Extraction of foetal heartbeat rate from a single passive sound sensor on the mother’s abdomen is demonstrated. The extraction is based on the assumption that a disjoint band of frequencies exist and foetal signal is...Extraction of foetal heartbeat rate from a single passive sound sensor on the mother’s abdomen is demonstrated. The extraction is based on the assumption that a disjoint band of frequencies exist and foetal signal is concentrated in this band, and further that it can be represented conveniently as a set of wavelet coefficients. The algorithm has been applied to each stream of data obtained from six different channels and the detection performance is elaborated. The algorithm has also been tested on signals from non-pregnant abdomens to show successful rejection of adult heartbeat. The extraction of the desired signal is done in two stages so as to eliminate components from the maternal heart-beat.展开更多
Owing to the recent trends in remote health monitoring,real-time appli-cations for measuring Heartbeat Rate and Respiration Rate(HARR)from video signals are growing rapidly.Photo Plethysmo Graphy(PPG)is a method that ...Owing to the recent trends in remote health monitoring,real-time appli-cations for measuring Heartbeat Rate and Respiration Rate(HARR)from video signals are growing rapidly.Photo Plethysmo Graphy(PPG)is a method that is operated by estimating the infinitesimal change in color of the human face,rigid motion of facial skin and head parts,etc.Ballisto Cardiography(BCG)is a non-surgical tool for obtaining a graphical depiction of the human body’s heartbeat by inducing repetitive movements found in the heart pulses.The resilience against motion artifacts induced by luminancefluctuation and the patient’s mobility var-iation is the major difficulty faced while processing the real-time video signals.In this research,a video-based HARR measuring framework is proposed based on combined PPG and BCG.Here,the noise from the input video signals is removed by using an Adaptive Kalmanfilter(AKF).Three different algorithms are used for estimating the HARR from the noise-free input signals.Initially,the noise-free sig-nals are subjected to Modified Adaptive Fourier Decomposition(MAFD)and then to Enhanced Hilbert vibration Decomposition(EHVD)andfinally to Improved Var-iation mode Decomposition(IVMD)for attaining three various results of HARR.The obtained values are compared with each other and found that the EHVD is showing better results when compared with all the other methods.展开更多
文摘Extraction of foetal heartbeat rate from a single passive sound sensor on the mother’s abdomen is demonstrated. The extraction is based on the assumption that a disjoint band of frequencies exist and foetal signal is concentrated in this band, and further that it can be represented conveniently as a set of wavelet coefficients. The algorithm has been applied to each stream of data obtained from six different channels and the detection performance is elaborated. The algorithm has also been tested on signals from non-pregnant abdomens to show successful rejection of adult heartbeat. The extraction of the desired signal is done in two stages so as to eliminate components from the maternal heart-beat.
文摘Owing to the recent trends in remote health monitoring,real-time appli-cations for measuring Heartbeat Rate and Respiration Rate(HARR)from video signals are growing rapidly.Photo Plethysmo Graphy(PPG)is a method that is operated by estimating the infinitesimal change in color of the human face,rigid motion of facial skin and head parts,etc.Ballisto Cardiography(BCG)is a non-surgical tool for obtaining a graphical depiction of the human body’s heartbeat by inducing repetitive movements found in the heart pulses.The resilience against motion artifacts induced by luminancefluctuation and the patient’s mobility var-iation is the major difficulty faced while processing the real-time video signals.In this research,a video-based HARR measuring framework is proposed based on combined PPG and BCG.Here,the noise from the input video signals is removed by using an Adaptive Kalmanfilter(AKF).Three different algorithms are used for estimating the HARR from the noise-free input signals.Initially,the noise-free sig-nals are subjected to Modified Adaptive Fourier Decomposition(MAFD)and then to Enhanced Hilbert vibration Decomposition(EHVD)andfinally to Improved Var-iation mode Decomposition(IVMD)for attaining three various results of HARR.The obtained values are compared with each other and found that the EHVD is showing better results when compared with all the other methods.
