WO2016107217A1 - Procédé et terminal de surveillance du sommeil - Google Patents

Procédé et terminal de surveillance du sommeil Download PDF

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Publication number
WO2016107217A1
WO2016107217A1 PCT/CN2015/089873 CN2015089873W WO2016107217A1 WO 2016107217 A1 WO2016107217 A1 WO 2016107217A1 CN 2015089873 W CN2015089873 W CN 2015089873W WO 2016107217 A1 WO2016107217 A1 WO 2016107217A1
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WO
WIPO (PCT)
Prior art keywords
segment
sleep state
preset
inter
terminal
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PCT/CN2015/089873
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English (en)
Chinese (zh)
Inventor
刘均
康晓云
龙知才
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深圳市元征科技股份有限公司
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Publication of WO2016107217A1 publication Critical patent/WO2016107217A1/fr

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Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16Z—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS, NOT OTHERWISE PROVIDED FOR
    • G16Z99/00—Subject matter not provided for in other main groups of this subclass

Definitions

  • the present invention relates to the field of electronic technologies, and in particular, to a sleep monitoring method and a terminal.
  • Sleep is a normal physiological activity necessary for the human body, and one third of human life is spent in sleep. Sleep can promote brain development, promote growth, eliminate fatigue, restore physical strength, consolidate memory, delay aging, enhance immunity, and protect the nervous system. Sleep disorders such as sleep disorders and sleep disorders can affect a person's mental state and are precursors and triggers for other diseases. The occurrence of sleep problems is random, unpredictable, and requires long-term sleep monitoring of patients to detect sleep problems.
  • subjective evaluation method and objective evaluation method which are subjective evaluation method and objective evaluation method respectively.
  • Subjective assessment patients indirectly assess the quality of sleep by filling out the evaluation scale. This method is simple, easy, and very low cost, and is suitable for large-scale use, but the evaluation effect is closely related to the status of the person being evaluated.
  • the objective evaluation method is to measure the quality of sleep by measuring various physiological indexes in human sleep.
  • the main monitoring methods are as follows: polysomnography, bispectral index, sleep state video monitoring, blood oxygen saturation sleep monitoring, temperature Change recorders, activity recorders, etc., this method is more cumbersome.
  • Embodiments of the present invention provide a sleep monitoring method and a terminal, which can improve the accuracy of sleep monitoring, and are simple and convenient to operate.
  • a first aspect of the embodiments of the present invention provides a sleep monitoring method, including:
  • the terminal detects acceleration data of the terminal
  • the terminal calculates a body motion strength according to the acceleration data; [0013] the terminal calculates the body motion strength according to a preset algorithm to obtain a first body motion strength of the first preset interval;
  • the terminal determines, according to the first body motion strength, a sleep state of the user in the first preset session.
  • a second aspect of the embodiment of the present invention provides a terminal, including:
  • a detecting unit configured to detect acceleration data of the terminal
  • a first calculating unit configured to calculate a body motion strength according to the acceleration data detected by the detecting unit
  • a second calculating unit configured to calculate the body motion intensity according to a preset algorithm to obtain a first body motion strength of the first preset inter-turn segment
  • an analyzing unit configured to analyze, according to the first body motion intensity, a sleep state of the user in the first preset interval.
  • the terminal detects the acceleration data of the terminal; the terminal calculates the body motion strength according to the acceleration data; the terminal calculates the body motion strength according to a preset algorithm to obtain the first pre- The first body motion strength of the inter-segment segment is set; the terminal determines the sleep state of the user in the first preset inter-segment segment according to the first body motion strength.
  • FIG. 1 is a schematic flow chart of a first embodiment of a sleep monitoring method according to an embodiment of the present invention
  • FIG. 2 is a schematic flowchart of a second embodiment of a sleep monitoring method according to an embodiment of the present invention
  • FIG. 3 is a schematic flow chart of a third embodiment of a sleep monitoring method according to an embodiment of the present invention.
  • FIG. 4 is a schematic flowchart diagram of a fourth embodiment of a sleep monitoring method according to an embodiment of the present invention.
