WO2016201817A1 - 脉搏周期检测设备和方法和可穿戴电子设备 - Google Patents

脉搏周期检测设备和方法和可穿戴电子设备 Download PDF

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WO2016201817A1
WO2016201817A1 PCT/CN2015/090278 CN2015090278W WO2016201817A1 WO 2016201817 A1 WO2016201817 A1 WO 2016201817A1 CN 2015090278 W CN2015090278 W CN 2015090278W WO 2016201817 A1 WO2016201817 A1 WO 2016201817A1
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pulse period
pulse
wave signal
time
period detecting
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French (fr)
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袁佐
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BOE Technology Group Co Ltd
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BOE Technology Group Co Ltd
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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow
    • A61B5/024—Measuring pulse rate or heart rate
    • A61B5/02416—Measuring pulse rate or heart rate using photoplethysmograph signals, e.g. generated by infrared radiation
    • A61B5/02427—Details of sensor
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow
    • A61B5/024—Measuring pulse rate or heart rate
    • A61B5/02416—Measuring pulse rate or heart rate using photoplethysmograph signals, e.g. generated by infrared radiation
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235—Details of waveform analysis
    • A61B5/7239—Details of waveform analysis using differentiation including higher order derivatives
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow
    • A61B5/021—Measuring pressure in heart or blood vessels
    • A61B5/02108—Measuring pressure in heart or blood vessels from analysis of pulse wave characteristics
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording for evaluating the cardiovascular system, e.g. pulse, heart rate, blood pressure or blood flow
    • A61B5/024—Measuring pulse rate or heart rate
    • A61B5/02438—Measuring pulse rate or heart rate with portable devices, e.g. worn by the patient
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration or pH-value ; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid or cerebral tissue
    • A61B5/1455—Measuring characteristics of blood in vivo, e.g. gas concentration or pH-value ; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid or cerebral tissue using optical sensors, e.g. spectral photometrical oximeters
    • A61B5/14551—Measuring characteristics of blood in vivo, e.g. gas concentration or pH-value ; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid or cerebral tissue using optical sensors, e.g. spectral photometrical oximeters for measuring blood gases
    • A61B5/14552—Details of sensors specially adapted therefor

Definitions

  • the present invention relates to the field of vital sign detection technology, and in particular to a pulse period detecting device and method and a wearable electronic device.
  • wearable health monitoring devices have received increasing attention.
  • wearable pulse (heart rate) monitoring devices blood oxygen sensor based devices are one of the common types.
  • the principle of pulse measurement is based on the fact that the absorption of light by oxyhemoglobin and reduced hemoglobin in the blood varies with the periodic variation of the pulse wave, and pulse detection can be achieved by detecting changes in the amount of light absorbed by the blood.
  • the pulse wave signal is modulated in the measured optical signal.
  • the pulse wave period or heart rate can be calculated by analyzing the photoplethysmographic pulse signal (PPG) detected by the blood oxygen sensor (the pulse rate can be regarded as the heart rate).
  • PPG photoplethysmographic pulse signal
  • the blood oxygen sensor may include a transmissive sensor and a reflective sensor depending on the manner in which it is collected. Since the reflective sensor can be applied to measurement of various parts such as an arm or a wrist, a forehead, an earlobe, and the like, and does not cause an uncomfortable feeling of the subject (for example, compression by a finger-type device based on a transmissive sensor), It has a good application prospect in wearable devices. However, the PPG signal detected by the reflective sensor is usually weaker than the transmissive sensor, so that its measurement accuracy is affected.
  • the differential threshold method is one of the commonly used pulse wave signal analysis methods, which can easily determine the peak-to-peak value of the pulse wave signal.
  • the typical differential threshold method is based on the following ideas:
  • S 1 be the (preprocessed) pulse wave signal sequence
  • S 2 is calculated as follows
  • S 2 is a special differentiation of the pulse wave signal S 1
  • k is a step size, which is generally an empirical value. For example, when the sampling frequency is 100 Hz, the value of k may be 5 to 10.
