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 THE REMOTE ANALYSIS OF BREATH SOUND IN COVID-19 PATIENTS: A SERIES OF CLINICAL CASES

2020 ◽  
Author(s):  
Evgeny G. Furman ◽  
Artem Charushin ◽  
Ekaterina Eirikh ◽  
Sergey Malinin ◽  
Valerii Sheludko ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Healthy Volunteers ◽  
Sampling Rate ◽  
Computer Method ◽  
Respiratory Sounds ◽  
Computer Assistance ◽  
Self Testing ◽  
Diagnostic Values ◽  
Is Development ◽  
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. Purpose: The communication aim is development of fast remote computer-assistance diagnosis of COVID-19, based on analysis of respiratory sounds. Materials and Methods: Fast Fourier transform (FFT) was applied for analyses of respiratory sounds recorded near the mouth of 9 COVID-19 patients and 4 healthy volunteers. Sampling rate was 48 kHz. Results: Comparing of FFT spectrums of the respiratory sounds of the patients and volunteers we proposed numerical healthy-ill criterions. Conclusions: The proposed computer method, 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. This method can be applied at development of noninvasive self-testing kits for COVID-19.

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.

scholarly journals RTLIO: Real-Time LiDAR-Inertial Odometry and Mapping for UAVs

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 3955
Author(s):  
Jung-Cheng Yang ◽  
Chun-Jung Lin ◽  
Bing-Yuan You ◽  
Yin-Long Yan ◽  
Teng-Hu Cheng
Keyword(s):  
Feedback Control ◽  
Real Time ◽  
High Frequency ◽  
Indoor Environment ◽  
Indoor Localization ◽  
Sampling Rate ◽  
Outdoor Environment ◽  
Position Accuracy ◽  
Graph Optimization ◽  
Pose Graph Optimization

Most UAVs rely on GPS for localization in an outdoor environment. However, in GPS-denied environment, other sources of localization are required for UAVs to conduct feedback control and navigation. LiDAR has been used for indoor localization, but the sampling rate is usually too low for feedback control of UAVs. To compensate this drawback, IMU sensors are usually fused to generate high-frequency odometry, with only few extra computation resources. To achieve this goal, a real-time LiDAR inertial odometer system (RTLIO) is developed in this work to generate high-precision and high-frequency odometry for the feedback control of UAVs in an indoor environment, and this is achieved by solving cost functions that consist of the LiDAR and IMU residuals. Compared to the traditional LIO approach, the initialization process of the developed RTLIO can be achieved, even when the device is stationary. To further reduce the accumulated pose errors, loop closure and pose-graph optimization are also developed in RTLIO. To demonstrate the efficacy of the developed RTLIO, experiments with long-range trajectory are conducted, and the results indicate that the RTLIO can outperform LIO with a smaller drift. Experiments with odometry benchmark dataset (i.e., KITTI) are also conducted to compare the performance with other methods, and the results show that the RTLIO can outperform ALOAM and LOAM in terms of exhibiting a smaller time delay and greater position accuracy.

scholarly journals High sampling rate thermistor string observations at the slope of Great Meteor Seamount

Ocean Science ◽  
2005 ◽  
Vol 1 (1) ◽  
pp. 17-28 ◽  
Author(s):  
H. van Haren ◽  
R. Groenewegen ◽  
M. Laan ◽  
B. Koster
Keyword(s):  
High Frequency ◽  
North Atlantic Ocean ◽  
Sampling Rate ◽  
Very High Frequency ◽  
High Sampling ◽  
High Sampling Rate ◽  
In Situ Calibration ◽  
Great Meteor Seamount ◽  
Very High

Abstract. A high sampling rate (1 Hz) thermistor string has been built to accommodate the scientific need to accurately monitor high-frequency and vigorous internal wave and overturning processes in the ocean. The thermistors and their custom designed electronics can register temperature at an estimated precision of about 0.001° C with a response time faster than 0.25 s down to depths of 6000 m. With a quick in situ calibration using SBE 911 CTD an absolute accuracy of 0.005° C is obtained. The present string holds 128 sensors at 0.5 m intervals, which are all read-out within 0.5 s. When sampling at 1 Hz, the batteries and the memory capacity of the recorder allow for deployments of up to 2 weeks. In this paper, the instrument is described in some detail. Its performance is illustrated with examples from the first moored observations, which show Kelvin-Helmholtz overturning and very high-frequency (Doppler-shifted) internal waves besides occasionally large turbulent bores moving up the sloping side of Great Meteor Seamount, Canary Basin, North-Atlantic Ocean.

