Heart Sound Monitor for Biomedical Instrumentation

2013 ◽  
Vol 303-306 ◽  
pp. 650-653
Author(s):  
Sirimonpak Sutdipong ◽  
Khanchai Tunlasakun
Keyword(s):  
Fourier Transforms ◽  
Heart Sound ◽  
Digital Signal ◽  
Electrical Signal ◽  
Sound Card ◽  
Sound Processing ◽  
Biomedical Instrumentation ◽  
Condenser Microphone ◽  
Processing Program ◽  
Short Time

This research presents the design and development of the heart sound monitor for biomedical instrumentation which can be worked with a personal computer. The prototype will receive the heart sound via the condenser microphone built-in the stethoscope. The condenser microphone will be conversed the air pressure from heart beats to electrical signal that signal will transformed to computer via sound card. The sound card will be conversed the analog signal to digital signal for process by heart sound processing program developed by LabVIEW program. The signal will be analyzed with short time Fourier transforms in heart sound processing program by graphical user interface. The user is able to select a band pass of signal for filter and choose the frequency spectrum of heart sound for display. The output database from this prototype is necessary for Medical Education or Clinical Practice.

Heart Sound Monitor for Bio-Signal Learning

2013 ◽  
Vol 680 ◽  
pp. 644-648
Author(s):  
Khanchai Tunlasakun
Keyword(s):  
Fourier Transforms ◽  
Heart Sound ◽  
Digital Signal ◽  
Electrical Signal ◽  
Sound Card ◽  
Sound Processing ◽  
Condenser Microphone ◽  
Processing Program ◽  
Band Pass ◽  
Short Time

This research presents the design and development of the heart sound monitor for bio-signal learning which can be worked with a personal computer. The prototype will receive the heart sound via the condenser microphone built-in the stethoscope. The condenser microphone will be conversed the air pressure from heart beats to electrical signal that signal will transformed to computer via sound card. The sound card will be conversed the analog signal to digital signal for process by heart sound processing program developed by LabVIEW program. The signal will be analyzed with short time Fourier transforms in heart sound processing program by graphical user interface. The user is able to select a band pass of signal for filter and choose the power spectrum of heart sound for display. The output database from this prototype is necessary for Medical Education or Clinical Practice. The prototype was tested and it worked satisfactory.

Identification of Static Unbalance Wheel of Passenger Car Carried out on a Road

2014 ◽  
Vol 214 ◽  
pp. 48-57 ◽  
Author(s):  
Krzysztof Prażnowski ◽  
Sebastian Brol ◽  
Andrzej Augustynowicz
Keyword(s):  
Fourier Transform ◽  
Wavelet Transform ◽  
Constant Velocity ◽  
Fourier Transforms ◽  
Static Condition ◽  
Rotational Frequency ◽  
Acceleration Sensor ◽  
Short Time Fourier Transform ◽  
Road Roughness ◽  
Short Time

This paper presents a method of identification of non-homogeneity or static unbalance of the structure of a car wheel based on a simple road test. In particular a method the detection of single wheel unbalance is proposed which applies an acceleration sensor fixed on windscreen. It measures accelerations cause by wheel unbalance among other parameters. The location of the sensor is convenient for handling an autonomous device used for diagnostic purposes. Unfortunately, its mounting point is located away from wheels. Moreover, the unbalance forces created by wheels spin are dumped by suspension elements as well as the chassis itself. It indicates that unbalance acceleration will be weak in comparison to other signals coming from engine vibrations, road roughness and environmental effects. Therefore, the static unbalance detection in the standard way is considered problematic and difficult. The goal of the undertaken research is to select appropriate transformations and procedures in order to determine wheel unbalance in these conditions. In this investigation regular and short time Fourier transform were used as well as wavelet transform. It was found that the use of Fourier transforms is appropriate for static condition (constant velocity) but the results proves that the wavelet transform is more suitable for diagnostic purposes because of its ability of producing clearer output even if car is in the state of acceleration or deceleration. Moreover it was proved that in the acceleration spectrum of acceleration measured on the windscreen a significant peak can be found when car runs with an unbalanced wheel. Moreover its frequency depends on wheel rotational frequency. For that reason the diagnostic of single wheel unbalance can be made by applying this method.

scholarly journals Retention Of Cardiac Auscultation Skill Requires Paired Visual And Audio Information In New Learners

2008 ◽  
Vol 2 (2) ◽  
Author(s):  
Glenn Nordehn ◽  
Spencer Strunic ◽  
Tom Soldner ◽  
Nicholas Karlisch ◽  
Ian Kramer ◽  
...  
Keyword(s):  
Visual Information ◽  
Heart Sound ◽  
Heart Sounds ◽  
Sound Recognition ◽  
Cardiac Auscultation ◽  
Time Period ◽  
Significant Difference ◽  
Post Test ◽  
Short Time ◽  
Audio Information

Introduction: Cardiac auscultation accuracy is poor: 20% to 40%. Audio-only of 500 heart sounds cycles over a short time period significantly improved auscultation scores. Hypothesis: adding visual information to an audio-only format, significantly (p<.05) improves short and long term accuracy. Methods: Pre-test: Twenty-two 1st and 2nd year medical student participants took an audio-only pre-test. Seven students comprising our audio-only training cohort heard audio-only, of 500 heart sound repetitions. 15 students comprising our paired visual with audio cohort heard and simultaneously watched video spectrograms of the heart sounds. Immediately after trainings, both cohorts took audio-only post-tests; the visual with audio cohort also took a visual with audio post-test, a test providing audio with simultaneous video spectrograms. All tests were repeated in six months. Results: All tests given immediately after trainings showed significant improvement with no significant difference between the cohorts. Six months later neither cohorts maintained significant improvement on audio-only post-tests. Six months later the visual with audio cohort maintained significant improvement (p<.05) on the visual with audio post-test. Conclusions: Audio retention of heart sound recognition is not maintained if: trained using audio-only; or, trained using visual with audio. Providing visual with audio in training and testing allows retention of auscultation accuracy. Devices providing visual information during auscultation could prove beneficial.

