Method and system for monitoring sleep quality based on pulse wave data

[0025] Example one

[0026] figure 1 The implementation process of the method for monitoring sleep quality based on pulse wave data provided in the first embodiment of the present invention is shown. The pulse wave monitoring bracelet is the main body of execution, and the details are as follows:

[0027] It should be noted that the theory of sleep health preservation in traditional Chinese medicine includes the detoxification time of various organs in the sleep process, such as figure 2 As shown, each organ detoxification corresponds to different time periods.

[0028] In step S101, the pulse wave data is monitored in real time by the pulse wave infrared detection sensor, and the pulse wave data includes several pulse rate values.

[0029] In this embodiment, the pulse wave data is a human hand pulse wave signal collected by a pulse wave infrared detection sensor.

[0030] In step S102, the motion data of the monitored person during sleep is monitored by the motion sensor, and the motion data includes big and small movements.

[0031] In this embodiment, the processor of the pulse wave monitoring bracelet receives the motion data collected by the motion sensor, analyzes and obtains the amplitude of the motion of the monitored person during sleep, and the sensor is worn on the experimenter with different degrees of exercise for many times. The analysis of the different values ​​can judge the degree of the monitored person's movement through the results of the motion sensor. According to the results of using the motion sensor in different motion states, we divide the monitored person’s movements during sleep into small and large movements. Small movements refer to those where the body does not leave the bed or the center of gravity of the body is close to the bed, such as turning over or lying on the bed and stretching out your hands. Superficial movements, big movements refer to movements such as stepping, getting out of bed, or standing up, such as when the body leaves the bed or the center of gravity is not close to the surface of the bed.

[0032] In step S103, according to the pulse wave data, motion data, and detection time, obtain the sleep state of the subject, the start and end time of each sleep state, and the time period of each sleep state, the sleep state including the awakening period , Light sleep period, deep sleep period, dream interval, micro-wake period.

[0033] In this embodiment, the sleep state includes the awakening period, the light sleep period, the deep sleep period, the dream interval, and the micro-wake period. The awakening period includes two states: the awakening period before sleep, that is, the user's normal activity state, and the sleep state. The awakening period means that the user receives external stimuli during sleep, such as temperature, sound, or action stimuli, or awakens from sleep due to physical discomfort; in the light sleep period, the human body has entered sleep, but the depth of sleep is very shallow; During the sleep period, the human body has entered sleep and deep sleep, at this time the pulse rate of the human body will drop to a very low value; the dreaming interval, the human body is in the process of dreaming; the micro-awakening period is between sleep awakening and light sleep In an excessive state. The result of the motion sensor shows that the monitored person has no action within half an hour. Combined with the normal pulse wave data of the monitored person during this time period, it is considered that the monitored person enters the sleep process during this time period, and the start time of sleep is obtained. Ts; the data result of the motion sensor shows that the monitored person has a large amount of activity and pulse rate from the sleep process to a large extent, it is considered that the monitored person ends the sleep process during this time period, and the sleep end time Te is obtained .

[0034] Wherein, according to the pulse wave data and motion data, obtaining the sleep state of the subject specifically includes:

[0035] Step S11: Obtain a sleep state parameter K according to the pulse wave data, where K = the ratio of the pulse rate difference to the reference pulse rate, and the pulse rate difference is the difference between the pulse wave data and the reference pulse rate, The reference pulse rate is calculated from the pulse wave data;

[0036] In this embodiment, the calculation method of the reference pulse rate is specifically:

[0037] Step S111: Obtain the set B[1.2*Hv,1.5*Hv] through the relationship between the lowest average pulse rate Hv during sleep and the reference pulse rate. The reference pulse rate Hb belongs to the set B, in which all pulse rate values ​​during sleep are calculated Sort from small to large, after removing the first five pulse rate values, sum up the remaining top ten pulse rate values ​​and get the average value to get the lowest average sleep pulse rate Hv;

[0038] In step S112, by judging whether the pulse rate value within the preset time from the sleep start time point Ts belongs to the set B, all the pulse rates belonging to the set B are only summed and averaged to obtain the reference pulse rate Hb.

[0039] Step S12, if the K value is between 0 and 0.16, the sleep state is the awake period; if the K value is between -0.06 and -0.16, the sleep state is the light sleep period; if the K value is between -0.16 and -0.5, then sleep The state is the deep sleep period; if the K value at two time points is in the deep sleep period, but at least one point between the two points is in the light sleep period, then the interval between the two time points is the dreaming interval; if The K value is between -0.59 and -0.01, and the K value of the previous point and the K value of the next point at this time point are in the light sleep period or the deep sleep period, then the sleep state is a wakeful period.

