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关键词： Novel sensor technologies   Gaseous pollutants   Particulate matter   Time-activity-location patterns   Exposure misclassification   Dose estimation   Health outcomes  

摘要： Background Air pollution epidemiology has primarily relied on fixed outdoor air quality monitoring networks and static populations. Methods Taking advantage of recent advancements in sensor technologies and computational techniques, this paper presents a novel methodological approach that improves dose estimations of multiple air pollutants in large-scale health studies. We show the results of an intensive field campaign that measured personal exposures to gaseous pollutants and particulate matter of a health panel of 251 participants residing in urban and peri-urban Beijing with 60 personal air quality monitors (PAMs). Outdoor air pollution measurements were collected in monitoring stations close to the participants' residential addresses. Based on parameters collected with the PAMs, we developed an advanced computational model that automatically classified time-activity-location patterns of each individual during daily life at high spatial and temporal resolution. Results Applying this methodological approach in two established cohorts, we found substantial differences between doses estimated from outdoor and personal air quality measurements. The PAM measurements also significantly reduced the correlation between pollutant species often observed in static outdoor measurements, reducing confounding effects. Conclusions Future work will utilise these improved dose estimations to investigate the underlying mechanisms of air pollution on cardio-pulmonary health outcomes using detailed medical biomarkers in a way that has not been possible before.

关键词： Sensor technology   Accelerometer   Herd health   Precision dairy farming  

摘要： A significant number of lactating dairy cows are affected by health disorders in the early postpartum period. Precision dairy farming technologies have tremendous potential to support farmers in detecting disordered cows before clinical manifestation of a disease. The objective of this study was to evaluate if activity and rumination measures obtained by a commercial 3D-accelerometer system, i.e. "lying", "high active", "inactive", and "rumination" times, can be used for early identification of cows with health deviations before the clinical manifestation of disease. A total of 312 Holstein cows equipped with an ear attached accelerometer (Smartbow GmbH, Weibern, Austria) were monitored and analyzed from 14 days prior to parturition to eight days in milk (DIM). Animals were checked daily for clinical disorders from zero to eight DIM using standard operating procedures and by blood beta-hydroxybutyrate measurements at three, five, and eight DIM. Cows that presented no symptoms of health problems and with BHB concentrations <1.2 mmol/L in the first eight DIM were classified as healthy (n = 156) and used as the reference in this study. Cows with disorders were allocated in groups with one disorder (n = 65) and >1 disorders (n = 91). "Rumination" durations per day were already shorter five days before the clinical diagnosis (D0) in diseased cows (401.9 +/- 147.4 min/day) compared with healthy controls (434.6 +/- 140.3 min/day). "Rumination" time decreased before the diagnosis, with a nadir at Day -1 for healthy cows and cows with >1 disorder (392.0 +/- 147.9 vs. 313.4 +/- 162.6 min/day). Cows with one disorder reached a nadir on Day -3 (388.8 +/- 158.6 min/day). Similarly, the "high active" time started to become shorter three days before the clinical diagnosis in diseased cows compared to healthy cows (164.1 +/- 119.1 vs. 200.3 +/- 111.5 min/day). The times cows spent "inactive" were significantly longer three days before clinical diagnosis in diseased cows compared to

关键词： Sensor technologies   Theory guided technology development   Theory guided decision-making in sensor technologies  

摘要： Sensor technologies for health care, research, and consumers have expanded and evolved rapidly. Many technologies developed in commercial or engineering spaces, lack theoretical grounding and scientific evidence to support their need, safety, and efficacy. Theory is a mechanism for synthesizing and guiding knowledge generation for the discipline of nursing, including the design, implementation, and evaluation of sensors and related technologies such as artificial intelligence and machine learning. In this paper, three nurse scientists summarize their presentations at the Council for the Advancement of Nursing Science 2019 Advanced Methods Conference on Expanding Science of Sensor Technology in Research discussing the theoretical underpinnings of sensor technologies development and use in nursing research and practice. Multiple theories with diverse epistemological roots guide decision-making about whether or not to apply sensors to a given use;development of, components of, and mechanisms by which sensor technologies are expected to work;and possible outcomes.

关键词： Ethics   Innovation   Sensors   Technology  

摘要： Sensor-based technologies are used today in clinical practice, research, and for monitoring people's health in homes across the United States. Although the increasing growth and complexity of such technologies promises both direct and indirect benefits, significant ethical concerns are raised. We discuss several of these concerns, particularly those that arise in clinical research and outline ethical considerations that pertain to the concept of informed consent, participants' understanding of risks and benefits and the need for tailored and accessible information that will enable participants to fully understand research implications. Balancing the benefits with the potential risks of advanced information technology will require ethically astute researchers who can address the challenges that might arise while advancing knowledge with innovation that can improve the lives of patients and families.

关键词： Sensors   ehealth   environmental health   nursing   xenvironmental health   biomarkers   exercise   sleep  

摘要： Background: Electronic sensors measuring biological and behavioral aspects of health and the environment are becoming ubiquitous and, with advances in data science and ehealth technology, provide opportunities for new inquiry and innovative approaches to nursing research. Purpose: To conceptualize the use of sensor technology from the perspective of nursing science. Methods: This review reports the keynote presentation from the Expanding Science of Sensor Technology in Nursing Research Conference presented by the Council for Advancement of Nursing Science in 2019 Findings: Electronic sensors enable collection, recording, and transmission of data in real time in real life settings, remote monitoring, self-monitoring, and communication between health care professionals and patients. A deliberative approach to selecting and applying electronic sensors and analyzing and interpreting the data is needed for successful research. Discussion: Electronic sensors have high potential to advance nursing science.

关键词： 传感器   报警电路   EveryCircuit  

摘要： 该文主要基于高等职业教育课程理实一体化的理念,把EveryCircuit电路仿真软件应用于传感器实践教学报警器电路制作的过程中,克服了教学硬件的局限性,学生在智能手机上便可方便操作,适用于目前信息化教学的要求,同时符合”做中学,学中做”的教学模式,拓宽了学生的视野,提高了教学效率和学生的学习效果。