{"title":"一种用于测量实时运动数据的多媒体无创电子治疗框架","authors":"Mohamed Abdur Rahman, Saleh M. Basalamah","doi":"10.1109/IHTC.2014.7147549","DOIUrl":null,"url":null,"abstract":"In this paper we present an e-Therapy framework that can dynamically provide therapy services to a patient and therapist. Using off the shelf 3D depth sensing video camera and motion control sensors, the framework can detect, recognize and track 18 different therapeutic movements originated from 7 different joints of a Hemiplegic patient and deduce live kinematic data from these movements. The framework can detect flexion-extension of forearm at fingers, elbow, shoulder, hip, knee and vertebral columns; adduction-abduction motion at hip and at shoulder joint; and rotational motions of forearm such as pronation and supination. The obtained therapeutic data consists of a wide span of body joint and motion parameters that is assumed to help medical professionals in their clinical decision making. The proposed method is non-invasive as the patient does not need to wear any external devices in the body. Finally, we share our initial test result that is encouraging.","PeriodicalId":341818,"journal":{"name":"2014 IEEE Canada International Humanitarian Technology Conference - (IHTC)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A multimedia non-invasive e-Therapy framework for measuring live kinematic data\",\"authors\":\"Mohamed Abdur Rahman, Saleh M. Basalamah\",\"doi\":\"10.1109/IHTC.2014.7147549\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we present an e-Therapy framework that can dynamically provide therapy services to a patient and therapist. Using off the shelf 3D depth sensing video camera and motion control sensors, the framework can detect, recognize and track 18 different therapeutic movements originated from 7 different joints of a Hemiplegic patient and deduce live kinematic data from these movements. The framework can detect flexion-extension of forearm at fingers, elbow, shoulder, hip, knee and vertebral columns; adduction-abduction motion at hip and at shoulder joint; and rotational motions of forearm such as pronation and supination. The obtained therapeutic data consists of a wide span of body joint and motion parameters that is assumed to help medical professionals in their clinical decision making. The proposed method is non-invasive as the patient does not need to wear any external devices in the body. Finally, we share our initial test result that is encouraging.\",\"PeriodicalId\":341818,\"journal\":{\"name\":\"2014 IEEE Canada International Humanitarian Technology Conference - (IHTC)\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE Canada International Humanitarian Technology Conference - (IHTC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IHTC.2014.7147549\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE Canada International Humanitarian Technology Conference - (IHTC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IHTC.2014.7147549","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A multimedia non-invasive e-Therapy framework for measuring live kinematic data
In this paper we present an e-Therapy framework that can dynamically provide therapy services to a patient and therapist. Using off the shelf 3D depth sensing video camera and motion control sensors, the framework can detect, recognize and track 18 different therapeutic movements originated from 7 different joints of a Hemiplegic patient and deduce live kinematic data from these movements. The framework can detect flexion-extension of forearm at fingers, elbow, shoulder, hip, knee and vertebral columns; adduction-abduction motion at hip and at shoulder joint; and rotational motions of forearm such as pronation and supination. The obtained therapeutic data consists of a wide span of body joint and motion parameters that is assumed to help medical professionals in their clinical decision making. The proposed method is non-invasive as the patient does not need to wear any external devices in the body. Finally, we share our initial test result that is encouraging.