Novel monitor paradigm for real-time exposure assessment

Digital Transformation in Toxicology: Improving Communication and Efficiency in Risk Assessment

Toxicology is undergoing a digital revolution, with mobile apps, sensors, artificial intelligence (AI), and machine learning enabling better record-keeping, data analysis, and risk assessment. Additionally, computational toxicology and digital risk assessment have led to more accurate predictions of chemical hazards, reducing the burden of laboratory studies. Blockchain technology is emerging as a promising approach to increase transparency, particularly in the management and processing of genomic data related with food safety. Robotics, smart agriculture, and smart food and feedstock offer new opportunities for collecting, analyzing, and evaluating data, while wearable devices can predict toxicity and monitor health-related issues. The review article focuses on the potential of digital technologies to improve risk assessment and public health in the field of toxicology. By examining key topics such as blockchain technology, smoking toxicology, wearable sensors, and food security, this article provides an overview of how digitalization is influencing toxicology. As well as highlighting future directions for research, this article demonstrates how emerging technologies can enhance risk assessment communication and efficiency. The integration of digital technologies has revolutionized toxicology and has great potential for improving risk assessment and promoting public health.

A Scoping Review of Technologies and Their Applicability for Exposome-Based Risk Assessment in the Oil and Gas Industry

INTRODUCTION

Oil and gas workers have been shown to be at increased risk of chronic diseases including cancer, asthma, chronic obstructive pulmonary disease, and hearing loss, among others. Technological advances may be used to assess the external (e.g. personal sensors, smartphone apps and online platforms, exposure models) and internal exposome (e.g. physiologically based kinetic modeling (PBK), biomonitoring, omics), offering numerous possibilities for chronic disease prevention strategies and risk management measures. The objective of this study was to review the literature on these technologies, by focusing on: (i) evaluating their applicability for exposome research in the oil and gas industry, and (ii) identifying key challenges that may hamper the successful application of such technologies in the oil and gas industry.

METHOD

A scoping review was conducted by identifying peer-reviewed literature with searches in MEDLINE/PubMed and SciVerse Scopus. Two assessors trained on the search strategy screened retrieved articles on title and abstract. The inclusion criteria used for this review were: application of the aforementioned technologies at a workplace in the oil and gas industry or, application of these technologies for an exposure relevant to the oil and gas industry but in another occupational sector, English language and publication period 2005-end of 2019.

RESULTS

In total, 72 articles were included in this scoping review with most articles focused on omics and bioinformatics (N = 22), followed by biomonitoring and biomarkers (N = 20), external exposure modeling (N = 11), PBK modeling (N = 10), and personal sensors (N = 9). Several studies were identified in the oil and gas industry on the application of PBK models and biomarkers, mainly focusing on workers exposed to benzene. The application of personal sensors, new types of exposure models, and omics technology are still in their infancy with respect to the oil and gas industry. Nevertheless, applications of these technologies in other occupational sectors showed the potential for application in this sector.

DISCUSSION AND CONCLUSION

New exposome technologies offer great promise for personal monitoring of workers in the oil and gas industry, but more applied research is needed in collaboration with the industry. Current challenges hindering a successful application of such technologies include (i) the technological readiness of sensors, (ii) the availability of data, (iii) the absence of standardized and validated methods, and (iv) the need for new study designs to study the development of disease during working life.

Future Prospects of Occupational Exposure Modelling of Substances in the Context of Time-Resolved Sensor Data

This commentary explores the use of high-resolution data from new, miniature sensors to enrich models that predict exposures to chemical substances in the workplace. To optimally apply these sensors, one can expect an increased need for new models that will facilitate the interpretation and extrapolation of the acquired time-resolved data. We identified three key modelling approaches in the context of sensor data, namely (i) enrichment of existing time-integrated exposure models, (ii) (new) high-resolution (in time and space) empirical models, and (iii) new 'occupational dispersion' models. Each approach was evaluated in terms of their application in research, practice, and for policy purposes. It is expected that substance-specific sensor data will have the potential to transform workplace modelling by re-calibrating, refining, and validating existing (time-integrated) models. An increased shift towards 'sensor-driven' models is expected. It will allow for high-resolution modelling in time and space to identify peak exposures and will be beneficial for more individualized exposure assessment and real-time risk management. New 'occupational dispersion models' such as interpolation, computational fluid dynamic models, and assimilation techniques, together with sensor data, will be specifically useful. These techniques can be applied to develop site-specific concentration maps which calculate personal exposures and mitigate worker exposure through early warning systems, source finding and improved control design and control strategies. Critical development and investment needs for sensor data linked to (new) model development were identified such as (i) the generation of more sensor data with reliable sensor technologies (achieved by improved specificity, sensitivity, and accuracy of sensors), (ii) investing in statistical and new model developments, (iii) ensuring that we comply with privacy and security issues of concern, and (iv) acceptance by relevant target groups (such as employers and employees) and stimulation of these new technologies by policymakers and technology developers.