  • the threshold S 2max is the maximum value in S 2 (i-1), S 2 (i-2)...S 2 (in). Pulse period may be determined in accordance with the waveform S 3.
  • the above method requires recording a segment of the pulse wave signal S 1 and deriving S 3 after obtaining the differential value sequence S 2 of the pulse wave signal S 1 and further calculating the pulse period based on the waveform of S 3 . Therefore, the traditional differential threshold method is computationally intensive and difficult to meet the requirements of real-time applications.
  • the detection site of the pulse wave is usually located in the peripheral blood circulation, the blood vessel has a strong smoothing effect on the pulse wave, especially when the pulsation of the subject is weak, so the amplitude of the pulse wave and the steepness of the rising edge are obvious. The reduction makes the anti-interference ability and measurement accuracy of the traditional differential threshold method poor, resulting in frequent false detection or missed detection.
  • a pulse period detecting apparatus comprising: a sensor for sensing a pulse wave signal of a subject; and a processor for sensing the sensor
  • the digitally converted digital pulse wave signal is processed to detect a pulse period of the subject, wherein the processor is configured to perform an operation of calculating a differential value of the digital pulse wave signal over time And each time the differential value changes from positive to negative, determining that the pulse wave signal reaches a maximum value point, and recording a time value corresponding to the maximum value point; once the differential value is less than a dynamic threshold, Identifying the most recently recorded maximum point in the past time as the peak point of the pulse wave signal; and calculating a difference between time values corresponding to the two consecutive peak points for deriving the pulse period.
  • a pulse period detecting method for processing a digital pulse wave signal to detect a pulse period of a subject comprising: calculating the digital pulse wave signal over time a differential value; each time the differential value changes from positive to negative, determining that the pulse wave signal reaches a maximum value point, and recording a time value corresponding to the maximum value point; once the differential value is less than dynamic
  • the threshold value identifies the most recently recorded maximum point in the past time as the peak point of the pulse wave signal; and calculates the difference between the time values corresponding to the two consecutive peak points for deriving the pulse period.
  • a wearable electronic device comprising the pulse period detecting device provided by the first aspect of the invention.
  • FIG. 1 schematically illustrates a block diagram of a pulse period detecting apparatus according to an embodiment of the present invention
  • FIG. 2(a) schematically illustrates an optical path of a pulse period detecting device using a reflective oximetry sensor at the time of detection, according to an embodiment of the present invention
  • FIG. 2(b) is a schematic plan view showing the structure of a reflective oximetry sensor in a pulse period detecting apparatus according to an embodiment of the present invention
  • FIG. 2(c) is a schematic plan view showing another structure of a reflective blood oxygen sensor in a pulse period detecting device according to an embodiment of the present invention
  • FIG. 3 illustrates a flow chart of a pulse period detection method in accordance with an embodiment of the present invention
  • Figure 5 illustrates the operations in the steps of calculating the pulse period in the method illustrated in Figure 3;
  • Figure 6 illustrates the operation in the step of calculating the heart rate in the method shown in Figure 3.
  • FIG. 1 schematically illustrates a block diagram of a pulse period detection apparatus 100 in accordance with an embodiment of the present invention.
  • the pulse period detection device 100 can include a sensor, a processor, a power source, and a communication interface and/or display. As shown, the sensor, processor, and communication interface and/or display are electrically coupled in sequence, and the power source is electrically coupled to the various components.
  • the sensor is used to sense the pulse wave signal of the subject.
  • the sensor can be a transmissive oximetry sensor or a reflective oximetry sensor.
  • the processor can be configured to process the analog-to-digital converted digital pulse wave signal sensed by the blood oxygen sensor to detect a pulse period of the subject.
  • the processor can also be used to calculate the heart rate based on the subject's pulse period.
  • an ARM core based processor can be used.
  • the display can be used to display at least one of a digital pulse wave signal, a pulse period, or a heart rate.
