Title :
Application of gait analysis for hemiplegic patients using six-axis wearable inertia sensors
Author :
Qiang Fang ; Zhe Zhang ; Yinjun Tu
Author_Institution :
Sch. of Electr. Eng., RMIT Univ., Melbourne, VIC, Australia
Abstract :
Gait analysis is considered as an important process which has been wildly adopted in many clinical applications to identify and quantify the lower body functioning impairment of hemiplegic patients. On contrary to the traditional measures which were based on manual observation, numerous researches in recent years have been carried out on utilizing modern assistive devices to analyze gait pattern and produce objective results. In this paper, a novel hemiplegic gait analysis approach based on 6-axis inertial measurement is proposed. The patients´ gait data are collected using a set of wearable wireless inertial sensor network and processed to extract gait parameters including step length, hip and knee joint angle. By comparing the sample features between healthy and hemiplegic participants, it is demonstrated that the abnormalities in gait pattern such as irregularity and asymmetry can be found and quantified. This provides clinicians an effective tool to analysis hemiplegic patient´s impairment level and recovery progress objectively.
Keywords :
biomedical telemetry; body sensor networks; data acquisition; data analysis; feature extraction; gait analysis; medical disorders; medical signal processing; telemedicine; 6-axis inertial measurement; clinical application; gait analysis application; gait parameter extraction; gait pattern abnormality quantification; gait pattern analysis; gait pattern asymmetry; gait pattern irregularity; hemiplegic gait analysis; hip joint angle extraction; knee joint angle extraction; lower body function impairment identification; lower body function impairment quantification; modern assistive device; objective hemiplegic patient impairment level analysis; objective hemiplegic patient recovery progress analysis; patient gait data collection; patient gait data processing; sample feature comparison; six-axis wearable inertia sensor; step length extraction; wearable wireless inertial sensor network; Correlation; Hip; Joints; Knee; Legged locomotion; Sensors; Wireless sensor networks; Gait analysis; Hemiplegic gait; inertia sensors;
Conference_Titel :
Industrial Electronics Society, IECON 2014 - 40th Annual Conference of the IEEE
DOI :
10.1109/IECON.2014.7049099