{"title":"使用深度学习的腕带跌落检测系统","authors":"Kulwarun Warunsin, Thongchai Phairoh","doi":"10.1109/icccs55155.2022.9846023","DOIUrl":null,"url":null,"abstract":"Fall is one of the significant problems threatening older people. Ambient Assisted Living (AAL) is equipment and process for supporting older people’s independent and safe living. AAL includes elderly fall detection. The life of older people will be safe if rescue comes to help in the safety period after fall. Then fall detection is needed for life safety. The development of microcontrollers is very fast with tiny in size, high calculation performance, and low power consumption. In addition, the software for machine learning is extensive interest and developed. This study developed a fall detection system by applying an accelerometer as a sensor and a deep learning algorithm as a fall pattern recognition. We used an ESP32 microcontroller to determine the pattern of the user’s activity. If ESP32 detects the fall, it will send a fall alert to the provider via Wi-Fi with the LINE application. The fall detection model of this study has an accuracy of 96.55% with the testing data.","PeriodicalId":121713,"journal":{"name":"2022 7th International Conference on Computer and Communication Systems (ICCCS)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Wristband Fall Detection System Using Deep Learning\",\"authors\":\"Kulwarun Warunsin, Thongchai Phairoh\",\"doi\":\"10.1109/icccs55155.2022.9846023\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Fall is one of the significant problems threatening older people. Ambient Assisted Living (AAL) is equipment and process for supporting older people’s independent and safe living. AAL includes elderly fall detection. The life of older people will be safe if rescue comes to help in the safety period after fall. Then fall detection is needed for life safety. The development of microcontrollers is very fast with tiny in size, high calculation performance, and low power consumption. In addition, the software for machine learning is extensive interest and developed. This study developed a fall detection system by applying an accelerometer as a sensor and a deep learning algorithm as a fall pattern recognition. We used an ESP32 microcontroller to determine the pattern of the user’s activity. If ESP32 detects the fall, it will send a fall alert to the provider via Wi-Fi with the LINE application. The fall detection model of this study has an accuracy of 96.55% with the testing data.\",\"PeriodicalId\":121713,\"journal\":{\"name\":\"2022 7th International Conference on Computer and Communication Systems (ICCCS)\",\"volume\":\"27 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-04-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 7th International Conference on Computer and Communication Systems (ICCCS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/icccs55155.2022.9846023\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 7th International Conference on Computer and Communication Systems (ICCCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/icccs55155.2022.9846023","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Wristband Fall Detection System Using Deep Learning
Fall is one of the significant problems threatening older people. Ambient Assisted Living (AAL) is equipment and process for supporting older people’s independent and safe living. AAL includes elderly fall detection. The life of older people will be safe if rescue comes to help in the safety period after fall. Then fall detection is needed for life safety. The development of microcontrollers is very fast with tiny in size, high calculation performance, and low power consumption. In addition, the software for machine learning is extensive interest and developed. This study developed a fall detection system by applying an accelerometer as a sensor and a deep learning algorithm as a fall pattern recognition. We used an ESP32 microcontroller to determine the pattern of the user’s activity. If ESP32 detects the fall, it will send a fall alert to the provider via Wi-Fi with the LINE application. The fall detection model of this study has an accuracy of 96.55% with the testing data.