  • the communication interface can be used to transmit at least one of a digital pulse wave signal, a pulse period, or a heart rate to other receiving devices, such as to a smart terminal for display and storage.
  • the communication interface can be a wireless interface such as infrared, Bluetooth, Wi-Fi, etc., or a wired interface such as a serial interface, Universal Serial Bus (USB), 12C, and the like.
  • the power source is used to power the various components of the inspection device 100. For example, a lithium battery can be used as the power source.
  • FIG. 2(a) schematically illustrates an optical path of a pulse period detecting device employing a reflective oximetry sensor 200 in operation, in accordance with an embodiment of the present invention.
  • a light source LED 210
  • a photosensitive receiving device photodiode 230
  • the shield 220 is used to block light emitted from the LED 210 such that it does not directly illuminate the photodiode 230.
  • the incident light generated by the LED light source 210 is scattered multiple times by the subcutaneous tissue of the subject, and a part of the light is returned to the skin surface.
  • the photodiode 230 receives the optical signal reflected by the tissue of the subject and converts it into an electrical signal.
  • the pulse period detecting apparatus 100 may include an insulating cushion (not shown) disposed around the reflective oximetry sensor 200 to isolate ambient light, thereby reducing external illumination conditions. The interference caused by the reflective blood oxygen sensor 200. This is advantageous for further improving the detection accuracy.
  • the insulating cushion may have a chevron shape or may have a ring shape (not shown).
  • the insulating cushion can also improve the comfort of the user when wearing the wearable device, for example, the insulating cushion can be in contact with the human skin while surrounding the reflective blood oxygen sensor 200, such that While improving the detection accuracy, the wearer's comfort is also improved.
  • FIG. 2(b) schematically illustrates a plan view of the structure of the reflective oximetry sensor 200 in the pulse period detecting apparatus according to an embodiment of the present invention.
  • the photodiode 230 may include a plurality of photodiode cells 230_1, 230_2, 230_3, 230_4 integrated together (four photodiode cells are shown by way of example in the figure).
  • the integrated photodiode cells 230_1, 230_2, 230_3, and 230_4 are illustrated as being arranged side by side on the substrate 240 in such a manner that the distance to the LEDs 210 is increasing.
  • FIG. 2(c) schematically illustrates a top view of another configuration of the reflective oximetry sensor 200 in the pulse period detecting apparatus according to an embodiment of the present invention, wherein the integrated photodiode units 230_1, 230_2, 230_3 and 230_4 are arranged side by side on the substrate 240 in such a manner that the distances to the LEDs 210 are equal.
  • Each signal channel can provide a separate pulse wave signal to the processor. Subsequent operations performed by the processor (discussed later), data of a plurality of channels (for example, an average of data of a plurality of channels) can be utilized to improve the detection accuracy of the pulse period.
  • an LED device that emits green light (for example, a wavelength of 500 to 560 nm) is preferably used as the LED 210.
  • Green light can provide good penetration and thus provide a pulse wave signal with good signal strength and signal to noise ratio.
  • FIG. 3 illustrates a flow chart of a pulse period detection method in accordance with an embodiment of the present invention.
  • the blood oxygen sensor senses the pulse wave signal of the subject.
  • the blood oxygen sensor can be a transmissive sensor or a reflective sensor.
  • a reflective sensor having an integrated plurality of photodiode cells 230_x as previously described may be employed as the blood oxygen sensor.
  • the processor preprocesses the pulse wave signal sensed by the blood oxygen sensor.
  • the pre-processing may include at least one of moving average filtering and band pass filtering.
  • the moving average filtering is, for example, a 10-point moving average filter. By using moving average filtering, the abrupt component of the pulse wave signal can be filtered out.
  • Bandpass filtering is accomplished, for example, by a bandpass filter with a passband of 0.1 Hz to 10 Hz to reduce noise interference.
  • the pre-processing may also include first taking an average of the multi-channel data. By taking the average of the multi-channel data, the sampling accuracy of the pulse wave signal can be improved, thereby improving the accuracy of the detected pulse cycle.
