A method and algorithm for remote monitoring of patients in asthma

Glazova, Anna; Yuldashev, Z. M.; Bashkova, Anna

doi:10.1109/usbereit.2018.8384556

Cited by 3 publications

(1 citation statement)

References 8 publications

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“…This introduced a combined framework of wavelet packet transform (WPT) and singular value decomposition (SVD), and the results were found to be satisfactory. Glazova et al [ 30 ] created a monitoring system remotely that monitored asthma patients by analyzing the duration of the tracheal sound. However, the system could not be made fully autonomous.…”

Section: Literature Reviewmentioning

confidence: 99%

Wavelet and Spectral Analysis of Normal and Abnormal Heart Sound for Diagnosing Cardiac Disorders

Hossain

Uddin

Rahman

et al. 2022

BioMed Research International

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Body auscultation is a frequent clinical diagnostic procedure used to diagnose heart problems. The key advantage of this clinical method is that it provides a cheap and effective solution that enables medical professionals to interpret heart sounds for the diagnosis of cardiac diseases. Signal processing can quantify the distribution of amplitude and frequency content for diagnostic purposes. In this experiment, the use of signal processing and wavelet analysis in screening cardiac disorders provided enough evidence to distinguish between the heart sounds of a healthy and unhealthy heart. Real-time data was collected using an IoT device, and the noise was reduced using the REES52 sensor. It was found that mean frequency is sufficiently discriminatory to distinguish between a healthy and unhealthy heart, according to features derived from signal amplitude distribution in the time and frequency domain analysis. The results of the present study indicate the adequate discrimination between the characteristics of heart sounds for automatic detection of cardiac problems by signal processing from normal and abnormal heart sounds.

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Section: Literature Reviewmentioning

confidence: 99%