scholarly journals Ergonomic Risk Assessment of Dental Students—RULA Applied to Objective Kinematic Data

2021 ◽  
Vol 18 (19) ◽  
pp. 10550
Author(s):  
Kim Sarah Blume ◽  
Fabian Holzgreve ◽  
Laura Fraeulin ◽  
Christina Erbe ◽  
Werner Betz ◽  
...  
Keyword(s):  
Inertial Sensors ◽  
Treatment Time ◽  
Dental Students ◽  
Body Parts ◽  
Upper Arm ◽  
Left Wrist ◽  
Kinematic Data ◽  
Dental Assistant ◽  
Dental Work ◽  
Ergonomic Risk

Musculoskeletal disorder (MSD) is already prevalent in dental students despite their young age and the short duration of dental practice. The current findings state that the causes of MSD are related to posture during dental work. This study aims to investigate the ergonomic risk of dental students. In order to analyze the ergonomic risk of dental students, 3D motion analyses were performed with inertial sensors during the performance of standardized dental activities. For this purpose, 15 dental students and 15 dental assistant trainees (all right-handed) were measured in a team. Data were analyzed using the Rapid Upper Limb Assessment (RULA), which was modified to evaluate objective data. Ergonomic risk was found for the following body parts in descending order: left wrist, right wrist, neck, trunk, left lower arm, right lower arm, right upper arm, left upper arm. All relevant body parts, taken together, exhibited a posture with the highest RULA score that could be achieved (median Final Overall = 7), with body parts in the very highest RULA score of 7 for almost 80% of the treatment time. Dental students work with poor posture over a long period of time, exposing them to high ergonomic risk. Therefore, it seems necessary that more attention should be paid to theoretical and practical ergonomics in dental school.

scholarly journals Ergonomic Comparison of Four Dental Workplace Concepts Using Inertial Motion Capture for Dentists and Dental Assistants

2021 ◽  
Vol 18 (19) ◽  
pp. 10453
Author(s):  
Daniela Ohlendorf ◽  
Laura Fraeulin ◽  
Jasmin Haenel ◽  
Werner Betz ◽  
Christina Erbe ◽  
...  
Keyword(s):  
Motion Capture ◽  
Musculoskeletal Diseases ◽  
Body Parts ◽  
Inertial Motion ◽  
Kinematic Data ◽  
Working Posture ◽  
Dental Assistants ◽  
Very High ◽  
Dental Professionals ◽  
Ergonomic Risk

When the inventory is arranged in a dental practice, a distinction can be made between four different dental workplace concepts (DWCs). Since the prevalence of musculoskeletal diseases in dental professionals is very high, preventive solution need to be investigated. As the conventionally used DWCs have, to date, never been studied in terms of their ergonomics, this study aims to investigate the ergonomic risk when working at the four different DWCs. In total, 75 dentists (37 m/38 f) and 75 dental assistants (16 m/59 f) volunteered to take part in this study. Standardized cooperative working procedures were carried out in a laboratory setting and kinematic data were recorded using an inertial motion capture system. The data were applied to an automated version of the Rapid Upper Limb Assessment (RULA). Comparisons between the DWCs and between the dentists and dental assistants were calculated. In all four DWCs, both dentists and dental assistants spent 95–97% of their working time in the worst possible RULA score. In the trunk, DWCs 1 and 2 were slightly favorable for both dentists and dental assistants, while for the neck, DWC 4 showed a lower risk score for dentists. The ergonomic risk was extremely high in all four DWCs, while only slight advantages for distinct body parts were found. The working posture seemed to be determined by the task itself rather than by the different inventory arrangements.

