scholarly journals Capabilities of computer analysis of breath sounds in patients with COVID-19

2021 ◽  
Vol 38 (3) ◽  
pp. 97-109
Author(s):  
E. G. Furman ◽  
A. O. Charushin ◽  
E. S. Eirikh ◽  
G. B. Furman ◽  
V. L. Sokolovsky ◽  
...  
Keyword(s):  
Healthy Volunteers ◽  
Computer Analysis ◽  
High Frequency ◽  
Breath Sound ◽  
Respiratory Sound ◽  
Computer Diagnosis ◽  
Computer Methods ◽  
Breath Sounds ◽  
Healthy Persons ◽  
Diagnosis Of Diseases

Objective. To develop methods for a rapid distance computer diagnosis of COVID-19 based on the analysis of breath sounds. It is known that changes in breath sounds can be the indicators of respiratory organs diseases. Computer analysis of these sounds can indicate their typical changes caused by COVID-19, and can be used for a rapid preliminary diagnosis of this disease. Materials and methods. The method of fast Fourier transform (FFT) was used for computer analysis of breath sounds, recorded near the mouth of 14 COVID-19 patients (aged 1880 years) and 17 healthy volunteers (aged 548 years). The frequency of breath sound records ranged from 44 to 96 kHz. Unlike the conventional methods of computer analysis for diagnosis of diseases based on respiratory sound studying, we offer to test a high-frequency part of FFT (20006000 kHz). Results. While comparing the breath sound FFT in patients and healthy volunteers, we developed the methods for COVID-19 computer diagnosis and determined the numerical criteria in patients and healthy persons. These criteria do not depend on sex and age of the examined persons. Conclusions. The offered computer methods based on the analysis of breath sound FFT in patients and volunteers permit to diagnose COVID -19 with relatively high diagnostic parameters. These methods can be used in development of noninvasive means for preliminary self-express diagnosis of COVID-19.

The Remote Analysis of Breath Sound in COVID-19 Patients: A Series of Clinical cases (Preprint)

2021 ◽  
Author(s):  
Gregory Furman
Keyword(s):  
Computer Analysis ◽  
High Frequency ◽  
Sampling Rate ◽  
Respiratory Sounds ◽  
Computer Methods ◽  
Computer Assistance ◽  
Self Testing ◽  
Gender And Age ◽  
Diagnostic Values ◽  
Remote Analysis

BACKGROUND Respiratory sounds have been recognized as a possible indicator of behavior and health. Computer analysis of these sounds can indicate of characteristic sound changes caused by COVID-19 and can be used for diagnosis of this illness OBJECTIVE The communication aim is development of fast remote computer-assistance diagnosis methods for COVID-19, based on analysis of respiratory sounds METHODS Fast Fourier transform (FFT) was applied for computer analysis of respiratory sounds recorded near the mouth of 14 COVID-19 patients (age 18-80) and 17 healthy volunteers (age from 5 to 48). Sampling rate was from 44 to 96 kHz. Unlike usual computer-assistance methods of diagnostics of illness, based on respiratory sound analysis, we propose to test the high frequency part of the FFT spectrum (2000-6000 Hz). RESULTS Comparing FFT spectrums of the respiratory sounds of the patients and volunteers we developed computer-assistance methods of COVID 19 diagnostics and determined numerical healthy-ill criterions. These criterions are independent of gender and age of the tested person. CONCLUSIONS The proposed computer methods, based on analysis of the FFT spectrums of respiratory sounds of the patients and volunteers, allows one to automatically diagnose COVID-19 with sufficiently high diagnostic values. These methods can be applied to develop noninvasive self-testing kits for COVID-19.

scholarly journals Artifacts removal from breath sound recordings in pediatric population

2018 ◽  
Vol 154 ◽  
pp. 01046
Author(s):  
Yusuf A Amrulloh ◽  
Jawahir A K Haq
Keyword(s):  
Signal To Noise Ratio ◽  
Pediatric Population ◽  
Breath Sound ◽  
Discrete Wavelet ◽  
Band Pass Filter ◽  
Pass Filter ◽  
Sound Recordings ◽  
Breath Sounds ◽  
Band Pass ◽  
Lower Magnitude

Breath sound recordings from pediatric subjects pose more processing complications. Children, especially the younger ones, are not able to follow instructions to stay calm during recording. This makes their recordings not only contain stationary artifacts but also non-stationary artifacts such as movement of subjects and their heartbeats. Further, the breath sounds from pediatric subjects also have lower magnitude compared to adults. In this work, we proposed to address those problems by developing a method to remove the artifacts from breath sound recordings. We implemented a combination of a Butterworth band pass filter and a discrete wavelet filter. We tested three types of wavelets (Coiflet, Symlet and Daubechies). Ten level decompositions and a set of hard thresholds were implemented in our work. Our results show that our developed method was capable of removing the artifacts significantly while maintaining the signal of interest. The highest signal to noise ratio improvement (10.65dB) was achieved by 32 orders Symlet.

