Results 201 to 210 of about 2,203 (234)

Deciphering Neural Mechanisms Underlying Marmoset Dynamic Natural Behaviors Using a Miniaturized Wireless Large-Scale Coverage Neural Recorder. [PDF]

open access: yesAdv Sci (Weinh)
Liu H   +22 more
europepmc   +1 more source

Automated Cockpit Voice Recorder Sound Classification Using MFCC Features and Deep Convolutional Neural Network

open access: yesLecture Notes on Data Engineering and Communications Technologies, 2021
The main purpose of a cockpit voice recorder (CVR) is to record sounds in the cockpit of an aircraft, including the conversation of the pilots in order to facilitate the investigation of aircraft accidents and incidents. Although the audio recorded by the CVR is a crucial source of evidence for the aircraft crash investigation, it is often a strenuous ...
Rafeed Rahman, Jia Uddin, Uddin Jia
exaly   +3 more sources
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Automated Quality Assessment for Accelerometer-Based Heart Sounds Recorded with a Novel Subcutaneous Medical Implant

2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2022
In the context of monitoring patients with heart failure conditions, the automated assessment of heart sound quality is of major importance to insure the relevance of the medical analysis of the heart sound data. We propose in this study a technique of quality classification based on the selection of a small set of representative features.
Eric Tatulli   +2 more
openaire   +2 more sources

An Automated Digital Sound Recording System: The Amphibulator

Eighth IEEE International Symposium on Multimedia (ISM'06), 2006
Automated digital recording systems are important for studying and monitoring wildlife. Here we describe a new recording system, easily programmable and highly flexible, designed to control the Marantz Professional Solid State Recorder PMD 660. The system is currently being used to monitor the effects of global warming on populations of several species
Mark E. Cambron, Richard G. Bowker
openaire   +1 more source

Automated signal quality assessment of mobile phone-recorded heart sound signals

Journal of Medical Engineering & Technology, 2016
Mobile phones, due to their audio processing capabilities, have the potential to facilitate the diagnosis of heart disease through automated auscultation. However, such a platform is likely to be used by non-experts, and hence, it is essential that such a device is able to automatically differentiate poor quality from diagnostically useful recordings ...
David B, Springer   +7 more
openaire   +2 more sources

Reduction of heart sounds from lung sound recordings by automated gain control and adaptive filtering techniques

2001 Conference Proceedings of the 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2005
Auscultation is an attractive, simple, and noninvasive method for the diagnosis of cardiovascular and pulmonary disorders. However, heart sounds contaminates severely lung sound recordings. The results of our previous researches indicated that the Laplacian electrocardiographic signal (LECG) could be used as a reference for adaptive filtering to reduce
L. Yip, Y.T. Zhang
openaire   +1 more source

Breath sounds analysis for asthma monitoring: A method for automated detection of flow events from tracheal recordings

2014 IEEE Healthcare Innovation Conference (HIC), 2014
Asthma patients often have trouble gaining control of their disease because there is no optimal and reliable method to monitor their progress. While spirometry in the clinic provides adequate information for diagnosis and initial prescription, symptom journals and peak flow meters used at home are not particularly helpful in preventing asthma attacks ...
Matthew A. Christensen   +5 more
openaire   +1 more source

Method of automated signal processing for the carrier rate fluctuations of magnetic recording and detonation of sound

Measurement Techniques, 1991
I. B. K. Bul', Principles of the Theory and Analysis of Magnetic Loops [in Russian], Energiya, Moscow-Leningrad (1964). 2. K.S. Demirchyan and V. L. Chechurin, Machine Methods of Analyzing Electromagnetic Fields [in Russian], Yysshaya Shkola, Moscow (1986), p. 240. 3. E. G. Ismiev, Radiotekh. Elektron., 34, No. 7, 1427 (1989). 4. A.
A. V. Machul'skii, Yu. I. Moroz
openaire   +1 more source

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