combined with a graphic interface which provides a visual feedback, the patient can adjust the two limbs to a coordinative motion. This system can perform the training to those patients with some muscle strength. However, usually the rehabilitation training is hierarchical and those patients with little muscle strength can even not lift their own limbs. Therefore, a light-weight exoskeleton device is applied and this device could provide partial assisting force, thus the patient can gradually adapt to the training. In this article, an issue about the effectiveness of feedback is discussed and verified with several contrast experiments.
Keywords :
computer based training; control engineering computing; educational robots; graphical user interfaces; handicapped aids; haptic interfaces; human-robot interaction; image motion analysis; image sensors; medical computing; medical robotics; neurophysiology; object detection; patient rehabilitation; robot vision; Phantom Premium; bilateral rehabilitation training system development; coordinative limb motion; elbow function recovery; graphic interface; haptic device; hemiparesis; inertia sensors; light-weight exoskeleton device; limb motion detection; muscle strength; neuro-rehabilitation theory; partial assisting force; passive training; resistance training; stroke patient motor-function recovery; visual feedback; Elbow; Exoskeletons; Force; Force feedback; Phantoms; Sensors; Training; Bilateral training; Exoskeleton device; Feedback; Haptic device; Upper limb rehabilitation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mechatronics and Automation (ICMA), 2014 IEEE International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-1-4799-3978-7
Type :
conf
DOI :
10.1109/ICMA.2014.6885766
Filename :
6885766
Link To Document :
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