Literature DB >> 33668234

Review of Wearable Sensor-Based Health Monitoring Glove Devices for Rheumatoid Arthritis.

Jeffrey Henderson1, Joan Condell1, James Connolly2, Daniel Kelly1, Kevin Curran1.   

Abstract

Early detection of Rheumatoid Arthritis (RA) and other neurological conditions is vital for effective treatment. Existing methods of detecting RA rely on observation, questionnaires, and physical measurement, each with their own weaknesses. Pharmaceutical medications and procedures aim to reduce the debilitating effect, preventing the progression of the illness and bringing the condition into remission. There is still a great deal of ambiguity around patient diagnosis, as the difficulty of measurement has reduced the importance that joint stiffness plays as an RA identifier. The research areas of medical rehabilitation and clinical assessment indicate high impact applications for wearable sensing devices. As a result, the overall aim of this research is to review current sensor technologies that could be used to measure an individual's RA severity. Other research teams within RA have previously developed objective measuring devices to assess the physical symptoms of hand steadiness through to joint stiffness. Unfamiliar physical effects of these sensory devices restricted their introduction into clinical practice. This paper provides an updated review among the sensor and glove types proposed in the literature to assist with the diagnosis and rehabilitation activities of RA. Consequently, the main goal of this paper is to review contact systems and to outline their potentialities and limitations. Considerable attention has been paid to gloved based devices as they have been extensively researched for medical practice in recent years. Such technologies are reviewed to determine whether they are suitable measuring tools.

Entities:  

Keywords:  data gloves; joint measurement; range of motion; rehabilitation; rheumatoid arthritis; smart sensing

Year:  2021        PMID: 33668234     DOI: 10.3390/s21051576

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  5 in total

1.  Identifying daily activities of patient work for type 2 diabetes and co-morbidities: a deep learning and wearable camera approach.

Authors:  Hao Xiong; Hoai Nam Phan; Kathleen Yin; Shlomo Berkovsky; Joshua Jung; Annie Y S Lau
Journal:  J Am Med Inform Assoc       Date:  2022-07-12       Impact factor: 7.942

Review 2.  Characteristics and Applications of Technology-Aided Hand Functional Assessment: A Systematic Review.

Authors:  Ciro Mennella; Susanna Alloisio; Antonio Novellino; Federica Viti
Journal:  Sensors (Basel)       Date:  2021-12-28       Impact factor: 3.576

Review 3.  A broad look into the future of rheumatoid arthritis.

Authors:  Johanna Mucke; Martin Krusche; Gerd R Burmester
Journal:  Ther Adv Musculoskelet Dis       Date:  2022-02-09       Impact factor: 5.346

4.  Text Score Analysis under the IPE Environment Based on Improved Transformer.

Authors:  Jinghong Qi; Xinli Jia
Journal:  J Environ Public Health       Date:  2022-09-29

5.  State-of-the-Art Sensors Research in Ireland.

Authors:  John Barton; Mark Ferguson; Cian Ó Mathúna; Elfed Lewis
Journal:  Sensors (Basel)       Date:  2022-01-14       Impact factor: 3.576

  5 in total

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