People lifting patterns—a reference dataset for practitioners
| dc.contributor.author | Kluwak, K. | |
| dc.contributor.author | Klempous, R. | |
| dc.contributor.author | Chaczko, Z. | |
| dc.contributor.author | Rozenblit, J.W. | |
| dc.contributor.author | Kulbacki, M. | |
| dc.date.accessioned | 2021-07-14T02:01:52Z | |
| dc.date.available | 2021-07-14T02:01:52Z | |
| dc.date.issued | 2021 | |
| dc.identifier.citation | Kluwak, K., Klempous, R., Chaczko, Z., Rozenblit, J. W., & Kulbacki, M. (2021). People lifting patterns—A reference dataset for practitioners. Sensors, 21(9). | |
| dc.identifier.issn | 1424-8220 | |
| dc.identifier.doi | 10.3390/s21093142 | |
| dc.identifier.uri | http://hdl.handle.net/10150/660443 | |
| dc.description.abstract | Many health professionals do not use correct person transfer techniques in their daily practice. This results in damage to the paraspinal musculature over time, resulting in lower back pain and injuries. In this work, we propose an approach for the accurate multimodal measurement of people lifting and related motion patterns for ergonomic education regarding the application of correct patient transfer techniques. Several examples of person lifting were recorded and processed through accurate instrumentation and the well-defined measurements of kinematics, kinetics, surface electromyography of muscles as well as multicamera video. This resulted in a complete measurement protocol and unique reference datasets of correct and incorrect lifting schemes for caregivers and patients. This understanding of multimodal motion patterns provides insights for further independent investigations. © 2021 by the authors. Licensee MDPI, Basel, Switzerland. | |
| dc.language.iso | en | |
| dc.publisher | MDPI AG | |
| dc.rights | Copyright © 2021 by the authors. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). | |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | Data processing tag detection | |
| dc.subject | Decision support | |
| dc.subject | Ergonomics in people lifting | |
| dc.subject | Human motion dataset | |
| dc.subject | Human motion lab | |
| dc.subject | Motion analysis | |
| dc.subject | Recommending systems | |
| dc.subject | Tag detection | |
| dc.title | People lifting patterns—a reference dataset for practitioners | |
| dc.type | Article | |
| dc.type | text | |
| dc.contributor.department | Department of Electrical and Computer Engineering, University of Arizona | |
| dc.contributor.department | Department of Surgery, University of Arizona | |
| dc.identifier.journal | Sensors | |
| dc.description.note | Open access journal | |
| dc.description.collectioninformation | This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu. | |
| dc.eprint.version | Final published version | |
| dc.source.journaltitle | Sensors | |
| refterms.dateFOA | 2021-07-14T02:01:52Z |