  • analog signal needs to be converted to a digital signal during the sampling process.
  • the analog to digital conversion can be performed, for example, by an A/D converter built in the blood oxygen sensor.
  • the analog to digital conversion can be performed by an A/D converter built into the processor chip or an A/D converter separate from the processor chip.
  • the processor calculates the differential value of the analog-to-digital converted digital pulse wave signal in real time.
  • S 1 be the (preprocessed) pulse wave signal sequence
  • S 2 is calculated as follows
  • the processor calculates a pulse period based on the characteristics of the differential value sequence diff of the pulse wave signal (discussed later).
  • the processor further calculates according to the calculated pulse period. Heart rate.
  • step S330 is described in detail below with reference to FIGS. 4 and 5, wherein FIG. 4 illustrates waveforms of an exemplary pulse wave signal (PPG) and a corresponding differential value sequence (diff), and FIG. 5 illustrates FIG. The operation in step S330 of calculating the pulse period in the illustrated method.
  • PPG pulse wave signal
  • Diff differential value sequence
  • the pulse period is calculated based on the improved differential threshold method, wherein the pulse period is directly calculated using the differential value without further processing of the differential value of the pulse wave signal, for example, the differential value of the differential value sequence (second order) Or) to move down the differential value and so on.
  • a dynamic differentiation threshold is set.
  • dynamic is meant that the threshold changes over time (discussed later).
  • the time value when the pulse wave signal reaches the maximum value point is recorded. Since the maximum point of the pulse wave signal corresponds to a positive to negative transition (zero crossing) of the differential value, it can be determined whether the pulse wave signal reaches the maximum point by detecting the transition of the differential value. If a positive to negative transition of the differential value is detected, the corresponding time value is recorded. In the three periods of T1, T2, and T3 of the exemplary pulse wave signal shown in FIG. 4, six maximum points can be detected, including four true peak points p1, p2, p3, and p4, and two Local maximum points p1' and p2'. During the detection process, the dynamic thresholds mentioned above are used to identify which maximum point is the true peak point.
  • step S533 it is determined whether the current differential value satisfies the dynamic threshold condition.
  • the relationship between the differential value and the dynamic threshold actually reflects information about the steep falling edge of the pulse wave signal.
  • the peak points p1, p2, p3 and p4 of the pulse wave signal PPG (which corresponds to a positive to negative transition of the differential value) and the differential value
  • the minimum value of the sequence diff is related in time. That is, for each of the peak points p1, p2, p3, and p4, the transition from positive to negative of the differential value is followed by a minimum of the differential value, and for the local maximum points p1' and p2' This is not the case. Therefore, such temporal correlation can be utilized to identify true peak points.
  • the most recently recorded maximum point in the past time is identified as the peak point of the pulse wave signal.
  • the most recently recorded maximum point in the past time is identified (ie, , p1) is the peak point.
  • a peak can be determined within a few tens of milliseconds (from the transition of the differential value from positive to negative to less than the dynamic threshold, as shown in Figure 4). point.
  • the dynamic threshold may be 1/2 of the minimum differential value over a predetermined time interval in the past. For example, the predetermined time interval is 4 seconds.
  • the dynamic threshold needs to be updated in each determination, which involves finding (e.g., using a lookup algorithm known in the art) the minimum differential value over the past 4 seconds from the current time. Such lookup and update operations can incur a heavy computational burden, especially if the differential values are calculated point by point.
  • the dynamic threshold may be 1/2 of the minimum differential value in the last threshold update period.
  • the scheme of the threshold update period is such that the threshold is updated every fixed period of time from the time of starting the detection. For example, a variable representing the minimum differential value may be maintained for the threshold update period, and each differential value is calculated each time during each threshold update period, and then compared to the variable. If the calculated differential value is less than the value of the variable, the variable is updated with the calculated differential value.
  • the threshold updated in the last threshold update period is used as the threshold to be used in the current threshold update period.