scholarly journals Development of a New Analytical Method for the Electrocardiogram Using Short-Time First Fourier Transforms

1999 ◽  
Vol 63 (12) ◽  
pp. 941-944 ◽  
Author(s):  
Masatoshi Hara ◽  
Katsuhiko Tsuchiya ◽  
Toshihiko Nanke ◽  
Narumi Mori ◽  
Fumihiko Miyake ◽  
...  
Keyword(s):  
Analytical Method ◽  
Fourier Transforms ◽  
Short Time

The Functional Study of Artificial Heart Valve Based on HHT

2014 ◽  
Vol 568-570 ◽  
pp. 249-253
Author(s):  
Bin Bin Liu ◽  
Ke Liang Zhou ◽  
Cen Ye ◽  
Ming Li Zhang
Keyword(s):  
Heart Valve ◽  
Artificial Heart ◽  
Heart Sound ◽  
Artificial Heart Valve ◽  
Functional Study ◽  
Hilbert Spectrum ◽  
Hilbert Huang Transform ◽  
Time Frequency ◽  
Time Average ◽  
Short Time

The functional study of artificial heart valve has the positive significance on the postoperative care of the patients with valvular heart disease and the precaution of postoperative complications. The analysis of the heart sounds is the most direct way to estimate the function normally of heart. Because of the heart sound is nonlinear and nonstationary. Compared with the normal method of time-frequency analysis, Hilbert-Huang transform can analyze the nonstationary and nonlinear signals more accurate and more effective. Hilbert-Huang transform is introduced to the functional study of artificial heart valve. It used for extracting the inherent characteristics. Using the empirical mode decomposition (EMD), the heart sound was decomposed into a series of intrinsic mode functions (IMF). The Hilbert spectrum was established by the calculating results of these IMFs. The Hilbert spectrum has the characters of time-frequency-energy, and then the marginal spectrum was structured. Comparison with the characters of pre-operation and post-operation was used for reveal the function of artificial heart valve. At last, we use the short-time average energy and the short-time average range to verify the credibility of Hilbert-Huang transforms method. The result of simulation show that this method was well analyzed the function of artificial heart valve.

Independent component analysis of short-time Fourier transforms for spontaneous EEG/MEG analysis

NeuroImage ◽  
2010 ◽  
Vol 49 (1) ◽  
pp. 257-271 ◽  
Author(s):  
Aapo Hyvärinen ◽  
Pavan Ramkumar ◽  
Lauri Parkkonen ◽  
Riitta Hari
Keyword(s):  
Independent Component Analysis ◽  
Fourier Transforms ◽  
Component Analysis ◽  
Independent Component ◽  
Short Time

scholarly journals Stepwise Transformation of Algorithms into Array Processor Architectures by the DECOMP

VLSI Design ◽  
1995 ◽  
Vol 3 (1) ◽  
pp. 67-80
Author(s):  
Uwe Vehlies
Keyword(s):  
Digital Signal ◽  
Design Flow ◽  
Array Processor ◽  
Formal Approach ◽  
Processor Architectures ◽  
Massively Parallel Systems ◽  
Signal Processing Algorithms ◽  
Hardware Description ◽  
High Level ◽  
Short Time

A formal approach for the transformation of computation intensive digital signal processing algorithms into suitable array processor architectures is presented. It covers the complete design flow from algorithmic specifications in a high-level programming language to architecture descriptions in a hardware description language. The transformation itself is divided into manageable design steps and implemented in the CAD-tool DECOMP which allows the exploration of different architectures in a short time. With the presented approach data independent algorithms can be mapped onto array processor architectures. To allow this, a known mapping methodology for array processor design is extended to handle inhomogeneous dependence graphs with nonregular data dependences. The implementation of the formal approach in the DECOMP is an important step towards design automation for massively parallel systems.

scholarly journals Electronic Stetoscope Design And Analysis Application Of Heart Sound With Digital Signal Processing

2015 ◽  
Vol 1 (1) ◽  
pp. 1-8
Author(s):  
Arya Adhi Nugraha
Keyword(s):  
Heart Sound ◽  
Digital Signal ◽  
Sound Analysis ◽  
Client Server ◽  
Electronic Application ◽  
Recorded Sound ◽  
Sample Data ◽  
Value Range ◽  
Analysis Application ◽  
Sound Spectrum

In this paper and has implemented a stethoscope electronic application sound analysis in heart client-server. A stethoscope electronics will catch a heart and menghantarkannya to computer so that the computer can sound mendigitalisasi heart. The application will process, sound analysis heart store and display a heart condition and sound spectrum of the heart. Extraction habitude anything undertaken to gain special habitude from the heart to perform the process of decomposing paket wavelet and root mean square ( rms ) at the sound of the heart. From the data obtained, in different heart conditions, decomposition of wavelet package give value range min 6 up to a maximum of 23 is much larger and RMS only give minimal range 0.04 to 0.16 in band 0-125Hz of variations of the same types of heart conditions. Sample Data obtained from 5 persons recorded sound his heart and then analyzed with the same two methods. The Data obtained are more closer to the normal heart sound so it can be deduced from the 5 sample data used is the sound of the heart under normal conditions.

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