Wearable Devices in Health Monitoring from the Environmental towards Multiple Domains: A Survey

The World Health Organization (WHO) recognizes the environmental, behavioral, physiological, and psychological domains that impact adversely human health, well-being, and quality of life (QoL) in general. The environmental domain has significant interaction with the others. With respect to proactive and personalized medicine and the Internet of medical things (IoMT), wearables are most important for continuous health monitoring. In this work, we analyze wearables in healthcare from a perspective of innovation by categorizing them according to the four domains. Furthermore, we consider the mode of wearability, costs, and prolonged monitoring. We identify features and investigate the wearable devices in the terms of sampling rate, resolution, data usage (propagation), and data transmission. We also investigate applications of wearable devices. Web of Science, Scopus, PubMed, IEEE Xplore, and ACM Library delivered wearables that we require to monitor at least one environmental parameter, e.g., a pollutant. According to the number of domains, from which the wearables record data, we identify groups: G1, environmental parameters only; G2, environmental and behavioral parameters; G3, environmental, behavioral, and physiological parameters; and G4 parameters from all domains. In total, we included 53 devices of which 35, 9, 9, and 0 belong to G1, G2, G3, and G4, respectively. Furthermore, 32, 11, 7, and 5 wearables are applied in general health and well-being monitoring, specific diagnostics, disease management, and non-medical. We further propose customized and quantified output for future wearables from both, the perspectives of users, as well as physicians. Our study shows a shift of wearable devices towards disease management and particular applications. It also indicates the significant role of wearables in proactive healthcare, having capability of creating big data and linking to external healthcare systems for real-time monitoring and care delivery at the point of perception.

Technologies Enabling Situational Awareness During Disaster Response: A Systematic Review

Situational awareness (SA) is critical to mobilizing a rapid, efficient, and effective response to disasters. Limited by time and resources, response agencies must make decisions about rapidly evolving situations, which requires the collection, analysis, and sharing of actionable information across a complex landscape. Emerging technologies, if appropriately applied, can enhance SA and enable responders to make quicker, more accurate decisions. The aim of this systematic review is to identify technologies that can improve SA and assist decision-making across the United States Government and the domestic and international agencies they support during disaster response operations. A total of 1459 articles and 36 after-action reports were identified during literature searches. Following the removal of duplicates and application of inclusion/exclusion criteria, 302 articles and after-action reports were included in the review. Our findings suggest SA is constrained primarily due to unreliable and significantly delayed communications, time-intensive data analysis and visualization, and a lack of interoperable sensor networks and other capabilities providing data to shared platforms. Many of these challenges could be addressed by existing technologies. Bridging the divide between research and development efforts and the operational needs of response agencies should be prioritized.

Occupational Risk Prevention through Smartwatches: Precision and Uncertainty Effects of the Built-In Accelerometer

Wearable technology has had a significant growth in the last years; this is particularly true of smartwatches, due to their potential advantages and ease of use. These smart devices integrate sensors that can be potentially used within industrial settings and for several applications, such as safety, monitoring, and the identification of occupational risks. The accelerometer is one of the main sensors integrated into these devices. However, several studies have identified that sensors integrated into smart devices may present inaccuracies during data acquisition, which may influence the performance of their potential applications. This article presents an analysis from the metrological point of view to characterize the amplitude and frequency response of the integrated accelerometers in three currently available commercial smartwatches, and it also includes an analysis of the uncertainties associated with these measurements by adapting the procedures described in several International Organization for Standardization (ISO) standards. The results show that despite the technical limitations produced by the factory configuration, these devices can be used in various applications related to occupational risk assessment. Opportunities for improvement have also been identified, which will allow us to take advantage of this technology in several innovative applications within industrial settings and, in particular, for occupational health purposes.