[0040] Wherein, the calculation method of the start and end time of each sleep state is specifically:

[0041] Step S31: Analyze the pulse wave data of the monitored person during sleep, where Hr represents the pulse wave data of the monitored person during sleep, and the CNTn variable represents the number of pulse wave data that meet the corresponding conditions, n = The first preset duration, then Td is the deep sleep time, otherwise Td is the light sleep time; if the Kr value does not belong to the interval [-0.5, -0.16], judge whether the Kr value belongs to the interval [-0.16,-0.06] , If it is skip to step S32; the first preset duration is 15 min.

[0042] Step S32: add 1 to CNT2, Ts=CNT2*t, judge if Ts> = The second preset duration, Ts is the light sleep time; otherwise, it is judged whether the next Kr value belongs to the interval [-0.5, -0.16], if yes, skip to step S35, if not, then Ts is the light sleep time; otherwise Jump to determine whether the value of Kr belongs to the interval [-0.06, 0], if it is to jump to step S33; the second preset duration is 10 minutes.

[0043] Step S33: add 1 to CNT3, Ta=CNT3*t, judge if Ta

[0044] Step S34: add 1 to CNT4, Tw=CNT4*t, judge if Tw

[0045] Step S35: add 1 to CNT5, Tm=CNT5*t, Tm is the dreaming time; otherwise, skip to step S31; this loop until the end of the sleep process.

[0046] Specifically, when the pulse wave data of the monitored person is judged to be S32 or S33, if the data result of the motion sensor is expressed as a small movement, it means the turning over state. For the convenience of expression, the variable Bf represents the number of turning over during the sleep of the monitored person. It is judged that the turning over state Bf is increased by 1 and saved in the memory until the end of the sleep process. When the pulse wave data of the monitored person is judged to be S34, if the data result of the motion sensor indicates a large motion and the duration exceeds 7 minutes, it indicates the end of the sleep process; if the data result of the motion sensor indicates a small motion, and the duration More than 15 minutes indicates the end of the sleep process.

[0047] In step S104, the sleep quality of the monitored person is obtained according to the start and end time of each sleep state and the time period each sleep state is in, combined with the sleep regimen theory of traditional Chinese medicine.

[0048] In this embodiment, the sleep state of the monitored person is judged according to the pulse wave data during sleep and the motion sensor data during sleep, and the total sleep process time, the total deep sleep time, the proportion of awakening time, and The number of turns over, the number of waking up during sleep, the start and end time of sleep; the sleep state of the monitored person will be judged according to the pulse wave data during sleep and the motion sensor data during sleep. The total sleep process time and deep sleep will be calculated The total time, the proportion of awakening time, the number of turning over, the number of awakenings during sleep, and the start and end time of sleep are combined with the results of traditional Chinese medicine to determine whether the start and end time of sleep is appropriate. Whether the time period of deep sleep is within the stipulation that human organs are detoxified by time period in the sleep process included in the sleep regimen of traditional Chinese medicine, combined with the arm surface temperature change obtained by the body surface temperature sensor, scientific and reasonable suggestions for improving the quality of sleep are given.

[0049] Preferably, it further includes transmitting the pulse wave data, sleep quality, and sleep quality corresponding reasonable sleep quality improvement suggestions to the smart terminal. The smart terminals include smart phones, computers, and notebooks.

[0050] In this embodiment, the pulse wave signal of the human body is collected through the pulse wave monitoring sensor module, which has high collection efficiency and accurate data, which is conducive to accurate analysis of sleep quality. The wireless network module is used for detection data transmission without affecting sleep quality. Can detect sleep quality for a long time.

[0051] Example two

[0052] image 3 The specific structural block diagram of the system for monitoring sleep quality based on pulse wave data provided in the second embodiment of the present invention is shown. For ease of description, only the parts related to the embodiment of the present invention are shown. In this embodiment, the system for monitoring sleep quality based on pulse wave data includes: a pulse wave monitoring bracelet 1 and a smart terminal device 2, which communicate through a wireless network. Such as Figure 4 As shown, the pulse wave monitoring bracelet 1 is composed of a gravity sensor, a pulse rate sensor, a body surface temperature sensor, a storage module, a communication module, and an MCU module.

