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Presents a special methodological approach to the study of stress and strain at work, in order to reduce excessive workload by allowing extra time for the operation. In the study three methods were used: activity sampling; job analysis and evaluation; and measurement of workplace conditions. Also, a method was used which gives criteria and grades for research and evaluation of stresses at the workplace. These are physical stress (dynamical and statical); thermal; visual; noise stress; stress caused by contact with aerosols; gases; vapours; stress caused by monotony. They are measured as ecological, physiological and comfort indexes. It is clear that stress factors enable the evaluation of most physical work. The application scope for our model of defining the ergonomic coefficient was the clothing industry. The defined ergonomic coefficient represents a smaller addition to standard time than the strain and the environmental coefficients used at present.

The purpose of this paper is to investigate physiological indices related to comfort and health condition, based on which corresponding electronic equipment are selected and applied. A wearable monitoring system using sensor and liquid crystal display (LCD) techniques are then designed. Sensors are used to collect and transmit recording required signals from the wearer. A microcomputer with the type of AT89C52 is used to record and analyze the collected data. LCD is applied to display the health and comfort condition of the wearer.

A novel wearable monitoring system for the measurement of physiological indices and clothing microclimate is proposed in this study in order to monitoring both health and comfort condition of the wearer.

The proposed system provides reference for the application of sensor and display technologies in the field of smart clothing, which can be further applied to infant and child care, health care, home entertainment, military and industry.

This paper, first, investigated a framework of a wearable monitoring system considering both comfort and health condition and summarized the related physiological indices. The requirements of both comfort and health condition monitoring are analyzed to select appropriate electronic elements.

The purpose of this paper was to investigate the physiological cost of concrete construction activities.

Five concrete construction workers were recruited. The workers’ three-week heart rate (HR) data were collected in summer and autumn. In this paper, several HR indexes were used to investigate the physiological cost of work in concrete construction trades, including average working HR, relative HR and ratio of working HR to resting HR.

This paper measures how absolute and relative HRs vary throughout a workday and how working HR compares to resting HR for individual workers.

Field observations are usually extremely difficult as researchers need to overcome a number of barriers, including employers’ resistance to perceived additional liabilities, employees’ fear that their level of activity will be reported to managers and many other practical and technical difficulties. As these challenges increase exponentially with the number of employers, subjects and sites, this study was limited to a small number of subjects all working for the same employer on the same jobsite. Still, challenges are often unpredictable and lessons learned from this study are expected to guide both our and other researchers’ continuation of this work.

The time effect on the physiological cost of work has not been considered in previous studies. Thus, this study is noteworthy owing to the depth of the data collected rather than the breadth of the data.

The purpose of this study was to identify the role of two kinds of leisure activities (i.e. casual and serious leisure) in reducing psychological and physiological stresses and, specifically, to investigate the differences between pre- and post-psychological and physiological stresses.

The data analyses were conducted using the Statistical Package for the Social Sciences 20.0 program. Descriptive analyses were calculated to identify the characteristics of the sample, including gender, education and age. Because of the small sample size (n < 30), this study uses a nonparametric test. The Wilcoxon signed-rank test was used to examine the differences between pre- and post-stresses of psychological and physiological approaches. The Mann-Whitney U test was used to examine the differences of stresses between the casual and serious leisure groups. In addition, the Kendall rank correlation coefficient was used to measure the association between leisure experiences and stresses.

The findings from this study indicated that pre-overall affective stress was significantly higher than post-overall affective stress. There were significant differences between pre- and post-physiological stresses during serious leisure. Research findings also suggested that serious leisure experiences have a significant and negative relationship with cognitive stress and physiological stress.

The data were obtained from two different types of leisure setting, and hence, the generalizability of the study findings to other regions needs to be explored in future studies. Research across other leisure settings also might permit the validation of more stable relationships between leisure and stresses. Future research is needed to investigate other important antecedents of individuals’ psychological and physiological stresses in the leisure setting and may identify the complex nature of leisure participants’ perceptions and their relationships with experiences.

Despite the growth of stress and leisure research, physiological-based analyses in this area are limited. Numerous studies have focused on leisure coping with negative life events based on social psychological perspectives. The finding of this study would be helpful to leisure practitioners to manifest the strengths and opportunities of experiences and performances associated with the leisure activity.

Understanding how health status and physiological factors affect performance is a daunting task. This chapter will discuss physiological, behavioral, and psychological factors that influence or determine the capacity to fight, and will consider metrics that can be used to measure their status. The premise of this discussion is that there is a set of physiological and psychological factors that intimately affect performance and that the relative contribution of these variables is individually unique. These factors can be identified and assessed, and are amenable to modification. A fuller understanding of these variables can lead the effort to maintain and improve performance in the adverse and challenging environments of military operations.

Heat stress, having caused preventable and lamentable deaths, is hazardous to construction workers in the hot and humid summers of Hong Kong. The purpose of this paper is to develop a heat stress model, based on the Wet Bulb Globe Temperature (WBGT) index.

Field studies were conducted during the summer time in Hong Kong (July to September 2010). Based upon 281 sets of synchronized meteorological and physiological data collected from construction workers in four different construction sites between July and September 2010, physiological, work‐related, environmental and personal parameters were measured to construct and verify the heat stress model.