  • FIG. 5 is a schematic structural diagram of a first embodiment of a terminal according to an embodiment of the present disclosure
  • FIG. 5b is another schematic structural diagram of a first embodiment of a terminal according to an embodiment of the present disclosure
  • FIG. 6 is a schematic structural diagram of a second embodiment of a terminal according to an embodiment of the present disclosure.
  • FIG. 7 is a schematic structural diagram of a third embodiment of a terminal according to an embodiment of the present invention.
  • FIG. 8 is a schematic structural diagram of a fourth embodiment of a terminal according to an embodiment of the present invention.
  • FIG. 9 is a schematic structural diagram of a fifth embodiment of a terminal according to an embodiment of the present invention.
  • the terminal may include, but is not limited to, a notebook computer, a mobile phone, a tablet computer, a smart wearable device, and the like.
  • the system of the terminal refers to the operating system of the terminal, and may include, but is not limited to, an Android system, a Symbian system, a Windows system, an IOS (Apple's mobile operating system) system, and the like.
  • the Android terminal refers to the terminal of the Android system
  • the Saipan terminal refers to the terminal of the Saipan system, and the like.
  • the above terminals are merely examples, not exhaustive, and include but are not limited to the above terminals.
  • FIG. 1 is a schematic flow chart of a first embodiment of a sleep monitoring method according to an embodiment of the present invention.
  • the sleep monitoring method described in this embodiment includes the steps of:
  • the terminal detects acceleration data of the terminal.
  • the terminal may detect the acceleration data of the terminal through the acceleration sensor of the terminal.
  • the acceleration sensor data can include acceleration data in three directions of X, ⁇ , and ⁇ axes.
  • the acceleration data can take acceleration data in any direction, acceleration data in any two directions, or acceleration in three directions.
  • the acceleration sensor can collect the acceleration data of the three axes ( ⁇ , ⁇ , ⁇ , respectively) and send the data to the sleep monitoring algorithm. After the operation of the sleep monitoring algorithm, the result value is transmitted to the App, App of the mobile phone. You can display a few days or a few minutes or a few minutes of sleep, deep sleep and light sleep. Users can know if they should adjust their schedule according to their sleep.
  • the terminal calculates a body motion strength according to the acceleration data.
  • the terminal calculates the body motion strength according to the acceleration data.
  • the body motion intensity is determined by the acquired acceleration data, and the body motion strength is a parameter for measuring the motion state of the acceleration sensor in the preset inter-turn interval.
  • the terminal calculates the body motion intensity by calculating the acceleration data according to a preset formula. Specifically, the method described in FIG. 2
  • the terminal calculates the body motion strength according to a preset algorithm to obtain a first body motion strength of the first preset session.
  • the terminal calculates the body motion strength according to a preset algorithm to obtain a first integral dynamic strength of the first preset inter-segment.
  • the preset algorithm is specifically as described in FIG.
  • the first predetermined interval is a period of time, such as a few minutes, a few seconds, or a small flaw, preferably a few minutes or tens of minutes, for example, 7 minutes.
  • S104 The terminal analyzes a sleep state of the user in the first preset interval according to the first body motion strength.
  • the terminal analyzes a sleep state of the user in the first preset interval according to the first body motion strength.
  • the sleep state can be a setting of the system, such as the awake state is 1, and the sleep state is 0.
  • a feasible definition manner if the first body motion strength is greater than 0, the sleep state of the i-th minute is 1, indicating an awake state, otherwise, if the first body motion strength is less than or equal to 0, the sleep state of the i-th minute is 0, indicating sleep state.
  • the terminal detects the acceleration data of the terminal; the terminal calculates the body motion strength according to the acceleration data; and the terminal calculates the body motion strength according to a preset algorithm to obtain the first pre- The first body motion strength of the inter-segment segment is set; the terminal analyzes a sleep state of the user in the first preset inter-segment segment according to the first body motion strength.
  • the embodiment of the invention can improve the accuracy of sleep monitoring, and the operation is simple and convenient.