  • the threshold update period is set to 4 seconds, so the dynamic threshold remains constant for the 4 second period shown in the figure. In this way, frequent updates of the threshold can be avoided, thereby reducing the computational burden.
  • Both of the dynamic thresholds discussed above are associated with a particular duration, and they may not be compatible with dramatic changes in the pulse period (eg, when the subject transitions from a calm state to a motion state).
  • the dynamic threshold may be 1/2 of the minimum differential value within a predetermined number of pulse periods in the past.
  • Such dynamic thresholds are associated with the last few pulse periods of the past time, rather than a specific duration, so they can follow dramatic changes in the pulse period.
  • the predetermined time interval or threshold update period may be set to be less than or equal to 2 seconds and greater than or equal to 1 second, or the predetermined number may be, for example, 1, 2 or 3.
  • the predetermined time interval or threshold update period may be set to be less than or equal to 2 seconds and greater than or equal to 1 second within a predetermined period of time from the detection start time. And is set to 4 seconds after the predetermined period of time.
  • the predetermined period of time may be, for example, 2 seconds, 3 seconds, or even more.
  • a time difference between two adjacent peak points is calculated for deriving the pulse period.
  • the corresponding time difference between two consecutive peak points can be calculated after identifying a plurality of peak points. This is advantageous in the case where it is necessary to calculate the average of a plurality of pulse periods to improve the detection accuracy, however, such scheme suffers loss in real time due to having to wait for recording a plurality of peak points.
  • the difference in time values corresponding to the two peak points can be calculated immediately each time two peak points are continuously identified. As described above, since a peak point can be determined within several tens of milliseconds, the pulse period (heart rate) can be calculated within a few tens of milliseconds after the end of one pulse period. This greatly enhances the real-time nature of pulse period detection.
  • Figure 6 illustrates the operation in the step of calculating the heart rate in the method shown in Figure 3.
  • the time difference between the most recently measured two pulse periods is compared.
  • Medical research has shown that there may be differences between adjacent two pulse cycles under normal conditions, which may reach tens of milliseconds (for humans). If the difference exceeds a predetermined threshold (e.g., 100 milliseconds), it can be inferred that the measured pulse period is disturbed and thus invalid.
  • an average of a plurality of (eg, five) calculated heart rates may be taken as the final heart rate measurement.
  • steps S641 through S644 are not required.
  • the heart rate can be directly calculated from the pulse period calculated at step S330, which is acceptable in some low cost applications.
  • a pulse period detecting apparatus and method improves pulse period (heart rate) in both signal acquisition and signal processing by employing an (optional) integrated reflective oximetry sensor and an improved differential threshold method Real-time and accuracy of detection (error is ⁇ 2bpm), and can reduce the amount of calculation, thus the wearable pulse cycle (heart rate)
  • the inspection equipment provides the desired options.
  • the present invention also provides a wearable electronic device comprising a pulse period detecting device as described above.
  • the wearable electronic device can take the form of, for example, a wristband, a wristband, a collar, a headset, etc., so that it can be worn on the user.
  • the reflective oximetry sensor as described above can acquire a pulse wave signal, and the pulse period detecting device calculates a pulse or heart rate based on the pulse wave signal and provides corresponding detection information for the wearable electronic device.

