METHODS: A pulmonary function test using a spirometer was carried out to measure the lung function of the traffic policemen. The personal exposure level to PM2.5 was measured using a pump with a PVC filter and 5.0μm pore size. A questionnaire requesting the background data, such as age, height, and weight, was also used for testing lung function abnormalities.
RESULTS: The PM2.5 personal exposure level was found to be significantly related to lung function (predicted FEV1 and predicted FVC) at p-value function deterioration among traffic policemen. These baseline data can serve as a reference for the top management of traffic police to aid in the development of occupational safety and health guidelines for police officers, as the traffic police are not covered by the Occupational Safety and Health Act (OSHA, Act 514 1994).
METHODS: Medline (1946-) and Embase (1947-) were searched until July 1, 2017. A search strategy was used to identify studies that reported NPIF values for defined healthy or disease states. All studies providing original data were included. The study population was defined as having either normal nasal breathing or nasal obstruction. A meta-analysis of the mean data was presented in forest plots, and data were presented as mean (95% confidence interval [CI]).
RESULTS: The search yielded 1,526 studies, of which 29 were included. The included studies involved 1,634 subjects with normal nasal breathing and 817 subjects with nasal obstruction. The mean NPIF value for populations with normal nasal breathing was 138.4 (95% CI: 127.9-148.8) L/min. The mean value for populations with nasal obstruction was 97.5 (95% CI: 86.1-108.8) L/min.
CONCLUSIONS: Current evidence confirms a difference between mean NPIF values of populations with and without nasal obstruction. The mean value of subjects with no nasal obstruction is 138.4 L/min, and the mean value of nasally obstructed populations is 97.5 L/min. Prospective studies adopting a standardized procedure are required to further assess normative NPIF values. Laryngoscope, 131:260-267, 2021.
OBJECTIVE: The main objective of this paper is to develop a robust algorithm to extract respiration rate using the contactless displacement sensor.
METHODS: In this study, chest movements were used as an indicative of inspiration and expiration to measure respiratory rate using the contactless displacement sensor. The contactless optical signals were recorded from 32 healthy subjects in four different controlled breathing conditions: rest, coughing, talking and hand movement to obtain the motion artifacts that the patients may have in the emergency department. The Empirical mode decomposition (EMD) algorithm was used to derive continuous RR signal from the contactless optical signal.
RESULTS: The analysis showed that there is a good correlation (0.9702) with RMSE of 0.33 breaths per minutes between the contact respiration rate and contactless respiration rate using empirical mode decomposition method.
CONCLUSION: It can be concluded that the empirical mode decomposition method can extract the respiration rate of the contactless optical signal from chest movement.