It is found that drinking habit, age and work duration are the top three significant predictors to determine construction workers' physiological responses. Other predictors include percentage of body fat, resting heart rate, air pollution index, WBGT, smoking habit, energy consumption, and respiratory exchange rate. The accuracy of the model is verified against data which have not been used in developing the model. The accuracy of the heat stress model is found to be statistically acceptable (Mean Absolute Percentage Error=5.6 percent, Theil's U inequality coefficients=0.003).

Based on these findings, appropriate work‐rest pattern can be designed to safeguard the well being of workers when working in a hot and humid environment.

The model reported in this paper provides a more scientific and reliable prediction of the reality which may benefit the industry to produce solid guidelines for working in hot weather.

The purpose of this paper is to test the attenuated-anger and heightened-anger hypotheses of psychopathy by assessing the physiological, behavioral, and subjective measures of anger in individuals with and without psychopathic traits.

In all, 62 male college students were assigned to one of three groups based on evidence of elevated affective-interpersonal (Factor 1) and antisocial lifestyle (Factor 2) traits associated with psychopathy (the IF1+F2 group), evidence of only Factor 2 traits (the F2 only group), or based on the absence of psychopathic traits (the control group), using Gough’s (1957) Socialization scale and a modified, interview only form of Hare’s (1991) Psychopathy Checklist-Revised. To induce anger, participants received unjust criticism about their performance on a computer-based affective lexical decision task and were denied a performance bonus they had reason to expect.

Following provocation, the three groups displayed similar increases in blood pressure, pulse, and self-reported anger. The control and IF1+F2 groups also displayed similar retaliation toward the confederate. However, the IF1+F2 group displayed smaller increases on two of three measures of facial muscle activity associated with anger.

This study is one of the first to assess anger responsiveness in individuals with psychopathic traits using a powerful anger induction and using physiological, behavioral, and subjective indices of anger. It is also the first to assess both the attenuated-anger and the heightened-anger hypotheses of psychopathy. The findings appear largely inconsistent with both perspectives.

The Guilty Knowledge Test (GKT) is a psychophysiological questioning technique that can be used as part of a polygraph examination which purports to assess whether suspects conceal “guilty knowledge” by measuring their physiological responses while responding to a series of multiple choice questions. The present study sets out to consider a number of key issues in relation to the GKT paradigm. Specifically, the following questions were considered: Does response mode matter? Does motivation influence outcome? Are combined physiological measures better than single ones? Does gender have an effect on physiological responsivity during a polygraph examination? Results demonstrated real variations between the physiological measures used. Gender differences were also observed in polygraph response patterns. These findings are discussed in relation to the validity of the Guilty Knowledge Test.

The purpose of this paper is to provide an overview of the human factors/ergonomics (HFE) studies for respirator.

This review paper describes and discusses the various factors and methodologies of HFE, for the purpose of better considering human factors, used in respirator studies and further human-centered product development.

Many attempts have been made to study human factors for respirators mainly including fit, human performance, comfort, and mood. Physical, psychological, and physiological indices of people are extremely valuable to HFE studies for respirator. Objective and subjective measures were methodologies widely used. Quantitative and qualitative approaches were adopted to illustrate the human performance and well-being influenced by respirators. A summary table presented with major methods used for indices of respirators in the field of HFE. According to the current researches, this review indicated three particular challenges facing HFE studies of respirators now.

With the ever increasing role of protection from air pollution in society, respirator has become an increasingly important part of our daily lives. HFE intervene in optimizing the relationships between respirators and the human using them. Plenty of efforts have been dedicated for the development of protection capability, but HFE studies for respirators are lacking. In recent years, there has been a tremendous interest in introducing HFE research methods that can evaluate respirators from the perspective of human and translate them into constraints for designing human-centered respirators.

This is a first paper in the field of HFE studies for respirator, which will remain helpful to the scientific community to start further human-centered research work and product development.

As drones are rapidly transforming tasks such as mapping and surveying, safety inspection and progress monitoring, human operators continue to play a critical role in ensuring safe drone missions in compliance with safety regulations and standard operating procedures. Research shows that operator's stress and fatigue are leading causes of drone accidents. Building upon the authors’ past work, this study presents a systematic approach to predicting impending drone accidents using data that capture the drone operator's physiological state preceding the accident.

The authors collect physiological data from 25 participants in real-world and virtual reality flight experiments to design a feedforward neural network (FNN) with back propagation. Four time series signals, namely electrodermal activity (EDA), skin temperature (ST), electrocardiogram (ECG) and heart rate (HR), are selected, filtered for noise and used to extract 92 time- and frequency-domain features. The FNN is trained with data from a window of length t = 3…8 s to predict accidents in the next p = 3…8 s.

Analysis of model performance in all 36 combinations of analysis window (t) and prediction horizon (p) combinations reveals that the FNN trained with 8 s of physiological signal (i.e. t = 8) to predict drone accidents in the next 6 s (i.e. p = 6) achieved the highest F1-score of 0.81 and AP of 0.71 after feature selection and data balancing.

The safety and integrity of collaborative human–machine systems (e.g. remotely operated drones) rely on not only the attributes of the human operator or the machinery but also how one perceives the other and adopts to the evolving nature of the operational environment. This study is a first systematic attempt at objective prediction of potential drone accident events from operator's physiological data in (near-) real time. Findings will lay the foundation for creating automated intervention systems for drone operations, ultimately leading to safer jobsites.