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Post-Stroke Rehabilitation Exosceleton Movement Control using EMG Signal
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@article{IJASEIT4960, author = {Akif Rahmatillah and Osmalina Nur Rahma and Muhammad Amin and Septian Indra Wicaksana and Khusnul Ain and Riries Rulaningtyas}, title = {Post-Stroke Rehabilitation Exosceleton Movement Control using EMG Signal}, journal = {International Journal on Advanced Science, Engineering and Information Technology}, volume = {8}, number = {2}, year = {2018}, pages = {616--621}, keywords = {Post-stroke rehabilitation; EMG; Exoskeleton; IIR Filter; Kalman Filter}, abstract = {Post-stroke rehabilitation device is very important nowadays, considering the high rate of disability caused by stroke especially arm function. About 50% of stroke survivors experience the unilateral motor deficits which decreased upper extremity function. Therefore, hand and shoulders therapy are generally performed in advance to support patients’ daily activities. Electromyograph (EMG) signals from selective muscles were proven to provide additional power for post-stroke rehabilitation device to recover more quickly because the patient participates actively in rehabilitation. This paper describes a preliminary prototype of upper limb exoskeleton for post-stroke therapy devices utilizes automatic control algorithm to control human arm movement with one degree of freedom based on a myoelectric signal of muscle biceps brachii from their unaffected side. This study used low-cost instruments and digital signal processing, such as IIR low pass filter followed by Kalman filter to generate the myoelectric signal that separated from noise as an input for controlling the DC motor which moved the exoskeleton of arm therapy mechanic. The accuracy of system performance in this study was 95%. Hopefully, this device can help stroke survivors to perform therapy independently without depending on therapists so that rehabilitation will be more effective and efficient.}, issn = {2088-5334}, publisher = {INSIGHT - Indonesian Society for Knowledge and Human Development}, url = {http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=4960}, doi = {10.18517/ijaseit.8.2.4960} }
EndNote
%A Rahmatillah, Akif %A Rahma, Osmalina Nur %A Amin, Muhammad %A Wicaksana, Septian Indra %A Ain, Khusnul %A Rulaningtyas, Riries %D 2018 %T Post-Stroke Rehabilitation Exosceleton Movement Control using EMG Signal %B 2018 %9 Post-stroke rehabilitation; EMG; Exoskeleton; IIR Filter; Kalman Filter %! Post-Stroke Rehabilitation Exosceleton Movement Control using EMG Signal %K Post-stroke rehabilitation; EMG; Exoskeleton; IIR Filter; Kalman Filter %X Post-stroke rehabilitation device is very important nowadays, considering the high rate of disability caused by stroke especially arm function. About 50% of stroke survivors experience the unilateral motor deficits which decreased upper extremity function. Therefore, hand and shoulders therapy are generally performed in advance to support patients’ daily activities. Electromyograph (EMG) signals from selective muscles were proven to provide additional power for post-stroke rehabilitation device to recover more quickly because the patient participates actively in rehabilitation. This paper describes a preliminary prototype of upper limb exoskeleton for post-stroke therapy devices utilizes automatic control algorithm to control human arm movement with one degree of freedom based on a myoelectric signal of muscle biceps brachii from their unaffected side. This study used low-cost instruments and digital signal processing, such as IIR low pass filter followed by Kalman filter to generate the myoelectric signal that separated from noise as an input for controlling the DC motor which moved the exoskeleton of arm therapy mechanic. The accuracy of system performance in this study was 95%. Hopefully, this device can help stroke survivors to perform therapy independently without depending on therapists so that rehabilitation will be more effective and efficient. %U http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=4960 %R doi:10.18517/ijaseit.8.2.4960 %J International Journal on Advanced Science, Engineering and Information Technology %V 8 %N 2 %@ 2088-5334
IEEE
Akif Rahmatillah,Osmalina Nur Rahma,Muhammad Amin,Septian Indra Wicaksana,Khusnul Ain and Riries Rulaningtyas,"Post-Stroke Rehabilitation Exosceleton Movement Control using EMG Signal," International Journal on Advanced Science, Engineering and Information Technology, vol. 8, no. 2, pp. 616-621, 2018. [Online]. Available: http://dx.doi.org/10.18517/ijaseit.8.2.4960.
