Heart health monitoring system based on multi-dimensional physiological information
A technology of health monitoring system and physiological information, applied in the direction of cardiac catheterization, medical science, blood characterization device, etc., can solve the problems of low accuracy rate of heart disease diagnosis and failure to detect cardiac danger in time, and achieve the effect of preventing sudden death
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specific Embodiment approach 1
[0069] DETAILED DESCRIPTION figure 1 and figure 2 Specifically, the present embodiment will be described in this embodiment, a cardiac health monitoring system based on multi-dimensional physiological information, including: an electrocardiographic signal detection module, a heart sound signal detection module, a cardiogram signal detection module, a heart rate detection module, blood pressure Detection module, blood oxygen detection module, storage module and central control and processing unit,
[0070] The heart rate detection module, blood pressure detection module and blood oxygen detection module are used to detect heart rate, blood pressure and blood oxygen saturation;
[0071] The cardiogram signal detection module, the heart sound signal detection module, and the heart shock diagram signal detection module are used to collect electrocardiographic, heart sound and heart impact signals;
[0072] When the core rate, blood pressure and blood oxygen saturation value exceeds th...
specific Embodiment approach 2
[0074] DETAILED DESCRIPTION OF THE INVENTION 2: This embodiment is a further explanation of a specific embodiment, and the difference between the present embodiment and the particular embodiment is that the central control and processing unit are specifically performed as follows:
[0075] Step 1: Get an electrocardiographic signal detection module, the heart sound signal detection module, and the heart shock map signal detection module collected by the electrocardiographic, heart sound and heart impact synchronization signal;
[0076] Step 2: The acquired signal is extracted by the wavelet scattering transformation, and then the extracted feature is reduced to the extracted feature by the main component analysis method to obtain a desired feature;
[0077] Step 3: Depending on the collected signal and utilize the wavelet transform to acquire the wave-wave coefficient, then establish an image feature extraction of the wavelet coefficient time frequency diagram feature of the convo...
specific Embodiment approach 3
[0080] DETAILED DESCRIPTION OF THE INVENTION 3: The present embodiment is a further explanation of the second embodiment, and the difference between the second embodiment is the specific process of the wavelet scattering transformation:
[0081] Convolution of the input signal and the wavelet, and consolidate with the low pass filter after molding, after multiple iterations, finally connect all steps of scattering coefficients to the output of the scattering network:
[0082] Suppose the input signal is X (u), the scatter coefficient of the scattering transformation is After the first layer of the scattering network, the 0th step is obtained:
[0083] S 0 X = a J X (u) = x * φ J (2 J u)
[0084] Where * is convolution operation, φ J For a window size is 2 J Low pass filter, A J For the average filtering case, the signal represents the calculation process of local extraction mean by the low-pass filter,
[0085] Master wavelet ψ in scale 1≤2 j ≤2 J Zoom, get a small wave cluster ψ...
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