Mood Effects of Prefrontal Repetitive High-Frequency TMS in Healthy Volunteers

CNS Spectrums ◽  
1997 ◽  
Vol 2 (1) ◽  
pp. 53-68 ◽  
Author(s):  
Juliet Dearing Martin ◽  
Mark S. George ◽  
Benjamin D. Greenberg ◽  
Eric M. Wassermann ◽  
Thomas E. Schlaepfer ◽  
...  
Keyword(s):  
Healthy Volunteers ◽  
High Frequency ◽  
Mood Effects

Identification of Ulnar Artery Perforators Using Color Doppler Ultrasonography

2020 ◽  
Vol 36 (09) ◽  
pp. 667-672
Author(s):  
Megumi Ishiko ◽  
Koichi Yano ◽  
Ema Onode ◽  
Kiyohito Takamatsu
Keyword(s):  
Healthy Volunteers ◽  
High Frequency ◽  
Doppler Ultrasonography ◽  
Color Doppler ◽  
Ulnar Artery ◽  
Color Doppler Ultrasonography ◽  
Doppler Us ◽  
Frequency Transducer ◽  
High Frequency Transducer ◽  
Color Doppler Us

Abstract Background The ulnar artery perforator (UAP) flap, which is hairless, thin, and pliable, has been used for the reconstruction of soft tissues from the finger to the elbow. Preoperative planning is essential for a perforator flap surgery, and there are some tests to identify perforators. Color Doppler ultrasonography (US) with a high-frequency transducer helps in detecting decreased flow in smaller vessels, such as perforators. The purpose of this study was to determine the anatomical locations and origins of perforators arising from the ulnar artery using color Doppler US in healthy volunteers. Methods Forty forearms of 20 healthy volunteers were included in the study. Perforators arising from the ulnar artery, within 100 mm proximal to the pisiform, were investigated using color Doppler US with a high-frequency transducer. Results A total of 205 perforators were identified. On comparing the locations in each 20 mm section from the pisiform, the largest number of perforators was 58 (28%), within 20 mm proximal to the pisiform. The axial view demonstrated 44 (21%), 64 (31%), 32 (16%), and 65 (32%) perforators in the radial, ulnar, superficial, and deep aspects of the ulnar artery, respectively. Fifty-two and 28 essential perforators were supplied by the UAPs arising from the superficial and ulnar aspect within 20 mm proximal to the pisiform and between 21 and 40 mm proximal to the pisiform, respectively, while elevating the UAP flap. Conclusion This is the first study to assess the UAP using color Doppler US. Identification of UAP using color Doppler US can be used as a preoperative assessment for reliable elevation of a UAP flap.

SAFETY AND TOLERABILITY OF DIFFERENT PROTOCOLS OF HIGH-FREQUENCY RHYTHMIC TRANSCRANIAL MAGNETIC STIMULATION

2019 ◽  
pp. 26-37
Author(s):  
I.S. Bakulin ◽  
A.G. Poydasheva ◽  
D.Yu. Lagoda ◽  
K.M. Evdokimov ◽  
A.Kh. Zabirova ◽  
...  
Keyword(s):  
Transcranial Magnetic Stimulation ◽  
Side Effects ◽  
Healthy Volunteers ◽  
Brain Stimulation ◽  
High Frequency ◽  
Magnetic Stimulation ◽  
Facial Muscle ◽  
Non Invasive ◽  
Mood Changes ◽  
Invasive Method

Rhythmic transcranial magnetic stimulation (rTMS) is a non-invasive method for brain stimulation, widely used in the treatment of various diseases and in research. In this regard, the problems of rTMS safety and tolerability are becoming especially relevant. Most studies describe only serious side effects of rTMS, which, in fact, are extremely rare. Other side effects which affect rTMS tolerability have been studied to a much lesser extent. The objective of the study is to examine all side effects which occur during and after rTMS sessions through prospective open observation of patients and healthy volunteers. Materials and Methods. Using standardized questionnaires, the authors analyzed the incidence of side effects during high-frequency rTMS and within 24 hours after the procedure in 51 patients with various diseases of the nervous system and in 11 healthy volunteers. Results. The overall frequency of side effects was 59.5 % during stimulation and 50.2 % within 24 hours after the procedure. Serious side effects, which led to cessation of stimulation were recorded in 5 % of cases (n=3). They were associated with the syncope development (n=1) and severe headache (n=2). During rTMS, the most frequent manifestations of side effects were drowsiness (30.4 %), headache (25.8 %) and facial muscle contraction (14.7 %). Twenty-four hours after rTMS the most common manifestations were headache (15.7 %), mood changes (10.2 %) and mental alertness problems (9.4 %). It was found out, that headache was statistically more frequent at the beginning of the rTMS course. During rTMS, headache is often not so heavy and it is usually throbbing. However, within 24 hours after stimulation headache is usually moderate, pressing or dull. Conclusion. The obtained data confirm the importance of using standardized questionnaires for studying side effects and developing methods for their prevention and relief. Keywords: transcranial magnetic stimulation, non-invasive brain stimulation, safety, tolerance, side effects, headache, syncope.

scholarly journals Cough induction by high-frequency chest percussion in healthy volunteers and patients with common cold

2004 ◽  
Vol 98 (8) ◽  
pp. 771-776 ◽  
Author(s):  
P.C.L Lee ◽  
R Eccles
Keyword(s):  
Healthy Volunteers ◽  
Common Cold ◽  
High Frequency
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