Gait Analysis From a Single Ear-Worn Sensor: Reliability and Clinical Evaluation for Orthopaedic Patients
File(s)paper_revised %281%29.pdf (7.36 MB)
Accepted version
Author(s)
Type
Journal Article
Abstract
Objective assessment of detailed gait patterns after orthopaedic surgery is important for post-surgical follow-up and rehabilitation. The purpose of this paper is to assess the use of a single ear-worn sensor for clinical gait analysis. A reliability measure is devised for indicating the confidence level of the estimated gait events, allowing it to be used in free-walking environments and for facilitating clinical assessment of orthopaedic patients after surgery. Patient groups prior to or following anterior cruciate ligament (ACL) reconstruction and knee replacement were recruited to assess the proposed method. The ability of the sensor for detailed longitudinal analysis is demonstrated with a group of patients after lower limb reconstruction by considering parameters such as temporal and force-related gait asymmetry derived from gait events. The results suggest that the ear-worn sensor can be used for objective gait assessments of orthopaedic patients without the requirement and expense of an elaborate laboratory setup for gait analysis. It significantly simplifies the monitoring protocol and opens the possibilities for home-based remote patient assessment.
Date Issued
2015-09-09
Date Acceptance
2015-09-07
Citation
IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2015, 24 (8), pp.882-892
ISSN
1558-0210
Publisher
Institute of Electrical and Electronics Engineers
Start Page
882
End Page
892
Journal / Book Title
IEEE Transactions on Neural Systems and Rehabilitation Engineering
Volume
24
Issue
8
Copyright Statement
© 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Sponsor
Engineering & Physical Science Research Council (EPSRC)
Grant Number
EP/H009744/1
Subjects
Science & Technology
Technology
Life Sciences & Biomedicine
Engineering, Biomedical
Rehabilitation
Engineering
e-AR (ear-worn activity recognition) sensor
gait
rehabilitation
singular spectrum analysis (SSA)
SINGULAR SPECTRUM ANALYSIS
DECISION-MAKING
TRIAXIAL ACCELEROMETER
CEREBRAL-PALSY
SIGNALS
WALKING
VALIDATION
SYMMETRY
EVENTS
SYSTEM
Biomedical Engineering
0903 Biomedical Engineering
0906 Electrical And Electronic Engineering
Publication Status
Published