Results from 37 people diagnosed with COVID-19 revealed evolutionary forms of these parameters at all stages of the disease, from initial diagnosis to hospitalization and final recovery at home.
Systematic imaging studies show a correlation between cough, speaking and laughing time and intensity, and total droplet production as an approximate indicator of the likelihood of disease spread. Sensors installed in COVID-19 patients, as well as healthy controls both in the hospital and at home, continuously record cough frequency and intensity along with other biometrics.
The results show a decaying trend in the frequency and intensity of cough during disease recovery, but vary widely across patient groups. The method creates opportunities to study biometric models between individuals and population groups.
Because COVID-19 is a respiratory disease, cough and other sounds in the thoracic cavity, trachea, and esophagus are examples of highly relevant biometrics. Laboratory studies show cough-based diagnoses of various respiratory diseases by measuring frequency, intensity, persistence, and unique sound characteristics. Studies of audio recording data show differences in the audio images of COVID-19 positive and negative subjects, including the recording of speech, respiration, and cough sounds. The results may suggest possibilities for disease surveillance in asymptomatic patients.
The results presented here bypass these disadvantages in order to continuously assess respiratory biomarkers related to health status and droplet / aerosol production and to provide additional information on traditional vital functions.
Here, a simple wireless monitor combines a cloud interface and data analytics mode to continuously monitor normal (e.g., heart rate, respiration rate, physical activity, body orientation, and temperature) and abnormal (e.g., coughing, talking) physiological parameters that have a direct bearing on COVID. 19.
The results are quantitative criteria for 1) early detection of symptoms in health care workers and other high-risk populations, 2) monitoring of symptomatic progression of infected individuals, and 3) monitoring of treatment responses in clinical settings. In addition, the systematic studies presented here show that cough, speech, and laughter events measured with these devices correlate with total droplet production.
These results provide an opportunity to quantify the infectivity of individuals as critical information in patient care and for better stratification of risks in contact tracing and individual quarantines.
Statistics can provide insights into the development of guidelines for disease management and isolation. However, further studies in an expanded patient population with detailed demographic information are necessary to conduct large-scale studies on demographic dependence and / or individual variability in relevant biometrics.
Source: ANI
Source: The Nordic Page