On January 12th, 2022, Healthcare published our latest peer-reviewed research on Heart Rate Variability (HRV). The paper is titled “Trends in Daily Heart Rate Variability Fluctuations Are Associated with Longitudinal Changes in Stress and Somatisation in Police Officers” and is part of a special issue on Mental and Behavioral Healthcare. In this blogpost, I will attempt to summarize the article and how it complements our prior research in more lay language.
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The emergence of wearable sensors that allow for unobtrusive monitoring of physiological and behavioural patterns introduces new opportunities to study the impact of stress in a real-world context. This study explores to what extent within-subject trends in daily Heart Rate Variability (HRV) and daily HRV fluctuations are associated with longitudinal changes in stress, depression,anxiety, and somatisation. Nine Dutch police officers collected daily nocturnal HRV data using an Oura ring during 15–55 weeks. Participants filled in the Four-Dimensional Symptoms Questionnaire every 5 weeks. A sample of 47 five-week observations was collected and analysed using multiple regression. After controlling for trends in total sleep time, moderate-to-vigorous physical activityand alcohol use, an increasing trend in the seven-day rolling standard deviation of the HRV (HRVsd) was associated with increases in stress and somatisation over 5 weeks. Furthermore, an increasing HRV trend buffered against the association between HRVsd trend and somatisation change, undoing this association when it was combined with increasing HRV. Depression and anxiety could not berelated to trends in HRV or HRVsd, which was related to observed floor effects. These results show that monitoring trends in daily HRV via wearables holds promise for automated stress monitoring and providing personalised feedback.
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In the literature about web survey methodology, significant e orts have been made to understand the role of time-invariant factors (e.g. gender, education and marital status) in (non-)response mechanisms. Time-invariant factors alone, however, cannot account for most variations in (non-)responses, especially fluctuations of response rates over time. This observation inspires us to investigate the counterpart of time-invariant factors, namely time-varying factors and the potential role they play in web survey (non-)response. Specifically, we study the effects of time, weather and societal trends (derived from Google Trends data) on the daily (non-)response patterns of the 2016 and 2017 Dutch Health Surveys. Using discrete-time survival analysis, we find, among others, that weekends, holidays, pleasant weather, disease outbreaks and terrorism salience are associated with fewer responses. Furthermore, we show that using these variables alone achieves satisfactory prediction accuracy of both daily and cumulative response rates when the trained model is applied to future unseen data. This approach has the further benefit of requiring only non-personal contextual information and thus involving no privacy issues. We discuss the implications of the study for survey research and data collection.
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At gas stations, tetrahydrothiophene (THT) is added to odorless biogas (and natural gas) for quick leak detection through its distinctive smell. However, for low bio and natural gas velocities, evaporation is not complete and the odorization process is compromised, causing odor fluctuations and undesired liquid accumulation on the pipeline. Inefficient odorization not only endangers the safety and well-being of gas users, but also increases gas distribution companies OPEX. To enhance THT evaporation during low bio and natural gas flow, an alternative approach involves improve the currently used atomization process. Electrohydrodynamic Atomization (EHDA), also known as Electrospray (ES), is a technology that uses strong electric fields to create nano and micro droplets with a narrow size distribution. This relatively new atomization technology can improve the odorization process as it can manipulate droplet sizes according to the natural and bio gas flow. BiomEHD aims to develop, manufacture, and test an EHDA odorization system for applying THT in biogas odorization.
