scholarly journals The Reliability of the Microsoft Kinect and Ambulatory Sensor-Based Motion Tracking Devices to Measure Shoulder Range-of-Motion: A Systematic Review and Meta-Analysis

Sensors ◽  
2021 ◽  
Vol 21 (24) ◽  
pp. 8186
Author(s):  
Peter Beshara ◽  
David B. Anderson ◽  
Matthew Pelletier ◽  
William R. Walsh
Keyword(s):  
Range Of Motion ◽  
Motion Tracking ◽  
Human Motion ◽  
Microsoft Kinect ◽  
Smartphone Applications ◽  
Health Measurement ◽  
Rater Reliability ◽  
Shoulder Range Of Motion ◽  
Cosmin Checklist ◽  
Tracking Devices

Advancements in motion sensing technology can potentially allow clinicians to make more accurate range-of-motion (ROM) measurements and informed decisions regarding patient management. The aim of this study was to systematically review and appraise the literature on the reliability of the Kinect, inertial sensors, smartphone applications and digital inclinometers/goniometers to measure shoulder ROM. Eleven databases were screened (MEDLINE, EMBASE, EMCARE, CINAHL, SPORTSDiscus, Compendex, IEEE Xplore, Web of Science, Proquest Science and Technology, Scopus, and PubMed). The methodological quality of the studies was assessed using the consensus-based standards for the selection of health Measurement Instruments (COSMIN) checklist. Reliability assessment used intra-class correlation coefficients (ICCs) and the criteria from Swinkels et al. (2005). Thirty-two studies were included. A total of 24 studies scored “adequate” and 2 scored “very good” for the reliability standards. Only one study scored “very good” and just over half of the studies (18/32) scored “adequate” for the measurement error standards. Good intra-rater reliability (ICC > 0.85) and inter-rater reliability (ICC > 0.80) was demonstrated with the Kinect, smartphone applications and digital inclinometers. Overall, the Kinect and ambulatory sensor-based human motion tracking devices demonstrate moderate–good levels of intra- and inter-rater reliability to measure shoulder ROM. Future reliability studies should focus on improving study design with larger sample sizes and recommended time intervals between repeated measurements.

scholarly journals The Reliability and Validity of Wearable Inertial Sensors Coupled with the Microsoft Kinect to Measure Shoulder Range-of-Motion

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7238
Author(s):  
Peter Beshara ◽  
Judy F. Chen ◽  
Andrew C. Read ◽  
Pierre Lagadec ◽  
Tian Wang ◽  
...  
Keyword(s):  
Construct Validity ◽  
Range Of Motion ◽  
Inertial Sensors ◽  
Objective Assessment ◽  
Reliability And Validity ◽  
Human Movement ◽  
Microsoft Kinect ◽  
Rater Reliability ◽  
Shoulder Range Of Motion ◽  
Shoulder Flexion

Background: Objective assessment of shoulder joint active range of motion (AROM) is critical to monitor patient progress after conservative or surgical intervention. Advancements in miniature devices have led researchers to validate inertial sensors to capture human movement. This study investigated the construct validity as well as intra- and inter-rater reliability of active shoulder mobility measurements using a coupled system of inertial sensors and the Microsoft Kinect (HumanTrak). Methods: 50 healthy participants with no history of shoulder pathology were tested bilaterally for fixed and free ROM: (1) shoulder flexion, and (2) abduction using HumanTrak and goniometry. The repeat testing of the standardised protocol was completed after seven days by two physiotherapists. Results: All HumanTrak shoulder movements demonstrated adequate reliability (intra-class correlation (ICC) ≥ 0.70). HumanTrak demonstrated higher intra-rater reliability (ICCs: 0.93 and 0.85) than goniometry (ICCs: 0.75 and 0.53) for measuring free shoulder flexion and abduction AROM, respectively. Similarly, HumanTrak demonstrated higher intra-rater reliability (ICCs: 0.81 and 0.94) than goniometry (ICCs: 0.70 and 0.93) for fixed flexion and abduction AROM, respectively. Construct validity between HumanTrak and goniometry was adequate except for free abduction. The differences between raters were predominately acceptable and below ±10°. Conclusions: These results indicated that the HumanTrak system is an objective, valid and reliable way to assess and track shoulder ROM.

scholarly journals Assessment of Shoulder Range of Motion Using a Wireless Inertial Motion Capture Device—A Validation Study

