An Ergonomic Evaluation Method Using a Mobile Depth Sensor and Pose Estimation. de Freitas, P. V. A.; Mendes, P. R. C.; Busson, A. J. G.; Guedes, Á. L. V.; Silva, G. L. F. d.; de Paiva, A. C.; and Colcher, S. In Proceedings of the 25th Brazillian Symposium on Multimedia and the Web, of WebMedia '19, pages 445–452. ACM.
An Ergonomic Evaluation Method Using a Mobile Depth Sensor and Pose Estimation [link]Paper  doi  abstract   bibtex   
An ergonomic evaluation is an observation of a person in order to identify musculoskeletal disorders (WMSDs) caused by prolonged or repeated harmful poses that a person adopts during work tasks. Nowadays, an ergonomist or other health professional perform such evaluations based on a set of posture rules and checklists, which can be subjective and thus lead to erroneous risk classifications. Moreover, this professional usually perform such evaluation in the patient work environment. In order to make those evaluations more objective and concise we propose a evaluation method using a mobile depth sensor. Different from other methods based in fixed depth sensors (e.g. Kinect), our method enable professionals easily perform it in the patient work environment. More precisely, we present an experiment that uses a smartphone from Google's Tango project and the Ovako Working Posture Analysing System (OWAS) method. To evaluate our approach, we also perform the ergonomic assessment using the Kinect sensor, a device that has a good reliability in the automated ergonomic evaluation. Both evaluations involved a set of 34 poses performed by 3 volunteers and annotated by an ergonomist. The Kinect has achieved accuracy of 57,08% on torso classification, 58,33% for arms and 25,00% for legs positions. While the approach using the mobile depth sensor has achieved 35,41% on torso classification, 93,05% for arms and 66,23% for legs positions on the same set of poses. Although the small sample, the achieved results may indicate that our mobile depth sensor approach can be as viable as methods based fixed depth sensor.
@inproceedings{de_freitas_ergonomic_2019,
	location = {New York, {NY}, {USA}},
	title = {An Ergonomic Evaluation Method Using a Mobile Depth Sensor and Pose Estimation},
	rights = {All rights reserved},
	isbn = {978-1-4503-6763-9},
	url = {http://doi.acm.org/10.1145/3323503.3349550},
	doi = {10.1145/3323503.3349550},
	series = {{WebMedia} '19},
	abstract = {An ergonomic evaluation is an observation of a person in order to identify musculoskeletal disorders ({WMSDs}) caused by prolonged or repeated harmful poses that a person adopts during work tasks. Nowadays, an ergonomist or other health professional perform such evaluations based on a set of posture rules and checklists, which can be subjective and thus lead to erroneous risk classifications. Moreover, this professional usually perform such evaluation in the patient work environment. In order to make those evaluations more objective and concise we propose a evaluation method using a mobile depth sensor. Different from other methods based in fixed depth sensors (e.g. Kinect), our method enable professionals easily perform it in the patient work environment. More precisely, we present an experiment that uses a smartphone from Google's Tango project and the Ovako Working Posture Analysing System ({OWAS}) method. To evaluate our approach, we also perform the ergonomic assessment using the Kinect sensor, a device that has a good reliability in the automated ergonomic evaluation. Both evaluations involved a set of 34 poses performed by 3 volunteers and annotated by an ergonomist. The Kinect has achieved accuracy of 57,08\% on torso classification, 58,33\% for arms and 25,00\% for legs positions. While the approach using the mobile depth sensor has achieved 35,41\% on torso classification, 93,05\% for arms and 66,23\% for legs positions on the same set of poses. Although the small sample, the achieved results may indicate that our mobile depth sensor approach can be as viable as methods based fixed depth sensor.},
	pages = {445--452},
	booktitle = {Proceedings of the 25th Brazillian Symposium on Multimedia and the Web},
	publisher = {{ACM}},
	author = {de Freitas, Pedro Vinicius A. and Mendes, Paulo Renato C. and Busson, Antonio José G. and Guedes, Álan Livio V. and Silva, Giovanni Lucca F. da and de Paiva, Anselmo Cardoso and Colcher, Sérgio},
	urldate = {2019-11-15},
	date = {2019}
}
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