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IMU Sensor-based Electronic Goniometric Glove for clinical finger movement analysis

Connolly, James, Condell, Joan, O'Flynn, Brendan, Torres Sanchez, Javier and Gardiner, Philip (2018) IMU Sensor-based Electronic Goniometric Glove for clinical finger movement analysis. IEEE Sensors, 18 (3). pp. 1273-1281. [Journal article]

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DOI: 10.1109/JSEN.2017.2776262


Arthritis remains a disabling and painful disease, and involvement of finger joints is a major cause of disability and loss of employment. Traditional arthritis measurements require labour intensive examination by clinical staff. These manual measurements are inaccurate and open to observer variation.This paper presents the development and testing of a next generation wireless smart glove to facilitate the accurate measurement of finger movement through the integration of multiple IMU sensors, with bespoke controlling algorithms. Our main objective was to measure finger and thumb joint movement. These dynamic measurements will provide clinicians with a new and accurate way to measure loss of movement in patients with Rheumatoid Arthritis. Commercially available gaming gloves are not fitted with sufficient sensors for this particular application, and require calibration for each glove wearer. Unlike these state-of-the-art data gloves, the Inertial Measurement Unit (IMU) glove uses a combination of novel stretchable substrate material and 9 degree of freedom (DOF) inertial sensors in conjunction with complex data analytics to detect joint movement. Our novel iSEG-Glove requires minimal calibration and is therefore particularly suited to the healthcare environment. Inaccuracies may arise for wearers who have varying degrees of movement in their finger joints, variance in hand size or deformities. The developed glove is fitted with sensors to overcome these issues. This glove will help quantify joint stiffness and monitor patient progression during the arthritis rehabilitation process.

Item Type:Journal article
Keywords:Data glove, wireless sensor networks, Inertial Measurement Unit, Rheumatoid Arthritis, sensor calibration
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Intelligent Systems
Faculty of Art, Design and the Built Environment
Faculty of Art, Design and the Built Environment > School of the Built Environment
Research Institutes and Groups:Computer Science Research Institute > Intelligent Systems Research Centre
Computer Science Research Institute
ID Code:39286
Deposited By: Dr Joan Condell
Deposited On:21 Feb 2018 10:45
Last Modified:21 Feb 2018 10:45

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