Objective
The purpose of this study was to develop an approach to predict hand posture (pinch versus grip) and grasp force using forearm surface electromyography (sEMG) and artificial neural networks ...(ANNs) during tasks that varied repetition rate and duty cycle.
Background
Prior studies have used electromyography with machine learning models to predict grip force but relatively few studies have assessed whether both hand posture and force can be predicted, particularly at varying levels of duty cycle and repetition rate.
Method
Fourteen individuals participated in this experiment. sEMG data for five forearm muscles and force output data were collected. Calibration data (25, 50, 75, 100% of maximum voluntary contraction (MVC)) were used to train ANN models to predict hand posture (pinch versus grip) and force magnitude while performing tasks that varied load, repetition rate, and duty cycle.
Results
Across all participants, overall hand posture prediction accuracy was 79% (0.79 ± .08), whereas overall hand force prediction accuracy was 73% (0.73 ± .09). Accuracy ranged between 0.65 and 0.93 based on varying repetition rate and duty cycle.
Conclusion
Hand posture and force prediction were possible using sEMG and ANNs, though there were important differences in the accuracy of predictions based on task characteristics including duty cycle and repetition rate.
Application
The results of this study could be applied to the development of a dosimeter used for distal upper extremity biomechanical exposure measurement, risk assessment, job (re)design, and return to work programs.
BackgroundAlthough recent studies have identified important risk factors associated with incident carpal tunnel syndrome (CTS), risk factors associated with its severity have not been well ...explored.ObjectiveTo examine the associations between personal, workplace psychosocial and biomechanical factors and incident work disability among workers with CTS.MethodsBetween 2001 and 2010 five research groups conducted coordinated prospective studies of CTS and related work disability among US workers from various industries. Workers with prevalent or incident CTS (N=372) were followed for up to 6.4 years. Incident work disability was measured as: (1) change in work pace or work quality, (2) lost time or (3) job change following the development of CTS. Psychosocial factors were assessed by questionnaire. Biomechanical exposures were assessed by observation and measurements and included force, repetition, duty cycle and posture. HRs were estimated using Cox models.ResultsDisability incidence rates per 100 person-years were 33.2 for changes in work pace or quality, 16.3 for lost time and 20.0 for job change. There was a near doubling of risk for job change among those in the upper tertile of the Hand Activity Level Scale (HR 2.17; 95% CI 1.17 to 4.01), total repetition rate (HR 1.75; 95% CI 1.02 to 3.02), % time spent in all hand exertions (HR 2.20; 95% CI 1.21 to 4.01) and a sixfold increase for high job strain. Sensitivity analyses indicated attenuation due to inclusion of the prevalent CTS cases.ConclusionPersonal, biomechanical and psychosocial job factors predicted CTS-related disability. Results suggest that prevention of severe disability requires a reduction of both biomechanical and organisational work stressors.
Seat pitch, defined as the distance from a point on the back of one seat to the same point on the seat in front, is one of the most important factors influencing aircraft seating comfort. This study ...assessed the influence of different airline seat pitches on subjective ratings of discomfort and body-seat interface contact pressures. This was a laboratory within-subjects study using an aircraft interior mock up to vary seat pitch. Twelve participants completed 1 h of sitting in each of five different seat pitches (28inches, 30inches, 32inches, 34inches, and 36inches). Interface pressure mats measured seat and backrest pressure distribution, subjective rating scales were used to measure overall and local body region discomfort. The results showed that overall body and local body region discomfort ratings tend to be lower when the seat pitch increased from 28 inches to 36 inches (p < 0.05). For pressure variables, the upper back average contact area, upper/lower back average contact pressure, upper/lower back average peak contact pressure, right buttock average contact area, left/right thigh buttock average peak contact pressure, and left buttock average peak contact pressure were significantly affected by seat pitch(p < 0.05). Separate analyses support that seat pitch was more strongly correlated with backrest interface pressure than with seat pan pressure. In conclusion, seat pitch was found to be an important factor associated with body-seat contact pressure and discomfort ratings.
•12 participants completed short-term sessions in five different seat pitches (28inches, 30inches, 32inches, 34inches, and 36inches) in an aircraft cabin mock-up.•There was significant (p < 0.05) interaction effect of seat pitch condition on overall rating and local body part ratings.•Backrest average contact pressure, backrest peak pressure, and backrest average peak contact pressure were significantly affected by the seat condition.•There were 23 pressure variables significantly correlated either with overall or local body comfort ratings.
Two computer vision algorithms were developed to automatically estimate exertion time, duty cycle (DC) and hand activity level (HAL) from videos of workers performing 50 industrial tasks. The average ...DC difference between manual frame-by-frame analysis and the computer vision DC was −5.8% for the Decision Tree (DT) algorithm, and 1.4% for the Feature Vector Training (FVT) algorithm. The average HAL difference was 0.5 for the DT algorithm and 0.3 for the FVT algorithm. A sensitivity analysis, conducted to examine the influence that deviations in DC have on HAL, found it remained unaffected when DC error was less than 5%. Thus, a DC error less than 10% will impact HAL less than 0.5 HAL, which is negligible. Automatic computer vision HAL estimates were therefore comparable to manual frame-by-frame estimates.
Practitioner Summary: Computer vision was used to automatically estimate exertion time, duty cycle and hand activity level from videos of workers performing industrial tasks.