Deadlift Recognition and Application based on Multiple Modalities using Recurrent Neural Network

2020 ◽  
Vol 2020 (17) ◽  
pp. 2-1-2-6
Author(s):  
Shih-Wei Sun ◽  
Ting-Chen Mou ◽  
Pao-Chi Chang
Keyword(s):  
Neural Network ◽  
Recurrent Neural Network ◽  
Network Structure ◽  
Inertial Sensors ◽  
Body Movement ◽  
The Body ◽  
Body Parts ◽  
Multimodal Sensing ◽  
Multiple Devices ◽  
Neural Network Structure

To improve the workout efficiency and to provide the body movement suggestions to users in a “smart gym” environment, we propose to use a depth camera for capturing a user’s body parts and mount multiple inertial sensors on the body parts of a user to generate deadlift behavior models generated by a recurrent neural network structure. The contribution of this paper is trifold: 1) The multimodal sensing signals obtained from multiple devices are fused for generating the deadlift behavior classifiers, 2) the recurrent neural network structure can analyze the information from the synchronized skeletal and inertial sensing data, and 3) a Vaplab dataset is generated for evaluating the deadlift behaviors recognizing capability in the proposed method.

scholarly journals Atendimento odontológico em tempos de COVID-19: compartilhando boas práticas protetivas e de biossegurança

2020 ◽  
Vol 11 (1) ◽  
pp. 73
Author(s):  
Daniela Costa Moraes ◽  
Daniela Cristina Diniz Ferreira Galvão ◽  
Neiana Carolina Rios Ribeiro ◽  
Lisia Mariana Silva de Oliveira ◽  
Maria Cecília Fonsêca Azoubel ◽  
...  
Keyword(s):  
Dental Students ◽  
Protective Equipment ◽  
Oral Fluids ◽  
Patient Screening ◽  
Professional Category ◽  
Health Authorities ◽  
Dental Procedures ◽  
The World ◽  
Mucous Membranes ◽  
Dental Work

INTRODUCTION: During the COVID-19 pandemic, dentists were classified as a high-risk professional category for SARS-Cov2 infection and transmission, due to the proximity of the patient's face as well as the frequent performance of aerosol-generating procedures. Transmission of this pathogen during dental procedures can occur by inhaling aerosols/droplets from infected individuals or by direct contact with mucous membranes, oral fluids or contaminated instruments and surfaces. Aware of the risks inherent to the exercise of this profession and facing the world scenario, several recommendations have been suggested for dental surgeons and dental students in patient care. Although biosafety is already part of the dentist's routine, the pandemic context presupposes the need to revisit the guiding principles of this practice and to know the particularities imposed by a hitherto unknown virus. OBJECTIVE: This work aims to propose and discuss measures to deal with the spread of SARS-Cov2 in the dental environment, emphasizing the necessary care for the protection of professionals and patients, in the context of Dentistry in Brazil. METHODS: To this end, a compilation of measures and recommendations was made based on the main technical documents published in recent months by the health authorities. RESULTS: The main recommendations include patient screening, social distance, adjustments to personal protective equipment (PPE) and the use of appropriate disinfection products and techniques. CONCLUSION: This work presented, in an objective and practical way, essential measures for dental work during the COVID-19 pandemic, highlighting the probable permanence of these actions and the importance of adopting rigid, adequate and feasible measures.

Analysis and prevention of ergonomic risk factors among dental students

2020 ◽  
Author(s):  
Nataša Pejčić ◽  
Vanja Petrović ◽  
Milica Đurić‐Jovičić ◽  
Nataša Medojević ◽  
Angelina Nikodijević‐Latinović
Keyword(s):  
Risk Factors ◽  
Dental Students ◽  
Ergonomic Risk Factors ◽  
Ergonomic Risk

scholarly journals Effects of Gait Strategy and Speed on Regularity of Locomotion Assessed in Healthy Subjects Using a Multi-Sensor Method

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 513 ◽  
Author(s):  
Marco Rabuffetti ◽  
Giovanni Scalera ◽  
Maurizio Ferrarin
Keyword(s):  
Healthy Adult ◽  
Inertial Sensors ◽  
Cervical Vertebra ◽  
Body Parts ◽  
Autocorrelation Analysis ◽  
Human Movements ◽  
Or Groups ◽  
Seventh Cervical Vertebra ◽  
Acceleration Vector ◽  
Body Location

