Lakshmi Devi | National Engineering College (original) (raw)
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Papers by Lakshmi Devi
Wavelet transform are generally used for data denoising, compression, edge detection, etc. It is ... more Wavelet transform are generally used for data denoising, compression, edge detection, etc. It is used for minimizing the noise in the signal. After wavelet decomposition, the high frequency sub bands contain most of the noise and a low frequency sub band contains most of the signal information. Noise is minimized by decomposing the PPG signals into a set of wavelet sub bands. Discrete wavelet transform (DWT) provides sufficient information for analysis and synthesis of the original signal with significant reduction of computational time. In DWT the signal is passed through a high pass filters and through a low pass filters to analyze the high frequencies and low frequencies respectively. Here Photoplethysmography (PPG) signal is considered for analysis. PPG is used to detect volumetric changes in blood in peripheral circulation. Noise is one of the major challenges because it may lead to produce the faulty PPG signal. In this paper, wavelet transform is used to remove the noises in ...
– Internet of Things (IoT) promises to revolutionize the health-care sector through remote, conti... more – Internet of Things (IoT) promises to revolutionize the health-care sector through remote, continuous, and non-invasive monitoring of patients. An IoT platform for prediction of Cardiovascular Diseases using a Signal Quality Aware-IoT-enabled ECG telemetry system, intervals detection application has been presented that contains a Processing signal and alert physician for emergency through Android application. It is helpful for the physician to analysis the heart disease as easy and accurate. We are developing a continuous ECG monitoring system by which people can check their ECG signal even at their home, identify any problem in heart or identify cardiovascular diseases and alert the physician for emergency. The size of system is small and it requires less maintenance and operational cost.
— Wavelet transform are generally used for data de-noising, compression, edge detection, etc. It ... more — Wavelet transform are generally used for data de-noising, compression, edge detection, etc. It is used for minimizing the noise in the signal. After wavelet decomposition, the high frequency sub bands contain most of the noise and a low frequency sub band contains most of the signal information. Noise is minimized by decomposing the PPG signals into a set of wavelet sub bands. Discrete wavelet transform (DWT) provides sufficient information for analysis and synthesis of the original signal with significant reduction of computational time. In DWT the signal is passed through a high pass filters and through a low pass filters to analyze the high frequencies and low frequencies respectively. Here Photoplethysmography (PPG) signal is considered for analysis. PPG is used to detect volumetric changes in blood in peripheral circulation. Noise is one of the major challenges because it may lead to produce the faulty PPG signal. In this paper, wavelet transform is used to remove the noises in the PPG signal. For denoising different daubechies wavelet filters were applied. Among them db5 gives better denoised signal. De-noised Signal helps to extract the features of PPG signal to diagnose the cardiovascular diseases.
The main objective is to develop a novel method for the heart sound analysis for the detection of... more The main objective is to develop a novel method for the heart sound analysis for the detection of cardiovascular diseases. It can be considered as one of the important phases in the automated analysis of PCG signals. Heart sounds carry information about mechanical activity of the cardiovascular system. This information includes specific physiological state of the subject and the short term variability related to the respiratory cycle. The interpretation of sounds and extraction of changes in the physiological state while maintaining the short term variability are still an open problem and is subject of this paper. The system deals with the process of de-noising of the heart sound signal(PCG) and the signal is decomposed into several sub-bands and the de-noised heart sound signal is segmented into the basic heart sounds S1 and S2, along with the systolic and diastolic interval.. Also, the ECG signal is de-noised. Meanwhile, the R-peaks are identified from the ECG signal and RR interval is obtained. Extraction of features are done from both the heart sound signal and the ECG signal. From the features, the R-peaks are identified from the ECG signal and RR interval is obtained. The attribute selection is to find the best attribute values that can be used for the classification process. Finally, using classification technique, cardiac diseases are detected. This work is implemented by using MATLAB software.
Wavelet transform are generally used for data denoising, compression, edge detection, etc. It is ... more Wavelet transform are generally used for data denoising, compression, edge detection, etc. It is used for minimizing the noise in the signal. After wavelet decomposition, the high frequency sub bands contain most of the noise and a low frequency sub band contains most of the signal information. Noise is minimized by decomposing the PPG signals into a set of wavelet sub bands. Discrete wavelet transform (DWT) provides sufficient information for analysis and synthesis of the original signal with significant reduction of computational time. In DWT the signal is passed through a high pass filters and through a low pass filters to analyze the high frequencies and low frequencies respectively. Here Photoplethysmography (PPG) signal is considered for analysis. PPG is used to detect volumetric changes in blood in peripheral circulation. Noise is one of the major challenges because it may lead to produce the faulty PPG signal. In this paper, wavelet transform is used to remove the noises in ...
– Internet of Things (IoT) promises to revolutionize the health-care sector through remote, conti... more – Internet of Things (IoT) promises to revolutionize the health-care sector through remote, continuous, and non-invasive monitoring of patients. An IoT platform for prediction of Cardiovascular Diseases using a Signal Quality Aware-IoT-enabled ECG telemetry system, intervals detection application has been presented that contains a Processing signal and alert physician for emergency through Android application. It is helpful for the physician to analysis the heart disease as easy and accurate. We are developing a continuous ECG monitoring system by which people can check their ECG signal even at their home, identify any problem in heart or identify cardiovascular diseases and alert the physician for emergency. The size of system is small and it requires less maintenance and operational cost.
— Wavelet transform are generally used for data de-noising, compression, edge detection, etc. It ... more — Wavelet transform are generally used for data de-noising, compression, edge detection, etc. It is used for minimizing the noise in the signal. After wavelet decomposition, the high frequency sub bands contain most of the noise and a low frequency sub band contains most of the signal information. Noise is minimized by decomposing the PPG signals into a set of wavelet sub bands. Discrete wavelet transform (DWT) provides sufficient information for analysis and synthesis of the original signal with significant reduction of computational time. In DWT the signal is passed through a high pass filters and through a low pass filters to analyze the high frequencies and low frequencies respectively. Here Photoplethysmography (PPG) signal is considered for analysis. PPG is used to detect volumetric changes in blood in peripheral circulation. Noise is one of the major challenges because it may lead to produce the faulty PPG signal. In this paper, wavelet transform is used to remove the noises in the PPG signal. For denoising different daubechies wavelet filters were applied. Among them db5 gives better denoised signal. De-noised Signal helps to extract the features of PPG signal to diagnose the cardiovascular diseases.
The main objective is to develop a novel method for the heart sound analysis for the detection of... more The main objective is to develop a novel method for the heart sound analysis for the detection of cardiovascular diseases. It can be considered as one of the important phases in the automated analysis of PCG signals. Heart sounds carry information about mechanical activity of the cardiovascular system. This information includes specific physiological state of the subject and the short term variability related to the respiratory cycle. The interpretation of sounds and extraction of changes in the physiological state while maintaining the short term variability are still an open problem and is subject of this paper. The system deals with the process of de-noising of the heart sound signal(PCG) and the signal is decomposed into several sub-bands and the de-noised heart sound signal is segmented into the basic heart sounds S1 and S2, along with the systolic and diastolic interval.. Also, the ECG signal is de-noised. Meanwhile, the R-peaks are identified from the ECG signal and RR interval is obtained. Extraction of features are done from both the heart sound signal and the ECG signal. From the features, the R-peaks are identified from the ECG signal and RR interval is obtained. The attribute selection is to find the best attribute values that can be used for the classification process. Finally, using classification technique, cardiac diseases are detected. This work is implemented by using MATLAB software.