Ann David, StephenSukumaran ReethaJanetSureka, Sankaralingam Gayathri, Salai Jeyseelan Annamalai, Selvaraj Samuelkamleshkumar, Anju Kuruvilla, Henry Prakash Magimairaj, Skm Varadhan, Sivakumar Balasubramanian
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引用次数: 4
Abstract
Introduction: Accelerometry-based activity counting for measuring arm use is prone to overestimation due to non-functional movements. In this paper, we used an inertial measurement unit (IMU)-based gross movement (GM) score to quantify arm use.
Methods: In this two-part study, we first characterized the GM by comparing it to annotated video recordings of 5 hemiparetic patients and 10 control subjects performing a set of activities. In the second part, we tracked the arm use of 5 patients and 5 controls using two wrist-worn IMUs for 7 and 3 days, respectively. The IMU data was used to develop quantitative measures (total and relative arm use) and a visualization method for arm use.
Results: From the characterization study, we found that GM detects functional activities with 50-60% accuracy and eliminates non-functional activities with >90% accuracy. Continuous monitoring of arm use showed that the arm use was biased towards the dominant limb and less paretic limb for controls and patients, respectively.
Conclusions: The gross movement score has good specificity but low sensitivity in identifying functional activity. The at-home study showed that it is feasible to use two IMU-watches to monitor relative arm use and provided design considerations for improving the assessment method.Clinical trial registry number: CTRI/2018/09/015648.