The regularity of pseudo-periodic human movements, including locomotion, can be assessed by autocorrelation analysis of measurements using inertial sensors. Though sensors are generally placed on the trunk or pelvis, movement regularity can be assessed at any body location. Pathological factors are expected to reduce regularity either globally or on specific anatomical subparts. However, other non-pathological factors, including gait strategy (walking and running) and speed, modulate locomotion regularity, thus potentially confounding the identification of the pathological factor. The present study’s objectives were (1) to define a multi-sensor method based on the autocorrelation analysis of the acceleration module (norm of the acceleration vector) to quantify regularity; (2) to conduct an experimental study on healthy adult subjects to quantify the effect on movement regularity of gait strategy (walking and running at the same velocity), gait speed (four speeds, lower three for walking, upper two for running), and sensor location (on four different body parts). Twenty-five healthy adults participated and four triaxial accelerometers were located on the seventh cervical vertebra (C7), pelvis, wrist, and ankle. The results showed that increasing velocity was associated with increasing regularity only for walking, while no difference in regularity was observed between walking and running. Regularity was generally highest at C7 and ankle, and lowest at the wrist. These data confirm and complement previous literature on regularity assessed on the trunk, and will support future analyses on individuals or groups with specific pathologies affecting locomotor functions.

scholarly journals Effectiveness of Ergonomics Awareness Training Programme in Minimizing the Ergonomic Risk Factors in Dental Surgeons

2013 ◽  
Vol 10 ◽  
pp. 148-153
Author(s):  
Abdul Rahim Shaik ◽  
B.H. Sripathi Rao ◽  
Akhter Husain ◽  
Juliana Linnette D’Sa
Keyword(s):  
Risk Factors ◽  
Test Scores ◽  
Material Handling ◽  
Training Programme ◽  
Dental Students ◽  
The Body ◽  
Awareness Training ◽  
High Productivity ◽  
Ergonomic Risk Factors ◽  
Ergonomic Risk

The professional work usually carried out by the dental surgeons results in developing ergonomic risk factors such as forward bends and rotated positions of the body while handling variety of tools. The successful application of ergonomics assures high productivity, avoidance of illnesses and injuries and increased satisfaction among dental surgeons. The study was carried out to find the effectiveness of ergonomics awareness training programme in minimizing the ergonomic risk factors in dental surgeons. For this purpose, one hundred and thirty dental surgeons among post graduate dental students, faculty members and private practitioners from in and around Mangalore city, Southern Karnataka District, India, with more than one year of experience were selected by using non-probability convenience sampling method. A six week of ergonomics awareness training programme for selected dental surgeons was developed and imparted during the training. In order to determine the effectiveness of ergonomics awareness training programme, a pre-tested structured dental work station observation check list was used. The result indicates that, mean post-test scores of manual material handling (0.23), physical energy demands (0.18), instruments (0.00), environment (0.00) and other musculoskeletal demands (1.35) were lower than the mean pre-test scores i.e., 1.98, 1.95, 0.14, 0.01 and 7.53 respectively. Based on the results of the study we conclude that, ergonomics awareness training programme will be effective in minimizing the ergonomic risk factors in dental surgeons. Key words: Ergonomics awareness; Ergonomic risk factors; Dental surgeons; Work-related musculoskeletal disorders (WMSDs)

scholarly journals Estimation of Body Height from Head Length among Dental Students of a Dental College

2018 ◽  
Vol 56 (213) ◽  
pp. 861-865 ◽  
Author(s):  
Bipana Manandhar ◽  
Ritee Shrestha
Keyword(s):  
Significant Positive Correlation ◽  
Body Height ◽  
Age Groups ◽  
College Teaching ◽  
Dental Students ◽  
Regression Equation ◽  
The Body ◽  
Head Length ◽  
Body Parts ◽  
Positive Correlation