  • FIG. 2 is a schematic diagram of a second embodiment of a sleep monitoring method according to an embodiment of the present invention
  • FIG. 2 is a specific refinement of S102 in the method described in FIG.
  • the sleep monitoring method described in this embodiment includes the steps of:
  • S201 The terminal performs a difference sum of the acceleration data according to a preset sequence.
  • the terminal obtains a difference sum of the acceleration data according to a preset order.
  • the smart bracelet has sensors such as acceleration, heart rate, and temperature and humidity, including a step counter module, a sleep monitoring module, and a heart rate monitoring module, and the sleep monitoring module is used to monitor sleep.
  • the preset order may be a sequence of times, and preferably, the order of the acceleration data sampling is used.
  • the sleep monitoring module is composed of a sleep monitoring algorithm. The calculation can be as follows:
  • each minute of the 100 minutes is divided into 30 segments, and each segment takes a differential accumulation of 100 acceleration data, and the body motion intensity is calculated according to the differential accumulation per minute. Further, the sleep state per minute can be judged based on the body motion intensity.
  • the sleep state value can be defined as a deep sleep, 0 is defined as light sleep, and 1 is defined as awake. The terminal can update the sleep state value every minute, judge the deep sleep state or the light sleep state, and record the sleep distribution.
  • the latter acceleration data representing the current acceleration data indicates the sum of the differences. Each difference is added from zero, preferably one hundred times, because there are 100 acceleration data. The differential accumulation of each of the 100 acceleration data is prepared for the subsequent differential accumulation per minute.
  • the body motion strength may be calculated by taking acceleration data in one direction, and the calculation formulas are as follows:
  • the body motion strength may be calculated by taking acceleration data in any two directions, and the calculation formulas are as follows:
  • S202 The terminal performs a square operation on the difference sum of the second preset segments in the difference sum to calculate the body motion strength.
  • the terminal performs a square operation on the difference sum of the second preset segments in the difference sum to calculate the body motion strength.
  • the terminal in the embodiment of the present invention performs differential summation on the acceleration data according to a preset sequence; the terminal performs a square operation on the difference sum of the second preset inter-segment segments in the difference sum to calculate
  • the body strength is derived.
  • the body motion strength can be defined.
  • FIG. 3 is a schematic flow chart of a third embodiment of a sleep monitoring method according to an embodiment of the present invention.
  • Figure 3 is a detailed refinement of S103 of the method described in Figure 1.
  • the sleep monitoring method described in this embodiment is specifically combined with the method described in the embodiment of FIG. 1 and FIG. 2, including the steps of:
  • the terminal acquires a body motion strength of a third preset inter-segment segment with the first preset inter-segment segment as an intermediate inter-segment segment.
  • the terminal acquires the body motion strength of the third preset inter-segment segment with the first preset inter-segment segment as the intermediate inter-segment segment.
  • the third predetermined interval is 7 minutes as described below. Wherein, the third preset interval is greater than During the first preset interval, the third predetermined interval includes 7 segments, and the first predetermined interval is the fourth minute within 7 minutes.
  • the terminal calculates the body motion strength according to the preset algorithm to obtain a first body motion strength of the first preset inter-segment.
  • the terminal calculates the body motion intensity according to a preset algorithm to obtain the first integral motion strength of the first preset inter-segment.
  • the first preset inter-segment is a preset period of time, as described in the following 1 minute.
  • the preset algorithm is as shown in the following equation (11).
  • the terminal determines the sleep state of the middle one minute by the physical strength of the continuous seven minutes. Since the sleep state per minute is highly correlated with the physical strength of the seven consecutive minutes around the minute, continuous use is available.
  • the seven-minute body motion strength calculates the sleep state in the middle for one minute, and its calculation formula is as shown in equation (11):
  • W ⁇ MmSF i ⁇ 4] indicates the body motion intensity at the i-4th minute
  • the terminal performs a standard deviation process on the difference sum to obtain a sleep state value.
