Network of movement and proximity sensors for monitoring upper-extremity motor activity after stroke: proof of principle.

Objective: To test the convergent validity of an objective method, Sensor-Enabled Radio-frequency Identification System for Monitoring Arm Activity (SERSMAA), that distinguishes between functional and nonfunctional activity.

Design: Cross-sectional study.

Setting: Laboratory.

Participants: Participants (N=25) were ≥0.2 years poststroke (median, 9) with a wide range of severity of upper-extremity hemiparesis.

Interventions: Not applicable.

Main Outcome Measures: After stroke, laboratory tests of the motor capacity of the more-affected arm poorly predict spontaneous use of that arm in daily life. However, available subjective methods for measuring everyday arm use are vulnerable to self-report biases, whereas available objective methods only provide information on the amount of activity without regard to its relation with function. The SERSMAA consists of a proximity-sensor receiver on the more-affected arm and multiple units placed on objects. Functional activity is signaled when the more-affected arm is close to an object that is moved. Participants were videotaped during a laboratory simulation of an everyday activity, that is, setting a table with cups, bowls, and plates instrumented with transmitters. Observers independently coded the videos in 2-second blocks with a validated system for classifying more-affected arm activity.

Results: There was a strong correlation (r=.87, P<.001) between time that the more-affected arm was used for handling objects according to the SERSMAA and functional activity according to the observers.

Conclusions: The convergent validity of SERSMAA for measuring more-affected arm functional activity after stroke was supported in a simulation of everyday activity.