Comparing the Data Quality of Global Positioning System Devices and Mobile Phones for Assessing Relationships Between Place, Mobility, and Health: Field Study

Background

Mobile devices are increasingly used to collect location-based information from individuals about their physical activities, dietary intake, environmental exposures, and mental well-being. Such research, which typically uses wearable devices or mobile phones to track location, benefits from the growing availability of fine-grained data regarding human mobility. However, little is known about the comparative geospatial accuracy of such devices.

Objective

In this study, we compared the data quality of location information collected from two mobile devices that determine location in different ways—a global positioning system (GPS) watch and a mobile phone with Google’s Location History feature enabled.

Methods

A total of 21 chronically ill participants carried both devices, which generated digital traces of locations, for 28 days. A mobile phone–based brief ecological momentary assessment (EMA) survey asked participants to manually report their location at 4 random times throughout each day. Participants also took part in qualitative interviews and completed surveys twice during the study period in which they reviewed recent mobile phone and watch trace data to compare the devices’ trace data with their memory of their activities on those days. Trace data from the devices were compared on the basis of (1) missing data days, (2) reasons for missing data, (3) distance between the route data collected for matching day and the associated EMA survey locations, and (4) activity space total area and density surfaces.

Results

The watch resulted in a much higher proportion of missing data days (P<.001), with missing data explained by technical differences between the devices as well as participant behaviors. The mobile phone was significantly more accurate in detecting home locations (P=.004) and marginally more accurate (P=.07) for all types of locations combined. The watch data resulted in a smaller activity space area and more accurately recorded outdoor travel and recreation.

Conclusions

The most suitable mobile device for location-based health research depends on the particular study objectives. Furthermore, data generated from mobile devices, such as GPS phones and smartwatches, require careful analysis to ensure quality and completeness. Studies that seek precise measurement of outdoor activity and travel, such as measuring outdoor physical activity or exposure to localized environmental hazards, would benefit from the use of GPS devices. Conversely, studies that aim to account for time within buildings at home or work, or those that document visits to particular places (such as supermarkets, medical facilities, or fast food restaurants), would benefit from the greater precision demonstrated by the mobile phone in recording indoor activities.

User acceptance of location-tracking technologies in health research: Implications for study design and data quality

Research regarding place and health has undergone a revolution due to the availability of consumer-focused location-tracking devices that reveal fine-grained details of human mobility. Such research requires that participants accept such devices enough to use them in their daily lives. There is a need for a theoretically grounded understanding of acceptance of different location-tracking technology options, and its research implications. Guided by an extended Unified Theory of Acceptance and Use of Technology (UTAUT), we conducted a 28-day field study comparing 21 chronically ill people's acceptance of two leading, consumer-focused location-tracking technologies deployed for research purposes: (1) a location-enabled smartphone, and (2) a GPS watch/activity tracker. Participants used both, and completed two surveys and qualitative interviews. Findings revealed that all participants exerted effort to facilitate data capture, such as by incorporating devices into daily routines and developing workarounds to keep devices functioning. Nevertheless, the smartphone was perceived to be significantly easier and posed fewer usability challenges for participants than the watch. Older participants found the watch significantly more difficult to use. For both devices, effort expectancy was significantly associated with future willingness to participate in research although prosocial motivations overcame some concerns. Social influence, performance expectancy and use behavior were significantly associated with intentions to use the devices in participants' personal lives. Data gathered via the smartphone was significantly more complete than data gathered via the watch, primarily due to usability challenges. To make longer-term participation in location tracking research a reality, and to achieve complete data capture, researchers must minimize the effort involved in participation; this requires usable devices. For long-term location-tracking studies using similar devices, findings indicate that only smartphone-based tracking is up to the challenge.