  • the terminal can update the sleep monitoring algorithm, such as the sleep state update every minute, and can be divided into two parts: One part is to obtain the sleep state value by using the differential accumulation data of seven consecutive minutes to obtain the sleep state value, and the calculation formula of the sleep state value. For:
  • Sqri denotes the square root operation, which represents the sum of the squares of the sum of the differential accumulations per minute for seven consecutive minutes.
  • the terminal in the embodiment of the present invention acquires a third preset ⁇ with the first preset interval as an intermediate segment The body motion strength of the interval; the terminal calculates the body motion strength according to the preset algorithm to obtain the first body motion strength of the first preset segment.
  • the embodiment of the invention can improve the accuracy of sleep monitoring, and the operation is simple and convenient.
  • FIG. 4 is a schematic flow chart of a fourth embodiment of a sleep monitoring method according to an embodiment of the present invention.
  • Figure 4 is a subsequent optimization of the method described in Figures 1 through 3, which depicts the optimization of the sleep monitoring algorithm.
  • the sleep monitoring method described in this embodiment includes the steps of:
  • the sleep state value of the first preset segment of the terminal is compared with the first preset reference value.
  • the first preset reference value is an empirical value, which may be specifically analyzed according to data collected in a specific application.
  • the terminal If the sleep state value is greater than the first preset reference value, the terminal updates the sleep state corresponding to the sleep state value of the first preset segment to an awake state. .
  • the terminal updates the sleep state corresponding to the sleep state value of the first preset segment to the awake state.
  • the terminal sets the first preset interval
  • the sleep state corresponding to the sleep state value is updated to a light sleep state.
  • the terminal updates the sleep state corresponding to the sleep state value of the first preset segment to shallow Sleeping state.
  • the light sleep state can be defined as zero.
  • the terminal updates the sleep state corresponding to the sleep state value of the fourth preset segment to a deep sleep. a state in which the fourth predetermined inter-segment segment is equal to the inter-turn length of the first inter-segment segment, and the fourth predetermined inter-segment segment is the previous inter-turn of the first inter-segment segment segment.
  • the terminal updates the sleep state corresponding to the sleep state value of the fourth preset segment to a deep sleep state, where the fourth preset segment With the first section
  • the lengths of the turns are equal
  • the fourth predetermined interval is the previous inter-segment of the first inter-segment.
  • the fourth predetermined inter-segment segment may be an inter-segment segment that is equal in length to the first preset inter-segment segment.
  • the sleep state is a sleep state or an awake state
  • the sleep state is a deep sleep state or a light sleep state
  • the sleep state value is greater than the first preset reference value a, and the first preset reference value a is a value obtained according to a statistical rule
  • the current one minute sleep state should be updated to the awake state
  • the sleep state The state value is smaller than the first preset reference value a, and the second preset reference value b is also obtained according to the statistical rule, and the current one minute sleep state is updated to shallow.
  • the sleep state if the standard deviation is less than the value b, the current one minute sleep state should be updated to the deep sleep state.
  • the previous inter-segment of the first preset inter-segment is a fifth preset inter-segment, and the next one of the first preset inter-segments If the inter-segment is the sixth preset inter-segment, if the sleep state corresponding to the sleep state value of the first preset inter-segment is the sleep state, and the fifth preset inter-segment The sleep state corresponding to the sleep state is an awake state, and the sleep state corresponding to the sleep state value of the sixth preset segment is an awake state, and the terminal sets the first preset segment The sleep state corresponding to the sleep state value is updated to the awake state.
  • the sleep state in the middle of one minute between three consecutive minutes is the sleep state, and the state of one minute before and after is the awake state, the sleep state in the middle one minute can be changed to the awake state, because it is impossible. I fell asleep for a minute in the middle of waking.
  • the terminal may finally record the sleep state per minute according to the record of the sleep distribution, and the structure includes a continuous inter-segment segment and a sleep state between each segment.
  • the structure includes a continuous inter-segment segment and a sleep state between each segment.
  • the sleep state value of the first preset segment of the terminal is compared with a first preset reference value, where the sleep state value is greater than the first preset reference value.
