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Introduction and aim: Electrocardiography is one of the most useful and common tools for examining heart function. In studies in the 1960s, heart rate variability (HRV) was introduced and used as a non-invasive tool to evaluate the functions of the autonomic nervous system and other functional disorders of the heart under various conditions. In addition to the clinical applications of heart rate variability, this physiological parameter is also widely used in ergonomics and occupational health. In the study of mental workload, exposure to industrial noise, shift work, stress, and other parameters related to the workplace benefit heart rate variability. Heart rate variability is regulated by the autonomic nervous system and by the sinoatrial (SA) node. The autonomic nervous system is divided into sympathetic and parasympathetic branches, the autonomic nervous system is divided into sympathetic and parasympathetic branches, thereby affecting the heart rate and heart rate variability. Sympathetic activity tends to increase heart rate and decrease heart rate variability, while parasympathetic tend to reduce heart rate and increase heart rate variability. The most prominent component of the variable heart rate period is a respiratory arrhythmia (RSA), which is considered to be 0.15 to 0.4 Hz. The high-frequency component is only affected by parasympathetic neural activity. Another component of heart rate variability is the low-frequency (LF) component in the frequency range, 0.04 to 0.15 Hz. This component is affected by sympathetic and parasympathetic neural activity. Many computational methods have been developed for HRV analysis, each of which is associated with strengths and weaknesses. Although there may still be difficulties in interpreting this index, it provides researchers and health experts with reliable non-invasive physiological information. HRV parameters can be classified in terms of time, frequency, and nonlinear methods. The commercially available ECG equipment does not usually include HRV features due to the lack of standard diagnostic protocols. As an alternative to this commercial software, many simple, online and free, device-independent, and portable software has been developed for HRV analysis and cardiovascular research. Heart Rate Variability Quantification: Heart rate variability can be measured in long-term (24 hours), short-term (5 minutes), and very short-term periods (less than 5 minutes) and can be analyzed as time- -domain, frequency-domain, and non-linear. 1. Time-domain measures The simplest method to analyze heart rate variability is time-domain. Analysis of heart rate variability in the time-domain is performed through both statistical and geometric analysis, both of which are based on heart rate or RR intervals between successive QRS series. Using these methods, the heart rate can be assessed at any point in time or between normal consecutive sets. Statistical parameters recommended by the European Society of Cardiology and the American Society of Pacing Electrophysiology include: 1) SDNN 2) NN50 3) SDSD 4) SDANN 5) RMSSD 6) SDSD 7) NN50 count (Table 1). Table 1: time-domain measures of HRV Variable Units Description [1]SDNN ms Standard deviation of all NN intervals SDRR[2] ms standard deviation of RR interval series SDANN ms Standard deviation of the averages of NN intervals in all 5 min segments of the entire recording SDNN index ms Mean of the standard deviations of all NN intervals for all 5 min segments of the entire recording pNN50 % NN50 count divided by the total number of all NN intervals HR Max –HR Min bmp The average difference between the highest and lowest HRs during each respiratory cycle rMSSD ms Root mean square of successive RR interval difference HRV triangular index Integral of the density of the RR interval histogram divided by its height TINN ms Baseline width of the RR interval histogram 2. Frequency-domain measures: Time-domain measurements information about the overall change in time series or maximum variable amplitude, but no information about periodic heart rate fluctuations. Data frequency domain analysis provides information on how power distribution is a function of frequency. According to the European Society of Cardiology, the power range of a healthy person is usually divided into four main frequency bands. The range of components used is usually: high-frequency (0.4 - 0.15 Hz), low-frequency (0.15-0.04 Hz), very low frequency (0.04 - 0.003 Hz) and infinitely low frequency (

Abstract: Background and aims: Performance assessment and also performance indicators have a great importance in all aspects of life. By these indicators appropriate responses to what is happening for make some improvement, could be determined. In the past, the safety and health performance of organizations was measured with using of some indicators from the USA Occupational Health and Safety Administration (OSHA) such as the rate of recorded injuries, the rate of lost days, the rate of workerschr('39') complaints, and so on. Determining of this information were done to compare the health and safety status of contractors and industries and ranking them. However, improvement or weakening the safety and health status is cleared by the OSHA indicators, but the ways were not determined by these indicators. The main objective of measuring safety and health performance is to provide the necessary information on the developments and current status of strategies, processes and activities that an organization is conducting to control health and safety risks. Safety performance indicators are divided into two main categories: the leading and the lagging indicators. The leading indicators are the organizationchr('39')s actions for predicting and preventing incidents and accidents before they occur, while the lagging indicators are shown the organizationchr('39')s performance after the occurrence of the accidents to reduce its consequences. Sustainable urban development is a high-profile goal, and its realization in metropolitan areas requires the use of efficient management practices and extensive planning. The extent and complexity of urban issues and the urban ever- increasing development have made urban management a difficult task. In addition to issues such as transportation, urban planning and management is one of the important factors that has a main influence on urban constructive factors. In organizations such as the municipality, and on a