Heartbeat detection using a Doppler radar sensor based on the scaling function of wavelet transform

2019 ◽  
Vol 61 (7) ◽  
pp. 1792-1796 ◽  
Author(s):  
Cheol‐Ho Choi ◽  
Jae‐Hyun Park ◽  
Ha‐Neul Lee ◽  
Jong‐Ryul Yang
Keyword(s):  
Wavelet Transform ◽  
Doppler Radar ◽  
Scaling Function ◽  
Radar Sensor ◽  
The Scaling Function

Wavelet analysis on developable surface base on area preserving projection

2015 ◽  
Vol 13 (01) ◽  
pp. 1550007 ◽  
Author(s):  
Bao Qin Wang ◽  
Gang Wang ◽  
Xiao Hui Zhou ◽  
Yu Su
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Scaling Function ◽  
Discrete Wavelet ◽  
Developable Surface ◽  
Simple Method ◽  
Multi Resolution Analysis ◽  
Resolution Analysis ◽  
Area Preserving ◽  
The Scaling Function

In this paper, a simple method is given in order to construct an area preserving mapping from a developable surface M to a plane. Based on the area preserving projection, we give some important formulas on M, and define a multi-resolution analysis on L2(M). We provide the conditions to further discuss the continuous wavelet transform and discrete wavelet transform on developable surface. At the same time, we derived two-scale equations that the scaling function and wavelet function on developable surface satisfied, we also define and discuss the orthogonality, and several important theorems are given. Finally, we construct the numerical examples. The focus of this paper is the area preserving mapping that from developable surface M to a plane, and the discrete wavelet transform on developable surface.

scholarly journals Correction: Park, J.-H. et al. 915-MHz Continuous-Wave Doppler Radar Sensor for Detection of Vital Signs. Electronics 2019, 8, 561

Electronics ◽  
2019 ◽  
Vol 8 (8) ◽  
pp. 855 ◽  
Author(s):  
Park ◽  
Jeong ◽  
Lee ◽  
Oh ◽  
Yang
Keyword(s):  
Continuous Wave ◽  
Doppler Radar ◽  
Vital Signs ◽  
Radar Sensor ◽  
Continuous Wave Doppler ◽  
Published Paper

The authors wish to make the following corrections to the published paper [...]

Assessing Model Uncertainty for the Scaling Function Inversion of Potential Fields

Geophysics ◽  
2021 ◽  
pp. 1-39
Author(s):  
Mahak Singh Chauhan ◽  
Ivano Pierri ◽  
Mrinal K. Sen ◽  
Maurizio FEDI
Keyword(s):  
Simulated Annealing Algorithm ◽  
Scaling Function ◽  
Vertical Section ◽  
Gravity Data ◽  
Geometric Model ◽  
Salt Dome ◽  
The Body ◽  
Gravity Inversion ◽  
Geometrical Parameters ◽  
The Scaling Function

We use the very fast simulated annealing algorithm to invert the scaling function along selected ridges, lying in a vertical section formed by upward continuing gravity data to a set of altitudes. The scaling function is formed by the ratio of the field derivative by the field itself and it is evaluated along the lines formed by the zeroes of the horizontal field derivative at a set of altitudes. We also use the same algorithm to invert gravity anomalies only at the measurement altitude. Our goal is analyzing the different models obtained through the two different inversions and evaluating the relative uncertainties. One main difference is that the scaling function inversion is independent on density and the unknowns are the geometrical parameters of the source. The gravity data are instead inverted for the source geometry and the density simultaneously. A priori information used for both the inversions is that the source has a known depth to the top. We examine the results over the synthetic examples of a salt dome structure generated by Talwani’s approach and real gravity datasets over the Mors salt dome and the Decorah (USA) basin. For all these cases, the scaling function inversion yielded models with a better sensitivity to specific features of the sources, such as the tilt of the body, and reduced uncertainty. We finally analyzed the density, which is one of the unknowns for the gravity inversion and it is estimated from the geometric model for the scaling function inversion. The histograms over the density estimated at many iterations show a very concentrated distribution for the scaling function, while the density contrast retrieved by the gravity inversion, according to the fundamental ambiguity density/volume, is widely dispersed, this making difficult to assess its best estimate.

