Design of movement sequences for arm rehabilitation of post-stroke
Rashidah Suhaimi, Kamil S. Talha, Wan Khairunizam, Mohd Asri Ariffin
Abstract
Rashidah Suhaimi, Kamil S. Talha, Wan Khairunizam, Mohd Asri Ariffin
Abstract
This article presents the design of movement sequences for arm rehabilitation of stroke patient. The objective of this research is to develop the best movement sequences suitable for arm rehabilitation of hemiparesis sufferers based on the features analyzed that represent muscle activity. 8 healthy subjects including both male and female performed four arm movement sequences task consist of arm lifting and reaching movement in real environment. Muscle activities are recorded using electromyography (EMG) involving deltoid anterior, deltoid lateral, biceps and triceps. Based on the previous research, Amount of movement (AOM) feature is calculated to observe the muscle activation for each movement sequence task. The experimental results show that it is likely to produce optimum arm movement sequences for arm rehabilitation and the sequences are suitable to deploy in virtual reality in future research.
OpenAlex reports 9 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
This article presents the design of movement sequences for arm rehabilitation of stroke patient. The objective of this research is to develop the best movement sequences suitable for arm rehabilitation of hemiparesis sufferers based on the features analyzed that represent muscle activity. 8 healthy subjects including both male and female performed four arm movement sequences task consist of arm lifting and reaching movement in real environment. Muscle activities are recorded using electromyography (EMG) involving deltoid anterior, deltoid lateral, biceps and triceps. Based on the previous research, Amount of movement (AOM) feature is calculated to observe the muscle activation for each movement sequence task. The experimental results show that it is likely to produce optimum arm movement sequences for arm rehabilitation and the sequences are suitable to deploy in virtual reality in future research.
Key concepts: Biceps, Movement (music), Rehabilitation, Physical medicine and rehabilitation, Hemiparesis, Deltoid muscle, Deltoid curve, Electromyography