Title: Finger movement measurements in arthritic patients using wearable sensor enabled gloves

 

Author: J. Condell; Kevin Curran; T. Quigley; P. Gardiner; M. McNeill; J. Winder; E. Xie; Z. Qi; J. Connolly

 

Address: Faculty of Computing and Engineering, Magee College, University of Ulster, Londonderry, BT48 7JL, Northern Ireland. ' Faculty of Computing and Engineering, Magee College, University of Ulster, Londonderry, BT48 7JL, Northern Ireland. ' Faculty of Arts, Magee College, University of Ulster, Londonderry, BT48 7JL, Northern Ireland. ' Western Health and Social Care Trust, Altnagelvin Hospital, Londonderry, BT47 3RD, Northern Ireland. ' Faculty of Computing and Engineering, Magee College, University of Ulster, Londonderry, BT48 7JL, Northern Ireland ' School of Health Sciences, University of Ulster, Jordanstown, BT37 0QB, Northern Ireland. ' Faculty of Computing and Engineering, Magee College, University of Ulster, Londonderry, BT48 7JL, Northern Ireland. ' Faculty of Computing and Engineering, Magee College, University of Ulster, Londonderry, BT48 7JL, Northern Ireland. ' Faculty of Computing and Engineering, Magee College, University of Ulster, Londonderry, BT48 7JL, Northern Ireland

 

Journal: Int. J. of Human Factors Modelling and Simulation, 2011 Vol.2, No.4, pp.276 - 292

 

Abstract: This paper outlines the initial ideas and results surrounding the development of an accurate hand movement measurement tool. The system consists of a wearable glove measurement tool and a 3D interface. Real time data captured from each glove sensor will be displayed numerically and graphically. It will accurately quantify patients' flexion, extension, adduction and abduction of finger and thumb joint movements in degrees, maximum and minimum joint range and compare joint range with normal ROM values to determine the degree of deformity of the hand and stiffness of moving finger joints. The system can simultaneously record angles from multiple fingers to detect previously unidentifiable movement patterns. It measures a shift in the position of fingers in relation to the direction of the thumb by measuring web space and recording the minimum, maximum and average values during a number of tests to analyse joint movement and identify areas for joint protection benefit. Data is recorded and used for future comparison analysis. It will be the first ambulatory system to detect joint stiffness at home and will help quantify and understand the symptom of 'early morning stiffness'.

 

Keywords: rheumatoid arthritis; assisted technology; healthcare technology; medical informatics; wireless sensors; e-health; electronic healthcare; finger movement measurements; hand movement; arthritic patients; wearable sensors; sensor enabled gloves; flexion; extension; adduction; abduction; thumb joint movements; hand deformity; joint stiffness; ambulatory systems; early morning stiffness; home care.

 

DOI: 10.1504/IJHFMS.2011.045000

10.1504/11.45000

 

 

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