scholarly journals Multi-frequency Model Fusion for Robust Breathing Rate Estimation

2019 ◽  
Author(s):  
Soumaya Khreis ◽  
Ge Di ◽  
Zhu Jian ◽  
Guy Carrault
Keyword(s):  
Breathing Rate ◽  
Frequency Model ◽  
Model Fusion ◽  
Rate Estimation

ComplexBeat: Breathing Rate Estimation from Complex CSI

2021 ◽  
Author(s):  
Sitian Li ◽  
Andreas Toftegaard Kristensen ◽  
Andreas Burg ◽  
Alexios Balatsoukas-Stimming
Keyword(s):  
Breathing Rate ◽  
Rate Estimation

scholarly journals C-Band FMCW Radar Design and Implementation for Breathing Rate Estimation

2020 ◽  
Vol 5 (5) ◽  
pp. 1299-1307
Author(s):  
Mohammad Mohammad Abdul-Atty ◽  
Ahmed Sayed Ismail Amar ◽  
Mohamed Mabrouk
Keyword(s):  
Breathing Rate ◽  
Fmcw Radar ◽  
Rate Estimation ◽  
Design And Implementation

Breathing Rate Estimation Using Kalman Smoother With Electrocardiogram and Photoplethysmogram

2020 ◽  
Vol 67 (3) ◽  
pp. 893-904 ◽  
Author(s):  
Soumaya Khreis ◽  
Di Ge ◽  
Hala Abdul Rahman ◽  
Guy Carrault
Keyword(s):  
Breathing Rate ◽  
Rate Estimation ◽  
Kalman Smoother

scholarly journals Breathing Rate Estimation From the Electrocardiogram and Photoplethysmogram: A Review

2018 ◽  
Vol 11 ◽  
pp. 2-20 ◽  
Author(s):  
Peter H. Charlton ◽  
Drew A. Birrenkott ◽  
Timothy Bonnici ◽  
Marco A. F. Pimentel ◽  
Alistair E. W. Johnson ◽  
...  
Keyword(s):  
Breathing Rate ◽  
Rate Estimation

scholarly journals Human Breathing Rate Estimation from Radar Returns Using Harmonically Related Filters

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Mohamed Mabrouk ◽  
Sreeraman Rajan ◽  
Miodrag Bolic ◽  
Mohamad Forouzanfar ◽  
Hilmi R. Dajani ◽  
...  
Keyword(s):  
Mean Absolute Error ◽  
Absolute Error ◽  
Breathing Rate ◽  
Computationally Efficient ◽  
Estimation Errors ◽  
Rate Estimation ◽  
Estimation Algorithms ◽  
Comb Filters ◽  
The Subject ◽  
The Mean

Radar-based noncontact sensing of life sign signals is often used in safety and rescue missions during disasters such as earthquakes and avalanches and for home care applications. The radar returns obtained from a human target contain the breathing frequency along with its strong higher harmonics depending on the target’s posture. As a consequence, well understood, computationally efficient, and the most popular traditional FFT-based estimators that rely only on the strongest peak for estimates of breathing rates may be inaccurate. The paper proposes a solution for correcting the estimation errors of such single peak-based algorithms. The proposed method is based on using harmonically related comb filters over a set of all possible breathing frequencies. The method is tested on three subjects for different postures, for different distances between the radar and the subject, and for two different radar platforms: PN-UWB and phase modulated-CW (PM-CW) radars. Simplified algorithms more suitable for real-time implementation have also been proposed and compared using accuracy and computational complexity. The proposed breathing rate estimation algorithms provide a reduction of about 81% and 80% in the mean absolute error of breathing rates in comparison to the traditional FFT-based methods using strongest peak detection, for PN-UWB and PM-CW radars, respectively.

TR-BREATH: Time-Reversal Breathing Rate Estimation and Detection

2018 ◽  
Vol 65 (3) ◽  
pp. 489-501 ◽  
Author(s):  
Chen Chen ◽  
Yi Han ◽  
Yan Chen ◽  
Hung-Quoc Lai ◽  
Feng Zhang ◽  
...  
Keyword(s):  
Time Reversal ◽  
Breathing Rate ◽  
Rate Estimation
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