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01 August 2009

Risk-tendency graph (RTG): a new gait-analysis technique for monitoring FES-assisted paraplegic walking stability

Dong MingABCEFG, Yong HuADEFG, Yatwa WongDF, Baikun WanCDEF, Keith D.K. LukAG, John C.Y . LeongAG

Med Sci Monit 2009; 15(8): MT105-112 :: ID: 878124

Abstract

Background
Gait analysis techniques guide the use and design of functional electrical stimulation (FES) systems for paraplegic walking. However, published studies on dynamic gait stability for the effective use of FES are limited. This paper introduces a new risk-tendency graph (RTG) technique to analyze and process gait stability in FES-assisted paraplegic walking.
Material and Method
The main instrument was a specialized walker dynamometer system based on a multi-channel strain-gauge bridge network affixed to the frame of the walker. This system collects force information for the handle reaction vector (HRV) between the patient's upper extremities and the walker during walking. The information is then converted into a walker tipping index (WTI), which is an indicator of the patient's walking stability. Dynamic gait stability is then combined with spatio-temporal locating methods for WTI and visually described as morphological curves in the temporal and spatial domains, namely RTGs.
Results
To demonstrate the potential usefulness of RTG in gait analysis, a preliminary clinical trial was conducted with one male paraplegic patient who was undergoing FES walking training. The gait stability levels for the patient under different stimulation patterns were quantified using the results of temporal and 3-D spatial RTG. Relevant instable phases in the gait cycle and dangerous inclinations of the patient's body while walking were also clearly identified.
Conclusions
The new RTG technique is a practical method for distinguishing useful gait information from the viewpoint of stability and may be further applied in FES-assisted paraplegic walking rehabilitation.

Keywords: Time Factors, Pilot Projects, Paraplegia - physiopathology, Gravitation, Gait - physiology, Electric Stimulation Therapy - methods, Biomechanical Phenomena, Walking - physiology

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Medical Science Monitor eISSN: 1643-3750