Comprehensive measurement of stroke gait characteristics with a single accelerometer in the laboratory and community: a feasibility, validity and reliability study

Well shit, without an objective analysis of gait defects we will NEVER be able to correlate interventions to results. You have been in an unregulated clinical trial as a guinea pig by your therapists and doctors since the beginning.  With no protocols everyone trying to treat you is shooting in the dark. Hope you don't mind the inaccuracy and the lack of recovery.  I got the 'Walk this way' from my PT, totally useless.

• Sarah A. MooreEmail authorView ORCID ID profile,
• Aodhan Hickey,
• Sue Lord,
• Silvia Del Din,
• Alan Godfrey and
• Lynn Rochester

Journal of NeuroEngineering and Rehabilitation201714:130

https://doi.org/10.1186/s12984-017-0341-z

©  The Author(s). 2017

Received: 8 August 2017

Accepted: 13 December 2017

Published: 29 December 2017

Abstract

Background

Application of objective measurement of stroke gait with accelerometer-based wearable technology and associated algorithms is increasing, despite reports questioning the accuracy of this technique in quantifying specific stroke-related gait impairments. The aim of this study is to determine the feasibility, validity and reliability of a low-cost open-source system incorporating algorithms and a single tri-axial accelerometer-based wearable to quantify gait characteristics in the laboratory and community post-stroke.

Methods

Twenty-five participants with stroke wore the wearable (AX3, Axivity) on the lower back during a laboratory 2 minute continuous walk (preferred pace) on two occasions a week apart and continuously in the community for two consecutive 7 day periods. Video, instrumented walkway (GaitRite) and an OPAL accelerometer-based wearable were used as laboratory references.

Results

Feasibility of the proposed system was good. The system was valid for measuring step count (ICC 0.899). Inherent differences in gait quantification between algorithm and GaitRite resulted in difficulties comparing agreement between the different systems. Agreement was moderate-excellent (ICC 0.503–0.936) for mean and variability gait characteristics vs. OPAL. Agreement was moderate-poor between the system and OPAL for asymmetry characteristics. Moderate-excellent reliability (ICC 0.534–0.857) was demonstrated for 11/14 laboratory measured gait characteristics. Community test-retest reliability was good-excellent (ICC 0.867–0.983) for all except one (ICC 0.699) of the 19 gait characteristics.

Conclusion

The proposed system is a low-cost, reliable tool for quantifying gait post-stroke with multiple potential applications. Further refinement to optimise gait quantification algorithms for certain gait characteristics including gait asymmetry is required.