Wearable Biosensors to Understand Construction Workers' Mental and Physical Stress

Occupational stress is defined as harmful physical and mental responses when job requirements are greater than a worker's capacity. Construction is one of the most stressful occupations because it involves physiologically and psychologically demanding tasks performed in a hazardous environment this stress can jeopardize construction safety, health, and productivity. Various instruments, such as surveys and interviews, have been used for measuring workers’ perceived mental and physical stress. However valuable, such instruments are limited by their invasiveness, which prevents them from being used for continuous stress monitoring. The recent advancement of wearable biosensors has opened a new door toward the non-invasive collection of a field worker’s physiological signals that can be used to assess their mental and physical status. Despite these advancements, challenges remain: acquiring physiological signals from wearable biosensors can be easily contaminated from diverse sources of signal noise. Further, the potential of these devices to assess field workers’ mental and physical status has not been examined in the naturalistic work environment. To address these issues, this research aims to propose and validate a comprehensive and efficient stress-measurement framework that recognizes workers mental and physical stress in a naturalistic environment. The focus of this research is on two wearable biosensors. First, a wearable EEG headset, which is a direct measurement of brain waves with the minimal time lag, but it is highly vulnerable to various artifacts. Second, a very convenient wristband-type biosensor, which may be used as a means for assessing both mental and physical stress, but there is a time lag between when subjects are exposed to stressors and when their physiological signals change. To achieve this goal, five interrelated and interdisciplinary studies were performed to; 1) acquire high-quality EEG signals from the job site; 2) assess construction workers’ emotion by measuring the valence and arousal level by analyzing the patterns of construction workers’ brainwaves; 3) recognize mental stress in the field based on brain activities by applying supervised-learning algorithms;4) recognize real-time mental stress by applying Online Multi-Task Learning (OMTL) algorithms; and 5) assess workers’ mental and physical stress using signals collected from a wristband biosensor. To examine the performance of the proposed framework, we collected physiological signals from 21 workers at five job sites. Results yielded a high of 80.13% mental stress-recognition accuracy using an EEG headset and 90.00% physical stress-recognition accuracy using a wristband sensor. These results are promising given that stress recognition with wired physiological devices within a controlled lab setting in the clinical domain has, at best, a similar level of accuracy. The proposed wearable biosensor-based, stress-recognition framework is expected to help us better understand workplace stressors and improve worker safety, health, and productivity through early detection and mitigation of stress at human-centered, smart and connected construction sites.PHDCivil EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/149965/1/hjebelli_1.pd

Experiencing Extreme Height for The First Time: The Influence of Height, Self-Judgment of Fear and a Moving Structural Beam on the Heart Rate and Postural Sway During the Quiet Stance

Falling from elevated surfaces is the main cause of death and injury at construction sites. Based on the Bureau of Labor Statistics (BLS) reports, an average of nearly three workers per day suffer fatal injuries from falling. Studies show that postural instability is the foremost cause of this disproportional falling rate. To study what affects the postural stability of construction workers, we conducted a series of experiments in the virtual reality (VR). Twelve healthy adults—all students at the University of Nebraska-Lincoln—were recruited for this study. During each trial, participants’ heart rates and postural sways were measured as the dependent factors. The independent factors included a moving structural beam (MB) coming directly at the participants, the presence of VR, height, the participants’ self-judgment of fear, and their level of acrophobia. The former was designed in an attempt to simulate some part of the steel erection procedure, which is one of the key tasks of ironworkers. The results of this study indicate that height increase the postural sway. Self-judged fear significantly was found to decrease postural sway, more specifically the normalized total excursion of the center of pressure (TE), both in the presence and absence of height. Also, participants’ heart rates significantly increase once they are confronted by a moving beam in the virtual environment (VE), even though they are informed that the beam will not ‘hit’ them. The findings of this study can be useful for training novice ironworkers that will be subjected to height and/or steel erection for the first time

Evaluation of hydrogen storage technology in risk-constrained stochastic scheduling of multi-carrier energy systems considering power, gas and heating network constraints

