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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Howard, A. Brooks, D. Brown, E. Gebregiorgis, A. Yu-Ping Chen |
| Copyright Year | 2013 |
| Description | Author affiliation: Dept. of Phys. Therapy, Georgia State Univ., Atlanta, GA, USA (Yu-Ping Chen) || Georgia Inst. of Technol., Atlanta, GA, USA (Howard, A.; Brooks, D.) || Dept. of Electr. Eng., Rochester Inst. of Technol., Rochester, NY, USA (Brown, E.; Gebregiorgis, A.) |
| Abstract | In recent years, robot-assisted rehabilitation has gained momentum as a viable means for improving outcomes for therapeutic interventions. Such therapy experiences allow controlled and repeatable trials and quantitative evaluation of mobility metrics. Typically though these robotic devices have been focused on rehabilitation within a clinical setting. In these traditional robot-assisted rehabilitation studies, participants are required to perform goal-directed movements with the robot during a therapy session. This requires physical contact between the participant and the robot to enable precise control of the task, as well as a means to collect relevant performance data. On the other hand, non-contact means of robot interaction can provide a safe methodology for extracting the control data needed for in-home rehabilitation. As such, in this paper we discuss a contact and non-contact based method for upper-arm rehabilitation exercises that enables quantification of upper-arm movements. We evaluate our methodology on upper-arm abduction/adduction movements and discuss the advantages and limitations of each approach as applied to an in-home rehabilitation scenario. |
| Starting Page | 1 |
| Ending Page | 6 |
| File Size | 2775320 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781467360227 |
| ISSN | 19457901 |
| e-ISBN | 9781467360241 |
| DOI | 10.1109/ICORR.2013.6650487 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2013-06-24 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | vision-based assessment EMG measurements Hidden Markov models Shoulder robotic rehabilitation Electromyography Data mining therapeutic robotics Joints Elbow Robots |
| Content Type | Text |
| Resource Type | Article |
| Subject | Rehabilitation Control and Systems Engineering Electrical and Electronic Engineering |
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