wider dimension in societies, various plans and policies such as environmental plans, safety plans, crisis management, educational policies, occupational health plans, as well as some international standards for sustainable urban development were used. The Integrated Health, Safety and Environment Management System (HSE-MS), by providing the appropriate structure and model, manages all these policies and plans, and, in addition to creating a specific order in the implementation of these programs helps to centralize costs and improve the economic status of the organization and the achievement of sustainable urban development. Performance measurement is the main issue at all levels of the organization and its improvement needs to be measured, so an organization cannot be conceived without a performance evaluation system. Measuring the performance of an organization in the HSE field is a precondition for continuous improvement. Different organizations and industries need to design performance measurement indicators to assessment and monitor the performance of the HSE management system and determine the effectiveness of themselves performance. Determining the performance assessment indicators of HSE in addition to measuring of the management system performance can lead to systematic identification of improvement points and reduction of HSE related risk factors and ultimately lead to increased organizational productivity. The research shows that the applied, comprehensive and structured model has not yet been designed and implemented to ensure the efficiency and effectiveness of the HSE management system in different metropolitan areas. Although there are some retrospective and prospective HSE performance assessment indicators in municipalities but these indicators are purely result-oriented and the creation and institutionalization of processes related to the seven components of the health, safety and environmental management system cannot be measured by them. What matters here is to create an appropriate method with sufficient accuracy to determine the effectiveness of the system. This research, while introducing an innovative model for quantitative ranking of different municipality areas of metropolitans according to the HSE performance assessment with using of AHP technique, the final goal is the determine of key indicators of urban HSE performance assessment. Methods: This descriptive-applied study was conducted in four steps. Step 1: Selecting HSE Performance Measurement Indicators and Urban Management: In the first step, a variety of safety and health management systems (HSE-MS, OHSAS 18001, ISO 14001, etc.), a variety of existing national and international health and safety assessment methods, guidelines, and requirements for safety and health management systems for determining the performance measurement indicators were studied. At this step, through the field visits of the different areas of the municipality and observing work processes, interviewing and organizing various meetings with HSE managers and experts, and studying documentation, the HSE performance assessment indicators in the three areas including process-oriented, result-oriented and urban management were categorized. Step 2: Selecting the components of the performance monitoring system: The findings suggest that the use of a systematic approach in different domains, in addition to integrating activities, has improved efficiency and effectiveness and increased operational efficiency. Accordingly, many organizations have set up various health, safety and environmental management systems as the basis of themselves operations. The use of the main components of an integrated management system to identify weaknesses or strengths of system is one of the effective measures for measuring performance. At this step, after determining the assessment axes, the performance assessment components were identified for each of the performance monitoring axes. Step 3: Development of Urban HSE Performance Assessment Indicators: At this step, the indicators for assessing the performance of the urban HSE management system were determined based on the components of each of the performance monitoring axes. According to the main components, the HSE management system was included 18 components such as commitment and leadership, policy, resources, etc. Also in the urban management part 6 components including economic sustainability, social sustainability, architecture and urbanization, demographics, political, legal, and industrial was considered. Indicators related to the result performance were also developed based on the components of the HSE performance output monitoring system in the six areas including safety, health, environment, education, culture and HSE of citizenship. Step 4: Select Key Performance Indicators: To create an effective HSE-MS performance measurement method, it is necessary to reduce the number of LPIs to fewer or the most important KPIs. This means that among the existing indicators, the best and most important indicators are selected based on the considered criteria. At this step, key performance indicators were selected from the sum of the extracted indicators based on the elements of the HSE management system using the AHP method. All indicators were compared in pairs and each of them was prioritized as a number between 1-9, 1 as lowest priority and 9 as most preferred. Couple comparisons were conducted based on SMART criteria and expert’s opinion. In this study, the paired comparison of axes and performance indicators and determining the weight vector of the indicators was performed using Expert Choice11 software. Results: In addition to examining the HSE management systems deployed in the municipalities, as well as using previous studies, the axes and indicators for assessing the performance of the urban HSE management system were determined. Of the 30 components and 155 indicators of performance assessment, 18 components and 98 indicators were related to monitoring of management system of HSE based on the seven elements and sub elements of the Health, Safety and Environment Management System (HSE-MS). Performance output and urban management axes with 40 and 17 indicators, respectively, have a smaller share of the total indicators developed. Between the process-oriented performance axes, the commitment and leadership axes (0.198) and the HSE records of occupations (0.016) have the highest and lowest weight, respectively. The safety components (0.247) and