With the completion of this thesis, the research’s constraints should be overcome in the future. Furthermore, throughout this thesis, certain new questions emerge that deserve further investigation. Following are some concepts that should be investigated more in the future.
7.5.1 Research Extension
A bigger study sample with more variety in demographic trait scores is required to con-firm the feasibility of this technique. Our current study was based on a small sample of automotive sector workers, which may have resulted in data that was shortened (i.e. with few extreme scores in the traits scales). The findings of this study suggest that person-ality will improve with larger data sets and practical health decision-making scenarios.
Additional factors can be measured and calculated to supplement the postural analysis.
Weight and tool vibration are two characteristics that could be investigated in production environments. As an example, these two feature were impelemented in experiment5.
NLP ML-NLP
(AI)
Human-centered eXplanaible AI
(HCXAI)
HCXAI Recommendation
Industrial microErgo Risk
Assessment
Figure 7.1: Overall view of project
Figure7.1shows the overall prospective of this study. The last green part is mainly in future work. For example, having the new patients can integrate in theHCXAI. Col-laborative filtering and content-base recommendors are the methods to predict injuries for new workers withoutMRs.
7.5.1.1 Other XAI Methods
Six ofMLmodels were created as a result of the effort. These were grouped by data set and demographic feature, and the one with the highest accuracy was chosen, regardless of the model’s inherent algorithm. When the interpretability of the results is complicated, a threshold between the complexity of the model algorithm and the end accuracy should be considered, even if the accuracy is slightly worsened, rather than selecting the model based on its error. As a result, alternativeXAI, such as Lime, can be used.
7.5.1.2 Aid in the Making of Medical Decisions
Research that links expert physicians’ decision-making styles to the next injured body part(s) that should be operated on, in order to aid and guide non-experienced physicians with the optimal method for solving multi-side pain based on their occupational profile.
7.5.1.3 Beyond Individual, Organizational and Work-related Factors
Only organizational, individual, and work-related features are examined in the produced work, and the results are always compared to those of medical appointment workers.
Given that an individual trait is a stable characteristic of an individual that explains how that individual typically behaves, a long-term experiment should be conducted to determine which measures of behavior are truly related to the individual trait and if they are not simply influenced by the individual’s state. The state is a transient state that is linked to one’s mood and is thus only felt for a brief time. The condition reflects how the worker is feeling at the time, but the feature reflects who he or she is. Theorists have just recently decided on a description of OHPPs, and even if the FWAstatues of employees have strong internal consistency, the responses could be influenced by the subjective interpretation of the multi-side body regions injuries. Taking this into account, one strategy that could be used is to group workers according on their human behavior using transformers approaches. Psychologists may draw certain inferences about the qualities of individuals based on how they react after analyzing the characteristics of each group.
7.5.2 Future implications
Using theRL(utility-based) based on the recommendation system to give the microErgo recommendation risk assessment. This industrial microErgo integrates with job rotation by team leaders ([128]). Figure7.1shows overall perspective of the project demonstrates
the overall prospective of this thesis and the last blue part is mainly for future work.
For example, a strategy based on RLthe can be created on an online dashboard. This dashboard can track the workers’ industrial microergo recommendations by providing motion variables such as signals in order to evaluate the ergonomic recommendation score based on each worker’s health history and medical appointment.
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