  • the terminal updates the sleep state corresponding to the sleep state value of the first preset segment to an awake state; if the sleep state value is smaller than the first preset reference value, The sleep state value is greater than the second preset reference value, and the terminal updates the sleep state corresponding to the sleep state value of the first preset interval to a light sleep state;
  • the second preset reference value the terminal updates the sleep state corresponding to the sleep state value of the fourth preset interval to a deep sleep state, where
  • the fourth predetermined inter-segment segment is equal to the inter-turn length of the first inter-segment segment, and the fourth predetermined inter-segment segment is the previous inter-segment segment of the first inter-segment segment.
  • the sleep state corresponding to the sleep state value of the first preset segment is the sleep state
  • the sleep state corresponding to the sleep state value of the fifth preset segment is the awake state
  • the sleep state corresponding to the sleep state value of the sixth preset segment is an awake state
  • the terminal updates the sleep state corresponding to the sleep state value of the first preset segment to an awake state.
  • the embodiment of the invention can improve the accuracy of sleep monitoring, and the operation is simple and convenient.
  • FIG. 5a is a schematic structural diagram of a first embodiment of a terminal according to an embodiment of the present invention.
  • the detecting unit 501 is configured to detect acceleration data of the terminal.
  • the detecting unit 501 can detect acceleration data of the terminal.
  • the acceleration sensor data can include acceleration data in three directions of X, ⁇ , and ⁇ axes.
  • the acceleration data can take acceleration data in any direction, acceleration data in any two directions, or acceleration data in three directions.
  • the acceleration sensor can collect the acceleration data of the three axes ( ⁇ , ⁇ , ⁇ , respectively) and send the data to the sleep monitoring algorithm. After the operation of the sleep monitoring algorithm, the result value is transmitted to the App, App of the mobile phone. You can display a few days or a few minutes or a few minutes of sleep, deep sleep and light sleep. Users can know if they should adjust their schedule according to their sleep.
  • the first calculating unit 502 is configured to calculate a body strength according to the acceleration data detected by the detecting unit.
  • the first calculating unit 502 can calculate the body motion strength according to the acceleration data detected by the detecting unit.
  • the body motion strength is determined by the acquired acceleration data, which is a parameter that measures the motion state of the acceleration sensor in the preset inter-turn.
  • the terminal calculates the acceleration data according to the preset formula to obtain the body strength.
  • the second calculating unit 503 is configured to calculate the body motion strength according to a preset algorithm to obtain a first body motion strength of the first preset inter-segment.
  • the second calculating unit 503 is configured to calculate the body motion intensity according to a preset algorithm to obtain the first body motion strength of the first preset inter-segment.
  • the first predetermined interval is a period of time, such as a few minutes, a few seconds, or a small flaw, preferably a few minutes or tens of minutes, for example, 7 minutes.
  • the analyzing unit 504 is configured to analyze, according to the first body motion strength, a sleep state of the user in the first preset interval.
  • the analyzing unit 504 is configured to analyze a sleep state of the user in the first preset interval according to the first body motion strength.
  • the sleep state may be a setting of the system, such as the awake state is 1, and the sleep state is 0. - a feasible definition manner, if the first body motion strength is greater than 0, the sleep state of the i-th minute is 1, Indicates the awake state. Otherwise, if the first body motion strength is less than or equal to 0, the sleep state of the i-th minute is 0, indicating that the sleep state is already present.
  • the terminal further includes a standard deviation calculation unit 505, configured to perform standard deviation processing on the difference sum to obtain the sleep. Status value.
  • the detecting unit 501 detects the acceleration data of the terminal in the embodiment of the present invention; the first calculating unit 502 calculates the body motion strength according to the acceleration data detected by the detecting unit; the second calculating unit 503 follows the preset algorithm.
  • the body motion strength is calculated to obtain a first body motion strength of the first preset inter-turn segment; the analyzing unit 504 analyzes the sleep state of the user in the first preset inter-segment segment according to the first body motion strength .
  • the embodiment of the invention can improve the accuracy of sleep monitoring, and the operation is simple and convenient.
