I. H. Kusumah, Paiz Ilham Mauludi, Anggy Pradiftha Junfithrana, Edwinanto
{"title":"基于Android应用的老年人穿戴式跌倒检测简易带设计","authors":"I. H. Kusumah, Paiz Ilham Mauludi, Anggy Pradiftha Junfithrana, Edwinanto","doi":"10.1109/ICCED53389.2021.9664840","DOIUrl":null,"url":null,"abstract":"Falling is a human movement that can cause injury, either minor injury or serious injury can even cause someone’s death. Age is one of the causes of a person’s decline in movement. When elderly people experience falls, they experience not only physical but also psychological disorders such as loss of self-esteem and feelings of fear of walking to avoid the danger of falling. if emergency treatment arrives too late, a fall injury can result in disability, paralysis, and even death. The objectives are to develop tools and applications that can detect the fall of a person. The Method uses wearable fall detection with a simple belt design that implements a threshold-based detection algorithm that uses accelerometer and gyroscope sensors and can also be monitored through an application installed on an Android smartphone. The Results of the data that has been tested can be obtained with an accuracy value of 85%, a sensitivity value of 77%, and a specificity value of 100%. This device is very promising and being developed at the Sukabumi nursing home. The injuries suffered by falling victims will be slightly minimized because when someone falls it will be detected by the surrounding family so that the victim will be evacuated immediately.","PeriodicalId":6800,"journal":{"name":"2021 IEEE 7th International Conference on Computing, Engineering and Design (ICCED)","volume":"14 1","pages":"1-5"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Wearable Fall Detection for Elderly with Simple Belt Design Using Android Application\",\"authors\":\"I. H. Kusumah, Paiz Ilham Mauludi, Anggy Pradiftha Junfithrana, Edwinanto\",\"doi\":\"10.1109/ICCED53389.2021.9664840\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Falling is a human movement that can cause injury, either minor injury or serious injury can even cause someone’s death. Age is one of the causes of a person’s decline in movement. When elderly people experience falls, they experience not only physical but also psychological disorders such as loss of self-esteem and feelings of fear of walking to avoid the danger of falling. if emergency treatment arrives too late, a fall injury can result in disability, paralysis, and even death. The objectives are to develop tools and applications that can detect the fall of a person. The Method uses wearable fall detection with a simple belt design that implements a threshold-based detection algorithm that uses accelerometer and gyroscope sensors and can also be monitored through an application installed on an Android smartphone. The Results of the data that has been tested can be obtained with an accuracy value of 85%, a sensitivity value of 77%, and a specificity value of 100%. This device is very promising and being developed at the Sukabumi nursing home. The injuries suffered by falling victims will be slightly minimized because when someone falls it will be detected by the surrounding family so that the victim will be evacuated immediately.\",\"PeriodicalId\":6800,\"journal\":{\"name\":\"2021 IEEE 7th International Conference on Computing, Engineering and Design (ICCED)\",\"volume\":\"14 1\",\"pages\":\"1-5\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-08-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE 7th International Conference on Computing, Engineering and Design (ICCED)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCED53389.2021.9664840\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 7th International Conference on Computing, Engineering and Design (ICCED)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCED53389.2021.9664840","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Wearable Fall Detection for Elderly with Simple Belt Design Using Android Application
Falling is a human movement that can cause injury, either minor injury or serious injury can even cause someone’s death. Age is one of the causes of a person’s decline in movement. When elderly people experience falls, they experience not only physical but also psychological disorders such as loss of self-esteem and feelings of fear of walking to avoid the danger of falling. if emergency treatment arrives too late, a fall injury can result in disability, paralysis, and even death. The objectives are to develop tools and applications that can detect the fall of a person. The Method uses wearable fall detection with a simple belt design that implements a threshold-based detection algorithm that uses accelerometer and gyroscope sensors and can also be monitored through an application installed on an Android smartphone. The Results of the data that has been tested can be obtained with an accuracy value of 85%, a sensitivity value of 77%, and a specificity value of 100%. This device is very promising and being developed at the Sukabumi nursing home. The injuries suffered by falling victims will be slightly minimized because when someone falls it will be detected by the surrounding family so that the victim will be evacuated immediately.