The operation of energy systems considering a multi-carrier scheme takes several advantages of economical, environmental, and technical aspects by utilizing alternative options is supplying different kinds of loads such as heat, gas, and power. This study aims to evaluate the influence of power to hydrogen conversion capability and hydrogen storage technology in energy systems with gas, power, and heat carriers concerning risk analysis. Accordingly, conditional value at risk (CVaR)-based stochastic method is adopted for investigating the uncertainty associated with wind power production. Hydrogen storage system, which can convert power to hydrogen in off-peak hours and to feed generators to produce power at on-peak time intervals, is studied as an effective solution to mitigate the wind power curtailment because of high penetration of wind turbines in electricity networks. Besides, the effect constraints associated with gas and district heating network on the operation of the multi-carrier energy systems has been investigated. A gas-fired combined heat and power (CHP) plant and hydrogen storage are considered as the interconnections among power, gas and heat systems. The proposed framework is implemented on a system to verify the effectiveness of the model. The obtained results show the effectiveness of the model in terms of handling the risks associated with multi-carrier system parameters as well as dealing with the penetration of renewable resources

ASSESSING GAIT AND POSTURAL STABILITY OF CONSTRUCTION WORKERS USING WEARABLE WIRELESS SENSOR NETWORKS

Falling accidents are a leading cause of fatal and nonfatal injuries in the construction industry. This fact demonstrates the need for a comprehensive fall-risk analysis that incorporates the effects of construction workers’ physiological characteristics. In this context, the objective of the thesis is to investigate and validate the usefulness of the gait- and postural-stability metrics in assessing construction workers’ fall risks. Diverse metrics that assess the capability to keep the body balanced and maintain coordination of body segments during locomotion (gait stability) and stationary postures (postural stability) have been introduced and used in clinical applications. However, their usefulness in the industry settings, in particular construction domain, has not been fully examined. Specifically, the thesis investigates the usefulness of one gait-stability metric and two postural-stability metrics which are computed using kinematic data captured from wearable inertial measurement units (IMUs). The usefulness of the selected metrics is validated by demonstrating their distinguishable powers in characterizing construction tasks with different fall-risk profiles. This thesis consists of three independent papers that have been published in other venues. The first paper focuses on validating the predictive power of fall risk of the Maximum Lyapunov exponent (Max LE), a gait-stability metric established in clinical settings. The results of the first paper demonstrate that the Max LE is able to distinguish workers’ gait stability while doing tasks with different fall-risk profiles. The second paper aims to test the usefulness of two postural-stability metrics that can be calculated from inertial measurement unit (IMU) data—the velocity of the bodily center of pressure (COPv) and the resultant accelerometer (rAcc)—as predictors for measuring construction workers’ fall risk in stationary postures. The results showed the distinguishing powers of Acc and COPv in tasks with different fall-risk profiles in stationary postures. The third paper explores the application of the postrual-stability metrics to analyze fall risks of the effects of tool-loading formation on workers’ fall risks. The results of the last paper demonstrate the higher risk values associated with tools connected asymmetrically to a full-body safety harness. The postrual- and dyanamic-stability metrics demonstrated in this thesis can be used as the metrics to find tasks and postures that have a higher risk of falling. Knowing the most dangerous locations at construction sites can help the manager provide appropriate fall-prevention systems; these can decrease the hazards at the job sites. Merging the suggested approach with certain alarm systems can provide real-time monitoring, which can assess the fall risk of construction workers. Advisor: Changbum R. Ah

Fall risk analysis of construction workers using inertial measurement units: Validating the usefulness of the postural stability metrics in construction

Fall accidents are a leading cause of fatalities and injuries in the construction industry, and the loss of bodily stability is one of the primary factors contributing to such falls. Body stability can be analyzed by studying dynamic and postural stability, the assessment of which can ultimately improve worker safety on the job sites. Previous studies have introduced a method for assessing construction workers' gait stability, but there remains a need for a comprehensive method that can analyze the fall-risk of construction workers' in stationary postures. This study aims to test the usefulness of two metrics-velocity of the bodily center of pressure (COPv) and the resultant accelerometer (rAcc)-as predictors with which to measure workers' fall risk in stationary postures. A laboratory experiment was designed and conducted to gather IMU data and compare the resulting stability metrics (I-COPv and rAcc) with the postural stability observed while conducting the same activities on a forceplate (F-COPv). The experiment evaluated stationary-posture tasks with various fall-risk profiles: standing and squatting in different situations (e.g. wearing a loaded harness with a symmetric and an asymmetric load, and holding a toolbox). The analysis's results demonstrated a significant difference in I-COPv and rAcc values across different postures and tasks and also showed considerable correlations between the metrics from both the force plate and the IMU sensors. The results showed the distinguishing power of I-COPv and rAcc in measuring the fall risk of different construction workers' tasks in the stationary posture.N

