CN-122004846-A - Non-contact bedridden data monitoring method, system and device

CN122004846ACN 122004846 ACN122004846 ACN 122004846ACN-122004846-A

Abstract

The embodiment of the specification discloses a non-contact bedridden data monitoring method, a non-contact bedridden data monitoring system and a non-contact bedridden data monitoring device, wherein the monitoring method comprises the steps of obtaining an acquisition signal comprising a dynamic force detection signal and a static force detection signal which are homologous to each other on a bed body, obtaining body movement fractions representing the intensity of body movement of a tested object, which correspond to each monitoring period, based on the acquisition signal, for any monitoring period, determining the body movement state of the monitoring period based on the body movement fractions corresponding to the monitoring period, obtaining the respiratory rate value of the monitoring period based on the body movement state and the acquisition signal of the monitoring period, and outputting bedridden data comprising the body movement state and the respiratory rate value, which correspond to the monitoring period. According to the scheme, robustness, accuracy and continuity of bedridden data monitoring under dynamic interference are remarkably improved through quantitative body movement assessment, multi-sensor signal dynamic fusion and a self-adaptive decision mechanism.

Inventors

WANG JIADONG
DAI YIFAN
LI ZHENZHEN

Assignees

浙江麒盛数据服务有限公司

Dates

Publication Date: 20260512
Application Date: 20260413

Claims (10)

