Magister Chirurgiae Dentium (MChD) / Occupational hazards are common among many professions and dentistry is no exception. Occupational hazards include percutaneous injuries, inhalation of noxious chemicals, noise and musculoskeletal disorders (MSD). Despite the fact that MSD have been documented to be very prevalent among dentists in various countries, there is a paucity of literature from South Africa. Aim The aim of the present study was to determine the prevalence of musculoskeletal disorders among the dentists in KwaZulu-Natal (KZN), South Africa and to identify risk factors associated with it. The study was a cross-sectional, descriptive one and questionnaires were used to elicit information regarding socio-demographic details, medical history, work history and work-related posture information from dentists based in KwaZulu-Natal. A convenience sample of all qualified dentists in this region who were registered members of the South African Dental Association (SADA) was used. Results One hundred and nine dentists responded to the questionnaire. The response rate was 31%. The majority were male; a third aged between 30 - 39 years and the ratio of females to males was 1:3. Almost all the dentists reported pain in the neck, lower back and shoulder. Less than a quarter of the dentists in KZN reported hand pain, numbness in the hands and a tingling sensation in the hands. More than three quarters reported that they had no negative effects when performing restorative work and scaling and polishing, but 3.1% reported having extreme levels of pain. The most common working position reported was the 2 0' clock position. Nearly three quarters rotated their necks while performing clinical dentistry and a third tilted their shoulders towards their dominant hand. There was no relationship between Body Mass Index (BMI) and whether respondents treated patients while seated or standing and neither was there a relationship between pain in the lower back and BMI. There was a strong association between pain in the neck while performing clinical work and the number of years in practice confounded by age. When compared to other countries the prevalence of MSD is very high. The highest occurrence was for neck, back and shoulder pain. Avoiding these injuries is critical and self-recognition is important in either preventing further injuries or in increasing severity of the condition. The findings of this study suggests that it may be valuable to include ergonomic work practice in the training of dentists and dentists should be involved in a proper exercise routine which should include stretching and weight training to prevent injuries. Regular breaks should be taken to perform stretching exercises in-between the management of patients in order to reduce the risk of MSD.

<p>Surface electromyography (sEMG) has been used to monitor muscle activity and predict fatigue in the workplaces. However, objectively measuring fatigue is challenging in complex work with unpredictable work cycles, where sEMG may be influenced by the dynamically changing posture demands. The sEMG is affected by various variables and substantial change in mean power frequencies (MPF), and a decline over 8-9% is primarily considered musculoskeletal fatigue. These MPF thresholds have been frequently used, and there were limited efforts to test their appropriateness in determining musculoskeletal fatigue in live workplaces (which predominantly consist of complex tasks). In addition, the techniques that consider both muscular and postural measurements that incorporate dynamic posture changes observed in complex work have not yet been explored. The overall objective of this work is to leverage both postural and muscular cues to identify musculoskeletal fatigue in complex tasks/jobs (i.e., tasks involving different levels of exertions, durations, and postures). The work was completed in two studies.</p> The first study aimed to (1) predict subjective fatigue using objective measurements in non-repetitive tasks, (2) determine whether the musculoskeletal fatigue thresholds in non-repetitive tasks differed from the previously reported threshold, and (3) utilize the empirically calculated thresholds to test their appropriateness in determining musculoskeletal fatigue in live surgical workplaces. The findings showed that the multi-modal measurements indicate better sensitivity than single-modality (sEMG) measurements in detecting decreases in MPF, a predictor of fatigue. In addition, the results showed that the thresholds in dynamic non-repetitive tasks, like surgery, are different than the previously reported 8% threshold. Additionally, implementing muscle-specific thresholds increased the likelihood of more accurately reporting subjective fatigue. The second study aimed to develop a multi-modal fatigue index to detect musculoskeletal fatigue. A controlled laboratory study was performed to simulate the non-repetitive physical demands at different postures. A series of experiments were conducted to test the effectiveness of various metrics/models to identify subjective fatigue in complex tasks. Next, the composite fatigue index (CFI) function was developed using the time-synced integration of both muscular signals (measured with sEMG sensors) and postural signals (measured with Inertial Measurement Unit (IMU) sensors). The variables from sEMG (amplitude, frequency, and the number of muscles showing signs of fatigue) and IMU (the prevalence of static and demanding postures and the number of shoulders in static/demanding posture) sensors were integrated to generate the CFI function. The prevalence of static/demanding postures was developed using the cumulative exposures to static/demanding postures based on the material fatigue failure theory. The single value fatigue index was obtained using the resultant CFI function, which incorporates both muscular and postural variables, to quantify the muscular fatigue in dynamic non-repetitive tasks. The findings suggested that the propagation of musculoskeletal fatigue can be detected using the multi-modal composite fatigue index in complex tasks. The resultant CFI function was then applied to surgery tasks to differentiate the fatigued and non-fatigued groups. The findings showed that the multi-modal fatigue assessment techniques could be utilized to incorporate the muscular and postural measurements to identify fatigue in complex tasks beyond single-modality assessment approaches.