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After stroke, capacity to complete tasks in the treatment setting with the more-affected arm is an unreliable index of actual use of that extremity in daily life. Available objective methods for monitoring real-world arm use rely on placing movement sensors on patients. These methods provide information on amount but not type of arm activity, e.g., functional versus nonfunctional movement. This paper presents an approach that places sensors on patients and household objects, overcoming this limitation. An accelerometer and the transmitter component of a radio-frequency proximity sensor are attached to objects; the receiver component is attached to the arm of interest. The receiver triggers an on-board radio-frequency identification tag to signal proximity when that arm is within 23 cm of an instrumented object. In benchmark testing, this system detected perfectly which arm was used to move the target object on 200 trials. In a laboratory study with 35 undergraduates, increasing the amount of time target objects were moved with the arm of interest resulted in a corresponding increase in system output (p <; 0.0001) . Moreover, measurement error was low (≤2.5%). The results support this system's reliability and validity in individuals with unimpaired movement; testing is now warranted in stroke patients.
Neural Systems and Rehabilitation Engineering, IEEE Transactions on (Volume:20 , Issue: 6 )
Date of Publication: Nov. 2012