CN-121606263-B - Sleep evaluation method and device and computer equipment

CN121606263BCN 121606263 BCN121606263 BCN 121606263BCN-121606263-B

Abstract

The invention discloses a sleep evaluation method, a sleep evaluation device and computer equipment, which comprise the steps of obtaining sleep monitoring data of a user to be evaluated, determining at least one continuity abnormal event based on the sleep monitoring data, calculating event influence time of each continuity abnormal event based on time attribute and characteristic attribute of each continuity abnormal event, and determining a sleep continuity evaluation result of the user to be evaluated based on the event influence time of each continuity abnormal event. The computer equipment identifies different types of continuity abnormal events from the sleep monitoring data, and calculates corresponding event influence time based on time attributes and characteristic attributes of each continuity abnormal event, so that influence of different abnormal conditions on the whole sleep in the sleep process is quantitatively integrated in a time dimension, the actual degree of continuity damage in the sleep process can be reflected by the sleep continuity assessment result more accurately, and objectivity and rationality of sleep continuity assessment are improved.

Inventors

SUN XIAOXUAN
Gu Zixiong
NAN XIQING
YU KECHENG
JIN YUAN
WU E

Assignees

爱梦睡眠(珠海)智能科技有限公司

Dates

Publication Date: 20260512
Application Date: 20260202

Claims (4)

