First Heart Sound Detection Methods - A Comparison of Wavelet Transform and Fourier Analysis in Different Frequency Bands

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 139643-139652 ◽  
Author(s):  
Haixia Li ◽  
Yongfeng Ren ◽  
Guojun Zhang ◽  
Renxin Wang ◽  
Jiangong Cui ◽  
...  

1965 ◽  
Vol 48 (4) ◽  
pp. 401-407 ◽  
Author(s):  
TSUGUYA SAKAMOTO ◽  
REIZO KUSUKAWA ◽  
DONALD M. MACCANON ◽  
ALDO A. LUISADA

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4508
Author(s):  
Boyan Liu ◽  
Liuyang Han ◽  
Lyuming Pan ◽  
Hongzheng Li ◽  
Jingjing Zhao ◽  
...  

This research introduces an idea of producing both nanoscale and microscale pores in piezoelectric material, and combining the properties of the molecular β-phase dipoles in ferroelectric material and the space charge dipoles in order to increase the sensitivity of the sensor and modulate the response frequency bandwidth of the material. Based on this idea, a bi-nano-micro porous dual ferro-electret hybrid self-powered flexible heart sound detection sensor is proposed. Acid etching and electrospinning were the fabrication processes used to produce a piezoelectric film with nanoscale and microscale pores, and corona poling was used for air ionization to produce an electret effect. In this paper, the manufacturing process of the sensor is introduced, and the effect of the porous structure and corona poling on improving the performance of the sensor is discussed. The proposed flexible sensor has an equivalent piezoelectric coefficient d33 of 3312 pC/N, which is much larger than the piezoelectric coefficient of the common piezoelectric materials. Experiments were carried out to verify the function of the flexible sensor together with the SS17L heart sound sensor (BIOPAC, Goleta, CA, USA) as a reference. The test results demonstrated its practical application for wearable heart sound detection and the potential for heart disease detection. The proposed flexible sensor in this paper could realize batch production, and has the advantages of flexibility, low production cost and a short processing time compared with the existing heart sound detection sensors.


Circulation ◽  
1962 ◽  
Vol 26 (6) ◽  
pp. 1296-1301 ◽  
Author(s):  
JOSE F. LOPEZ ◽  
HAROLD LINN ◽  
AARON B. SHAFFER

2013 ◽  
Vol 756-759 ◽  
pp. 3855-3859
Author(s):  
Jian Yi Li ◽  
Hui Juan Wang

Based on the research of the four kinds of algorithms of digital image segmentation, based on edge detection methods, based on region growing method, threshold segmentation method and digital image threshold segmentation method based on wavelet transform, using MATLAB simulation of all digital image enhancement and segmentation process, the obtained results are analyzed, proving the threshold segmentation wavelet transform method has unparalleled advantages in information extraction in medical image. Wavelet transform is a mathematical tool widely used in recent years, compared with the Fu Liye transform, the window of Fu Liye transform, wavelet transform is the local transform of space and frequency, it can be very effective in extracting information from the signal [[1.


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