Every day many lives are taken or individuals are handicapped due to the existence of mines remai... more Every day many lives are taken or individuals are handicapped due to the existence of mines remaining from wartime. The following robot is an intelligence system designed for detecting mines in an area. This robot is able to indicate the location of mines.
Proceedings of the Human Factors and Ergonomics Society Annual Meeting
Anxiety disorder is the most common mental health disorder in the United States. One of the key f... more Anxiety disorder is the most common mental health disorder in the United States. One of the key factors that leads to the development and aggravation of anxiety disorders is mental stress. In this study, we reviewed publications that used physiological responses and symptoms to assess mental stress. This review found that mental stress affects heart rate, hear rate variability, blood pressure, and skin conductance. Fuzzy logic, time series, and Poincare plots are prominent data analysis tools for physiological data. Most studies used a threshold (e.g., Poincaré plot) or variance (e.g., moving average models) to distinguish stress from normal conditions. The variations and thresholds, however, might fluctuate across various activities and individuals. Moreover, most research evaluated lab-generated stress data, which may be biased. Therefore, more naturalistic studies should be conducted for future research.
Journal of Construction Engineering and Management, 2021
AbstractRepeated exposure to hazards in road construction work zones often generates worker habit... more AbstractRepeated exposure to hazards in road construction work zones often generates worker habituation to risks associated with those hazards, a key causal factor in workplace accidents. Understan...
Proceedings of the Human Factors and Ergonomics Society Annual Meeting
The goal of this paper is to review the literature on machine learning (ML) and big data applicat... more The goal of this paper is to review the literature on machine learning (ML) and big data applications for mental health, emphasizing current research and practical implementations. To explore the field of ML in mental health, we used a scoping review process. The literature identified application domains of detection and prediction of stress as a contributor to mental health disorders. We evaluated the articles and data on the mental health application, machine learning approach, type of data (sensor, survey, etc.), and type of sensors. Most studies extracted features before developing AI-based stress detection algorithms. Findings revealed that heart rate, heart rate variability, and skin conductance features are the key indicators of stress. Moreover, among AI stress-detection methods, Random Forest and Neural Networks show promising results.
Water distribution systems (WDS) carry potable water with millions of miles of pipelines and deli... more Water distribution systems (WDS) carry potable water with millions of miles of pipelines and deliver purified water to residential areas. The incidents in the WDS cause leak and water loss, which imposes pressure gradient and public health crisis. Hence, utility managers need to assess the condition of pipelines periodically and localize the leak location (in case it is reported). In our previous works, we designed and developed a size-adaptable modular in-pipe robot [1] and controlled its motion in in-service WDS. However, due to the linearization of the dynamical equations of the robot, the stabilizer controller which is a linear quadratic regulator (LQR) cannot stabilize the large deviations of the stabilizing states due to the presence of obstacles that fails the robot during operation. To this aim, we design a “self-rescue” mechanism for the robot in which three auxiliary gear-motors retract and extend the arm modules with the designed controller towards a reliable motion in th...
The COVID-19 disease spreads swiftly, and nearly three months after the first positive case was c... more The COVID-19 disease spreads swiftly, and nearly three months after the first positive case was confirmed in China, Coronavirus started to spread all over the United States. Some states and counties reported high number of positive cases and deaths, while some reported lower COVID-19 related cases and mortality. In this paper, the factors that could affect the risk of COVID-19 infection and mortality were analyzed in county level. An innovative method by using K-means clustering and several classification models is utilized to determine the most critical factors. Results showed that mean temperature, percent of people below poverty, percent of adults with obesity, air pressure, population density, wind speed, longitude, and percent of uninsured people were the most significant attributes
10 Background: The human mind is multimodal. Yet most behavioral studies rely on century-old 11 m... more 10 Background: The human mind is multimodal. Yet most behavioral studies rely on century-old 11 measures such as task accuracy and latency. To create a better understanding of human behavior 12 and brain functionality, we should introduce other measures and analyze behavior from various 13 aspects. However, it is technically complex and costly to design and implement the experiments 14 that record multiple measures. To address this issue, a platform that allows synchronizing multiple 15 measures from human behavior is needed. 16 Method: This paper introduces an opensource platform named OpenSync, which can be used to 17 synchronize multiple measures in neuroscience experiments. This platform helps to automatically 18 integrate, synchronize and record physiological measures (e.g., electroencephalogram (EEG), 19 galvanic skin response (GSR), eye-tracking, body motion, etc.), user input response (e.g., from 20 mouse, keyboard, joystick, etc.), and task-related information (stimulus mar...