Introduction: Body height is an important measure of physical identity. Height exhibits a dimensional relationship with various parts of the body. This relationship helps to calculate height from dismembered and mutilated body parts in forensic examinations. As the cranial dimensions are more reliable and precise means of predicting the stature, this study was undertaken to find the relation between head length and height and to derive a regression formula for the estimation of height from head length among dental students. Methods: This descriptive cross-sectional study was conducted among 150 dental students of age group 18-21 years in the Department of Anatomy, Kantipur Dental College Teaching Hospital and Research Center, Basundhara, Kathmandu. The head length was measured with the help of spreading caliper. Height was measured with the help of a standard height measuring instrument. The head length and the height of the students were measured in centimeters. Data obtained were analyzed to find the correlation between head length and height and to derive a regression equation for the estimation of height. Results: A significant positive correlation was observed between head length and height (r=0.734, P<0.001). The regression equation for body height and head length including both sexes and all age groups of dental students was found to be y=12.9+8.45x where x is head length and y is body height. Conclusions: It was observed in the present study that there was a significant positive correlation between height and head length in all the age groups indicating that head length is a reliable indicator in estimation of height.

scholarly journals Influence of motivation and a new digitized training program on undergraduate dental students during preclinical scaling training

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Miriam Seidel ◽  
Simone Sutor ◽  
Jonas Conrad ◽  
Anne Sophie Engel ◽  
Antje Geiken ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Training Program ◽  
Computer Games ◽  
Treatment Time ◽  
Root Surface ◽  
Dental Students ◽  
Dental Student ◽  
Self Assessment ◽  
Significant Difference ◽  
Cleaning Efficacy

Abstract Background The current study evaluated whether a new digitized scaling training program (DTP: n = 30; supervisor-student-ratio 1:10) improves the performance of undergraduate dental student during a preclinical course in regard to two different instruments [sonic scalers (AIR) and Gracey curettes (GRA)] compared to a conventional training program (CTP: n = 19; supervisor-student-ratio 1:4). Methods All the participants received a two-hour lecture on both instruments, followed by a 12-week period with a weekly training program lasting 45 min (10 sessions); one group was supported by DTP. At the end of the training phase, all the participants performed the subgingival scaling of six equivalent test teeth using GRA and AIR. Treatment time, proportion of removed simulated biofilm (relative cleaning efficacy, RCE-b) and hard deposits (RCE-d) were recorded. By using a pseudonymized questionnaire with a 5-point Likert scale, self-assessment of scaling effort, handling, root surface roughness/destruction and effectiveness were evaluated. In addition, personal data such as age, gender, handedness, regularity of playing computer games/consoles and previous dental/technical or medical education were elevated and correlated with cleaning efficacy. Results The DTP participants showed higher effectiveness in RCE-b compared to those who used the CTP with GRA (71.54% vs. 67.23%, p = 0.004) and AIR (71.75% vs. 62.63%, p ≤ 0.001), and the DTP students were faster with both instruments (p ≤ 0.001). For RCE-d, there was no significant difference between the DTP and CTP groups (GRA p = 0.471; AIR p = 0.158), whereas DTP showed better RCE-d results with GRA versus AIR (84.68% vs. 77.85%, p < 0.001). According to the questionnaire, no significant differences were detected between the training groups in terms of self-assessment, handling, treatment time, root surface roughness/destruction or effectiveness of the instruments. The CTP group favored AIR compared to GRA regarding the fatigue effect. The CTP and playing computer games/consoles regularly was correlated with lower RCE-b, whereas previous education in medicine/dentistry was correlated with higher RCE-b values. Conclusions Within the limitations of the study, the DTP with a reduced supervision effort compared to the CTP resulted in higher effectiveness and lower instrumentation time for removing simulated biofilms.

