A clinically feasible kinematic assessment method of upper extremity motor function impairment after stroke

Öztürk, Ali; Tartar, Ahmet; Hüseyinsinoğlu, Burcu Ersöz; Ertas, Ahmet H.

doi:10.1016/j.measurement.2015.11.026

Cited by 50 publications

(60 citation statements)

References 35 publications

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“…Similarly, “Spine-Shoulder” in the Kinect-based records corresponded best to a marker on the manubrium (red spots in Fig. 1 ), which confirms the Kinect joints chosen by Ozturk et al, (2016) and Valdes et al, (2017) to determine trunk compensation during a reaching task [ 18 , 27 ]. Consequently, the Kinect joints chosen to be corresponding to CMS20s markers were the right wrist (for right head of the second metacarpal with CMS20s), left wrist (for left head of the second metacarpal with CMS20s) and spine-shoulder (for manubrium with CMS20s).…”

Section: Methodssupporting

confidence: 76%

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

Bakhti

Laffont

Muthalib

et al. 2018

J NeuroEngineering Rehabil

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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).

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Section: Methodssupporting

confidence: 76%

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

Bakhti

Laffont

Muthalib

et al. 2018

J NeuroEngineering Rehabil

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“…Authors did not notice remarkable difference between standing and seating while executing upper limb tasks, and the tracking was always adequate, considering that only upper limb data were considered. Some studies reported similar conclusions about adequateness of the Kinect V2 used in seated or comparable positions, while examining tasks including squatting [ 46 ], sitting [ 42 , 47 ], or even while seated in interaction with robotic devices [ 49 ]. Considering future applications on neurological patients (who may not be able of standing autonomously), a requirement for the study was to acquire normative data while in seated position.…”

Section: Methodsmentioning

confidence: 99%

“…Similar results were found in Parkinson disease assessment [ 44 ], in gait analysis and evaluation [ 45 ], and for dynamic movements in rehabilitation scenarios [ 46 ]. In [ 47 ], a small cohort of neurological patients is clinically evaluated by the means of Kinect V2. A recent study [ 48 ] assessed Kinect V2 as a tool for evaluating spinal muscular atrophy patients, matched with healthy controls, concluding that “Microsoft Kinect V2 sensor has the potential of being developed into a complementary output measure as it provides reproducible, objective and detailed information of body point motion.” In addition, [ 48 ] addresses the issue of Kinect V2 repeatability, with promising results to be furtherly investigated.…”

Section: Introductionmentioning

confidence: 99%

Kinect V2 Performance Assessment in Daily-Life Gestures: Cohort Study on Healthy Subjects for a Reference Database for Automated Instrumental Evaluations on Neurological Patients

Scano

Chiavenna

Malosio

et al. 2017

Applied Bionics and Biomechanics

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Background The increase of sanitary costs related to poststroke rehabilitation requires new sustainable and cost-effective strategies for promoting autonomous and dehospitalized motor training. In the Riprendo@Home and Future Home for Future Communities research projects, the promising approach of introducing low-cost technologies that promote home rehabilitation is exploited. In order to provide reliable evaluation of patients, a reference database of healthy people's performances is required and should consider variability related to healthy people performances. Methods 78 healthy subjects performed several repetitions of daily-life gestures, the reaching movement (RM) and hand-to-mouth (HtMM) movement with both the dominant and nondominant upper limbs. Movements were recorded with a Kinect V2. A synthetic biomechanical protocol based on kinematical, dynamical, and motor control parameters was used to assess motor performance of the healthy people. The investigation was conducted by clustering participants depending on their limb dominancy (right/left), gender (male/female), and age (young/middle/senior) as sources of variability. Results Results showed that limb dominancy has minor relevance in affecting RM and HtMM; gender has relevance in affecting the HtMM; age has major effect in affecting RM and HtMM. Conclusions An investigation of healthy subjects' upper limb performances during daily-life gestures was performed with the Kinect V2 sensor. Findings will be the basis for a database of normative data for neurological patients' motor evaluation.

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“…There is a common way to examine human UE motions quality by evaluating of kinematic parameters such as angles amplitudes and angular velocities during specified motions methodology [13,14]. Patient's upper extremity motions quality could be evaluated by comparing their kinematic motions parameters with healthy people parameters.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

Characteristic upper extremity kinematic parameters of healthy people during defined motions

Linkel

Griškevičius

Shippen

et al. 2016

Proccedings of 11th International Conference Biomdlore 2016

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Abstract. One of most common ways to examine the quality of the patient's upper extremity (UE) function is measuring the movement's kinematic parameters during the motion. However, is it reliable to compare a patient's UE motions data with healthy people's characteristic parameters? In this paper is shown that intrapersonal coefficient of variability (CV) in angles amplitudes differs from 3.2% during elbow flexion to 52.9% during wrist abduction and CV in angular velocity differs from 22.1% during shoulder abduction to 66.3% during wrist abduction.Keywords: upper extremity, objective parameters, motion capturing system, biomechanics. IntroductionThe loss of UE function is one of the most common results after Central Nervous System (CNS) injuries It is clear that only functional and clinical subjective scales are not enough for accurate motion quality measurements and that objective methods are required. Quantitative measures of UE movement's quality can be valuable in the rehabilitation field for evaluating the quality of actual motion and recovery progress [10] which might help physicians to compare accurately healthy and pathological movement conditions in a clinical setting. The purpose of the research was to find if particular kinematic parameters of healthy participant's UE motions are reliable to compare with further experiments results with patients who have UE disability and trying to recover previous movement's conditions.

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A clinically feasible kinematic assessment method of upper extremity motor function impairment after stroke

Cited by 50 publications

References 35 publications

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

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

Kinect V2 Performance Assessment in Daily-Life Gestures: Cohort Study on Healthy Subjects for a Reference Database for Automated Instrumental Evaluations on Neurological Patients

Characteristic upper extremity kinematic parameters of healthy people during defined motions

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