Abstract
We present a novel task-specific upper-extremity rehabilitation system that uses an instrumented cup and an interactive gaming environment to promote patient engagement during repetitive rehabilitative exercise. The designed system tracks the movement of the cup as a stroke patient uses her forearm to perform a complex goal-oriented and task-specific activity, namely, grasping, lifting, and tilting the cup to drink from it. A force sensitive resistive sensor is mounted on the cup to constantly monitor the grasp force and the cup is endowed with rich features allowing a webcam to track and estimate its location and pose with the aid of state-of-the-art machine learning algorithms. This bi-manual forearm rehabilitation system is designed to enable stroke patients to perform an activity of daily living, namely, grasping, lifting, and tilting, repetitively, at their home as an exercise, so that they can relearn the motions of arm, wrist, and hand related to drinking.
Original language | English |
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Title of host publication | 2019 International Symposium on Medical Robotics, ISMR 2019 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Electronic) | 9781538678251 |
DOIs | |
State | Published - May 8 2019 |
Externally published | Yes |
Event | 2019 International Symposium on Medical Robotics, ISMR 2019 - Atlanta, United States Duration: Apr 3 2019 → Apr 5 2019 |
Publication series
Name | 2019 International Symposium on Medical Robotics, ISMR 2019 |
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Conference
Conference | 2019 International Symposium on Medical Robotics, ISMR 2019 |
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Country/Territory | United States |
City | Atlanta |
Period | 04/3/19 → 04/5/19 |
Funding
This work is supported in part by the National Science Foundation grants DRK-12 DRL: 1417769, ITEST DRL: 1614085, and RET Site EEC: 1542286; NY Space Grant Consortium grant 76156-10488; and National Institute of Health grant R01HD071978.
Keywords
- Stroke
- machine vision
- pose estimation
- rehabilitation
- virtual environment