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

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)

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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: 17 Aug 2022 12:22 UTC
Resource URI: (The current URI for this page, for reference purposes)

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