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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