Original research
Toward Accurate Clinical Spasticity Assessment: Validation of Movement Speed and Joint Angle Assessments Using Smartphones and Camera Tracking

https://doi.org/10.1016/j.apmr.2018.11.026Get rights and content

Abstract

Objective

To investigate whether a three-dimensional (3-D) camera (Microsoft Kinect) and a smartphone can be used to accurately quantify the joint angular velocity and range of motion (ROM) compared to a criterion-standard 3-D motion analysis system during a lower limb spasticity assessment.

Design

Observational, criterion-standard comparison study.

Setting

Large rehabilitation center.

Participants

A convenience sample of 35 controls, 35 patients with a neurologic condition, and 34 rehabilitation professionals (physiotherapists and rehabilitation doctors) participated (N=104).

Interventions

Not applicable.

Main Outcome Measures

The Modified Tardieu Scale was used to assess spasticity of the quadriceps, hamstrings, soleus, and gastrocnemius. Data for each trial were collected concurrently using the criterion-standard Optitrack 3-D motion analysis (3DMA) system, Microsoft Kinect, and a smartphone. Each healthy control participant was assessed by 1 health professional and each patient with a neurological condition was assessed by 3 health professionals. Spearman correlation coefficient and intraclass correlation coefficient with 95% confidence intervals were used to report the strength of the relationships investigated.

Results

The smartphone and Microsoft Kinect demonstrated excellent concurrent validity with the 3DMA system. Overall, 74.8% of the relationships investigated demonstrated a very strong (≥0.80) correlation across all of the testing parameters. The Microsoft Kinect was superior to the smartphone for measuring joint start and end angle, the smartphone was superior for measuring joint angular velocity, and the 2 systems were comparable for measuring total joint ROM.

Conclusions

These findings provide preliminary evidence that user-friendly, low-cost technologies can be used to facilitate accurate measurements of joint angular velocity and angles during a lower limb spasticity assessment in a clinical setting.

Section snippets

Method

The study was approved by the Epworth HealthCare Human Research Ethics Committee (HREC; 681-15) and the University of Sunshine Coast HREC (S/17/1011). All participants provided written informed consent prior to assessment. One assessor (M.B.) piloted the data collection process in a control cohort without neurologic deficit. A larger cohort of assessors were recruited to validate the technologies in a cohort of patients with a neurologic condition. All data was collected in the therapy area of

Demographics

Thirty-five patients without neurologic deficit, 35 patients with a neurologic condition, and 34 assessors were recruited. No participants withdrew from the study. Table 2 outlines the demographics of the participants. The assessors included physiotherapists (n=28), rehabilitation consultants (n=5), and a rehabilitation registrar (n=1). The assessors had an average of 14.3 (range 4-40) years of experience.

Concurrent validity

The concurrent validity of the Microsoft Kinect, smartphone, and goniometer for each of

Discussion

The study demonstrated that clinically feasible, low-cost technologies can provide an accurate measure of joint start angle, end angle, ROM, and peak angular velocity when assessing lower limb spasticity using the MTS. When comparing the 3-D camera (Microsoft Kinect) to the smartphone, the 3-D camera is superior in measuring joint start and end angles. The primary limitation of the camera used in this study, the Microsoft Kinect, was a lower absolute ICC when measuring the angular velocity

Conclusions

This study demonstrated that user-friendly and low-cost technologies can facilitate an accurate assessment of lower limb spasticity in a clinical setting. The smartphone application was superior in measuring joint angular velocity, the Microsoft Kinect superior in measuring joint start and end angle, and the systems comparable when measuring ROM.

Suppliers

  • a.

    Optitrack 3-D Motion Analysis; NaturalPoint, Inc.

  • b.

    Microsoft Kinect motion-sensing device; Microsoft, Inc.

  • c.

    Samsung Galaxy S5; Samsung, Inc.

  • d.

    LabVIEW software; National Instruments.

  • e.

    Validity and Reliability Calculator; www.rehabtools.org/stats.html.

Acknowledgment

We thank Andrew Sean Drummond, MClinExPhys, who assisted in data processing.

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    Supported by the Royal Automobile Club of Victoria, Epworth Research Institute, and Physiotherapy Research Fund.

    Disclosures: Ross Clark is supported by a National Health and Medical Research Council R.D. Wright Biomedical Fellowship. The other authors have nothing to disclose.

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    © 2019 by the American Congress of Rehabilitation Medicine