Physiological information monitoring method, physiological information monitoring cushion, and mattress

A technology of physiological information and physiological signals, applied in the field of sleep monitoring, can solve the problem that it is not suitable for detecting the sleep status of two people or even many people.

Inactive Publication Date: 2018-10-23
SHENZHEN H&T DATA RESOURCES & CLOUD TECH LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The implementation mode of this application aims to solve the technical problem that the existing physiological information monitoring is not suitable for detecting the sleep status of two people or even multiple people

Method used

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  • Physiological information monitoring method, physiological information monitoring cushion, and mattress
  • Physiological information monitoring method, physiological information monitoring cushion, and mattress
  • Physiological information monitoring method, physiological information monitoring cushion, and mattress

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0068] Embodiment 1: Separate the respiratory signal from the physiological signal, and calculate the respiratory rate of the monitored object according to the respiratory signal.

[0069] First, Fourier transform is performed on the target respiratory signal of the voltage waveform collected by the micro-motion signal sensor. Then, the spectral peaks exceeding the preset energy threshold in the target respiratory signal after Fourier transform are determined, that is, the first few spectral peaks with the largest energy are found.

[0070] After these spectral peaks with higher energy are found, the respiratory frequency corresponding to the spectral peak is calculated as a candidate respiratory frequency. Finally, in combination with the historical data of the monitored object, the most reasonable respiratory frequency is selected from the candidate respiratory frequencies as the output of the monitored object's respiratory frequency.

[0071] In this embodiment, the histor...

Embodiment 2

[0073] Embodiment 2: Separating the cardiac signal from the physiological signal, and determining the heart rate of the monitoring object accordingly:

[0074] First, the baseline drift of the target cardiac signal is removed to obtain a standard cardiac signal. Specifically, a method for removing baseline drift in the time domain may be used to filter low-frequency signals. Of course, other suitable algorithms can also be used to filter the low-frequency signal in the cardiac signal, such as wavelet decomposition method, empirical mode decomposition method (EMD) and so on.

[0075] Then, the peak point and the valley point of the standard cardiac signal are detected. Filter the peak and trough points according to the dynamic threshold to obtain the target peak and trough points. Finally, the distance between the target peak point and the target trough point is determined as the heart rate of the monitored object.

[0076] Since the human cardiac signal collected by the mic...

Embodiment 3

[0077] Embodiment 3: Separating the body motion signal from the physiological signal and calculating the number of body motions.

[0078] Since the micro-motion signal sensor is very sensitive to pressure and vibration signals, when body motion occurs, the voltage waveform output by the micro-motion signal sensor will change abruptly or even saturate. Therefore, in this embodiment, the sudden change and saturation of the voltage waveform are used as the body motion signal.

[0079] The statistics of whether physical movement occurs and the number of physical movements are as follows:

[0080] First, when the waveform amplitude of the voltage waveform repeatedly exceeds the threshold several times, it can be determined that body motion has occurred. The threshold and the number of times it is repeatedly exceeded can be set according to actual conditions, for example, it can be set so that when the waveform amplitude repeatedly exceeds the threshold three times, it is determine...

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Abstract

The application relates to the technical field of sleep monitoring, in particular to a physiological information monitoring method and device and a physiological information monitoring cushion. The method includes the steps of receiving the first to the p physiological signals; detecting respiration signals in each physiological signal; when the respiration signals in the m adjacent physiological signals among the first to the p physiological signals accord with preset judgment conditions, determining that the m adjacent physiological signals correspond to monitored objects and counting the number of the monitored objects; through a preset signal processing algorithm, extracting, from the m adjacent physiological signals, physiological information corresponding to the monitored objects; recording the number of the monitored objects and the physiological information corresponding to each monitored object. The physiological information monitoring method provided by the application is suitable for monitoring sleep conditions of a plurality of persons and can accurately judge each monitored object, thereby facilitating mutual understanding about health conditions of the relatedmonitored objects when the objects fall asleep and providing guarantee for healthy sleep to all the monitored objects.

Description

technical field [0001] The present application relates to the technical field of sleep monitoring, in particular to a physiological information monitoring method, a physiological information monitoring pad, and a mattress. Background technique [0002] With the development of society and economy, people begin to pay more and more attention to personal health issues. Sleep quality is closely related to personal health, so it has also attracted people's attention. Household portable sleep detection equipment establishes a sleep detection algorithm by detecting the user's movement, respiration and heartbeat during sleep, and analyzes the user's sleep quality. This type of sleep detection equipment is useful for evaluating the user's work pressure, fatigue and mental status. Broad market prospects. [0003] The applicant found in the process of implementing this application that: on the one hand, most of the existing sleep monitoring devices are wearable devices, which are eas...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/0205A61B5/11A61B5/113
CPCA61B5/0205A61B5/11A61B5/113A61B5/4806A61B5/746A61B5/6892
Inventor 冯澍婷刘洪涛
Owner SHENZHEN H&T DATA RESOURCES & CLOUD TECH LTD
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