  • FIG. 6 is a schematic structural diagram of a second embodiment of a terminal according to an embodiment of the present invention. It is the specific structure of the first computing unit 502 in Figure 5a or Figure 5b.
  • the terminal described in this embodiment is as follows:
  • the summation unit 601 is configured to perform differential summation on the acceleration data in a preset order.
  • the summation unit 601 is configured to perform differential summation on the acceleration data in a preset order.
  • the smart bracelet has sensors such as acceleration, heart rate, and temperature and humidity, including a step counter module, a sleep monitoring module, and a heart rate monitoring module, and the sleep monitoring module is used to monitor sleep.
  • the preset order may be sequential between the turns, and preferably, the order of the acceleration data sampling is used.
  • the sleep monitoring module consists of a sleep monitoring algorithm, which can be calculated as follows:
  • each minute of 100 minutes is divided into 30 segments, and each segment takes a differential accumulation of 100 acceleration data, and the body motion intensity is calculated according to the differential accumulation per minute.
  • the sleep state per minute can be judged based on the body motion strength.
  • An optional sleep state definition mode the sleep state value can be defined as a deep sleep state for a negative number, 0 is defined as a light sleep state, and 1 is defined as a awake state.
  • the terminal can update the sleep state every minute, judge the deep sleep state or the light sleep state and record the sleep distribution.
  • the differential accumulation formula of each piece of 100 acceleration data is as shown in equations (13) and (14):
  • the latter acceleration data representing the current acceleration data indicates the sum of the differences. Each difference is added from zero, preferably one hundred times, because there are 100 acceleration data. The differential accumulation of each of the 100 acceleration data is prepared for the subsequent differential accumulation per minute.
  • the body motion strength may be calculated by taking acceleration data in one direction, and the calculation formulas are as follows:
  • the body motion strength can be calculated by taking acceleration data in any two directions, and the calculation formulas are as follows:
  • ⁇ ⁇ indicates the acceleration and one-minute differential accumulation and data of the x-axis acceleration sensor on the X-axis.
  • the square unit 602 is configured to perform a square operation on the difference sum of the second preset segments in the difference sum
  • the buffer unit 602 is configured to perform a square operation on the difference sum of the second preset segments in the difference sum to calculate the body motion strength.
  • the summation unit 601 performs a difference sum on the acceleration data according to a preset sequence; the buffer unit 602 performs a square operation on the difference sum of the second preset inter-segments in the difference sum. To calculate the body motion strength.
  • the embodiment of the invention can improve the accuracy of sleep monitoring, and the operation is simple and convenient.
  • FIG. 7 is a schematic structural diagram of a third embodiment of a terminal according to an embodiment of the present invention. It is the specific structure of the second calculation unit 503 in Fig. 5a or 5b.
  • the terminal described in this embodiment is specifically as follows:
  • the obtaining unit 701 is configured to acquire a body motion strength of the third preset segment that is the intermediate segment between the first preset segment.
  • the obtaining unit 701 acquires the body motion strength of the third preset inter-segment segment with the first preset inter-segment segment as the intermediate inter-segment segment.
  • the third predetermined interval is 7 minutes as described below. Wherein, the third preset interval is greater than the first predetermined interval, and the third predetermined interval includes 7 segments, and the first predetermined interval is 7 minutes. Four minutes.
  • the second calculating sub-unit 702 is configured to calculate the body motion strength according to the preset algorithm to obtain the first body motion strength of the first preset inter-segment.
  • the second calculating subunit 702 calculates the body motion intensity according to a preset algorithm to obtain the first The first body motion strength of the inter-segment segment is preset.
  • the first preset interval is a preset period of time, as described in the following one minute.
  • the preset algorithm is as shown in the following equation (23).
  • the terminal determines the sleep state of the middle one minute by the physical strength of the continuous seven minutes. Since the sleep state per minute is highly correlated with the physical strength of the seven consecutive minutes around the minute, the terminal may be continuously used.
