Efficient FES triggering applying Kalman filter during sensory supported treadmill walking

• Published in: Journal of medical engineering & technology Vol. 32; no. 2; pp. 133 - 144
• Main Authors: Cikajlo, I., Matja i, Z., Bajd, T.
• Format: Journal Article
• Language: English
• Published: England Informa UK Ltd 01.03.2008; Taylor & Francis
• Subjects: Adult; Algorithms; Computer Simulation; Electric Stimulation Therapy - instrumentation; Electric Stimulation Therapy - methods; FES control; Gait re-education; Humans; Leg - innervation; Leg - physiopathology; Male; Models, Biological; Muscle, Skeletal - innervation; Muscle, Skeletal - physiopathology; Paresis - physiopathology; Paresis - rehabilitation; Rehabilitation engineering; Sensation; Signal Processing, Computer-Assisted; Therapy, Computer-Assisted - methods; Tilt sensor; Treadmill; Treatment Outcome; Walking
• ISSN: 0309-1902; 1464-522X
• DOI: 10.1080/03091900601029627

In this paper an algorithm for a functional electrical stimulation (FES) gait re-education system for incomplete spinal cord injured persons, providing efficient stimulation triggering, is presented. During neurological impaired gait FES was provided as motor augmentation support. Simultaneously the gait kinematics were recorded using the proposed sensory system, which is equipped with a dual-axial accelerometer and a gyroscope. The sensory device was placed at the shank of the paretic leg. The data assessed were input into a mathematical algorithm applied for shank angle estimation. The algorithm is based on the Kalman filter, estimating the angle error and correcting the actual measurement. Furthermore the information was combined with other kinematic data for the purpose of efficient and reliable stimulation triggering. The algorithm was tested with preliminary measurements on several neurologically intact persons during even terrain and treadmill walking. Trial measurements were verified with a contactless optical measurement system, with FES only simulated on controller output. Later on a treadmill training in combination with FES triggering was carried out. The outcome of the measurements shows that the use of sensory integration may successfully solve the problem of data assessment in dynamic movement where an inclinometer does not provide sufficient information for efficient control of FES.