[0053] Wherein, the pulse wave monitoring bracelet 1 includes:

[0054] The first detection unit 11 is configured to monitor pulse wave data in real time through a pulse wave infrared detection sensor, and the pulse wave data includes several pulse rate values;

[0055] The second detection unit 12 is used for monitoring the motion data of the monitored person during sleep through the motion sensor, and the motion data includes big and small movements;

[0056] The state acquisition unit 13 is configured to acquire the sleep state of the subject, the start and end time of each sleep state, and the time period of each sleep state according to the pulse wave data, motion data, and detection time, the sleep state including Awakening period, light sleep period, deep sleep period, dreaming interval, micro-wake period;

[0057] The quality analysis unit 14 is used to obtain the sleep quality of the monitored person according to the start and end time of each sleep state and the time period each sleep state is in, combined with the theory of detoxification of human organs by time period in the sleep process of traditional Chinese medicine;

[0058] The smart terminal device 2 includes:

[0059] The data interaction unit 21 is configured to receive the pulse wave data, sleep quality, and sleep quality corresponding reasonable sleep quality improvement suggestions;

[0060] The result display unit 22 is used for replaying the pulse wave data and displaying sleep quality and reasonable sleep quality improvement suggestions corresponding to the sleep quality.

[0061] Further, the state obtaining unit is specifically configured to obtain a sleep state parameter K according to the pulse wave data, where K = the ratio of the pulse rate difference to the reference pulse rate, and the pulse rate difference is the pulse wave The difference between the data and the reference pulse rate, the reference pulse rate is calculated from the pulse wave data; if the K value is between 0 and 0.16, the sleep state is the awake period; if the K value is between -0.06 and -0.16, then The sleep state is a light sleep period; if the K value is between -0.16 to -0.5, the sleep state is a deep sleep period; if there are two time points in the K value in the deep sleep period, but at least one point between the two points In the light sleep period, the interval between the two time points is the dreaming interval; if the K value is between -0.59 and -0.01, and the K value at the previous point and the K value at the next point at that time point are in the light sleep period Or deep sleep period, the sleep state is a slightly awakened period.

[0062] Further, the state acquiring unit is further specifically configured to obtain the set B [1.2*Hv, 1.5*Hv] through the relationship between the lowest average pulse rate Hv of sleep and the reference pulse rate, and the reference pulse rate Hb belongs to the set B, where All pulse rate values ​​during sleep are sorted from small to large. After removing the first five pulse rate values, the remaining first ten pulse rate values ​​are summed and averaged to obtain the lowest average pulse rate Hv during sleep; Whether the pulse rate value within the preset time from the sleep start time point Ts belongs to set B, all the pulse rates belonging to set B are only summed and averaged to obtain the reference pulse rate Hb.

[0063] Further, the state acquisition unit is also used for step S31: analyzing the pulse wave data of the monitored person during sleep, where Hr represents the pulse wave data of the monitored person during sleep, and the CNTn variable represents the corresponding Number of conditional pulse wave data, n = The first preset duration, then Td is the deep sleep time, otherwise Td is the light sleep time; if the Kr value does not belong to the interval [-0.5, -0.16], judge whether the Kr value belongs to the interval [-0.16,-0.06] , If it is jump to step S32;

[0064] Step S32: add 1 to CNT2, Ts=CNT2*t, judge if Ts> = The second preset duration, Ts is the light sleep time; otherwise, it is judged whether the next Kr value belongs to the interval [-0.5, -0.16], if yes, skip to step S35, if not, then Ts is the light sleep time; otherwise Jump to judge whether the value of Kr belongs to the interval [-0.06, 0], if it is jump to step S33;

[0065] Step S33: add 1 to CNT3, Ta=CNT3*t, judge if Ta

[0066] Step S34: add 1 to CNT4, Tw=CNT4*t, judge if Tw

[0067] Step S35: add 1 to CNT5, Tm=CNT5*t, Tm is the dreaming time; otherwise, skip to step S31; this loop until the end of the sleep process.

[0068] Further, it also includes

[0069] The data transmission unit 25 is configured to transmit the pulse wave data, sleep quality, and sleep quality corresponding reasonable sleep quality improvement suggestions to the smart terminal.

[0070] The system for monitoring sleep quality based on pulse wave data provided by the embodiment of the present invention can be applied to the aforementioned corresponding method embodiment 1. For details, please refer to the description of the foregoing embodiment 1, which will not be repeated here.