Jarchi, Delaram, Lo, Benny, Wong, Charence, Ieong, Edmund, Nathwani, Dinesh, 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:10.1109/TNSRE.2015.2477720) (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided) (KAR id:69641)
PDF
Publisher pdf
Language: English Restricted to Repository staff only |
|
|
|
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 |
---|---|
DOI/Identification number: | 10.1109/TNSRE.2015.2477720 |
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: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing |
Depositing User: | Delaram Jarchi |
Date Deposited: | 18 Oct 2018 12:06 UTC |
Last Modified: | 05 Nov 2024 12:31 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/69641 (The current URI for this page, for reference purposes) |
- Export to:
- RefWorks
- EPrints3 XML
- BibTeX
- CSV
- Depositors only (login required):