Sensors ◽  
2019 ◽  
Vol 19 (8) ◽  
pp. 1781 ◽  
Author(s):  
Rigoni ◽  
Gill ◽  
Babazadeh ◽  
Elsewaisy ◽  
Gillies ◽  
...  
Keyword(s):  
Range Of Motion ◽  
Electronic Device ◽  
External Rotation ◽  
Secondary Analysis ◽  
Correlation Coefficients ◽  
Preliminary Evidence ◽  
Rater Reliability ◽  
Shoulder Range Of Motion ◽  
Technological Advances ◽  
Shoulder Range

(1) Background: Measuring joint range of motion has traditionally occurred with a universal goniometer or expensive laboratory based kinematic analysis systems. Technological advances in wearable inertial measurement units (IMU) enables limb motion to be measured with a small portable electronic device. This paper aims to validate an IMU, the ‘Biokin’, for measuring shoulder range of motion in healthy adults; (2) Methods: Thirty participants completed four shoulder movements (forward flexion, abduction, and internal and external rotation) on each shoulder. Each movement was assessed with a goniometer and the IMU by two testers independently. The extent of agreement between each tester’s goniometer and IMU measurements was assessed with intra-class correlation coefficients (ICC) and Bland-Altman 95% limits of agreement (LOA). Secondary analysis compared agreement between tester’s goniometer or IMU measurements (inter-rater reliability) using ICC’s and LOA; (3) Results: Goniometer and IMU measurements for all movements showed high levels of agreement when taken by the same tester; ICCs > 0.90 and LOAs < ±5 degrees. Inter-rater reliability was lower; ICCs ranged between 0.71 to 0.89 and LOAs were outside a prior defined acceptable LOAs (i.e., > ±5 degrees); (4) Conclusions: The current study provides preliminary evidence of the concurrent validity of the Biokin IMU for assessing shoulder movements, but only when a single tester took measurements. Further testing of the Biokin’s psychometric properties is required before it can be confidently used in routine clinical practice and research settings.

scholarly journals Smartphone applications for the evaluation of pathologic shoulder range of motion and shoulder scores—a comparative study

2018 ◽  
Vol 2 (1) ◽  
pp. 109-114 ◽  
Author(s):  
Kevyn Mejia-Hernandez ◽  
Angela Chang ◽  
Nathan Eardley-Harris ◽  
Ruurd Jaarsma ◽  
Tiffany K. Gill ◽  
...  
Keyword(s):  
Comparative Study ◽  
Range Of Motion ◽  
Smartphone Applications ◽  
Shoulder Range Of Motion ◽  
Shoulder Scores ◽  
Shoulder Range

A Platform for Mechanical Assembly Education Using the Microsoft Kinect

2014 ◽  
Author(s):  
Yizhe Chang ◽  
El-Sayed Aziz ◽  
Zhou Zhang ◽  
Mingshao Zhang ◽  
Sven Esche ◽  
...  
Keyword(s):  
Undergraduate Students ◽  
Computer Aided Design ◽  
Motion Tracking ◽  
Low Cost ◽  
Financial Burden ◽  
Human Motion ◽  
Microsoft Kinect ◽  
Input Device ◽  
Mechanical Assembly ◽  
Mechanical Parts

Mechanical assembly activities involve multiple factors including humans, mechanical parts, tools and assembly environments. In order to simulate assembly processes by computers for educational purposes, all these factors should be considered. Virtual reality (VR) technology, which aims to integrate natural human motion into real-world scenarios, provides an ideal simulation medium. Novel VR devices such as 3D glasses, motion-tracking gloves, haptic sensors, etc. are able to fulfill fundamental assembly simulation needs. However, most of these implementations focus on assembly simulations for computer-aided design, which are geared toward professionals rather than students, thus leading to complicated assembly procedures not suitable for students. Furthermore, the costs of these novel VR devices and specifically designed VR platforms represent an untenable financial burden for most educational institutions. In this paper, a virtual platform for mechanical assembly education based on the Microsoft Kinect sensor and Garry’s Mod (GMod) is presented. With the help of the Kinect’s body tracking function and voice recognition technology in conjunction with the graphics and physics simulation capabilities of GMod, a low-cost VR platform that enables educators to author their own assembly simulations was implemented. This platform utilizes the Kinect as the sole input device. Students can use voice commands to navigate their avatars inside of a GMod powered virtual laboratory as well as use their body’s motions to integrate pre-defined mechanical parts into assemblies. Under this platform, assembly procedures involving the picking, placing and attaching of parts can be performed collaboratively by multiple users. In addition, the platform allows collaborative learning without the need for the learners to be co-located. A pilot study for this platform showed that, with the instructor’s assistance, mechanical engineering undergraduate students are able to complete basic assembly operations.

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