scholarly journals Detection of Respiratory Phases in a Breath Sound and Their Subsequent Utilization in a Diagnosis

2021 ◽  
Vol 11 (14) ◽  
pp. 6535
Author(s):  
David Skalicky ◽  
Vaclav Koucky ◽  
Daniel Hadraba ◽  
Martin Viteznik ◽  
Martin Dub ◽  
...  
Keyword(s):  
Background Noise ◽  
Ambient Noise ◽  
Respiratory Sounds ◽  
Lung Sounds ◽  
New Approach ◽  
System A ◽  
Lung Auscultation ◽  
Human Ear ◽  
Low Sensitivity ◽  
Respiratory Phases

Detection of lung sounds and their propagation is a powerful tool for analysing the behaviour of the respiratory system. A common approach to detect the respiratory sounds is lung auscultation, however, this method has significant limitations including low sensitivity of human ear or ambient background noise. This article targets the major limitations of lung auscultation and presents a new approach to analyse the respiratory sounds and visualise them together with the respiratory phases. The respiratory sounds from 41 patients were recorded and filtered to eliminate the ambient noise and noise artefacts. The filtered signal is processed to identify the respiratory phases. The article also contains an approach for removing the noise that is very difficult to filter but the removal is crucial for identifying the respiratory phases. Finally, the respiratory phases are overlaid with the frequency spectrum which simplifies the orientation in the recording and additionally offers the information on the inter-individual ratio of the inhalation and exhalation phases. Such interpretation provides a powerful tool for further analysis of lung sounds, simplifythe diagnosis of various types of respiratory tract dysfunctions, and returns data which are comparable among the patients.

A new approach for the adaptation of HMMs to reverberation and background noise

2008 ◽  
Vol 50 (3) ◽  
pp. 244-263 ◽  
Author(s):  
Hans-Günter Hirsch ◽  
Harald Finster
Keyword(s):  
Background Noise ◽  
New Approach

A nano-composite resist system: A new approach to nanometer pattern fabrication

1997 ◽  
Vol 35 (1-4) ◽  
pp. 113-116 ◽  
Author(s):  
T. Ishii ◽  
H. Nozawa ◽  
T. Tamamura
Keyword(s):  
Nano Composite ◽  
New Approach ◽  
System A ◽  
Nanometer Pattern

Nasal Tramadol delivery system: A new approach for improved pain therapy

2011 ◽  
Vol 5 (S2) ◽  
pp. 449-452 ◽  
Author(s):  
Shaher Duchi ◽  
Elka Touitou ◽  
Lorenzo Pradella ◽  
Francesco Marchini ◽  
Denize Ainbinder
Keyword(s):  
Delivery System ◽  
Pain Therapy ◽  
New Approach ◽  
System A

scholarly journals Classification of Lung Sounds and Disease Prediction using Dense CNN Network

2021 ◽  
Vol 11 (1) ◽  
pp. 195-198
Author(s):  
Suyash Lakhani ◽  
◽  
Ridhi Jhamb ◽  
Keyword(s):  
Respiratory Sounds ◽  
Respiratory Sound ◽  
Lung Sounds ◽  
Dense Network ◽  
Lung Sound ◽  
Respiratory Dysfunction ◽  
Respiratory Disorders ◽  
Respiratory Illnesses ◽  
In The Beginning

Respiratory illnesses are a main source of death in the world and exact lung sound identification is very significant for the conclusion and assessment of sickness. Be that as it may, this method is vulnerable to doctors and instrument limitations. As a result, the automated investigation and analysis of respiratory sounds has been a field of great research and exploration during the last decades. The classification of respiratory sounds has the potential to distinguish anomalies and diseases in the beginning phases of a respiratory dysfunction and hence improve the accuracy of decision making. In this paper, we explore the publically available respiratory sound database and deploy three different convolutional neural networks (CNN) and combine them to form a dense network to diagnose the respiratory disorders. The results demonstrate that this dense network classifies the sounds accurately and diagnoses the corresponding respiratory disorders associated with them.

Prediction of pressure-generated earth motion using optimum filters

1975 ◽  
Vol 65 (3) ◽  
pp. 637-650
Author(s):  
E. J. Douze ◽  
G. G. Sorrells
Keyword(s):  
Atmospheric Pressure ◽  
Acoustic Waves ◽  
Background Noise ◽  
Single Channel ◽  
Pressure Variation ◽  
Long Period ◽  
System A ◽  
The Earth ◽  
Multichannel Filtering ◽  
Time Trace

abstract The performance of long-period seismographs is often seriously degraded by atmospheric pressure variation; the problem is particularly severe at periods greater than 20 sec. The pressure variations associated with wind-generated turbulence and acoustic waves are sufficient to deform the surface of the Earth, thus adding to the background noise level recorded by the seismometer. If microbarographs are operated together with the seismograph system, a large percentage of the atmospherically generated noise can be eliminated by the use of optimum filters. The filters are designed based on the least-mean-squares criterion, with the seismograph time trace as the desired output and the microbarographs as the inputs. Single-channel filters, using only one microbarograph, located at the seismometer vault are used to attenuate wind-generated noise. In order to attenuate the noise on windless days from other pressure sources, multichannel filtering is usually necessary and therefore an array of microbarographs is required. The filters used to predict the wind-generated noise are shown to be stable despite the complicated source. The performance of the multichannel varies widely depending on the structure of pressure variations predominating in the atmosphere.

Active Noise Control for Hearing Screening Test

2010 ◽  
Vol 1 (3) ◽  
pp. 67-78
Author(s):  
Dhifaf Azeez ◽  
Mohd Alauddin Mohd Ali ◽  
Hafizah Husain ◽  
Gan Kok Beng ◽  
Cila Umat
Keyword(s):  
Screening Test ◽  
Ambient Noise ◽  
Noise Control ◽  
Sampling Rate ◽  
Active Noise Control ◽  
Hearing Screening ◽  
Labview Software ◽  
Active Noise ◽  
Human Ear ◽  
Acoustic Domain

A hearing screening test is a method to determine human ear disorders and conventional audiometers and audiologists are required to perform the test. However, this procedure is difficult to implement, especially in a remote site such as a factory or a school due to the ambient noise that may cause test inaccuracy. In this work, the application of active noise control (ANC) is proposed to reduce the ambient noise using a personal computer in a hearing screening test. The ANC algorithm was simulated in MATLAB software and implemented using a computer with data acquisition modules and LabVIEW software. Results show that anti-noise was successfully generated in the electrical domain but no reduction was observed in the acoustic domain. ANC is a deterministic application that requires a real-time operating system to respond to the input with precisely timed output. To have an effective ANC system, the processing time has to be less than 0.125 ms at 8 KHz sampling rate.

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