Literature DB >> 24844445

Mobile smartphone applications for body position measurement in rehabilitation: a review of goniometric tools.

Patrizia Milani1, Carlo Alberto Coccetta2, Alessia Rabini3, Tommaso Sciarra4, Giuseppe Massazza5, Giorgio Ferriero6.   

Abstract

OBJECTIVE: To provide a systematic review of apps for smartphones validated for body position measurement relevant to physical medicine and rehabilitation. TYPE: Systematic search and review. LITERATURE SURVEY: A literature search was conducted on relevant articles indexed by PubMed before April 15, 2014. We selected only research papers published in English. Papers dealing with apps not relevant to physical medicine and rehabilitation or unavailable on the market were excluded.
METHODOLOGY: Two independent reviewers screened the articles (full text).We analyzed the following information for all apps: target population, object of the measure, body segment evaluated, modality of use, operating platform system, and validation results. SYNTHESIS: The literature search produced 27 papers, 17 of which met the inclusion criteria for our review. The included papers featured 12 apps validated for angle measurement: 7 were validated exclusively for upper and lower limb joint angles, 4 for spine measurements, ie, cervical or lumbar range of motion and curvature, Cobb angle on radiographs, and the scoliotic distortions of the torso, and 1 for both upper limb and spine measurement. The 12 apps used the inbuilt smartphone magnetometer, accelerometer, or camera to produce angle measurements. Most of the studies assessed the smartphone-apps' reliability (calculating the intraclass correlation coefficients) and validity (showing the limits of agreement).
CONCLUSION: This review highlights the validated goniometer apps that physiatrists and other health care practitioners can use with confidence in research and clinical practice. We found 12 apps corresponding to these criteria, but there is a need for validation studies on available or new apps focused on goniometric measurement in dynamic conditions, eg, during gait or when performing therapeutic exercises.
Copyright © 2014 American Academy of Physical Medicine and Rehabilitation. Published by Elsevier Inc. All rights reserved.

Mesh:

Year:  2014        PMID: 24844445     DOI: 10.1016/j.pmrj.2014.05.003

Source DB:  PubMed          Journal:  PM R        ISSN: 1934-1482            Impact factor:   2.298


  24 in total

1.  Viability of Hand and Wrist Photogoniometry.

Authors:  Clifton G Meals; Rebecca J Saunders; Sameer Desale; Kenneth R Means
Journal:  Hand (N Y)       Date:  2017-04-09

2.  Test-retest of the Subjective Visual Vertical Test performed using a mobile application with the smartphone anchored to a turntable.

Authors:  Laura Riera-Tur; Encarnación Antúnez-Estudillo; Juan M Montesinos-González; Antonio J Martín-Mateos; Alfonso M Lechuga-Sancho
Journal:  Eur Arch Otorhinolaryngol       Date:  2022-07-15       Impact factor: 3.236

Review 3.  A review of computational approaches for evaluation of rehabilitation exercises.

Authors:  Yalin Liao; Aleksandar Vakanski; Min Xian; David Paul; Russell Baker
Journal:  Comput Biol Med       Date:  2020-03-04       Impact factor: 4.589

4.  THE EFFECTS OF AN AQUATIC MANUAL THERAPY TECHNIQUE, AQUASTRETCH™ ON RECREATIONAL ATHLETES WITH LOWER EXTREMITY INJURIES.

Authors:  Timothy Alejo; Corey Shilhanek; Michael McGrath; John D Heick
Journal:  Int J Sports Phys Ther       Date:  2018-04

5.  Accuracy and repeatability of smartphone sensors for measuring shank-to-vertical angle.

Authors:  Brandon T Nguyen; Nick A Baicoianu; Darrin B Howell; Keshia M Peters; Katherine M Steele
Journal:  Prosthet Orthot Int       Date:  2020-04-21       Impact factor: 1.895

6.  Reliability and Validity Measurement of Sagittal Lumbosacral Quiet Standing Posture with a Smartphone Application in a Mixed Population of 183 College Students and Personnel.

Authors:  George A Koumantakis; Maria Nikoloudaki; Sara Thacheth; Kalliroi Zagli; Konstantina Bitrou; Andreas Nigritinos; Leon Botton
Journal:  Adv Orthop       Date:  2016-10-23

7.  Interrater Reliability of mHealth App Rating Measures: Analysis of Top Depression and Smoking Cessation Apps.

Authors:  Adam C Powell; John Torous; Steven Chan; Geoffrey Stephen Raynor; Erik Shwarts; Meghan Shanahan; Adam B Landman
Journal:  JMIR Mhealth Uhealth       Date:  2016-02-10       Impact factor: 4.773

8.  Performance Evaluation of Smartphone Inertial Sensors Measurement for Range of Motion.

Authors:  Quentin Mourcou; Anthony Fleury; Céline Franco; Frédéric Klopcic; Nicolas Vuillerme
Journal:  Sensors (Basel)       Date:  2015-09-15       Impact factor: 3.576

Review 9.  Mobile Phone-Based Joint Angle Measurement for Functional Assessment and Rehabilitation of Proprioception.

Authors:  Quentin Mourcou; Anthony Fleury; Bruno Diot; Céline Franco; Nicolas Vuillerme
Journal:  Biomed Res Int       Date:  2015-10-25       Impact factor: 3.411

10.  Is digital photography an accurate and precise method for measuring range of motion of the hip and knee?

Authors:  Russell R Russo; Matthew B Burn; Sabir K Ismaily; Brayden J Gerrie; Shuyang Han; Jerry Alexander; Christopher Lenherr; Philip C Noble; Joshua D Harris; Patrick C McCulloch
Journal:  J Exp Orthop       Date:  2017-09-07
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