期刊
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
卷 23, 期 5, 页码 2021-2029出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JBHI.2018.2875812
关键词
Gait analysis; gait assessment; gait features; inertial measurement unit (IMU)
类别
资金
- Erasmus Mundus Fusion Project [545831-EM-1-2013-1-IT-ERAMUNDUSEMA21]
- European Commission Marie Sklodowska-Curie SMOOTH (Smart Robots for Firefighting) Project [H2020-MSCA-RISE-2016-734875]
- European Commission Marie Sklodowska-Curie CHARMED (Characterisation of a green microenvironment and to study its impact upon health and well-being in the elderly as a way forward for health tourism_ Project) [H2020-MSCARISE-2016-734684]
- Royal Society International Exchanges Scheme (Adaptive Learning Control of a Cardiovascular Robot Using Expert Surgeon Techniques) Project [IE151224]
Objective assessment of gait is important in the treatment and rehabilitation of patients with different diseases. In this paper, we propose a gait evaluation system using the Procrustes and Euclidean distance matrix analysis. We design and develop an android app to collect real time synchronous accelerometer and gyroscope data from two inertial measurement unit sensors through Bluetooth connectivity. The data is collected from 12 young (ten for modeling and two for validation) and 20 older subjects. We analyze the data collected from real world for stride, step, stance, and swing gait features. We validate our method with the measurements of gait features. The generalized Procrustes analysis is used to estimate a standard normal mean gait shape (NMGS) for ten young subjects. Each gait feature of both young and older subjects is then converted to find the best match with the NMGS using the ordinary Procrustes analysis. The shape distance between the NMGS and each gait shape is estimated using Riemannian shape distance, Riemannian size-and-shape distance, Procrustes size-and-shape distance, and root-mean-square deviation. A t-test is performed to provide statistical evidence of gait shape differences between young and older gaits. A mean form, which is considered as a standard normal mean gait form (NMGF), and inter-feature distances are estimated from the set of ten young subjects. The form difference is estimated between the NMGF and individual gaits of young and older. The degree of abnormality is then estimated for individual features and the result is plotted to visualize the feature in a gait. Experimental results demonstrate the performance of the proposed method.
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