The COVID-19 disease spreads swiftly, and nearly three months after the first positive case was c... more The COVID-19 disease spreads swiftly, and nearly three months after the first positive case was confirmed in China, Coronavirus started to spread all over the United States. Some states and counties reported an extremely high number of positive cases and deaths, while some reported too few COVID-19 related cases and mortality. In this paper, the factors that could affect the transmission of COVID-19 and its risk-level in different counties have been determined and analyzed. Using Pearson Correlation, Kmeans clustering, and several classification models, the most critical ones were determined. Results showed that mean temperature, percent of people below poverty, percent of adults with obesity, air pressure, percentage of rural areas, and percent of uninsured people in each county were the most significant and effective attributes.
A handful of research has demonstrated the potential of mouse tracking for emotion assessment. Ye... more A handful of research has demonstrated the potential of mouse tracking for emotion assessment. Yet, theoretical and empirical bases for this approach remain opaque. If emotion influences motor control (e.g., controlling the movement of the computer mouse), how does that happen? What experimental situations constrain or promote the purported connection? To address these questions, we examined how prior emotional experience (viewing emotional photos) would influence participants' motor activity, as measured by the movement of the computer cursor. Results from two experiments indicate that emotional experience impacts both temporal (peak velocity) and spatial characteristics (deviation of the trajectory) of the cursor motion. But there are clear gender differences; for male participants, emotion influenced temporal features (peak velocity) but this impact was absent in female participants. It is suggested that emotion intervenes motor vigor and decision-making processes differently...
Background: The human mind is multimodal. Yet most behavioral studies rely on century-old measure... more Background: The human mind is multimodal. Yet most behavioral studies rely on century-old measures such as task accuracy and latency. To create a better understanding of human behavior and brain functionality, we should introduce other measures and analyze behavior from various aspects. However, it is technically complex and costly to design and implement the experiments that record multiple measures. To address this issue, a platform that allows synchronizing multiple measures from human behavior is needed. Method: This paper introduces an opensource platform named OpenSync, which can be used to synchronize multiple measures in neuroscience experiments. This platform helps to automatically integrate, synchronize and record physiological measures (e.g., electroencephalogram (EEG), galvanic skin response (GSR), eye-tracking, body motion, etc.), user input response (e.g., from mouse, keyboard, joystick, etc.), and task-related information (stimulus markers). In this paper, we explain ...
Every day many lives are taken or individuals are handicapped due to the existence of mines remai... more Every day many lives are taken or individuals are handicapped due to the existence of mines remaining from wartime. The following robot is an intelligence system designed for detecting mines in an area. This robot is able to indicate the location of mines.
Proceedings of the Human Factors and Ergonomics Society Annual Meeting
Anxiety disorder is the most common mental health disorder in the United States. One of the key f... more Anxiety disorder is the most common mental health disorder in the United States. One of the key factors that leads to the development and aggravation of anxiety disorders is mental stress. In this study, we reviewed publications that used physiological responses and symptoms to assess mental stress. This review found that mental stress affects heart rate, hear rate variability, blood pressure, and skin conductance. Fuzzy logic, time series, and Poincare plots are prominent data analysis tools for physiological data. Most studies used a threshold (e.g., Poincaré plot) or variance (e.g., moving average models) to distinguish stress from normal conditions. The variations and thresholds, however, might fluctuate across various activities and individuals. Moreover, most research evaluated lab-generated stress data, which may be biased. Therefore, more naturalistic studies should be conducted for future research.
Journal of Construction Engineering and Management, 2021
AbstractRepeated exposure to hazards in road construction work zones often generates worker habit... more AbstractRepeated exposure to hazards in road construction work zones often generates worker habituation to risks associated with those hazards, a key causal factor in workplace accidents. Understan...
Proceedings of the Human Factors and Ergonomics Society Annual Meeting
The goal of this paper is to review the literature on machine learning (ML) and big data applicat... more The goal of this paper is to review the literature on machine learning (ML) and big data applications for mental health, emphasizing current research and practical implementations. To explore the field of ML in mental health, we used a scoping review process. The literature identified application domains of detection and prediction of stress as a contributor to mental health disorders. We evaluated the articles and data on the mental health application, machine learning approach, type of data (sensor, survey, etc.), and type of sensors. Most studies extracted features before developing AI-based stress detection algorithms. Findings revealed that heart rate, heart rate variability, and skin conductance features are the key indicators of stress. Moreover, among AI stress-detection methods, Random Forest and Neural Networks show promising results.
