## 5 Conclusions and Further Remarks
### Future Research Topics and Challenges  
One limitation of this paper is that not many existing publications were relevant, since human-focused DT application for OSH is still an emerging research topic. Nevertheless, the number of relevant publications is increasing, and more and more applications will be studied and introduced in the future. Another limitation is that this paper focused primarily on the technological aspects of relevant applications, whereas legal and ethical issues resulting from human-focused DT applications have largely not been discussed. Based on these limitations and the survey results, this paper suggests the following future research topics and directions. The first research topic is the development of human-focused DT applications for various purposes related to OSH. While almost all existing applications concern postural risk and collisions between human workers and industrial robots, some other OSH issues can be solved by applying DT technology. Failures and accidents that can lead to illness and injury are caused by various factors such as organizational influences, supervisory factors, preconditions for unsafe acts, and unsafe acts [65]. There is a tendency to blame work personnel for accidents; however, determining the main cause of an accident is difficult [66]. Human-focused DT may thus be used to record and monitor the context of failures and accidents. Consequently, DT can also contribute to finding the main causes of accidents and reducing the blame on human workers involved in accidents. The second research topic is more simple and convenient data collection devices. With the advance in computer hardware and AI algorithms, cameras have emerged as a useful device for data collection in human-focused DT applications for OSH. State-of-the-art object detection and human motion recognition algorithms enable even low-cost webcams to be used to collect digital data on human workers, and the MoCap system and depth cameras have been widely adopted in existing applications. Human-focused DT applications could thus be implemented more quickly and conveniently if more simple data collection devices are used. Third, simulation modeling and experiments for purposes other than human motion simulation are another future research topic. Simulation is a tool for comparing the performances of a number of alternatives and for identifying the best one among them. Thus, simulation can be used to optimize a workplace such that risks are minimized. For instance, existing applications concerning HRC workplaces are typically designed to stop or slow down a robot when a collision risk is detected. This is obviously helpful for reducing the risk in a workplace; however, frequently stopping or slowing down a robot can decrease job efficiency and productivity. In this case, simulation can be used to find the optimal facility layout or motion path so that risks are minimized while maintaining job efficiency and productivity. Finally, some researchers might be interested in legal and ethical issues. Both employers and employees can regard human-focused DT applications that collect digital data from human workers as a means for monitoring human workers. On the one hand, human-focused DT applications might lead to the creation of novel people analytics, which would aim to evaluate human workers' behaviors and performances in a comprehensive manner. On the other hand, those applications can cause sensitive issues. For instance, the fact that digital data are being collected raises concerns for some human workers because they feel that their employers or supervisors are watching their every move, which can intensify work stress and can erode worker autonomy. In this case, should managers inform workers of what kinds of data are collected? Is data collection without worker consent illegal? How can employers mitigate the resistance of human workers to data collection? Some digital data, such as videos recorded during work, contain personal identifiable information.