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Position Error-Based Identification of Subject Participation in Robotic-Rehabilitation

Shrey Pareek, Pramod Chembrammel, John Nguyen, Thenkurussi Kesavadas

Year
2018
Citations
4

Abstract

In this paper, we present a haptics-based rehabilitation system that uses kinematics of a haptic device to monitor a subject's participation in therapy. In robot-assisted therapy, it is crucial to monitor if the patient is actively performing the rehabilitation task and is not just passively following the robot's motions. In this paper, we have used position-tracking error patterns as a metric for identifying whether the subject is actively participating in the therapy. Using a single feature identification scheme, our method demonstrated a real-time classification accuracy of 80.04% in separating active and passive participation during a therapy session.

Keywords

Computer scienceRehabilitationIdentification (biology)Task (project management)RobotHaptic technologyMetric (unit)Artificial intelligenceSession (web analytics)Rehabilitation robotics

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