Water distribution systems (WDS) carry potable water with millions of miles of pipelines and deli... more Water distribution systems (WDS) carry potable water with millions of miles of pipelines and deliver purified water to residential areas. The incidents in the WDS cause leak and water loss, which imposes pressure gradient and public health crisis. Hence, utility managers need to assess the condition of pipelines periodically and localize the leak location (in case it is reported). In our previous works, we designed and developed a size-adaptable modular in-pipe robot [1] and controlled its motion in in-service WDS. However, due to the linearization of the dynamical equations of the robot, the stabilizer controller which is a linear quadratic regulator (LQR) cannot stabilize the large deviations of the stabilizing states due to the presence of obstacles that fails the robot during operation. To this aim, we design a “self-rescue” mechanism for the robot in which three auxiliary gear-motors retract and extend the arm modules with the designed controller towards a reliable motion in th...
The COVID-19 disease spreads swiftly, and nearly three months after the first positive case was c... more The COVID-19 disease spreads swiftly, and nearly three months after the first positive case was confirmed in China, Coronavirus started to spread all over the United States. Some states and counties reported high number of positive cases and deaths, while some reported lower COVID-19 related cases and mortality. In this paper, the factors that could affect the risk of COVID-19 infection and mortality were analyzed in county level. An innovative method by using K-means clustering and several classification models is utilized to determine the most critical factors. Results showed that mean temperature, percent of people below poverty, percent of adults with obesity, air pressure, population density, wind speed, longitude, and percent of uninsured people were the most significant attributes
10 Background: The human mind is multimodal. Yet most behavioral studies rely on century-old 11 m... more 10 Background: The human mind is multimodal. Yet most behavioral studies rely on century-old 11 measures such as task accuracy and latency. To create a better understanding of human behavior 12 and brain functionality, we should introduce other measures and analyze behavior from various 13 aspects. However, it is technically complex and costly to design and implement the experiments 14 that record multiple measures. To address this issue, a platform that allows synchronizing multiple 15 measures from human behavior is needed. 16 Method: This paper introduces an opensource platform named OpenSync, which can be used to 17 synchronize multiple measures in neuroscience experiments. This platform helps to automatically 18 integrate, synchronize and record physiological measures (e.g., electroencephalogram (EEG), 19 galvanic skin response (GSR), eye-tracking, body motion, etc.), user input response (e.g., from 20 mouse, keyboard, joystick, etc.), and task-related information (stimulus mar...
The COVID-19 disease spreads swiftly, and nearly three months after the first positive case was c... more The COVID-19 disease spreads swiftly, and nearly three months after the first positive case was confirmed in China, Coronavirus started to spread all over the United States. Some states and counties reported an extremely high number of positive cases and deaths, while some reported too few COVID-19 related cases and mortality. In this paper, the factors that could affect the transmission of COVID-19 and its risk-level in different counties have been determined and analyzed. Using Pearson Correlation, Kmeans clustering, and several classification models, the most critical ones were determined. Results showed that mean temperature, percent of people below poverty, percent of adults with obesity, air pressure, percentage of rural areas, and percent of uninsured people in each county were the most significant and effective attributes.
A handful of research has demonstrated the potential of mouse tracking for emotion assessment. Ye... more A handful of research has demonstrated the potential of mouse tracking for emotion assessment. Yet, theoretical and empirical bases for this approach remain opaque. If emotion influences motor control (e.g., controlling the movement of the computer mouse), how does that happen? What experimental situations constrain or promote the purported connection? To address these questions, we examined how prior emotional experience (viewing emotional photos) would influence participants' motor activity, as measured by the movement of the computer cursor. Results from two experiments indicate that emotional experience impacts both temporal (peak velocity) and spatial characteristics (deviation of the trajectory) of the cursor motion. But there are clear gender differences; for male participants, emotion influenced temporal features (peak velocity) but this impact was absent in female participants. It is suggested that emotion intervenes motor vigor and decision-making processes differently...
Background: The human mind is multimodal. Yet most behavioral studies rely on century-old measure... more Background: The human mind is multimodal. Yet most behavioral studies rely on century-old measures such as task accuracy and latency. To create a better understanding of human behavior and brain functionality, we should introduce other measures and analyze behavior from various aspects. However, it is technically complex and costly to design and implement the experiments that record multiple measures. To address this issue, a platform that allows synchronizing multiple measures from human behavior is needed. Method: This paper introduces an opensource platform named OpenSync, which can be used to synchronize multiple measures in neuroscience experiments. This platform helps to automatically integrate, synchronize and record physiological measures (e.g., electroencephalogram (EEG), galvanic skin response (GSR), eye-tracking, body motion, etc.), user input response (e.g., from mouse, keyboard, joystick, etc.), and task-related information (stimulus markers). In this paper, we explain ...
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