Work-related musculoskeletal injuries and disorders remain an important problem in the construction industry. Exoskeletons are an emerging wearable technology that assists or augments a user's ...physical activity or capacity. This technology is a potential solution to reduce the physical demands and fatigue experienced by construction workers and help improve worker safety, health, and performance. As a first step towards enabling exoskeleton use in construction, we captured the perspectives of construction industry stakeholders regarding adopting exoskeletons and continued use in practice. Stakeholder responses highlighted several important questions and concerns, which were grouped using qualitative content analysis into three categories: (1) expected benefits, (2) exoskeleton technology adoption factors, and (3) perceived barriers to use. Uncertainties were expressed about the practical value and usability of exoskeleton technologies, and the impact of this technology on worker safety. Given this, and the limited state of current evidence, we summarize important research gaps that need to be addressed in future for successful adoption and use of exoskeleton technologies in the construction industry.
Objectives Most studies of carpal tunnel syndrome (CTS) incidence and prevalence among workers have been limited by small sample sizes or restricted to a small subset of jobs. We established a common ...CTS case definition and then pooled CTS prevalence and incidence data across six prospective studies of musculoskeletal outcomes to measure CTS frequency and allow better studies of etiology. Methods Six research groups collected prospective data at >50 workplaces including symptoms characteristic of CTS and electrodiagnostic studies (EDS) of the median and ulnar nerves across the dominant wrist. While study designs and the timing of data collection varied across groups, we were able to create a common CTS case definition incorporating both symptoms and EDS results from data that were collected in all studies. Results At the time of enrollment, 7.8% of 4321 subjects met our case definition and were considered prevalent cases of CTS. During 8833 person-years of follow-up, an additional 204 subjects met the CTS case definition for an overall incidence rate of 2.3 CTS cases per 100 person-years. Conclusions Both prevalent and incident CTS were common in data pooled across multiple studies and sites. The large number of incident cases in this prospective study provides adequate power for future exposure— response analyses to identify work- and non-work-related risk factors for CTS. The prospective nature allows determination of the temporal relations necessary for causal inference.
Sedentary behaviour among primary school students has been associated with unfavourable health outcomes, which have been believed to be exacerbated by distance learning during the COVID-19 pandemic. ...We present the methodology used to design and develop interventions to increase physical activity in 4th grade students using a participatory, systems approach while online learning. Preliminary formative evaluation of training has indicated a positive reception by the stakeholders. This study highlights the importance of a systems approach to engage stakeholders in the betterment of our students’ health.
Recent studies have successfully reported the accuracy of using artificial neural networks to predict grip force in controlled settings. However, only relying on accuracy to evaluate the machine ...learning models may lead to overoptimistic results, especially on imbalanced datasets. The Matthews correlation coefficient (MCC) showed an advantage in capturing all the data characteristics in the confusion matrix. Therefore, a binary classification approach and the MCC value were introduced to assess the performance of previously proposed machine learning models. Our results show that the overall correlations ranging between 0.48 and 0.59 indicate a strong relationship between predictions and actual scenarios. The binary classification approach and the MCC values could be used for future performance comparison with other machine learning models.
Few large epidemiologic studies have used rigorous case criteria, individual-level exposure measurements, and appropriate control for confounders to examine associations between workplace ...psychosocial and biomechanical factors and carpal tunnel syndrome (CTS).
Pooling data from five independent research studies, we assessed associations between prevalent CTS and personal, work psychosocial, and biomechanical factors while adjusting for confounders using multivariable logistic regression.
Prevalent CTS was associated with personal factors of older age, obesity, female sex, medical conditions, previous distal upper extremity disorders, workplace measures of peak forceful hand activity, a composite measure of force and repetition (ACGIH Threshold Limit Value for Hand Activity Level), and hand vibration.
In this cross-sectional analysis of production and service workers, CTS prevalence was associated with workplace and biomechanical factors. The findings were similar to those from a prospective analysis of the same cohort with differences that may be due to recall bias and other factors.
Background Between 2001 and 2010, five research groups conducted coordinated prospective studies of carpal tunnel syndrome (CTS) incidence among US workers from various industries and collected ...detailed subject-level exposure information with follow-up of symptoms, electrophysiological measures and job changes. Objective This analysis examined the associations between workplace biomechanical factors and incidence of dominant-hand CTS, adjusting for personal risk factors. Methods 2474 participants, without CTS or possible polyneuropathy at enrolment, were followed up to 6.5 years (5102 person-years). Individual workplace exposure measures of the dominant hand were collected for each task and included force, repetition, duty cycle and posture. Task exposures were combined across the workweek using time-weighted averaging to estimate job-level exposures. CTS case-criteria were based on symptoms and results of electrophysiological testing. HRs were estimated using Cox proportional hazard models. Results After adjustment for covariates, analyst (HR=2.17; 95% CI 1.38 to 3.43) and worker (HR=2.08; 95% CI 1.31 to 3.39) estimated peak hand force, forceful repetition rate (HR=1.84; 95% CI 1.19 to 2.86) and per cent time spent (eg, duty cycle) in forceful hand exertions (HR=2.05; 95% CI 1.34 to 3.15) were associated with increased risk of incident CTS. Associations were not observed between total hand repetition rate, per cent duration of all hand exertions, or wrist posture and incident CTS. Conclusions In this prospective multicentre study of production and service workers, measures of exposure to forceful hand exertion were associated with incident CTS after controlling for important covariates. These findings may influence the design of workplace safety programmes for preventing work-related CTS.
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