Thekla Stefanou, Allie J. Turton, A. Lenz, S. Dogramadzi
{"title":"Upper limb motion intent recognition using tactile sensing","authors":"Thekla Stefanou, Allie J. Turton, A. Lenz, S. Dogramadzi","doi":"10.1109/IROS.2017.8206573","DOIUrl":null,"url":null,"abstract":"Focusing on upper limb rehabilitation of weak stroke patients, this pilot study explores how motion intent can be detected using force sensitive resistors (FSR). This is part of a bigger project which will see the actuation and control of an intent-driven exoskeleton. The limited time stroke survivors have with their therapists means that they can not often get enough training. During active-assisted training, therapists guide the paralysed limb through a movement only after detecting visual or haptic cues of the motion intent from the patient. Aiming to replicate therapist practices of recognising patients' intention to move, a pilot study of a tactile system is performed. The system will perform consistently even with patients who have low muscle strength and control ability. Currently available devices for detecting muscle activity do not offer the robustness and performance necessary; Electromyography (EMG) sensors, a well-established method, is affected by factors like skin moisture and BCI (Brain Computer Interface) has a slow response time. The proposed tactile sensing system is a simple yet robust solution both from a sensing as well as a usability point of view. Pilot experiments have been performed with a healthy subject emulating low muscle activation conditions. An overall accuracy of 80.45% is achieved when detecting forearm and arm muscle contractions and hence motion intent.","PeriodicalId":6658,"journal":{"name":"2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"97 1","pages":"6601-6608"},"PeriodicalIF":0.0000,"publicationDate":"2017-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IROS.2017.8206573","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Focusing on upper limb rehabilitation of weak stroke patients, this pilot study explores how motion intent can be detected using force sensitive resistors (FSR). This is part of a bigger project which will see the actuation and control of an intent-driven exoskeleton. The limited time stroke survivors have with their therapists means that they can not often get enough training. During active-assisted training, therapists guide the paralysed limb through a movement only after detecting visual or haptic cues of the motion intent from the patient. Aiming to replicate therapist practices of recognising patients' intention to move, a pilot study of a tactile system is performed. The system will perform consistently even with patients who have low muscle strength and control ability. Currently available devices for detecting muscle activity do not offer the robustness and performance necessary; Electromyography (EMG) sensors, a well-established method, is affected by factors like skin moisture and BCI (Brain Computer Interface) has a slow response time. The proposed tactile sensing system is a simple yet robust solution both from a sensing as well as a usability point of view. Pilot experiments have been performed with a healthy subject emulating low muscle activation conditions. An overall accuracy of 80.45% is achieved when detecting forearm and arm muscle contractions and hence motion intent.