training (0.150) had the highest and lowest weight in the result-oriented performance axes respectively and economic sustainability (0.301) and architecture and urban planning (0.122) had the highest and lowest weight in among the urban management functional axes respectively. After weighting the indicators for measurement of performance, 70 indicators that had the highest weight than other indicators were selected as key performance indicators. Of the 70 indicators, 47, 16 and 7 indicators are related to the HSE process, the result and urban management respectively. Between the functional sub axes of the HSE process, accident management, inspection, and audit each with five key performance indicators, has the highest measurement index compared to other HSE process sub axes. In the functional axis of the HSE result, the sub axes of ecology with 4 key performance indicators and the sub-axes of safety and health, each with 3 indicators, had the highest number of indicators in this axis. In the urban management axis, sub axes including the socio-cultural and architecture and urbanism axes, each with two key performance indicators, had 4 indicators of total 70 selected key performance indicators. Conclusion: The results of this study indicate that the determination of HSE performance indicators in addition to the components of the HSE management system should be done based on the type of macro management structure and other influential parameters of the organization. The study of the municipals management structure shows that the extracted indicators based on the components of the HSE management system alone cannot cover the urban HSE performance because of factors such as economic sustainability, socio-cultural, demographic, architectural, urban, and industrial-industrial can significantly affect the performance status of the HSE management system of city. Therefore, it is essential to design and codification of indicators as a tool for measuring the performance of management systems, all aspects of the management system in order to achieve the more accuracy and reliability be considered.

Cognitive activities and the operation of tasks in the workplaces lead to the creation of a cognitive workload and specifically mental workload employee in the work environment. In order to measure these cognitive variables, physiological parameters are used. Electroencephalography is a non-invasive and relatively inexpensive method that can be used to evaluate neurophysiology and cognitive functions. Electroencephalography the electrical activity records a large number of brain neurons on the surface of the skull or the brain. The purpose of this article is to provide generalizations of imaging methods in neuroergonomic, brain wave bases, equipment and requirements for participants. It also describes the brainwave recording protocol step by step. Due to the expansion of interdisciplinary studies, the acquisition of brainwave recording skills is essential for researchers in the field of ergonomics and occupational health

Background and aims: The safety and health performance measurement, designed to provide the necessary information on the concern to progress and the current state of the organizationchr('39')s strategies, processes and activities. The purpose of this study is to present a new model for the development of safety performance indicators using the probability risk assessment model and applying expertschr('39') opinions. Methods: This descriptive-analytic study was carried out in 3 steps: categorize of the construction face activities and its related hazards identification; formation of the accident causal network occurred in the oil and gas refinery construction phase using the Bayesian network and the selection of key performance indicators using AHP method. Results: The statistical analysis of the recorded accidents showed that 21% of the incidence rate is related to the falling. Among all the construction phase activities, using the WBS analysis of the project, 27 activities with work at height risk of were identified. 18 active performance indicators were extracted the accident causal network that using SMART criteria and occurrence probability rate Calculated from the Bayesian network was selected as 5 active key performance indicators. Conclusion: Determining the leading performance indicators is influenced by various organizational, managerial, operational and other factors. As the project progresses, the nature and level of risk of the operation of construction projects is changing. Therefore, indicators of safety performance measurements in these projects should be sensitive to rapid changes. For this reason, active indicators with a short-term measurement period are more effective in measuring the safety performance of construction operations.

Background and aims: One of the most important and preventable hazard related to Healthcare Workers (HCWs) are Needle Stick Injuries (NSI). Biologic outcomes of these injuries can be so hazardous and can cause to transmission of disease such as AIDS, Hepatitis B and C. The aim of this study was determination of occupational exposure to needle stick and its risk factors in one of Sabzevar’s hospital. Methods: This is a cross sectional study on HCWs that by the help of related questionnaire, rate and characteristics of exposure of healthcare personnel was determined. Sampling method was in form of consensus and finally collected data with the help of STATA software and using descriptive and chi-square test were analyzed. Result: Occupational exposure to needle stick among participated HCWs with at least one injury in 12 months before study was close to 32.99%. Among the different variables that might have influenced on the needle stick injuries only training, education level and work experience had significant relationship. (p= 0.001, 0.009,0.009). About organizational factors, the result showed there is a good guideline for reporting injuries and about 79% of employees said they are familiar with how to report. In the case of cause of needle stick injuries, carelessness and high work load pressure were the most frequent respectively.(40.68, 38.98). Conclusion: regarding to high rate of needle stick injurie, its a very serious threat for health care workers to suffer from infectious diseases.detailed inspection in order to achieve to hidden causes and providing control solution for hazardous factors can help managers in improving the level of health and safety in health care system.