Combining Ergonomic Risk Assessment (RULA) with Inertial Motion Capture Technology in Dentistry—Using the Benefits from Two Worlds
| Autor: | Fabian Holzgreve, Christian Maurer-Grubinger, David A. Groneberg, Doerthe Brueggmann, Daniela Ohlendorf, Werner Betz, Eileen M. Wanke, Albert Nienhaus, Christina Erbe, Laura Fraeulin |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Male
Technology Ergonomic risk Inertial motion capture Computer science kinematic analysis Dentistry Context (language use) TP1-1185 Kinematics dental treatment concept work place evaluation Risk Assessment Biochemistry Article Analytical Chemistry Upper Extremity Score distribution 03 medical and health sciences 0302 clinical medicine Inertial measurement unit Humans 0501 psychology and cognitive sciences Musculoskeletal Diseases Electrical and Electronic Engineering Instrumentation 050107 human factors Maxillofacial surgeons business.industry Chemical technology wearable sensors dentist 05 social sciences Work (physics) 030210 environmental & occupational health Atomic and Molecular Physics and Optics Occupational Diseases ergonomics inertial motion units Female dental assistant business human factors |
| Zdroj: | Sensors (Basel, Switzerland) Sensors, Vol 21, Iss 4077, p 4077 (2021) Sensors Volume 21 Issue 12 |
| ISSN: | 1424-8220 |
| Popis: | Traditional ergonomic risk assessment tools such as the Rapid Upper Limb Assessment (RULA) are often not sensitive enough to evaluate well-optimized work routines. An implementation of kinematic data captured by inertial sensors is applied to compare two work routines in dentistry. The surgical dental treatment was performed in two different conditions, which were recorded by means of inertial sensors (Xsens MVN Link). For this purpose, 15 (12 males/3 females) oral and maxillofacial surgeons took part in the study. Data were post processed with costume written MATLAB® routines, including a full implementation of RULA (slightly adjusted to dentistry). For an in-depth comparison, five newly introduced levels of complexity of the RULA analysis were applied, i.e., from lowest complexity to highest: (1) RULA score, (2) relative RULA score distribution, (3) RULA steps score, (4) relative RULA steps score occurrence, and (5) relative angle distribution. With increasing complexity, the number of variables times (the number of resolvable units per variable) increased. In our example, only significant differences between the treatment concepts were observed at levels that are more complex: the relative RULA step score occurrence and the relative angle distribution (level 4 + 5). With the presented approach, an objective and detailed ergonomic analysis is possible. The data-driven approach adds significant additional context to the RULA score evaluation. The presented method captures data, evaluates the full task cycle, and allows different levels of analysis. These points are a clear benefit to a standard, manual assessment of one main body position during a working task. |
| Databáze: | OpenAIRE |
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