Valeria Longatelli, Beatrice Luciani, Alessandra Pedrocchi, Marta Gandolla
{"title":"Instrumented Upper Limb Functional Assessment Using a Robotic Exoskeleton: Normative References Intervals.","authors":"Valeria Longatelli, Beatrice Luciani, Alessandra Pedrocchi, Marta Gandolla","doi":"10.1109/ICORR58425.2023.10304788","DOIUrl":null,"url":null,"abstract":"<p><p>Upper-limb rehabilitation exoskeletons offer a valuable solution to support and enhance the rehabilitation path of neural-injured patients. Such devices are usually equipped with a network of sensors that can be exploited to evaluate and monitor the performances of the users. In this work, we assess the normality ranges of different motor-performance indicators on a group of 15 healthy participants, computed with the benchmark toolbox of AGREE, an upper limb motorized exoskeleton. The toolbox implements a benchmarking scheme for the evaluation of the upper limb, used to test anterior reaching at rest position height and hand-to-mouth motor skills. We selected kinematic and electromyography performance indicators to assess the different motor abilities. We performed a pilot evaluation on three neurological patients, to verify if the AGREE benchmark toolbox was able to distinguish patients from healthy subjects on the basis of the selected performance indicators. Through a comparison between results obtained by the healthy and the small group of motor-impaired users, we successfully calculated the normality ranges for the selected performance indicators, and we pilot-showed how data gathered from AGREE can be used to evaluate the current status of the patients.</p>","PeriodicalId":73276,"journal":{"name":"IEEE ... International Conference on Rehabilitation Robotics : [proceedings]","volume":"2023 ","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE ... International Conference on Rehabilitation Robotics : [proceedings]","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICORR58425.2023.10304788","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Upper-limb rehabilitation exoskeletons offer a valuable solution to support and enhance the rehabilitation path of neural-injured patients. Such devices are usually equipped with a network of sensors that can be exploited to evaluate and monitor the performances of the users. In this work, we assess the normality ranges of different motor-performance indicators on a group of 15 healthy participants, computed with the benchmark toolbox of AGREE, an upper limb motorized exoskeleton. The toolbox implements a benchmarking scheme for the evaluation of the upper limb, used to test anterior reaching at rest position height and hand-to-mouth motor skills. We selected kinematic and electromyography performance indicators to assess the different motor abilities. We performed a pilot evaluation on three neurological patients, to verify if the AGREE benchmark toolbox was able to distinguish patients from healthy subjects on the basis of the selected performance indicators. Through a comparison between results obtained by the healthy and the small group of motor-impaired users, we successfully calculated the normality ranges for the selected performance indicators, and we pilot-showed how data gathered from AGREE can be used to evaluate the current status of the patients.