Md. Fahim Bhuyain, Md. Ahsan-Ul Kabir Shawon, N. Sakib, Tasnuva Faruk, Md. Kafiul Islam, K. M. Salim
{"title":"基于eeg的四肢瘫痪电动轮椅控制系统的设计与开发","authors":"Md. Fahim Bhuyain, Md. Ahsan-Ul Kabir Shawon, N. Sakib, Tasnuva Faruk, Md. Kafiul Islam, K. M. Salim","doi":"10.1109/ICREST.2019.8644378","DOIUrl":null,"url":null,"abstract":"In this research, we have designed and developed an EOG-based Electric Wheelchair system for patients suffering from Quadriplegia or Quadriparesis or similar condition where a person is not only unable to walk but also unable to move fingers to press a button. The designed EOG recorder is used to capture intentional eye blink and eye movements (i.e. EOG signals) performed by the patient sitting in the Wheelchair. The recorded EOG signals are then processed in Arduino platform and converted to command signals to control the movement of the wheelchair in four directions (i.e. left, right, front and back) from four different EOG signals (i.e. left, right, up and down eye movements) along with start and stop commands from intentional eye blink signals. The electric wheelchair is also designed and implemented by converting a normal chair to wheelchair with necessary motors (2 DC brushed motors), wheels, and control circuitry along with the battery power supply. The EOG system is portable, wireless and user friendly which can be worn by the patient to control the wheelchair. Test experiment with subjects suggests that the proposed EOG system can detect different eye movements with an average accuracy of 90% in controlling the wheelchair. The overall cost of the developed system is around 20,000 BDT which is affordable. The proposed system has a huge potential to be used by our country’s rural and middle-income people suffering from similar disability who can’t afford commercially available expensive automated electric wheelchairs. This work can be further modified to use in other applications for the same type of patients such as EOG controlled mouse cursor for computer use. Thus this EOG-based human-machine interface applications can significantly enhance the quality of life for such middle-income or lower-middle income patients living in the developing countries such as Bangladesh.","PeriodicalId":108842,"journal":{"name":"2019 International Conference on Robotics,Electrical and Signal Processing Techniques (ICREST)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Design and Development of an EOG-based System to Control Electric Wheelchair for People Suffering from Quadriplegia or Quadriparesis\",\"authors\":\"Md. Fahim Bhuyain, Md. Ahsan-Ul Kabir Shawon, N. Sakib, Tasnuva Faruk, Md. Kafiul Islam, K. M. Salim\",\"doi\":\"10.1109/ICREST.2019.8644378\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this research, we have designed and developed an EOG-based Electric Wheelchair system for patients suffering from Quadriplegia or Quadriparesis or similar condition where a person is not only unable to walk but also unable to move fingers to press a button. The designed EOG recorder is used to capture intentional eye blink and eye movements (i.e. EOG signals) performed by the patient sitting in the Wheelchair. The recorded EOG signals are then processed in Arduino platform and converted to command signals to control the movement of the wheelchair in four directions (i.e. left, right, front and back) from four different EOG signals (i.e. left, right, up and down eye movements) along with start and stop commands from intentional eye blink signals. The electric wheelchair is also designed and implemented by converting a normal chair to wheelchair with necessary motors (2 DC brushed motors), wheels, and control circuitry along with the battery power supply. The EOG system is portable, wireless and user friendly which can be worn by the patient to control the wheelchair. Test experiment with subjects suggests that the proposed EOG system can detect different eye movements with an average accuracy of 90% in controlling the wheelchair. The overall cost of the developed system is around 20,000 BDT which is affordable. The proposed system has a huge potential to be used by our country’s rural and middle-income people suffering from similar disability who can’t afford commercially available expensive automated electric wheelchairs. This work can be further modified to use in other applications for the same type of patients such as EOG controlled mouse cursor for computer use. Thus this EOG-based human-machine interface applications can significantly enhance the quality of life for such middle-income or lower-middle income patients living in the developing countries such as Bangladesh.\",\"PeriodicalId\":108842,\"journal\":{\"name\":\"2019 International Conference on Robotics,Electrical and Signal Processing Techniques (ICREST)\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Conference on Robotics,Electrical and Signal Processing Techniques (ICREST)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICREST.2019.8644378\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Robotics,Electrical and Signal Processing Techniques (ICREST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICREST.2019.8644378","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Design and Development of an EOG-based System to Control Electric Wheelchair for People Suffering from Quadriplegia or Quadriparesis
In this research, we have designed and developed an EOG-based Electric Wheelchair system for patients suffering from Quadriplegia or Quadriparesis or similar condition where a person is not only unable to walk but also unable to move fingers to press a button. The designed EOG recorder is used to capture intentional eye blink and eye movements (i.e. EOG signals) performed by the patient sitting in the Wheelchair. The recorded EOG signals are then processed in Arduino platform and converted to command signals to control the movement of the wheelchair in four directions (i.e. left, right, front and back) from four different EOG signals (i.e. left, right, up and down eye movements) along with start and stop commands from intentional eye blink signals. The electric wheelchair is also designed and implemented by converting a normal chair to wheelchair with necessary motors (2 DC brushed motors), wheels, and control circuitry along with the battery power supply. The EOG system is portable, wireless and user friendly which can be worn by the patient to control the wheelchair. Test experiment with subjects suggests that the proposed EOG system can detect different eye movements with an average accuracy of 90% in controlling the wheelchair. The overall cost of the developed system is around 20,000 BDT which is affordable. The proposed system has a huge potential to be used by our country’s rural and middle-income people suffering from similar disability who can’t afford commercially available expensive automated electric wheelchairs. This work can be further modified to use in other applications for the same type of patients such as EOG controlled mouse cursor for computer use. Thus this EOG-based human-machine interface applications can significantly enhance the quality of life for such middle-income or lower-middle income patients living in the developing countries such as Bangladesh.