Adsorption Thermodynamic Analysis of a Quartz Tuning Fork Based Sensor for Volatile Organic Compounds Detection

A volatile organic compounds (VOC) sensor based on molecularly imprinted polymer (MIP) modified quartz tuning fork (QTF) has been developed. In this paper, the stability of the modified sensor as a function of the MIP composition, and the temperature effect of the analyte adsorption on the sensing transduction mechanism are evaluated. By mixing MIP and PS together, the stability was improved. A target analyte, o-xylene, was chosen as the VOC model to study the sensor response in a temperature range of 6-40 °C. Langmuir model fitted adsorption isotherms were used for thermodynamic analysis. The changes in the sensitivity of the QTF sensor to temperature rendered different behaviors. For a freshly modified QTF sensor, the adsorption response increased with increasing temperature, while for an aged QTF sensor, the adsorption response decreased with increasing temperature. The results indicated that the enthalpy change of the MIP and PS composition sensing material changes from positive to negative over the course of aging. The characterization of the reaction enabled the definition of sensor calibration conditions and stable sensor performance in field testing conditions.

Miniaturized Monitors for Assessment of Exposure to Air Pollutants: A Review

Air quality has a huge impact on different aspects of life quality, and for this reason, air quality monitoring is required by national and international regulations. Technical and procedural limitations of traditional fixed-site stations for monitoring or sampling of air pollutants are also well-known. Recently, a different type of miniaturized monitors has been developed. These monitors, due to their characteristics (e.g., low cost, small size, high portability) are becoming increasingly important for individual exposure assessment, especially since this kind of instrument can provide measurements at high spatial and temporal resolution, which is a notable advantage when approaching assessment of exposure to environmental contaminants. The aim of this study is indeed to provide information regarding current knowledge regarding the use of miniaturized air pollutant sensors. A systematic review was performed to identify original articles: a literature search was carried out using an appropriate query for the search of papers across three different databases, and the papers were selected using inclusion/exclusion criteria. The reviewed articles showed that miniaturized sensors are particularly versatile and could be applied in studies with different experimental designs, helping to provide a significant enhancement to exposure assessment, even though studies regarding their performance are still sparse.

Unraveling fabrication and calibration of wearable gas monitor for use under free-living conditions

Volatile organic compounds (VOC) are organic chemicals that have high vapor pressure at regular conditions. Some VOC could be dangerous to human health, therefore it is important to determine real-time indoor and outdoor personal exposures to VOC. To achieve this goal, our group has developed a wearable gas monitor with a complete sensor fabrication and calibration protocol for free-living conditions. Correction factors for calibrating the sensors, including sensitivity, aging effect, and temperature effect are implemented into a Quick Response Code (QR code), so that the pre-calibrated quartz tuning fork (QTF) sensor can be used with the wearable monitor under free-living conditions.

Translational bioinformatics in the era of real-time biomedical, health care and wellness data streams

Monitoring and modeling biomedical, health care and wellness data from individuals and converging data on a population scale have tremendous potential to improve understanding of the transition to the healthy state of human physiology to disease setting. Wellness monitoring devices and companion software applications capable of generating alerts and sharing data with health care providers or social networks are now available. The accessibility and clinical utility of such data for disease or wellness research are currently limited. Designing methods for streaming data capture, real-time data aggregation, machine learning, predictive analytics and visualization solutions to integrate wellness or health monitoring data elements with the electronic medical records (EMRs) maintained by health care providers permits better utilization. Integration of population-scale biomedical, health care and wellness data would help to stratify patients for active health management and to understand clinically asymptomatic patients and underlying illness trajectories. In this article, we discuss various health-monitoring devices, their ability to capture the unique state of health represented in a patient and their application in individualized diagnostics, prognosis, clinical or wellness intervention. We also discuss examples of translational bioinformatics approaches to integrating patient-generated data with existing EMRs, personal health records, patient portals and clinical data repositories. Briefly, translational bioinformatics methods, tools and resources are at the center of these advances in implementing real-time biomedical and health care analytics in the clinical setting. Furthermore, these advances are poised to play a significant role in clinical decision-making and implementation of data-driven medicine and wellness care.

A Novel Wireless Wearable Volatile Organic Compound (VOC) Monitoring Device with Disposable Sensors

A novel portable wireless volatile organic compound (VOC) monitoring device with disposable sensors is presented. The device is miniaturized, light, easy-to-use, and cost-effective. Different field tests have been carried out to identify the operational, analytical, and functional performance of the device and its sensors. The device was compared to a commercial photo-ionization detector, gas chromatography-mass spectrometry, and carbon monoxide detector. In addition, environmental operational conditions, such as barometric change, temperature change and wind conditions were also tested to evaluate the device performance. The multiple comparisons and tests indicate that the proposed VOC device is adequate to characterize personal exposure in many real-world scenarios and is applicable for personal daily use.