  • the seven-minute body motion strength calculates the sleep state in the middle for one minute, and the calculation formula is as shown in equation (23):
  • the sleep state of the i-th minute is 1, indicating that the state is awake, otherwise, if Less than or equal to 0, indicating that the state has been asleep.
  • the terminal may update the sleep monitoring algorithm, such as the sleep state update every minute, and may be divided into two parts: one part is to obtain the sleep state value by using the differential accumulation data of seven consecutive minutes to obtain the standard deviation.
  • the sleep state value is calculated as:
  • the acquiring unit acquires the body motion strength of the third preset inter-segment segment with the first preset inter-segment segment as the middle inter-segment segment; the second calculating sub-unit 702 follows the preset algorithm.
  • the body motion strength is calculated to obtain a first body motion strength of the first predetermined inter-turn segment.
  • FIG. 8 is a schematic structural diagram of a fourth embodiment of a terminal according to an embodiment of the present invention. It is the specific structure of the analysis unit 504 in Figure 5a or Figure 5b. The terminal described in this embodiment is specifically as follows: [0161]
  • the comparing unit 801 is configured to compare the sleep state value of the first preset segment with a first preset reference value.
  • the comparing unit 801 is configured to compare the sleep state value of the first preset segment with the first preset reference value.
  • the updating unit 802 is configured to: if the sleep state value is greater than the first preset reference value, update the sleep state corresponding to the sleep state value of the first preset segment to awake status.
  • the sleeping state is the sleeping state or the awake state
  • the sleeping state is the deep sleeping state or the shallow sleeping state.
  • the update unit 802 is further configured to:
  • the sleep state value of the first preset segment is corresponding to The sleep state is updated to a light sleep state.
  • the updating unit 802 is further configured to:
  • the sleep state value is smaller than the second preset reference value, updating the sleep state corresponding to the sleep state value of the fourth preset interval to a deep sleep state, where
  • the fourth predetermined inter-segment segment is equal to the inter-turn length of the first inter-segment segment, and the fourth predetermined inter-segment segment is the previous inter-segment segment of the first inter-segment segment.
  • the updating unit 802 is further configured to:
  • the sleep state corresponding to the sleep state value of the first preset segment is the sleep state, and the sleep state corresponding to the sleep state value of the fifth preset segment is awake a state, wherein the sleep state corresponding to the sleep state value of the sixth preset segment is an awake state, and updating the sleep state corresponding to the sleep state value of the first preset segment to an awake state .
  • the comparing unit 801 compares the sleep state value of the first preset segment with the first preset reference value. If the sleep state value is greater than the first preset reference value, the updating unit 802 updates the sleep state corresponding to the sleep state value of the first preset segment to an awake state; The state value is smaller than the first preset reference value, and the sleep state value is greater than the second preset reference value, and the updating unit 802 sets the sleep state corresponding to the sleep state value of the first preset segment The state is updated to a light sleep state, and if the sleep state value is smaller than the second preset reference value, the updating unit 802 sets the sleep state corresponding to the sleep state value of the fourth preset segment Updated to a deep sleep state, wherein the fourth predetermined inter-segment segment is equal to the inter-turn length of the first inter-segment segment, and the fourth predetermined inter-segment segment is the previous one of the first inter-segment segment If the sleep state corresponding to the sleep state value of the first preset reference value
  • FIG. 9 is a schematic structural diagram of a fifth embodiment of a terminal according to an embodiment of the present invention.
  • the terminal includes: at least one input device 1000; at least one output device 2000; at least one processor 3 000
  • the input device 1000, the output device 2000, the processor 3000, and the memory 4000 are connected by a bus 5000, for example, a CPU; and a memory 4000.
