TY  - JOUR
AU  - Röhling, Hanna Marie
AU  - Althoff, Patrik
AU  - Arsenova, Radina
AU  - Drebinger, Daniel
AU  - Gigengack, Norman
AU  - Chorschew, Anna
AU  - Kroneberg, Daniel
AU  - Rönnefarth, Maria
AU  - Ellermeyer, Tobias
AU  - Rosenkranz, Sina Cathérine
AU  - Heesen, Christoph
AU  - Behnia, Behnoush
AU  - Hirano, Shigeki
AU  - Kuwabara, Satoshi
AU  - Paul, Friedemann
AU  - Brandt, Alexander Ulrich
AU  - Schmitz-Hübsch, Tanja
PY  - 2022
DA  - 2022/4/1
TI  - Proposal for Post Hoc Quality Control in Instrumented Motion Analysis Using Markerless Motion Capture: Development and Usability Study
JO  - JMIR Hum Factors
SP  - e26825
VL  - 9
IS  - 2
KW  - instrumented motion analysis
KW  - markerless motion capture
KW  - visual perceptive computing
KW  - quality control
KW  - quality reporting
KW  - gait analysis
AB  - Background: Instrumented assessment of motor symptoms has emerged as a promising extension to the clinical assessment of several movement disorders. The use of mobile and inexpensive technologies such as some markerless motion capture technologies is especially promising for large-scale application but has not transitioned into clinical routine to date. A crucial step on this path is to implement standardized, clinically applicable tools that identify and control for quality concerns. Objective: The main goal of this study comprises the development of a systematic quality control (QC) procedure for data collected with markerless motion capture technology and its experimental implementation to identify specific quality concerns and thereby rate the usability of recordings. Methods: We developed a post hoc QC pipeline that was evaluated using a large set of short motor task recordings of healthy controls (2010 recordings from 162 subjects) and people with multiple sclerosis (2682 recordings from 187 subjects). For each of these recordings, 2 raters independently applied the pipeline. They provided overall usability decisions and identified technical and performance-related quality concerns, which yielded respective proportions of their occurrence as a main result. Results: The approach developed here has proven user-friendly and applicable on a large scale. Raters’ decisions on recording usability were concordant in 71.5%-92.3% of cases, depending on the motor task. Furthermore, 39.6%-85.1% of recordings were concordantly rated as being of satisfactory quality whereas in 5.0%-26.3%, both raters agreed to discard the recording. Conclusions: We present a QC pipeline that seems feasible and useful for instant quality screening in the clinical setting. Results confirm the need of QC despite using standard test setups, testing protocols, and operator training for the employed system and by extension, for other task-based motor assessment technologies. Results of the QC process can be used to clean existing data sets, optimize quality assurance measures, as well as foster the development of automated QC approaches and therefore improve the overall reliability of kinematic data sets. 
SN  - 2292-9495
UR  - https://humanfactors.jmir.org/2022/2/e26825
UR  - https://doi.org/10.2196/26825
UR  - http://www.ncbi.nlm.nih.gov/pubmed/35363150
DO  - 10.2196/26825
ID  - info:doi/10.2196/26825
ER  -