Authors:
A. Sant'Anna
1
;
N. Wickstrom
1
;
R. Zügner
2
and
R. Tranberg
2
Affiliations:
1
Halmstad University, Sweden
;
2
Sahlgrenska Academy and University of Gothenburg, Sweden
Keyword(s):
Gait Analysis, Inertial Sensors, Symmetry, Normality.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Applications and Services
;
Biomedical Engineering
;
Biomedical Signal Processing
;
Biometrics
;
Biometrics and Pattern Recognition
;
Computer Vision, Visualization and Computer Graphics
;
Devices
;
Health Information Systems
;
Human-Computer Interaction
;
Medical Image Detection, Acquisition, Analysis and Processing
;
Monitoring and Telemetry
;
Multimedia
;
Multimedia Signal Processing
;
Pattern Recognition
;
Physiological Computing Systems
;
Telecommunications
;
Wearable Sensors and Systems
Abstract:
Gait analysis (GA) is an important tool in the assessment of several physical and cognitive conditions. The lack
of simple and economically viable quantitative GA systems has hindered the routine clinical use of GA in many
areas. As a result, patients may be receiving sub-optimal treatment. The present study introduces and evaluates
measures of gait symmetry and gait normality calculated from inertial sensor data. These indices support the
creation of mobile, cheap and easy to use quantitative GA systems. The proposed method was compared to
measures of symmetry and normality derived from 3D kinematic data. Results show that the proposed method
is well correlated to the kinematic analysis in both symmetry (r=0.84, p<0.0001) and normality (r=0.81,
p<0.0001). In addition, the proposed indices can be used to classify normal from abnormal gait.