Comprehensive Fall-Risk Assessment of Construction Workers Using Inertial Measurement Units: Validation of the Gait-Stability Metric to Assess the Fall Risk of Iron Workers

In construction worksites, slips, trips, and falls are major causes of fatal injuries. This fact demonstrates the need for a safety assessment method that provides a comprehensive fall-risk analysis inclusive of the effects of physiological characteristics of construction workers. In this context, this research tests the usefulness of the maximum Lyapunov exponents (Max LE) as a metric to assess construction workers' comprehensive fall risk. Max LE, one of the gait-stability metrics established in clinical settings, estimates how the stability of a construction worker reacts to very small disruptions. In order to validate the use of Max LE, a laboratory experiment that asked a group of subjects to simulate iron workers' walking tasks on an I-beam was designed and conducted. These tasks were designed to showcase various fall-risk profiles: walking with a comfortable walking speed presented a low fall-risk profile; carrying a one-sided load and walking at a faster speed on the I-beam both presented high fall-risk profiles. Inertial measurement unit (IMU) sensors were attached to the right ankle of participants' bodies to collect kinematic data for the calculation of Max LE. The results showed that Max LE offers adequate distinguishing power for characterizing the fall risk of various construction workers' tasks, and the introduced approach to compute the gait stability from IMU sensor data captured from human bodies could provide a valuable analysis of the safety-related risks present in construction workers' motions. (C) 2015 American Society of Civil Engineers.N

The validation of gait-stability metrics to assess construction workers' fall risk

Falling from height is the top cause of injuries and fatalities in the construction industry. Understanding the fall risk at different work environment scan help to prevent fall accidents on a jobsite. While many previous studies attempted to assess the fall risk on a construction site, most of them are qualitative or subject to cognitive biases. In this context, this paper aims to introduce and validate a quantitative measure that allows researchers to characterize the fall risks of construction workers. In particular, this paper focuses on validating the fall risk predictive power of Maximum Lyapunov exponent (Max LE), which is one of the gait-stability metrics established in clinical settings. The kinematic data were collected using an inertial measurement unit (IMU) sensor attached to the right ankle of the subject performing different tasks. The Max LE for each tasks were then calculated based upon the IMU measurements. The results indicated a significant difference in the Max LE between different tasks, which indicates that Max LE has the potential to evaluate the dynamic stability of construction workers.N

Experiencing Extreme Height for The First Time: The Influence of Height, Self-Judgment of Fear and a Moving Structural Beam on the Heart Rate and Postural Sway During the Quiet Stance

Falling from elevated surfaces is the main cause of death and injury at construction sites. Based on the Bureau of Labor Statistics (BLS) reports, an average of nearly three workers per day suffer fatal injuries from falling. Studies show that postural instability is the foremost cause of this disproportional falling rate. To study what affects the postural stability of construction workers, we conducted a series of experiments in the virtual reality (VR). Twelve healthy adults—all students at the University of Nebraska-Lincoln—were recruited for this study. During each trial, participants’ heart rates and postural sways were measured as the dependent factors. The independent factors included a moving structural beam (MB) coming directly at the participants, the presence of VR, height, the participants’ self-judgment of fear, and their level of acrophobia. The former was designed in an attempt to simulate some part of the steel erection procedure, which is one of the key tasks of ironworkers. The results of this study indicate that height increase the postural sway. Self-judged fear significantly was found to decrease postural sway, more specifically the normalized total excursion of the center of pressure (TE), both in the presence and absence of height. Also, participants’ heart rates significantly increase once they are confronted by a moving beam in the virtual environment (VE), even though they are informed that the beam will not ‘hit’ them. The findings of this study can be useful for training novice ironworkers that will be subjected to height and/or steel erection for the first time