Kinect-based assessment of proximal arm non-use after a stroke

K K A Bakhti,I Laffont,M Muthalib,D Mottet,J Froger

doi:10.1186/s12984-018-0451-2

Abstract

BackgroundAfter a stroke, during seated reaching with their paretic upper limb, many patients spontaneously replace the use of their arm by trunk compensation movements, even though they are able to use their arm when forced to do so. We previously quantified this proximal arm non-use (PANU) with a motion capture system (Zebris, CMS20s). The aim of this study was to validate a low-cost Microsoft Kinect-based system against the CMS20s reference system to diagnose PANU.MethodsIn 19 hemiparetic stroke individuals, the PANU score, reach length, trunk length, and proximal arm use (PAU) were measured during seated reaching simultaneously by the Kinect (v2) and the CMS20s over two testing sessions separated by two hours.ResultsIntraclass correlation coefficients (ICC) and linear regression analysis showed that the PANU score (ICC = 0.96, r2 = 0.92), reach length (ICC = 0.81, r2 = 0.68), trunk length (ICC = 0.97, r2 = 0.94) and PAU (ICC = 0.97, r2 = 0.94) measured using the Kinect were strongly related to those measured using the CMS20s. The PANU scores showed good test-retest reliability for both the Kinect (ICC = 0.76) and CMS20s (ICC = 0.72). Bland and Altman plots showed slightly reduced PANU scores in the re-test session for both systems (Kinect: − 4.25 ± 6.76; CMS20s: − 4.71 ± 7.88), which suggests a practice effect.ConclusionWe showed that the Kinect could accurately and reliably assess PANU, reach length, trunk length and PAU during seated reaching in post stroke individuals. We conclude that the Kinect can offer a low-cost and widely available solution to clinically assess PANU for individualised rehabilitation and to monitor the progress of paretic arm recovery.Trial registrationThe study was approved by The Ethics Committee of Montpellier, France (N°ID-RCB: 2014-A00395–42) and registered in Clinical Trial (N° NCT02326688, Registered on 15 December 2014, https://clinicaltrials.gov/ct2/show/results/NCT02326688).

Highlights

After a stroke, during seated reaching with their paretic upper limb, many patients spontaneously replace the use of their arm by trunk compensation movements, even though they are able to use their arm when forced to do so
We extended the comparison of the Kinect and CMS20s towards classical kinematic variables often used to describe upper limb movements after a stroke: Movement Time (MT) and Number of Velocity Peaks (NVP)
Additional kinematic variables that have only been measured by the Kinect From the time series of 25 body landmarks provided by Kinect data, we examined the non-use of joints determining the proximal arm non-use (PANU) score, namely the non-use of shoulders and elbows

Summary

Introduction

After a stroke, during seated reaching with their paretic upper limb, many patients spontaneously replace the use of their arm by trunk compensation movements, even though they are able to use their arm when forced to do so. We previously quantified this proximal arm non-use (PANU) with a motion capture system (Zebris, CMS20s). Our reasoning is that the learned non-use phenomenon explains why some patients “forget” how to use the proximal joints of their paretic UL and instead overuse trunk compensation during reaching [3]. Long-term overuse of trunk compensation may lead to suboptimal motor

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