In this article, we develop and meta-analytically test the relationship between job demands and resources and burnout, engagement, and safety outcomes in the workplace. In a meta-analysis of 203 independent samples (N = 186,440), we found support for a health impairment process and for a motivational process as mechanisms through which job demands and resources relate to safety outcomes. In particular, we found that job demands such as risks and hazards and complexity impair employees' health and positively relate to burnout. Likewise, we found support for job resources such as knowledge, autonomy, and a supportive environment motivating employees and positively relating to engagement. Job demands were found to hinder an employee with a negative relationship to engagement, whereas job resources were found to negatively relate to burnout. Finally, we found that burnout was negatively related to working safely but that engagement motivated employees and was positively related to working safely. Across industries, risks and hazards was the most consistent job demand and a supportive environment was the most consistent job resource in terms of explaining variance in burnout, engagement, and safety outcomes. The type of job demand that explained the most variance differed by industry, whereas a supportive environment remained consistent in explaining the most variance in all industries.

Safety at work: a meta-analytic investigation of the link between job demands, job resources, burnout, engagement, and safety outcomes

Recent conceptual and methodological advances in behavioral safety research afford an opportunity to integrate past and recent research findings. Building on theoretical models of worker performance and work climate, this study quantitatively integrates the safety literature by meta-analytically examining person- and situation-based antecedents of safety performance behaviors and safety outcomes (i.e., accidents and injuries). As anticipated, safety knowledge and safety motivation were most strongly related to safety performance behaviors, closely followed by psychological safety climate and group safety climate. With regard to accidents and injuries, however, group safety climate had the strongest association. In addition, tests of a meta-analytic path model provided support for the theoretical model that guided this overall investigation. The implications of these findings for advancing the study and management of workplace safety are discussed.

Workplace safety: a meta-analysis of the roles of person and situation factors.

Published version made available following 12 month embargo from the date of publication [12 Feb 2015] according to publisher policy. Accessed 10/03/2015. Published version available from 13 February 2016.

/pdf/virtual-reality-for-stroke-rehabilitation-4evwp7ler3.pdf

Virtual reality for stroke rehabilitation

Experiments in hearing

In this paper, we review the state-of-the-art technologies for driver inattention monitoring, which can be classified into the following two main categories: 1) distraction and 2) fatigue. Driver inattention is a major factor in most traffic accidents. Research and development has actively been carried out for decades, with the goal of precisely determining the drivers' state of mind. In this paper, we summarize these approaches by dividing them into the following five different types of measures: 1) subjective report measures; 2) driver biological measures; 3) driver physical measures; 4) driving performance measures; and 5) hybrid measures. Among these approaches, subjective report measures and driver biological measures are not suitable under real driving conditions but could serve as some rough ground-truth indicators. The hybrid measures are believed to give more reliable solutions compared with single driver physical measures or driving performance measures, because the hybrid measures minimize the number of false alarms and maintain a high recognition rate, which promote the acceptance of the system. We also discuss some nonlinear modeling techniques commonly used in the literature.

Driver Inattention Monitoring System for Intelligent Vehicles: A Review

Biomedical signal monitoring systems have been rapidly advanced with electronic and information technologies in recent years. However, most of the existing physiological signal monitoring systems can only record the signals without the capability of automatic analysis. In this paper, we proposed a novel brain-computer interface (BCI) system that can acquire and analyze electroencephalogram (EEG) signals in real-time to monitor human physiological as well as cognitive states, and, in turn, provide warning signals to the users when needed. The BCI system consists of a four-channel biosignal acquisition/amplification module, a wireless transmission module, a dual-core signal processing unit, and a host system for display and storage. The embedded dual-core processing system with multitask scheduling capability was proposed to acquire and process the input EEG signals in real time. In addition, the wireless transmission module, which eliminates the inconvenience of wiring, can be switched between radio frequency (RF) and Bluetooth according to the transmission distance. Finally, the real-time EEG-based drowsiness monitoring and warning algorithms were implemented and integrated into the system to close the loop of the BCI system. The practical online testing demonstrates the feasibility of using the proposed system with the ability of real-time processing, automatic analysis, and online warning feedback in real-world operation and living environments.

