Gait Analysis From a Single Ear-Worn Sensor: Reliability and Clinical Evaluation for Orthopaedic Patients

Jarchi, Delaram and Lo, Benny and Wong, Charence and Ieong, Edmund and Nathwani, Dinesh and Yang, Guang-Zhong (2016) Gait Analysis From a Single Ear-Worn Sensor: Reliability and Clinical Evaluation for Orthopaedic Patients. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 24 (8). pp. 882-892. ISSN 1534-4320. (doi:https://doi.org/10.1109/TNSRE.2015.2477720) (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided)

PDF - Publisher pdf
Restricted to Repository staff only
Contact us about this Publication Download (9MB)
[img]
Official URL
http://dx.doi.org/10.1109/TNSRE.2015.2477720

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 mea- sure 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 lig- ament (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 tem- poral and force-related gait asymmetry derived from gait events. The results suggest that the ear-worn sensor can be used for objec- tive gait assessments of orthopaedic patients without the require- ment and expense of an elaborate laboratory setup for gait anal- ysis. It significantly simplifies the monitoring protocol and opens the possibilities for home-based remote patient assessment.

Item Type: Article
Uncontrolled keywords: e-AR (ear-worn activity recognition) sensor, gait, rehabilitation, singular spectrum analysis (SSA)
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
R Medicine
T Technology
Divisions: Faculties > Sciences > School of Computing
Depositing User: Delaram Jarchi
Date Deposited: 18 Oct 2018 12:06 UTC
Last Modified: 22 Oct 2018 15:43 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/69641 (The current URI for this page, for reference purposes)
Jarchi, Delaram: https://orcid.org/0000-0001-6699-8721
  • Depositors only (login required):

Downloads

Downloads per month over past year