Ni Wayan Yulya Wiani, A. Arifin, M. Fatoni, Josaphat Pramudijanto
{"title":"Instrumentation Design of Game Rehabilitation with Myoelectric Command","authors":"Ni Wayan Yulya Wiani, A. Arifin, M. Fatoni, Josaphat Pramudijanto","doi":"10.1109/BioSMART54244.2021.9677751","DOIUrl":null,"url":null,"abstract":"Stroke is a potentially fatal illness caused by clotting of the blood vessels that supply oxygen to the brain. Up to 65 percent of stroke patients are affected by Hemiparesis. Muscle weakness is a typical side effect, which might lead to a reduction in physical activity. This makes it difficult for post-stroke patients to carry out daily tasks. Therefore, a game-based rehabilitation strategy focused on grasping movement is recommended to help the upper limbs recover. Individual biomedical signals were used to control the game. EMG instrumentation used to process biomedical signals. To aid in this process, hand gloves are also used to evaluate the range of motion produced during rehabilitation. The game becomes more exciting by using Leap Motion to track patient hand movements and move virtual hands in the game. The experimental results revealed an average increase in the amplitude of the LEMG signal generated by participants 1 and 2. The average amplitude increase in subject 1 was 22.81 mV, while it was 89.60 mV in subject 2. For further research, a compact and sensitive EMG instrumentation can be built. In addition, real-time computing can be used to build rehabilitation systems that can detect the onset of LEMG and create more interactive games.","PeriodicalId":286026,"journal":{"name":"2021 4th International Conference on Bio-Engineering for Smart Technologies (BioSMART)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 4th International Conference on Bio-Engineering for Smart Technologies (BioSMART)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BioSMART54244.2021.9677751","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Stroke is a potentially fatal illness caused by clotting of the blood vessels that supply oxygen to the brain. Up to 65 percent of stroke patients are affected by Hemiparesis. Muscle weakness is a typical side effect, which might lead to a reduction in physical activity. This makes it difficult for post-stroke patients to carry out daily tasks. Therefore, a game-based rehabilitation strategy focused on grasping movement is recommended to help the upper limbs recover. Individual biomedical signals were used to control the game. EMG instrumentation used to process biomedical signals. To aid in this process, hand gloves are also used to evaluate the range of motion produced during rehabilitation. The game becomes more exciting by using Leap Motion to track patient hand movements and move virtual hands in the game. The experimental results revealed an average increase in the amplitude of the LEMG signal generated by participants 1 and 2. The average amplitude increase in subject 1 was 22.81 mV, while it was 89.60 mV in subject 2. For further research, a compact and sensitive EMG instrumentation can be built. In addition, real-time computing can be used to build rehabilitation systems that can detect the onset of LEMG and create more interactive games.