  • the processor 3000 is configured to detect acceleration data of the terminal
  • the processor 3000 is further configured to:
  • the processor 3000 is further configured to: calculate the body motion strength according to a preset algorithm to obtain a first body motion strength of the first preset interval;
  • the processor 3000 is further configured to:
  • the processor 3000 is further configured to:
  • the processor 3000 is further configured to:
  • the processor 3000 is further configured to:
  • the processor 3000 is further configured to:
  • the sleep state value is smaller than the first preset reference value, and the sleep state value is greater than the second preset reference value, the dormant state value of the first preset segment is corresponding to The sleep state is updated to a light sleep state;
  • the sleep state value is smaller than the second preset reference value, updating the sleep state corresponding to the sleep state value of the fourth preset interval to a deep sleep state, where
  • the fourth predetermined inter-segment segment is equal to the inter-turn length of the first inter-segment segment, and the fourth predetermined inter-segment segment is the previous inter-segment segment of the first inter-segment segment.
  • the processor 3000 is further configured to:
  • the first inter-segment of the first preset inter-segment is a fifth preset inter-segment
  • the next inter-segment of the first preset inter-segment is a sixth preset inter-segment
  • the sleep state corresponding to the sleep state value of the first preset segment is the sleep state
  • the sleep state corresponding to the sleep state value of the fifth preset segment In the awake state
  • the sleep state corresponding to the sleep state value of the sixth preset segment is an awake state
  • the sleep state corresponding to the sleep state value of the first preset segment is updated to Awake state.
  • the input device 1000, the output device 2000, and the processor 3000 described in the embodiments of the present invention may be configured in the first to fourth embodiments of the sleep monitoring method provided by the embodiments of the present invention.
  • the implementation manners of the terminals in the first to fourth embodiments of the terminal provided by the embodiments of the present invention are also implemented, and details are not described herein again.
  • the unit or subunit in all embodiments of the present invention may be implemented by a general-purpose integrated circuit, such as a CPU (Ce ntral Processing Unit), or by an ASIC (Application Specific Integrated Circuit).
  • a CPU CPU ntral Processing Unit
  • ASIC Application Specific Integrated Circuit
  • ROM read only memory
  • RAM random access memory

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Abstract

La présente invention concerne un procédé de surveillance du sommeil, comprenant : un terminal utilisé pour détecter des données d'accélération du terminal (S101); le terminal calcule une résistance de mouvement corporel selon les données d'accélération (S102); le terminal effectue un calcul sur la résistance de mouvement du corps selon un algorithme prédéfini, de manière à obtenir une première résistance de mouvement du corps d'une première période de temps prédéfinie (S103); le terminal détermine un état de sommeil d'un utilisateur dans la première période de temps préréglée conformément à la première résistance de mouvement du corps (S104). Le procédé de surveillance du sommeil analyse l'état de sommeil de l'utilisateur de manière à améliorer la précision de surveillance du sommeil, et les opérations sont simples et pratiques.
PCT/CN2015/089873 2014-12-31 2015-09-17 Procédé et terminal de surveillance du sommeil WO2016107217A1 (fr)

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CN105030199A (zh) * 2015-06-24 2015-11-11 深圳市元征软件开发有限公司 睡眠监测方法及装置
WO2017070852A1 (fr) * 2015-10-27 2017-05-04 深圳还是威健康科技有限公司 Procédé de mise à jour et de sortie d'état de sommeil, bracelet intelligent et terminal
CN107638165B (zh) * 2016-07-20 2021-01-26 平安科技（深圳）有限公司 一种睡眠检测方法及装置
CN106419893A (zh) * 2016-09-18 2017-02-22 广州视源电子科技股份有限公司 睡眠状态检测方法和装置
CN106333691A (zh) * 2016-10-27 2017-01-18 深圳市万机创意电子科技有限公司 判断人体睡眠状态、静止状态和运动状态的方法及装置
CN109199325B (zh) * 2017-07-05 2021-06-15 中移（杭州）信息技术有限公司 一种睡眠监测方法及装置
CN109303565B (zh) * 2017-07-26 2021-08-17 中移（杭州）信息技术有限公司 一种睡眠状态的预测方法及装置
CN108030467B (zh) * 2017-11-22 2021-07-02 广东思派康电子科技有限公司 电子手环及计算机可读存储介质
CN110604859B (zh) * 2019-10-24 2022-03-22 深圳易嘉恩科技有限公司 基于智能家居设备的辅助睡眠控制方法及系统
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