Behavioral evidence for post-pause reduced responsiveness in the electrosensory system ofGymnotus carapo

2002 ◽  
Vol 205 (16) ◽  
pp. 2525-2533 ◽  
Author(s):  
Stefan Schuster
Keyword(s):  
High Frequency ◽  
Sampling Rate ◽  
Sensory System ◽  
Low Frequency ◽  
Electric Organ ◽  
Weakly Electric Fish ◽  
Sensory Stimuli ◽  
Novelty Response ◽  
Electric Organ Discharges ◽  
Electrical Stimuli

SUMMARYGymnotiform weakly electric fish find their way in the dark using a continuously operating active sensory system. An electric organ generates a continuous train of discharges (electric organ discharges, EODs), and tuberous high-frequency electroreceptors monitor the pattern of transcutaneous current flow associated with each EOD. Here, I report that a prior interruption to the continuous train of EODs dramatically affects a response shown by many pulse-type gymnotids. In this so-called novelty response, fish normally raise their electrosensory sampling rate in response to novel sensory stimuli. The gymnotid Gymnotus carapo was induced to pause its EODs briefly, and the novelty response to sensory stimuli given post-pause was analyzed. Mechanosensory stimuli given as early as 20 EODs after a pause elicited clear novelty responses, but strong high-frequency electrical stimuli were ineffective at this time. Moreover, high-frequency electrical stimuli remained less efficient in eliciting normal-sized responses until approximately 2000 EODs, or 40s, after a pause. The post-pause inefficiency of high-frequency stimuli was not due to an inappropriate choice of intensity or their temporal patterning and did not result from the stimulation that caused the pausing. Low-frequency stimuli that also recruited ampullary electroreceptors were more efficient than high-frequency stimuli in eliciting post-pause responses. These findings show that continuous activity is required either to maintain sensitivity to high-frequency electrical stimuli or to ensure that such stimuli are able to modulate efficiently the pacemaker that sets the discharge frequency.

scholarly journals Optimization of sampling rate and smoothing improves classification of high frequency power in electrocorticographic brain signals

2018 ◽  
Vol 4 (4) ◽  
pp. 045012 ◽  
Author(s):  
Mariana P Branco ◽  
Zachary V Freudenburg ◽  
Erik J Aarnoutse ◽  
Mariska J Vansteensel ◽  
Nick F Ramsey
Keyword(s):  
High Frequency ◽  
Sampling Rate ◽  
High Frequency Power ◽  
Brain Signals ◽  
Frequency Power

EXPLORING MULTI-RESOLUTION AND MULTI-SCALING VOLATILITY FEATURES

Fractals ◽  
2004 ◽  
Vol 12 (02) ◽  
pp. 179-195 ◽  
Author(s):  
ENRICO CAPOBIANCO
Keyword(s):  
High Frequency ◽  
Asset Price ◽  
Sampling Rate ◽  
Time Frame ◽  
Stock Index ◽  
Variation Principle ◽  
Suitable Model ◽  
Integrated Volatility ◽  
Stochastic Characterization ◽  
Information Set

One of the most recent results in empirical finance is the achievement of an accuracy gain for the volatility estimates from the use of high-frequency samples. In many applications, for instance, the observed intra-day data become the best informative source of estimation for the daily volatilites. This information set, or filtration in probability terms, can in theory be optimally exploited while adopting an increasingly finer sampling rate, a fact which finds justification when assuming a stochastic characterization of the problem in terms of so-called semimartingales. These instruments are very useful for representing asset price dynamics, and in recent proposals supply realized and integrated volatility measures. The former volatility is the empirical approximation of the latter, an average of high frequency returns observed within a certain time frame. Semimartingales become suitable model tools by allowing for the quadratic variation principle to hold. This in turn means that the convergence of the realized to the integrated volatility can be verified; conversely, from both theoretical and experimental standpoints, the cumulative squared high frequency returns represent consistent estimators of the integrated volatility measure. The goal of this work is twofold: first, to show with simulations the quality of the convergence for time-based estimators, compared to that obtained when time-scale coordinate wavelet tranforms are considered. Second, to verify that special families of wavelet decompose returns and allow for multi-scaling features to be revealed, together with the possible presence of underlying nonlinear dynamics of stock index return volatility.

scholarly journals Clinical aspects of congenital microcephaly syndrome by Zika virus in a rehabilitation center for patients with microcephaly