RefMan/ProCite (RIS)
TY - JOUR AU - Rahmatillah, Akif AU - Rahma, Osmalina Nur AU - Amin, Muhammad AU - Wicaksana, Septian Indra AU - Ain, Khusnul AU - Rulaningtyas, Riries PY - 2018 TI - Post-Stroke Rehabilitation Exosceleton Movement Control using EMG Signal JF - International Journal on Advanced Science, Engineering and Information Technology; Vol. 8 (2018) No. 2 Y2 - 2018 SP - 616 EP - 621 SN - 2088-5334 PB - INSIGHT - Indonesian Society for Knowledge and Human Development KW - Post-stroke rehabilitation; EMG; Exoskeleton; IIR Filter; Kalman Filter N2 - Post-stroke rehabilitation device is very important nowadays, considering the high rate of disability caused by stroke especially arm function. About 50% of stroke survivors experience the unilateral motor deficits which decreased upper extremity function. Therefore, hand and shoulders therapy are generally performed in advance to support patients’ daily activities. Electromyograph (EMG) signals from selective muscles were proven to provide additional power for post-stroke rehabilitation device to recover more quickly because the patient participates actively in rehabilitation. This paper describes a preliminary prototype of upper limb exoskeleton for post-stroke therapy devices utilizes automatic control algorithm to control human arm movement with one degree of freedom based on a myoelectric signal of muscle biceps brachii from their unaffected side. This study used low-cost instruments and digital signal processing, such as IIR low pass filter followed by Kalman filter to generate the myoelectric signal that separated from noise as an input for controlling the DC motor which moved the exoskeleton of arm therapy mechanic. The accuracy of system performance in this study was 95%. Hopefully, this device can help stroke survivors to perform therapy independently without depending on therapists so that rehabilitation will be more effective and efficient. UR - http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=4960 DO - 10.18517/ijaseit.8.2.4960
RefWorks
RT Journal Article ID 4960 A1 Rahmatillah, Akif A1 Rahma, Osmalina Nur A1 Amin, Muhammad A1 Wicaksana, Septian Indra A1 Ain, Khusnul A1 Rulaningtyas, Riries T1 Post-Stroke Rehabilitation Exosceleton Movement Control using EMG Signal JF International Journal on Advanced Science, Engineering and Information Technology VO 8 IS 2 YR 2018 SP 616 OP 621 SN 2088-5334 PB INSIGHT - Indonesian Society for Knowledge and Human Development K1 Post-stroke rehabilitation; EMG; Exoskeleton; IIR Filter; Kalman Filter AB Post-stroke rehabilitation device is very important nowadays, considering the high rate of disability caused by stroke especially arm function. About 50% of stroke survivors experience the unilateral motor deficits which decreased upper extremity function. Therefore, hand and shoulders therapy are generally performed in advance to support patients’ daily activities. Electromyograph (EMG) signals from selective muscles were proven to provide additional power for post-stroke rehabilitation device to recover more quickly because the patient participates actively in rehabilitation. This paper describes a preliminary prototype of upper limb exoskeleton for post-stroke therapy devices utilizes automatic control algorithm to control human arm movement with one degree of freedom based on a myoelectric signal of muscle biceps brachii from their unaffected side. This study used low-cost instruments and digital signal processing, such as IIR low pass filter followed by Kalman filter to generate the myoelectric signal that separated from noise as an input for controlling the DC motor which moved the exoskeleton of arm therapy mechanic. The accuracy of system performance in this study was 95%. Hopefully, this device can help stroke survivors to perform therapy independently without depending on therapists so that rehabilitation will be more effective and efficient. LK http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=4960 DO - 10.18517/ijaseit.8.2.4960