Usability of corrected Kinect measurement for ergonomic evaluation in constrained environment

Abstract

Evaluation of potential risks of musculoskeletal disorders in real workstations is challenging as the environment is cluttered, which makes it difficult to correctly assess the pose of a worker. Being marker-free and calibration-free, Microsoft Kinect is a promising device to assess these poses, but it can deliver unreliable poses especially when occlusions occur. To overcome this problem, we propose to detect and correct badly recognised body parts thanks to a database of example poses. We applied the proposed method to compute rapid upper limb assessment (RULA) score in a realistic environment that involved sub-optimal Kinect placement and several types of occlusions. Results showed that when occlusions occur, the inaccurate raw Kinect data could be significantly improved using our correction method, leading to acceptable joint angles and RULA scores. Our method opens new perspectives to define new fatigue or solicitation indexes based on continuous measurement contrary to classical static images used in ergonomics.

Human motion capture and analysis systems: a systematic review/Sistemas de captura y análisis de movimiento cinemático humano: una revisión sistemática

“…Se encontró que aunque el sistema para el análisis de movimiento Kinect V2 es una herramienta que puede resultar apropiada para medir parámetros espaciotemporales de la marcha como la velocidad, el ancho, largo y tiempo del paso y la velocidad de oscilación del pie, los parámetros como la flexión de tobillo, rodilla y la cadera, máxima abducción de la rodilla y máxima oscilación de la rodilla, resultaron no ser válidos para [28] y válidos con un nivel de confianza del 90% para [29]. Algunos estudios indican que el sistema Kinect V2 puede utilizarse como herramienta de retroalimentación en tiempo real de poblaciones patológicas con alto riesgo de lesiones [29,30].…”

Effect of Face Blurring on Human Pose Estimation: Ensuring Subject Privacy for Medical and Occupational Health Applications

“…In applications, this fact raises a significant privacy problem. For instance, in ergonomics, vision-based human pose estimation can help workers prevent musculoskeletal disorders [ 4 , 7 , 8 , 9 , 10 ]. However, installing cameras in factories to capture workers’ motion leads to significant privacy concerns and workers might legitimately reject this tool.…”