scholarly journals Reliability and validity of clinically accessible smartphone applications to measure joint range of motion: A systematic review

PLoS ONE ◽  
2019 ◽  
Vol 14 (5) ◽  
pp. e0215806 ◽  
Author(s):  
Justin W. L. Keogh ◽  
Alistair Cox ◽  
Sarah Anderson ◽  
Bernard Liew ◽  
Alicia Olsen ◽  
...  
2004 ◽  
Vol 17 (2) ◽  
pp. 118-131 ◽  
Author(s):  
Susan L Michlovitz ◽  
Bette Ann Harris ◽  
Mary P Watkins

Author(s):  
Shibili Nuhmani ◽  
Moazzam H Khan ◽  
Shaji J Kachanathu ◽  
Mohd Arshad Bari ◽  
Turki S Abualait ◽  
...  

2019 ◽  
Vol 32 (2) ◽  
pp. 184-193 ◽  
Author(s):  
Kristin Valdes ◽  
Jessica D. Boyd ◽  
Scott B. Povlak ◽  
Malgorzata A. Szelwach

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1555
Author(s):  
Jeffrey Henderson ◽  
Joan Condell ◽  
James Connolly ◽  
Daniel Kelly ◽  
Kevin Curran

Capturi ng 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 used clinical tool for measuring joint ROM, developments in current sensor technology are providing clinicians with more measurement possibilities than ever. For rehabilitation and manual dexterity evaluations, different data gloves have been developed. However, the reliability and validity of sensor technologies when used within a smart device remain somewhat unclear. This study proposes a novel electronically controlled sensor monitoring system (ECSMS) to obtain the static and dynamic parameters of various sensor technologies for both data gloves and individual sensor evaluation. Similarly, the ECSMS was designed to closely mimic a human finger joint, to have total control over the joint, and to have an exceptionally high precision. In addition, the ECSMS device can closely mimic the movements of the finger from hyperextension to a maximum ROM beyond any person’s finger joint. Due to the modular design, the ECSMS’s sensor monitoring board is independent and extensible to include various technologies for examination. Additionally, 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. Moreover, the ECSMS 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 ECSMS was first validated against a recognised secondary device with an accuracy and resolution of 0.1°. Once validated, the system simultaneously determines real angles alongside the hand monitoring device or sensor. Due to its unique design, the system is independent of the gloves/sensors that were tested and can be used as a gold standard to realise more medical equipment/applications in the future. Consequently, 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 future because it provides crucial evidence of sensor characteristics. Similarly, this design greatly enhances the stability and maintainability of sensor assessments by 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.


2021 ◽  
Author(s):  
Prasad Dhage ◽  
Waqar M. Naqvi ◽  
Sakshi P. Arora ◽  
Chaitanya A. Kulkarni

Abstract Introduction: "Goniometry" is derived from two Greek words: Gonia, which means "angle," and Metron, which means "measure." The focus of the research is to see if a smartphone-based goniometer application for knee flexion range of motion was reliable. The technology of smartphones is one of the most often used alternatives. A literature evaluation of 12 studies showed that smartphone applications are sufficiently trustworthy to be employed in research and clinical practice. As ROM angulation is widely employed in treatment policy decisions, new measures have to be thoroughly tested before use in clinical practice. The study design used will be an observational study. The participants will be recruited using a simple random sampling method. The total number of participants will be 100 in the age group between 20-60. With Universal Goniometer and Goniometer records, three certified physiotherapists measured maximum active knee flexion in a supine position. Data will be collected and analyzed using SPSS (version: 20) and the Bland Altman Test.Discussion: The goal of this observational study is to examine the reliability of smartphone applications for computing knee joint range of motion.Conclusion: To conclude, this research seeks to examine the reliability of smartphone applications for computing knee joint range of motion in a healthy population. The study findings would help in developing a novel approach for computing and documenting the knee range of motion.


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