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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.
Background: Vacuum cleaning, which is associated with musculoskeletal complaints, is frequently carried out in private households and by professional cleaners. The aim of this pilot study was to quantify the movements during habitual vacuuming and to characterize the movement profile with regard to its variability. Methods: The data were collected from 31 subjects (21 f/10 m) using a 3D motion analysis system (XSens). Eight vacuum cleaners were used to vacuum polyvinyl chloride (PVC) and carpet floors. In 15 joints of the right upper extremity, the trunk and the lower extremities, Principal Component Analysis was used to determine the predominantly varying joints during vacuuming. Results: The movements of the trunk and the lower extremities were relatively constant and, therefore, had less influence. The shoulder, elbow and wrist joints were identified as joints that can be decisive for the movement profile and that can be influenced. These joints were represented in the course of the vacuuming cycle by the mean movement with its standard deviation. Conclusion: In summary, the generalization of a movement profile is possible for the trunk and the lower extremities due to the relative homogeneity. In future it will be necessary to identify factors influencing variability in order to draw conclusions about movement ergonomics.
Background: In general, the prevalence of work-related musculoskeletal disorders (WMSD) in dentistry is high, and dental assistants (DA) are even more affected than dentists (D). Furthermore, differentiations between the fields of dental specialization (e.g., general dentistry, endodontology, oral and maxillofacial surgery, or orthodontics) are rare. Therefore, this study aims to investigate the ergonomic risk of the aforementioned four fields of dental specialization for D and DA on the one hand, and to compare the ergonomic risk of D and DA within each individual field of dental specialization. Methods: In total, 60 dentists (33 male/27 female) and 60 dental assistants (11 male/49 female) volunteered in this study. The sample was composed of 15 dentists and 15 dental assistants from each of the dental field, in order to represent the fields of dental specialization. In a laboratory setting, all tasks were recorded using an inertial motion capture system. The kinematic data were applied to an automated version of the Rapid Upper Limb Assessment (RULA). Results: The results revealed significantly reduced ergonomic risks in endodontology and orthodontics compared to oral and maxillofacial surgery and general dentistry in DAs, while orthodontics showed a significantly reduced ergonomic risk compared to general dentistry in Ds. Further differences between the fields of dental specialization were found in the right wrist, right lower arm, and left lower arm in DAs and in the neck, right wrist, right lower arm, and left wrist in Ds. The differences between Ds and DAs within a specialist discipline were rather small. Discussion: Independent of whether one works as a D or DA, the percentage of time spent working in higher risk scores is reduced in endodontologists, and especially in orthodontics, compared to general dentists or oral and maxillofacial surgeons. In order to counteract the development of WMSD, early intervention should be made. Consequently, ergonomic training or strength training is recommended.
Background: The Rapid Upper Limb Assessment (RULA) is used for the risk assessment of workplace-related activities. Thus far, the paper and pen method (RULA-PP) has been predominantly used for this purpose. In the present study, this method was compared with an RULA evaluation based on kinematic data using inertial measurement units (RULA-IMU). The aim of this study was, on the one hand, to work out the differences between these two measurement methods and, on the other, to make recommendations for the future use of the respective method on the basis of the available findings. Methods: For this purpose, 130 (dentists + dental assistants, paired as teams) subjects from the dental profession were photographed in an initial situation of dental treatment and simultaneously recorded with the IMU system (Xsens). In order to compare both methods statistically, the median value of the difference of both methods, the weighted Cohen’s Kappa, and the agreement chart (mosaic plot) were applied. Results: In Arm and Wrist Analysis—area A—here were differences in risk scores; here, the median difference was 1, and the agreement in the weighted Cohen’s kappa test also remained between 0.07 and 0.16 (no agreement to poor agreement). In area B—Neck, Trunk, and Leg Analysis—the median difference was 0, with at least one poor agreement in the Cohen’s Kappa test of 0.23–0.39. The final score has a median of 0 and a Cohen’s Kappa value of 0.21–0.28. In the mosaic plot, it can be seen that RULA-IMU had a higher discriminatory power overall and more often reached a value of 7 than RULA-PP. Conclusion: The results indicate a systematic difference between the methods. Thus, in the RULA risk assessment, RULA-IMU is mostly one assessment point above RULA-PP. Therefore, future study results of RULA by RULA-IMU can be compared with literature results obtained by RULA-PP to further improve the risk assessment of musculoskeletal diseases.