Indoor Air Contamination from Hazardous Waste Sites: Improving the Evidence Base for Decision-Making

At hazardous waste sites, volatile chemicals can migrate through groundwater and soil into buildings, a process known as vapor intrusion. Due to increasing recognition of vapor intrusion as a potential indoor air pollution source, in 2015 the U.S. Environmental Protection Agency (EPA) released a new vapor intrusion guidance document. The guidance specifies two conditions for demonstrating that remediation is needed: (1) proof of a vapor intrusion pathway; and (2) evidence that human health risks exceed established thresholds (for example, one excess cancer among 10,000 exposed people). However, the guidance lacks details on methods for demonstrating these conditions. We review current evidence suggesting that monitoring and modeling approaches commonly employed at vapor intrusion sites do not adequately characterize long-term exposure and in many cases may underestimate risks. On the basis of this evidence, we recommend specific approaches to monitoring and modeling to account for these uncertainties. We propose a value of information approach to integrate the lines of evidence at a site and determine if more information is needed before deciding whether the two conditions specified in the vapor intrusion guidance are satisfied. To facilitate data collection and decision-making, we recommend a multi-directional community engagement strategy and consideration of environment justice concerns.

A wireless hybrid chemical sensor for detection of environmental volatile organic compounds

A hybrid sensor for monitoring volatile organic compounds (VOCs) in air is developed. The device combines two orthogonal sensing principles, selective molecular binding with a microfabricated quartz tuning fork detector and separation of analytes with a column. The tuning fork detector is functionalized with molecular imprinted polymers for selective binding to benzene, toluene, ethylbenzene, and xylenes (BTEX), and the separation column provides further discrimination of the analytes for real world complex sample analysis. The device is wireless, portable, battery-powered, and cell-phone operated, and it allows reliable detection in parts per billion (ppb) by volume-levels of BTEX in the presence of complex interferents. The hybrid device is suitable for occupational, environmental health, and epidemiological applications.

Quantifying human exposure to air pollution--moving from static monitoring to spatio-temporally resolved personal exposure assessment

Quantifying human exposure to air pollutants is a challenging task. Ambient concentrations of air pollutants at potentially harmful levels are ubiquitous in urban areas and subject to high spatial and temporal variability. At the same time, every individual has unique activity-patterns. Exposure results from multifaceted relationships and interactions between environmental and human systems, adding complexity to the assessment process. Traditionally, approaches to quantify human exposure have relied on pollutant concentrations from fixed air quality network sites and static population distributions. New developments in sensor technology now enable us to monitor personal exposure to air pollutants directly while people are moving through their activity spaces and varying concentration fields. The literature review on which this paper is based on reflects recent developments in the assessment of human exposure to air pollution. This includes the discussion of methodologies and concepts, and the elaboration of approaches and study designs applied in the field. We identify shortcomings of current approaches and discuss future research needs. We close by proposing a novel conceptual model for the integrated assessment of human exposure to air pollutants taking into account latest technological capabilities and contextual information.

A New Sensor for the Assessment of Personal Exposure to Volatile Organic Compounds

To improve our understanding of indoor and outdoor personal exposures to common environmental toxicants released into the environment, new technologies that can monitor and quantify the toxicants anytime anywhere are needed. This paper presents a wearable sensor to provide such capabilities. The sensor can communicate with a common smart phone and provides accurate measurement of volatile organic compound concentration at a personal level in real time, providing environmental toxicants data every three minutes. The sensor has high specificity and sensitivity to aromatic, alkyl, and chlorinated hydrocarbons with a resolution as low as 4 parts per billion (ppb), with a detection range of 4 ppb to 1000 ppm (parts per million). The sensor's performance was validated using Gas Chromatography and Selected Ion Flow Tube - Mass Spectrometry reference methods in a variety of environments and activities with overall accuracy higher than 81% (r(2) > 0.9). Field tests examined personal exposure in various scenarios including: indoor and outdoor environments, traffic exposure in different cities which vary from 0 to 50 ppmC (part-per-million carbon from hydrocarbons), and pollutants near the 2010 Deepwater Horizon's oil spill. These field tests not only validated the performance but also demonstrated unprecedented high temporal and spatial toxicant information provided by the new technology.