1. A sleep evaluation method, characterized in that the method comprises: acquiring sleep monitoring data of a user to be evaluated; Determining at least one continuous abnormal event based on the sleep monitoring data, wherein the continuous abnormal event is an arousal event, a non-sleep event or a continuous abnormal time duration abnormal event of each sleep stage in the sleep monitoring data; Calculating event influence time of each continuity abnormal event based on the time attribute and the characteristic attribute of each continuity abnormal event; Determining a sleep continuity evaluation result of the user to be evaluated based on the event influence time of each continuity abnormal event; the sleep monitoring data includes sleep event data, and the determining at least one continuity exception event based on the sleep monitoring data includes: determining the occurrence time point and the ending time point of arousal in the sleep event data; When the duration from the occurrence time point to the ending time point is smaller than the preset arousal duration, determining a sleep segment from the occurrence time point to the ending time point as the arousal event; the sleep monitoring data comprises sleep stage data, and the determining at least one continuity abnormal event based on the sleep monitoring data comprises the following steps: extracting stage labels of each sleep stage from the sleep stage data; if the stage label is not a preset sleep event label, the corresponding sleep stage is the non-sleep event; the determining at least one continuity abnormal event based on the sleep monitoring data further comprises: if the stage label is a preset sleep event label, determining the stage duration corresponding to the sleep stage; performing continuous duration deviation judgment in a preset reference duration data set based on the stage duration to obtain a judgment result; When the judging result is that the stage duration is smaller than the reference duration corresponding to the preset reference duration data set, the corresponding sleep stage is the duration abnormal event; the calculating the event influence time of each continuity abnormal event based on the time attribute and the characteristic attribute of each continuity abnormal event comprises the following steps: For the arousal event, the time attribute of the arousal event comprises the sleep time before the arousal event occurs and the duration of the arousal event, the characteristic attribute comprises the sleep cycle sequence number of the arousal event, the arousal degree of the arousal event and the weight corresponding to the sleep stage before the arousal event occurs, and the weight is set by the statistical probability of the arousal event in each sleep stage; Calculating event influence time of the arousal event based on sleep time before the arousal event occurs, duration of the arousal event, sleep cycle sequence number of the arousal event, arousal degree of the arousal event and weight corresponding to sleep stage before the arousal event occurs; for the non-sleep event, the time attribute comprises a sleep duration before the non-sleep event occurs, and the characteristic attribute comprises a sleep cycle sequence number before the non-sleep event occurs; Calculating the event influence time of the non-sleep event based on the sleep time before the non-sleep event and the sleep period sequence number before the non-sleep event; For the duration abnormal event, the time attribute comprises the actual duration of a sleep stage corresponding to the duration abnormal event and the reference duration corresponding to the sleep stage, the characteristic attribute comprises the sleep cycle number of the sleep stage and the weight corresponding to the sleep stage, and the weight is set according to the sleep depth of the user to be evaluated; And calculating event influence time of the duration abnormal event based on the actual duration of the sleep stage corresponding to the duration abnormal event, the reference duration corresponding to the sleep stage, the sleep cycle sequence number of the sleep stage and the weight corresponding to the sleep stage.
2. The sleep evaluation method according to claim 1, wherein, before the duration deviation judgment is made in a preset reference duration data set based on the stage duration, the method further comprises: Acquiring user information of the user to be evaluated and historical sleep monitoring data meeting preset conditions; based on the historical sleep monitoring data, calculating a reference time length calculation coefficient of each sleep stage; Calculating a coefficient and the user information based on the reference time length of each sleep stage, and calculating the reference time length of each sleep stage; and constructing the preset reference time length data set based on the reference time length of each sleep stage.
3. A sleep evaluation device, characterized in that the device comprises: The first acquisition module is used for acquiring sleep monitoring data of the user to be evaluated; the first determining module is used for determining at least one continuous abnormal event based on the sleep monitoring data, wherein the continuous abnormal event is an arousal event, a non-sleep event or a continuous abnormal time duration event of each sleep stage in the sleep monitoring data; The first calculation module is used for calculating the event influence time of each continuity abnormal event based on the time attribute and the characteristic attribute of each continuity abnormal event; The second determining module is used for determining a sleep continuity evaluation result of the user to be evaluated based on the event influence time of each continuity abnormal event; The sleep monitoring data includes sleep event data, and the first determining module is further configured to: determining the occurrence time point and the ending time point of arousal in the sleep event data; When the duration from the occurrence time point to the ending time point is smaller than the preset arousal duration, determining a sleep segment from the occurrence time point to the ending time point as the arousal event; the sleep monitoring data includes sleep stage data, and the first determining module is further configured to: extracting stage labels of each sleep stage from the sleep stage data; if the stage label is not a preset sleep event label, the corresponding sleep stage is the non-sleep event; the first determining module is further configured to: if the stage label is a preset sleep event label, determining the stage duration corresponding to the sleep stage; performing continuous duration deviation judgment in a preset reference duration data set based on the stage duration to obtain a judgment result; When the judging result is that the stage duration is smaller than the reference duration corresponding to the preset reference duration data set, the corresponding sleep stage is the duration abnormal event; the first computing module is further configured to: For the arousal event, the time attribute of the arousal event comprises the sleep time before the arousal event occurs and the duration of the arousal event, the characteristic attribute comprises the sleep cycle sequence number of the arousal event, the arousal degree of the arousal event and the weight corresponding to the sleep stage before the arousal event occurs, and the weight is set by the statistical probability of the arousal event in each sleep stage; Calculating event influence time of the arousal event based on sleep time before the arousal event occurs, duration of the arousal event, sleep cycle sequence number of the arousal event, arousal degree of the arousal event and weight corresponding to sleep stage before the arousal event occurs; for the non-sleep event, the time attribute comprises a sleep duration before the non-sleep event occurs, and the characteristic attribute comprises a sleep cycle sequence number before the non-sleep event occurs; Calculating the event influence time of the non-sleep event based on the sleep time before the non-sleep event and the sleep period sequence number before the non-sleep event; For the duration abnormal event, the time attribute comprises the actual duration of a sleep stage corresponding to the duration abnormal event and the reference duration corresponding to the sleep stage, the characteristic attribute comprises the sleep cycle number of the sleep stage and the weight corresponding to the sleep stage, and the weight is set according to the sleep depth of the user to be evaluated; And calculating event influence time of the duration abnormal event based on the actual duration of the sleep stage corresponding to the duration abnormal event, the reference duration corresponding to the sleep stage, the sleep cycle sequence number of the sleep stage and the weight corresponding to the sleep stage.
4. A computer device comprising a memory, a processor, and computer readable instructions stored on the memory and running on the processor, wherein the processor, when executing the computer readable instructions, implements the sleep assessment method of any one of claims 1 to 2.