1. A method for monitoring data of a non-contact bedridden patient, comprising the steps of: Acquiring acquisition signals of a dynamic force detection signal representing vibration change and a static force detection signal representing pressure change which are homologous on a bed body; Acquiring body movement scores representing the body movement intensity of the tested object, which correspond to each monitoring period, based on the acquired signals; For any monitoring period: determining the body movement state of the monitoring period based on the body movement score corresponding to the monitoring period, wherein the body movement state comprises a lying state, a slight body movement state and a severe body movement state; acquiring a respiration rate value of the monitoring period based on the body movement state of the monitoring period and the acquired signal; If the monitoring period is in a static and horizontal state, acquiring a respiration rate value of the monitoring period based on a signal segment of a corresponding acquisition signal of the monitoring period; if the monitoring period is in a slight body movement state, acquiring a respiration rate value of the monitoring period based on signal segments of acquired signals corresponding to the monitoring period and a plurality of monitoring periods adjacent to the monitoring period; If the monitoring period is in a severe body movement state, acquiring a respiration rate value of the monitoring period based on signal segments of acquired signals corresponding to a plurality of monitoring periods adjacent to the monitoring period; and outputting the bedridden data which corresponds to the monitoring period and comprises the body movement state and the respiration rate value.
2. The method of contactless bedridden data monitoring of claim 1, further comprising: extracting dynamic force body mover signals based on the dynamic force detection signals; extracting a static force body mover signal based on the static force detection signal; Carrying out signal processing of center difference, sliding window root mean square calculation and mutation point detection on dynamic force body rotor signals and static force body rotor signals; The acquiring the body movement score representing the body movement intensity of the tested object corresponding to each monitoring period based on the acquired signals comprises the following steps: And acquiring body movement scores which respectively correspond to each monitoring period and represent the body movement intensity of the tested object based on the dynamic force body rotor signals and the static force body rotor signals.
3. The method for monitoring data of a contactless bedridden patient according to claim 2, wherein the acquiring the body movement score representing the intensity of movement of the measured object based on the dynamic force body subsignal and the static force body subsignal, which corresponds to each monitoring period, comprises: Acquiring a first motion score representing the motion intensity of a measured object, which corresponds to each monitoring period, based on the dynamic force body rotor signals; acquiring second body movement scores which respectively correspond to each monitoring period and represent the movement intensity of the measured object based on the static force body mover signals; and for any monitoring period, acquiring the body movement score of the monitoring period based on the first body movement score and the second body movement score corresponding to the monitoring period.
4. A method for monitoring data of a contactless bedridden patient according to claim 3, wherein the acquiring the first motion score representing the intensity of motion of the measured object based on the dynamic force body subsignals, each corresponding to each monitoring period, comprises: acquiring a first feature set which corresponds to each monitoring period and comprises various dynamic force body motion signal features based on dynamic force body rotor signals; Acquiring a first motion score corresponding to each monitoring period based on a preset first weight set comprising a weight coefficient corresponding to each dynamic force motion signal characteristic and a first characteristic set corresponding to each monitoring period; the method for acquiring the second body movement score representing the body movement intensity of the measured object, which corresponds to each monitoring period, based on the static force body mover signal comprises the following steps: acquiring a second feature set which corresponds to each monitoring period and comprises a plurality of static force body motion signal features based on the static force body rotor signals; And acquiring a second motion score corresponding to each monitoring period based on a preset second weight set comprising a weight coefficient corresponding to each static force motion signal characteristic and a second characteristic set corresponding to each monitoring period.
5. The method for monitoring data in bed according to claim 4, wherein the step of obtaining the body movement score representing the intensity of movement of the subject for each monitoring period based on the dynamic force body subsignals and the static force body subsignals, further comprises: Acquiring a maximum gross movement monitoring period of a measured object based on the dynamic force body rotor signal and the static force body rotor signal; Acquiring a first characteristic reference set comprising various dynamic force body motion signal characteristics based on a signal segment of a maximum gross motion monitoring period corresponding to a dynamic force body rotor signal, wherein the first characteristic reference set is used for carrying out normalization processing on the first characteristic set corresponding to each monitoring period; and acquiring a second characteristic reference set comprising a plurality of static force body movement signal characteristics based on the signal segment of the maximum gross movement monitoring period corresponding to the static force body mover signal, and performing normalization processing on the second characteristic set corresponding to each monitoring period.
6. The method of contactless bedridden data monitoring of claim 1, further comprising: extracting dynamic force breathing sub-signals based on the dynamic force detection signals, and acquiring first signal quality scores corresponding to the signal segments of the dynamic force breathing sub-signals corresponding to each monitoring period based on the signal morphology regularity degree; extracting a static force breathing sub-signal based on the static force detection signal, and acquiring second signal quality scores corresponding to signal segments of the static force breathing sub-signal corresponding to each monitoring period based on the signal morphology regularity degree; Aiming at any monitoring period, acquiring a respiratory signal segment corresponding to the monitoring period based on a signal segment and a first signal quality fraction of a dynamic force respiratory sub-signal corresponding to the monitoring period, and a signal segment and a second signal quality fraction of a static force respiratory sub-signal corresponding to the monitoring period; The acquiring the respiration rate value of the monitoring period based on the body movement state and the acquisition signal of the monitoring period comprises the following steps: And acquiring the respiration rate value of the monitoring period based on the body movement state of the monitoring period and the corresponding respiration signal section.
7. The method for contactless bedridden data monitoring of claim 6, wherein the acquiring the respiratory signal segment corresponding to the monitoring period comprises: Acquiring a respiratory signal section corresponding to the monitoring period and a signal section quality fraction thereof; Outputting bedridden data corresponding to the monitoring period and comprising a body movement state and a respiration rate value, wherein the bedridden data comprises: and outputting bedridden data which corresponds to the monitoring period and comprises a body movement state, a respiration rate value and a signal segment mass fraction.
8. The method of claim 7, wherein if the monitoring period is in a slightly body movement state, acquiring the respiration rate value of the monitoring period based on the signal segments of the acquisition signal corresponding to each of the monitoring period and a plurality of monitoring periods adjacent to the monitoring period, comprises: if the monitoring period is in a slight body movement state, based on the respiration signal sections of the acquired signals corresponding to the monitoring period and a plurality of monitoring periods adjacent to the monitoring period, respectively acquiring respiration rate intermediate values corresponding to the respiration signal sections; And carrying out weighting processing on the respiration rate intermediate value corresponding to each of the plurality of respiration signal segments based on the signal segment mass fraction of the respiration signal segment of the acquisition signal corresponding to each of the monitoring period and a plurality of monitoring periods adjacent to the monitoring period and the time sequence of the monitoring period, and obtaining the respiration rate value of the monitoring period.
9. The non-contact bedridden data monitoring system is characterized by comprising a signal acquisition unit, a body movement score evaluation unit, a body movement state dividing unit, a physiological data calculation unit and a data output unit; the signal acquisition unit acquires acquisition signals of dynamic force detection signals representing vibration changes and static force detection signals representing pressure changes which are homologous on the bed body; The body movement score evaluation unit is used for acquiring body movement scores which respectively correspond to each monitoring period and represent the body movement intensity of the tested object based on the acquired signals; The body movement state dividing unit is used for determining the body movement state of any monitoring period based on the body movement score corresponding to the monitoring period, wherein the body movement state comprises a static state, a slight body movement state and a severe body movement state; The physiological data calculation unit is used for acquiring the respiration rate value of any monitoring period based on the body movement state and the acquisition signals of the monitoring period, acquiring the respiration rate value of the monitoring period based on the signal segments of the acquisition signals corresponding to the monitoring period if the monitoring period is in a static state, acquiring the respiration rate value of the monitoring period based on the signal segments of the acquisition signals corresponding to the monitoring period and a plurality of monitoring periods adjacent to the monitoring period if the monitoring period is in a slight body movement state, and acquiring the respiration rate value of the monitoring period based on the signal segments of the acquisition signals corresponding to the monitoring periods adjacent to the monitoring period if the monitoring period is in a severe body movement state; the data output unit outputs bedridden data which corresponds to any monitoring period and comprises a body movement state and a respiration rate value.
10. A contactless bedridden data monitoring device comprising a contactless bedridden data monitoring system as claimed in claim 9, and The signal acquisition equipment comprises a dynamic force detection unit for acquiring dynamic force detection signals and a static force detection unit for acquiring static force detection signals, and is used for providing homologous acquisition signals for the monitoring system; And the terminal equipment is used for carrying out information interaction with the monitoring system, wherein the information interaction comprises receiving bedridden data.