https://ir.nctu.edu.tw:443/bitstream/11536/9373/1/000255148600013.pdf

Development of Wireless Brain Computer Interface With Embedded Multitask Scheduling and its Application on Real-Time Driver's Drowsiness Detection and Warning

https://ir.nctu.edu.tw:443/bitstream/11536/14294/1/000253346500004.pdf

A cross-cultural study of organizational factors on safety: Japanese vs. Taiwanese oil refinery plants

This paper presents a fuzzy CBR (case-based reasoning) technique for generating new product ideas from a product database for enhancing the functions of a given product (called the baseline product). In the database, a product is modeled by a 100-attribute vector, 87 of which are used to model the use-scenario and 13 are used to describe the manufacturing/recycling features. Based on the use-scenario attributes and their relative weights - determined by a fuzzy AHP technique, a fuzzy CBR retrieving mechanism is developed to retrieve product-ideas that tend to enhance the functions of the baseline product. Based on the manufacturing/recycling features, a fuzzy CBR mechanism is developed to screen the retrieved product ideas in order to obtain a higher ratio of valuable product ideas. Experiments indicate that the retrieving-and-filtering mechanism outperforms the prior retrieving-only mechanism in terms of generating a higher ratio of valuable product ideas.

https://ir.nctu.edu.tw:443/bitstream/11536/9848/1/000250295300053.pdf

A fuzzy CBR technique for generating product ideas

This paper presents an approach to facilitate the generation of new product ideas. In this approach, a product is represented by a vector, which involves a number of product attributes. These attributes are defined based on the user-centered design (UCD) paradigm. That is, the context of use and interactions with users for the product is described by these attributes. By the product representation, a product database can be established. For a benchmarking product, we use the case-based reasoning (CBR) technique to retrieve those products, which are “sufficiently relevant” to the benchmarking one, from the database. The functions of the retrieved products are the candidate new ideas to be added on the benchmarking product. These retrieved products are screened manually to identify creative and valuable ideas. A prototype system of this approach has been implemented. Experiments show that the proposed approach outperforms the brainstorming technique, which has been widely used in industry.

https://ir.nctu.edu.tw:443/bitstream/11536/11964/1/000239392800021.pdf

A case-based reasoning approach to generating new product ideas

Organizational theorists have recently begun to pay research attention to the workforces of emerging countries in Asia, especially the greater China regions. However, little research has focused on the influence of organizational factors on safety in these countries. This study hypothesized that organizational factors, characterized as safety leadership perspective (management commitment, blame culture) and safety climate perspective (harmonious relationships), would influence group-level safety management, which would in turn influence individual level safety awareness and practices. To test this hypothesis, a safety climate questionnaire was distributed to ten Taiwanese plants in high-risk industries. Structural equation modeling (SEM) was used to analyze the linkages among organizational level factors, work-group-level factors, and workers’ safety awareness and practices. We found that safety leadership style and organizational harmony in Taiwanese high-risk industries can exert significant influences on work-group processes, which in turn have greater effects on individual safety awareness and practices. These findings and implications can serve as a basis for safety improvement in areas of the greater China region.

https://ir.nctu.edu.tw:443/bitstream/11536/32255/1/000283029000010.pdf

Shang Hwa Hsu

Papers

Development of Wireless Brain Computer Interface With Embedded Multitask Scheduling and its Application on Real-Time Driver's Drowsiness Detection and Warning

A cross-cultural study of organizational factors on safety: Japanese vs. Taiwanese oil refinery plants

A fuzzy CBR technique for generating product ideas

A case-based reasoning approach to generating new product ideas

The influence of organizational factors on safety in Taiwanese high-risk industries