Description

Sleep evaluation method and device and computer equipment Technical Field The present invention relates to the field of sleep data processing, and in particular, to a sleep evaluation method, apparatus, and computer device. Background Sleep continuity is one of the important indicators of sleep quality, reflecting whether sleep stages remain relatively stable during sleep, are frequently disturbed by awake or non-sleep states. Good sleep continuity generally helps to restore body function, while impaired sleep continuity may lead to daytime sleepiness, reduced attention, and multiple health risks. Therefore, objective and accurate assessment of sleep continuity is of great importance in the field of sleep health monitoring. With the development of wearable devices and contactless vital sign monitoring technologies, the prior art has been able to acquire multi-dimensional sleep monitoring data including sleep stage data and sleep event data. Sleep stage data is typically used to characterize sleep stages, such as non-rapid eye movement sleep stages, and awake states, of a user during different periods of time, and sleep event data is used to mark specific events occurring during sleep, such as arousal, wakefulness, or bed departure. In existing sleep evaluation methods, sleep continuity is generally evaluated by counting the number of wakefulness, the total length of wakefulness, or calculating the duty cycle of the wakefulness time in the whole night of sleep. However, such evaluation methods focus on statistics of occurrence frequency or duration of the event itself, and use a uniform counting or weighting method to process, so that it is difficult to accurately describe the actual degree of sleep continuity impairment. Therefore, how to more reasonably evaluate different types of continuity anomalies in the sleep process based on the existing sleep stage data and sleep event data is still a technical problem to be solved in the sleep continuity evaluation field. Disclosure of Invention Based on the foregoing, it is necessary to provide a sleep evaluation method, apparatus and computer device to solve the problem that it is difficult to accurately characterize sleep continuity in the conventional sleep evaluation method. A sleep assessment method, the method comprising: acquiring sleep monitoring data of a user to be evaluated; Determining at least one continuous abnormal event based on the sleep monitoring data, wherein the continuous abnormal event is an arousal event, a non-sleep event or a continuous abnormal time duration abnormal event of each sleep stage in the sleep monitoring data; Calculating event influence time of each continuity abnormal event based on the time attribute and the characteristic attribute of each continuity abnormal event; and determining a sleep continuity evaluation result of the user to be evaluated based on the event influence time of each continuity abnormal event. Optionally, the sleep monitoring data includes sleep event data, and the determining, based on the sleep monitoring data, at least one continuity exception event includes: determining the occurrence time point and the ending time point of arousal in the sleep event data; And when the duration from the occurrence time point to the ending time point is smaller than the preset arousal duration, determining the sleep segment from the occurrence time point to the ending time point as the arousal event. Optionally, the sleep monitoring data includes sleep stage data, and the determining, based on the sleep monitoring data, at least one continuity exception event includes: extracting stage labels of each sleep stage from the sleep stage data; If the stage label is not a preset sleep event label, the corresponding sleep stage is the non-sleep event. Optionally, the determining at least one continuity abnormal event based on the sleep monitoring data further includes: if the stage label is a preset sleep event label, determining the stage duration corresponding to the sleep stage; performing continuous duration deviation judgment in a preset reference duration data set based on the stage duration to obtain a judgment result; And when the judging result is that the stage duration is smaller than the reference duration corresponding to the preset reference duration data set, the corresponding sleep stage is the duration abnormal event. Optionally, before the duration deviation judgment is performed in the preset reference duration data set based on the stage duration, and the judgment result is obtained, the method further includes: Acquiring user information of the user to be evaluated and historical sleep monitoring data meeting preset conditions; based on the historical sleep monitoring data, calculating a reference time length calculation coefficient of each sleep stage; Calculating a coefficient and the user information based on the reference time length of each sleep stage, and calculating the reference time length of