Description

Non-contact bedridden data monitoring method, system and device Technical Field Embodiments of the present description relate to the field of health monitoring technology, and in particular to optimization of monitoring accuracy and continuity in contactless bedridden data monitoring. Background The non-contact bedridden monitoring technology is mainly realized by a sensor embedded in a bed body, and aims to continuously acquire vital sign information such as the state of leaving the bed, body movement, heart rate, respiratory rate and the like of a bedridden patient without sense. The technology has wide application prospect in the fields of intelligent endowment, health monitoring and the like because of the characteristics of no equipment wearing, good user experience and the like. Existing solutions typically rely on a single type of sensor (such as a vibration or piezoelectric sensor) or a simple multisensor combination. For example, a typical technical scheme adopts a sensor array which is arranged at intervals along the lying direction of a human body, and the on/off bed state and the basic prone position are judged by detecting the triggering condition of each point position signal. For body movement detection, a simple binary judgment of "on" or "off" is performed mainly by whether the amplitude of the sensor signal exceeds a preset threshold. And only when the tested object is still lying, vital sign data such as respiration, heart rate and the like are extracted from the sensor signals. However, strong noise generated by body movement can drown weak physiological signals, so that vital sign extraction fails or is misaligned, and the continuity and accuracy of monitoring cannot be maintained in a complex and dynamically-changed bedridden scene in the conventional scheme. Disclosure of Invention The embodiment of the specification provides a non-contact bedridden data monitoring method, a non-contact bedridden data monitoring system and a non-contact bedridden data monitoring device, which solve the problems of measurement misalignment and rough body movement state evaluation of vital sign monitoring data in a bedridden scene with complex body movement change in the prior monitoring technology. The technical scheme is as follows: In a first aspect, embodiments of the present disclosure provide a method for contactless bedridden data monitoring, comprising the steps of: Acquiring acquisition signals of a dynamic force detection signal representing vibration change and a static force detection signal representing pressure change which are homologous on a bed body; Acquiring body movement scores representing the body movement intensity of the tested object, which correspond to each monitoring period, based on the acquired signals; For any monitoring period: determining the body movement state of the monitoring period based on the body movement score corresponding to the monitoring period, wherein the body movement state comprises a lying state, a slight body movement state and a severe body movement state; acquiring a respiration rate value of the monitoring period based on the body movement state of the monitoring period and the acquired signal; If the monitoring period is in a static and horizontal state, acquiring a respiration rate value of the monitoring period based on a signal segment of a corresponding acquisition signal of the monitoring period; if the monitoring period is in a slight body movement state, acquiring a respiration rate value of the monitoring period based on signal segments of acquired signals corresponding to the monitoring period and a plurality of monitoring periods adjacent to the monitoring period; If the monitoring period is in a severe body movement state, acquiring a respiration rate value of the monitoring period based on signal segments of acquired signals corresponding to a plurality of monitoring periods adjacent to the monitoring period; and outputting the bedridden data which corresponds to the monitoring period and comprises the body movement state and the respiration rate value. As a preferred aspect, the bedridden data monitoring method further comprises: extracting dynamic force body mover signals based on the dynamic force detection signals; extracting a static force body mover signal based on the static force detection signal; Carrying out signal processing of center difference, sliding window root mean square calculation and mutation point detection on dynamic force body rotor signals and static force body rotor signals; The acquiring the body movement score representing the body movement intensity of the tested object corresponding to each monitoring period based on the acquired signals comprises the following steps: And acquiring body movement scores which respectively correspond to each monitoring period and represent the body movement intensity of the tested object based on the dynamic force body rotor signals and the static force body rotor signals. As