THE CONSTRUCTION OF A CLASS OF TRIVARIATE NONSEPARABLE COMPACTLY SUPPORTED WAVELETS

2009 ◽  
Vol 07 (03) ◽  
pp. 255-267 ◽  
Author(s):  
YONGDONG HUANG ◽  
SHOUZHI YANG ◽  
ZHENGXING CHENG
Keyword(s):  
General Theory ◽  
Mild Condition ◽  
Scaling Function ◽  
Moment Condition ◽  
Compactly Supported ◽  
Vanishing Moment ◽  
The Scaling Function

In this paper, under a mild condition, the construction of compactly supported [Formula: see text]-wavelets is obtained. Wavelets inherit the symmetry of the corresponding scaling function and satisfy the vanishing moment condition originating in the symbols of the scaling function. An example is also given to demonstrate the general theory.

scholarly journals Development of Alarm Service Using Doppler Radar Sensor

2015 ◽  
Vol 19 (3) ◽  
pp. 623-628
Author(s):  
Hyun-Jun Shin ◽  
Doo-Hyun Choi ◽  
Chang-Heon Oh
Keyword(s):  
Doppler Radar ◽  
Radar Sensor

NEW AMY AND DELPHI MULTIPLICITY DATA AND THE LOGNORMAL DISTRIBUTION

1991 ◽  
Vol 06 (03) ◽  
pp. 245-257 ◽  
Author(s):  
R. SZWED ◽  
G. WROCHNA ◽  
A.K. WRÓBLEWSKI
Keyword(s):  
Energy Dependence ◽  
Lognormal Distribution ◽  
Scaling Function ◽  
Average Multiplicity ◽  
Linear Functions ◽  
The Mean ◽  
Multiplicity Distributions ◽  
The Scaling Function ◽  
Skewness And Kurtosis

Multiplicity distributions for e+e−→ hadrons recently reported by the AMY and DELPHI collaborations are compared with the data obtained at lower energies. It is proven that the new data obey the KNO-G scaling and the scaling function can be described by the lognormal distribution. The dispersions are linear functions of the mean as for the data measured at lower energies and the standardized moments (such as skewness and kurtosis) are independent of the energy. The energy dependence of the average multiplicity is described by <nch>=β sα−1.

Noncontact Measurement of River Surface Velocity and Discharge Estimation With a Low-Cost Doppler Radar Sensor

2020 ◽  
Vol 58 (7) ◽  
pp. 5195-5207 ◽  
Author(s):  
Federico Alimenti ◽  
Stefania Bonafoni ◽  
Elisa Gallo ◽  
Valentina Palazzi ◽  
Roberto Vincenti Gatti ◽  
...  
Keyword(s):  
Doppler Radar ◽  
Low Cost ◽  
Surface Velocity ◽  
Radar Sensor ◽  
Noncontact Measurement ◽  
Discharge Estimation

scholarly journals Non-Contact Measurement of Human Respiration and Heartbeat Using W-band Doppler Radar Sensor

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5209 ◽  
Author(s):  
Heesoo Kim ◽  
Jinho Jeong
Keyword(s):  
Doppler Radar ◽  
Band Pass Filter ◽  
Radar Sensor ◽  
Pass Filter ◽  
Contact Measurement ◽  
W Band ◽  
Compact Size ◽  
Human Respiration ◽  
Low Pass ◽  
Respiration Signal

This paper presents a W-band continuous-wave (CW) Doppler radar sensor for non-contact measurement of human respiration and heartbeat. The very short wavelength of the W-band signal allows a high-precision detection of the displacement of the chest surface by the heartbeat as well as respiration. The CW signal at 94 GHz is transmitted through a high-gain horn antenna to the human chest at a distance of 1 m. The phase-modulated reflection signal is down-converted to the baseband by the quadrature mixer with an excellent amplitude and phase matches between I and Q channels, which makes the IQ mismatch correction in the digital domain unnecessary. The baseband I and Q data are digitized using data acquisition (DAQ) board. The arctangent demodulation with automatic phase unwrapping is applied to the low-pass filtered I and Q data to effectively solve the null point problem. A slow-varying DC component is rejected in the demodulated signal by the trend removal algorithm. Then, the respiration signal with a frequency of 0.27 Hz and a displacement of ~6.1 mm is retrieved by applying a low-pass filter. Finally, the respiration signal is removed by the band-pass filter and the heartbeat signal is extracted, showing a frequency of 1.35 Hz and a displacement of ~0.26 mm. The extracted respiration and heartbeat rates are very close to the manual measurement results. The demonstrated W-band CW radar sensors can be easily applied to find the angular location of the human body by using a phased array under a compact size.

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