The air quality index based on measurements of mobile air quality monitoring station at the waste-to-energy incineration plant PLTSa Bantargebang

Ambient air quality monitoring at waste-to-energy incineration pilot plant PLTSa Bantargebang is performed using a mobile monitoring station. The mobile monitoring station is equipped with meteorological and emission (CO, O3, NO2, PM10, PM2.5, and SO2) measurement. The monitoring was performed for 24 hour with 1 minute intervals. The emission measurement data was analyzed using Indonesian Air pollution standard index regulation (PermenLHK P.14/2020). The CO, O3, NO2, PM10, and SO2 index were in good category (1-50), while the PM2.5 index was classified as moderate (65.992). The results show that the air quality at PLTSa Bantargebang is still acceptable for human health.

Determination of the informational content of symptoms in the dynamic processes of assessing the patient’s condition in e-health

The study is devoted to substantiating the tactics of choosing the signs of the patient's condition for diagnostic decision-making on corrective medical intervention in mobile medicine. The aim of the research: to study a creation of a methodology for determining the integral informativeness of the patient's symptoms during remote monitoring of his condition. Materials and methods: this article is based on search results in PubMed, Scopus, MEDLINE, EMBASE, PsycINFO, Global Health, Web of Science, Cochrane Library, UK NHS HTA articles published between January 1991 and January 2021 and containing the search terms “information technology”, “Mobile medicine”, “digital pathology” and “deep learning”, as well as the results of the authors' own research. The authors independently extracted data on concealment of distribution, consistency of distribution, blindness, completeness of follow-up, and interventions. Results: concluded that to determine the Informativeness of symptoms in mobile monitoring of patients, it is possible to use risk indicators of predicted conditions as a universal method. Given that the Informativeness of the patient's condition changes constantly, for online diagnosis of conditions during remote monitoring of the patient it is recommended to use the function of informative symptoms from time to time and use a set of approaches to assess the Informativeness of patient symptoms. It is proposed to use the strategy of diagnosis and treatment using probabilistic algorithms based on the values of the risk of complications of the pathological process, as well as the formulas of Kulbach and Shannon to determine individual trends in the pathological patient process. Conclusion: there was proposed to use risk indicators of predicted conditions as a universal method for determining the informational content of symptoms in mobile monitoring of patients.

Mobile monitoring of traffic-related air pollution for a prospective cohort study in the greater Seattle area

Growing evidence links traffic-related air pollution (TRAP) to adverse health effects. Previous air pollution studies focused on a few commonly measured pollutants with poor spatial resolution. Well-designed mobile monitoring studies may address this limitation. We designed an extensive mobile monitoring campaign to characterize TRAP exposure levels for a Seattle-based cohort, the Adult Changes in Thought (ACT) study. The campaign measured particulate matter ≤ 2.5 µm in diameter (PM2.5), ultrafine particulates (UFP), black carbon (BC), nitrogen dioxide (NO2) and carbon dioxide (CO2) at 309 stop locations representative of the cohort. We collected about 29 two-minute measures at each location during all seasons, days of the week, and most times of day for a one-year period. Annual average concentrations of UFPs had similar degrees of spatial variability as BC and NO2 but higher degrees of variability as CO2 and PM2.5. UFPs had less temporal variability than other pollutants. Validation showed good agreement between our BC, NO2, and PM2.5 measurements and regulatory monitoring sites. The results from this campaign will be used to assess TRAP exposure in the ACT cohort.SynopsisWe assessed annual-average traffic-pollutant levels with high spatial resolution at locations representative of participant residences using a temporally balanced short-term mobile monitoring campaign.Abstract Figure

Clinical evaluation of a wearable sensor for mobile monitoring of respiratory rate on hospital wards

A wireless and wearable system was recently developed for mobile monitoring of respiratory rate (RR). The present study was designed to compare RR mobile measurements with reference capnographic measurements on a medical-surgical ward. The wearable sensor measures impedance variations of the chest from two thoracic and one abdominal electrode. Simultaneous measurements of RR from the wearable sensor and from the capnographic sensor (1 measure/minute) were compared in 36 ward patients. Patients were monitored for a period of 182 ± 56 min (range 68–331). Artifact-free RR measurements were available 81% of the monitoring time for capnography and 92% for the wearable monitoring system (p < 0.001). A total of 4836 pairs of simultaneous measurements were available for analysis. The average reference RR was 19 ± 5 breaths/min (range 6–36). The average difference between the wearable and capnography RR measurements was − 0.6 ± 2.5 breaths/min. Error grid analysis showed that the proportions of RR measurements done with the wearable system were 89.7% in zone A (no risk), 9.6% in zone B (low risk) and < 1% in zones C, D and E (moderate, significant and dangerous risk). The wearable method detected RR values > 20 (tachypnea) with a sensitivity of 81% and a specificity of 93%. In ward patients, the wearable sensor enabled accurate and precise measurements of RR within a relatively broad range (6–36 b/min) and the detection of tachypnea with high sensitivity and specificity.