PERANCANGAN MESIN PEMIPIL JAGUNG RAMAH LINGKUNGAN DENGAN PENDEKATAN NORDIC BODY MAP

2020 ◽  
Vol 6 (1) ◽  
pp. 26
Author(s):  
Firman Ardiansyah Ekoanindiyo ◽  
Antoni Yohanes ◽  
Endro Prihastono
Keyword(s):  
The Body ◽  
Food Plants ◽  
Upper Arm ◽  
Corn Production ◽  
Maize Production ◽  
Left Wrist ◽  
Left Hand ◽  
Left Elbow ◽  
Directorate General ◽  
Body Map

Based on calculations by the Directorate General of Food Plants (Ditjen TP), Ministry of Agriculture. Corn production in the last 5 years has increased by an average of 12.49% per year. According to the Secretary of the Directorate General of Food Crops of the Ministry of Agriculture (Kementan) Maman Suherman in 2019 maize production is estimated to reach 33 million tonnes of dry shell (PK) in an interview with Republika on January 6, 2019. Cepiring sub-district, Kendal district, apart from being planted with rice in the rainy season, rice fields also planted with maize. After harvesting, the corn that has been plucked is separated from the cob using a corn sheller. The shelling machine is used using diesel fuel and electricity, with workers standing for long periods of time, causing fatigue in the arms, waist, thighs and back. The data processing of the nordic body map questionnaire was carried out to determine the complaints on the skeleton and muscles of the workers. From the results of the questionnaire above, most Sido Rejo farmers feel complaints on their right shoulder, left upper arm, back, right upper arm, back, waist, left elbow, right elbow, left forearm, right forearm, left wrist, wrist right, left hand, right hand, left thigh, right thigh, left calf, right calf, left leg to right leg. With anthropometric measurements, the dimensions of the body used are the height of the sitting shoulders and the data used are the average data or the 50th percentile. With this solar sheller, it can save fuel and be environmentally friendly and reduce the complaints of the frame and muscles of farmers

scholarly journals Classifying Upper Arm Gym-Workouts via Convolutional Neural Network by Imputing a Biopotential-Kinematic Relationship

2021 ◽  
Vol 11 (6) ◽  
pp. 2845
Author(s):  
Ji Hyeon Yoo ◽  
Ho Jin Jung ◽  
Yi Sue Jung ◽  
Yoonbee Kim ◽  
Changjae Lee ◽  
...  
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Data Augmentation ◽  
Upper Arm ◽  
Kinematic Data ◽  
Joint Kinematic ◽  
Kinematic Relationship ◽  
Two Factors ◽  
Spatio Temporal ◽  
Image Type

This paper proposes a systemic approach to upper arm gym-workout classification according to spatio-temporal features depicted by biopotential as well as joint kinematics. The key idea of the proposed approach is to impute a biopotential-kinematic relationship by merging the joint kinematic data into a multichannel electromyography signal and visualizing the merged biopotential-kinematic data as an image. Under this approach, the biopotential-kinematic relationship can be imputed by counting on the functionality of a convolutional neural network: an automatic feature extractor followed by a classifier. First, while a professional trainer is demonstrating upper arm gym-workouts, electromyography and joint kinematic data are measured by an armband-type surface electromyography (sEMG) sensor and a RGB-d camera, respectively. Next, the measured data are augmented by adopting the amplitude adjusted Fourier Transform. Then, the augmented electromyography and joint kinematic data are visualized as one image by merging and calculating pixel components in three different ways. Lastly, for each visualized image type, upper arm gym-workout classification is performed via the convolutional neural network. To analyze classification accuracy, two-way rANOVA is performed with two factors: the level of data augmentation and visualized image type. The classification result substantiates that a biopotential-kinematic relationship can be successfully imputed by merging joint kinematic data in-between biceps- and triceps-electromyography channels and visualizing as a time-series heatmap image.

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