Upper Body Postural Analysis in Sitting Workplace Environment Using Microsoft Kinect V2 Sensor
Human postural analysis is paramount to ergonomic assessment of human-workplace systems. Traditionally, motion tracking systems are being used to assess human joint kinematics in laboratory environment. Motion tracking systems with marker technology make the measurements cumbersome and limit the area of scope to constrained environments. In the present work, cheap, marker less, calibration-free, portable system using Microsoft Kinect sensor was scrutinized for its viability on human body kinematic analysis. Kinect V2 (more accurate and technologically better than Kinect V1) sensor was used to examine the body postural data of 15 participants doing a sitting job. Most of the studies are being done by placing Kinect sensor in front of the body due to occlusions. Efforts were made to assess the human body posture using side view data by placing the Kinect sensor parallel to sagittal plane of human body. Parameters like joint angles were recorded and were analyzed ergonomically for all the participants. The result of the study suggests the possible use of infrared cameras like Kinect to have some insight on human upper body ergonomic assessment in workplace environment. Relevance to Industry: The results obtained from the study can help the ergonomists and concerned technicians to set up better ergonomic assessment tools for workplace. The possible stakeholders of the current study are people working in offices, IT companies, call centres, accounting and analytical tasks, clerical works and all kind of sitting jobs.
KeywordsKinect Musculoskeletal disorders Ergonomics LabView Posture Body angles
- 2.Thorp, A.A., Healy, G.N., Winkler, E., Clark, B.K., Gardiner, P.A., Owen, N., Dunstan, D.W.: Prolonged sedentary time and physical activity in workplace and non-work contexts: a cross-sectional study of office, customer service and call centre employees. Int J Behav Nutr Phy. 9, 128 (2012)CrossRefGoogle Scholar
- 6.Naqvi, S.A.: Study of forward sloping seats for VDT workstations. J. Hum. Ergol. 23, 41–49 (1994)Google Scholar
- 17.Lun, R., Zhao, W. (2015). A survey of applications and human motion recognition with microsoft kinect. Electr. Eng. Comput. Sci. Fac. Publ. 408Google Scholar
- 18.Wei, T., Lee, B., Qiao, Y., Kitsikidis, A., Dimitropoulos, K., Grammalidis, N.: Experimental study of skeleton tracking abilities from microsoft kinect non-frontal views. 2015 3DTV-conference: the true vision—capture, transmission and display of 3D Video (3DTV-CON). Lisbon 2015, 1–4 (2015)Google Scholar
- 20.Moya, S. et al.: Mapping joint ROM on a cube using electromagnetic trackers. In: First International Symposium on Digital Human Modeling. (2011)Google Scholar