Reliability and Validity of Clinically Accessible Smart Glove Technologies to Measure Joint Range of Motion

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Capturing hand motions for hand function evaluations is essential in the medical field. For many allied health professionals, measuring joint Range of Motion (ROM) is an important skill. While the Universal Goniometer (UG) is the most commonly used clinical tool for measuring joint ROM, developments in current technology provides the clinician with more measurement possibilities than ever. For rehabilitation and manual dexterity evaluations, different data gloves have been developed. However, the reliability and validity of these technologies when used within a smart device remains somewhat unclear. This study proposed a novel Electronically Controlled Sensor Measurement System (ECSMS) to obtain static and dynamic parameters of various sensor technologies for both data gloves and individual sensor evaluation. The system is designed to closely mimic a human finger joint, to have total control over the joint and to have an exceptional reliability. The ECSMS device can closely mimic movements of the finger from hyper extension to a maximum ROM beyond any person’s finger joint. Owing to the modular design, the sensor monitoring board is independent and extensible to include various technologies for examination. By putting these sensory devices through multiple tests, the system accurately measures the characteristics of any rotary/ linear sensor in and out of a glove. It tracks the movement of all types of sensors with respect to the angle values of finger joints. In order to demonstrate the effectiveness of sensory devices, the testing system was first validated against a recognized secondary device with an accuracy and resolution of 0.1˚. Once validated, the system determines real angles simultaneously alongside the hand monitoring device or sensor. Owing to the unique design, the system is independent of the gloves/ sensors being tested and can be used as a gold standard to realize more medical equipment/ applications in the future. This design greatly enhances testing measures within research contact and even non-contact systems. In conclusion, the ECSMS will benefit in the design of data glove technologies in the upcoming future as it provides crucial evidence of sensor characteristics. This design greatly enhances the stability and maintainability of sensor assessments eliminating unwanted errors. These findings provide ample evidence for clinicians to support the use of sensory devices that can calculate joint motion in place of goniometers.
Original languageEnglish
Article number1555
Pages (from-to)1-30
Number of pages30
Issue number5
Publication statusPublished (in print/issue) - 24 Feb 2021


  • Rheumatoid Arthritis
  • Parkinson’s Disease
  • Stroke Recovery
  • Smart Sensing
  • Data Gloves
  • Joint Measurement
  • Rehabilitation
  • Measurement system.


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