2019 ◽  
Vol 65 (10) ◽  
pp. 1249-1253 ◽  
Author(s):  
Kelson James Almeida ◽  
Augusto César Beserra Martins ◽  
Isadora Costa Coelho Gayoso e Almendra ◽  
Gabriel Medina Sobreira de Meneses ◽  
Thales Daniel de Oliveira Sampaio ◽  
...  
Keyword(s):  
Zika Virus ◽  
Medical Records ◽  
High Frequency ◽  
Clinical Aspects ◽  
Serological Tests ◽  
Cross Sectional ◽  
Clinical Variables ◽  
Gender And Age ◽  
High Prevalence ◽  
Congenital Microcephaly

SUMMARY OBJECTIVE In this study, we intend to identify the prevalence of clinical variables in children with microcephaly. METHODS This is a cross-sectional and observational study with data collected from medical records of patients admitted to the microcephaly outpatient clinic of a referral center in Teresina-PI. Demographic (gender and age) and clinical data (presence of epilepsy, dysphagia, irritability, and associated comorbidities) were collected. The frequency of Zika virus as a probable etiology was determined from computed tomography patterns and the exclusion of other etiologies by serological tests. RESULTS A total of 67 patient records were evaluated, of which 31 were male and 36 were female, with a mean age of 1 year and 10 months. The most prevalent clinical variables were epilepsy, present in 47 children (70.2%), and irritability in 37 (55.2%). Also with a high frequency, 22 had dysphagia (32.8%), and 13 had musculoskeletal comorbidities (19.4%). Only three patients in the sample had cardiac abnormalities (4.5%), and no endocrine comorbidity was found. A total of 38 children in the sample (56.7%) presented ZIKV as a probable etiology and, in these cases, there was a higher frequency of epilepsy and dysphagia compared to other etiologies, although not statistically significant. CONCLUSION Epilepsy, irritability, dysphagia, and musculoskeletal comorbidities were the most frequent clinical variables in children with microcephaly. There was a high prevalence of congenital ZIKV microcephaly syndrome in this sample.

scholarly journals A 10-bit 150MS/s Pipelined ADC with 2.5bit Gain Stage for High Frequency Applications

2019 ◽  
Vol 8 (10) ◽  
pp. 883-886
Keyword(s):  
Power Supply ◽  
High Frequency ◽  
Sampling Rate ◽  
High Accuracy ◽  
Pipelined Adc ◽  
Effective Number ◽  
Digital Converter ◽  
Analog To Digital ◽  
Computational Burden ◽  
Gain Stage

This paper proposes a 10-bit pipelined Analog to Digital Converter (ADC) which incorporates various techniques for lesser power and higher performance. The proposed method reduces the computational burden while comparing to the modified Monte-Carlo (MC) method. Pipelined ADC has N number of stages, it has higher resolution and higher frequency of conversion while comparing to other ADCs. The proposed ADC employs five 2.5bit gain stages; instead of 1.5bit gain stages for high accuracy. This method is implemented in the Tanner Software with the Generic 250nm library at a maximum power supply of 5V. The maximum frequency attained is 150MHz; and the ADC exhibits a SNR of 61.96dB. It also attains a 10bits as effective number of bits at the maximum sampling rate.

scholarly journals Antiforensics of Speech Resampling Using Dual-Path Strategy

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Diqun Yan ◽  
Yongkang Gong ◽  
Tianyun Liu
Keyword(s):  
High Frequency ◽  
Gaussian White Noise ◽  
Sampling Rate ◽  
Low Frequency ◽  
Frequency Component ◽  
High Frequency Component ◽  
Perceptual Quality ◽  
Median Filtering ◽  
Noise Perturbation

Resampling is an operation to convert a digital speech from a given sampling rate to a different one. It can be used to interface two systems with different sampling rates. Unfortunately, resampling may also be intentionally utilized as a postoperation to remove the manipulated artifacts left by pitch shifting, splicing, etc. To detect the resampling, some forensic detectors have been proposed. Little consideration, however, has been given to the security of these detectors themselves. To expose weaknesses of these resampling detectors and hide the resampling artifacts, a dual-path resampling antiforensic framework is proposed in this paper. In the proposed framework, 1D median filtering is utilized to destroy the linear correlation between the adjacent speech samples introduced by resampling on low-frequency component. And for high-frequency component, Gaussian white noise perturbation (GWNP) is adopted to destroy the periodic resampling traces. The experimental results show that the proposed method successfully deceives the existing resampling forensic algorithms while keeping good perceptual quality of the resampled speech.

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