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Cross-modal-mapping-based heart rate estimation method for ballistocardiogram signals

A ballistocardiogram and cross-modal technology, applied in the field of biomedical information processing, can solve the problem of low accuracy of heart rate estimation

Active Publication Date: 2020-11-06
XIDIAN UNIV
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AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to address the deficiencies in the prior art above, and propose a method for estimating the heart rate of the ballistocardiogram signal based on cross-modal mapping, which is used to solve the technical problem of low heart rate estimation accuracy existing in the prior art

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  • Cross-modal-mapping-based heart rate estimation method for ballistocardiogram signals
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  • Cross-modal-mapping-based heart rate estimation method for ballistocardiogram signals

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Embodiment Construction

[0035] The present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0036] refer to figure 1 , the present invention comprises steps as follows:

[0037] Step 1) collect the ballistocardiogram signal and the cardiac pulse signal:

[0038] Adopt finger clip type pulse sensor and hydraulic pressure sensor, and use f s Collect the subject’s heart pulse signal B and M ballistocardiogram signals A={A 1 ,A 2 ,...,A m ,...,A M}, where f s ≥100Hz, A m denote the mth ballistocardiogram signal, B and A m The length of each is T, where M=4, T=60000, f s = 100Hz; n and T too small will lead to a significant decrease in heart rate estimation accuracy, M, T and f s When it is too large, not only the accuracy of heart rate estimation is not significantly improved, but also the complexity of the algorithm will be greatly increased; the use of a finger-clip pulse sensor with the same sampling frequency as th...

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Abstract

The invention provides a cross-modal-mapping-based heart rate estimation method for ballistocardiogram signals. The method is used for solving the technical problem in the prior art that the accuracyof heart rate estimation is relatively low. The method comprises the implementation steps: acquiring the ballistocardiogram signals and heart pulse signals; filtering the ballistocardiogram signals; acquiring a training sample set and a testing sample set by using periodic prior knowledge of the ballistocardiogram signals; constructing a cross-modal mapping model based on periodicity and amplitudecharacteristics of the ballistocardiogram signals; training the cross-modal mapping model; and carrying out calculating by a peak searching algorithm and an average heart rate method, thereby obtaining a heart rate estimated value of the ballistocardiogram signals. According to the method, an idea of cross-modal mapping is introduced into heart rate estimation of the ballistocardiogram signals, and the ballistocardiogram signals are mapped into the heart pulse signals by using a one-dimensional convolutional neural network so as to lower difficulty of heartbeat detection; and meanwhile, the problem in the prior art that the ballistocardiogram signals corresponding to the same heart rate value are relatively large in difference is avoided, and the accuracy of heart rate estimation is improved to a great extent.

Description

technical field [0001] The invention belongs to the technical field of biomedical information processing, and relates to a method for estimating the heart rate of a ballistocardiogram signal, in particular to a method for estimating the heart rate of a ballocardiogram signal based on cross-modal mapping, which is used for assisting human health monitoring. Background technique [0002] With the continuous improvement of living standards, more and more people pay attention to their own heart health problems. Changes in heart rhythm beyond the normal range usually indicate the occurrence of a certain disease, such as sudden cardiac death, asphyxia, arrhythmia, etc. Therefore, heart rate monitoring in daily life is of great significance for the early detection and treatment of people's own diseases. [0003] Currently, electrocardiogram (ECG) is widely used in heart rate monitoring clinically, but this requires close contact of electrodes or heart probes with the human body, w...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/11A61B5/024
CPCA61B5/024A61B5/1102
Inventor 缑水平刘源洁刘宁涛沙毓焦昶哲海栋毛莎莎程家馨
Owner XIDIAN UNIV
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