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Abstract

一种脉搏周期检测设备（100）和方法，以及可穿戴电子设备，包括：传感器（200），用于感测受检者的脉搏波信号；以及处理器，用于对所述传感器（200）感测的、经模数转换后的数字脉搏波信号进行处理以检测所述受检者的脉搏周期，其中，处理器被配置成执行以下操作：随着时间的推移，计算数字脉搏波信号的微分值；每当微分值出现从正到负的转变，则确定脉搏波信号到达极大值点，并记录该极大值点对应的时间值；一旦微分值小于动态阈值，则识别过去时间内最近记录的极大值点为脉搏波信号的峰值点；以及计算两个连续峰值点对应的时间值之差以用于导出脉搏周期。提高了脉搏周期检测的实时性和精度。

Description

脉搏周期检测设备和方法和可穿戴电子设备 技术领域
本发明涉及生命体征检测技术领域，具体地涉及一种脉搏周期检测设备和方法和可穿戴电子设备。
背景技术
近年来，可穿戴式健康监测设备日益受到重视。在可穿戴式脉搏(心率)监测设备中，基于血氧传感器的设备是常见的类型之一。脉搏测量的原理基于以下事实：血液中的氧合血红蛋白和还原血红蛋白对光的吸收随着脉搏波的周期性变化而变化，通过检测血液对光吸收量的变化可以实现脉搏检测。换言之，脉搏波信号被调制在所测量的光信号中。可以通过对血氧传感器检测到的光电容积脉搏波信号(PPG)进行分析来计算脉搏波周期或心率(脉搏频率可以被认为是心率)。
取决于其采集方式，血氧传感器可以包括透射式传感器和反射式传感器。由于反射式传感器可以适用于手臂或手腕、额头、耳垂等各种部位的测量，并且不会引起受检者的不适感(例如，基于透射式传感器的指夹式设备所引起的压迫)，所以其在可穿戴式设备中具有良好的应用前景。然而，反射式传感器检测到的PPG信号通常比透射式传感器更微弱，使得其测量精度受到影响。
另外，微分阈值法是常用的脉搏波信号分析方法之一，其可以容易地确定脉搏波信号的峰-峰值。典型的微分阈值法基于以下思想：
设S1是(经预处理的)脉搏波信号序列，则S2计算如下
Figure PCTCN2015090278-appb-000001
其中，S2是对脉搏波信号S1的一种特殊微分，k为步长，一般为经验值，例如当采样频率100Hz时，k值可取5到10。
基于微分值序列S2，得到
Figure PCTCN2015090278-appb-000002
其中，阈值S2max为S2(i-1)，S2(i-2)…S2(i-n)中的最大值。脉搏周期可以根据S3的波形确定。
上述方法要求记录一段脉搏波信号S1，并且在得到脉搏波信号S1的微分值序列S2之后导出S3，并且进一步根据S3的波形来计算脉搏周期。因此，传统的微分阈值法计算量大且难以满足实时应用的要求。另外，由于脉搏波的检测部位通常位于外周血液循环，其中血管对脉搏波有较强的平滑作用，特别是当受检者的脉动较弱时，所以脉搏波的幅度和上升沿的陡峭程度明显降低，使得传统的微分阈值法的抗干扰能力和测量精度变得很差，导致经常出现误检或漏检。
因此，存在对于改进的脉搏周期检测设备和方法的需要。
发明内容
有利的是，获得一种至少解决上述问题中的一个的脉搏周期检测设备和方法。
在本发明的第一方面中，提供了一种脉搏周期检测设备，包括：传感器，用于感测受检者的脉搏波信号；以及处理器，用于对所述传感器感测的、经模数转换后的数字脉搏波信号进行处理以检测所述受检者的脉搏周期，其中，所述处理器被配置成执行以下操作：随着时间的推移，计算所述数字脉搏波信号的微分值；每当所述微分值出现从正到负的转变，则确定所述脉搏波信号到达极大值点，并记录该极大值点对应的时间值；一旦所述微分值小于动态阈值，则识别过去时间内最近记录的所述极大值点为所述脉搏波信号的峰值点；以及计算两个连续峰值点对应的时间值之差以用于导出所述脉搏周期。
根据本发明的第二方面，提供了一种脉搏周期检测方法，用于对数字脉搏波信号进行处理以检测受检者的脉搏周期，包括：随着时间的推移，计算所述数字脉搏波信号的微分值；每当所述微分值出现从正到负的转变，则确定所述脉搏波信号到达极大值点，并记录该极大值点对应的时间值；一旦所述微分值小于动态阈值，则识别过去时间内最近记录的所述极大值点为所述脉搏波信号的峰值点；以及计算两个连续峰值点对应的时间值之差以用于导出所述脉搏周期。
根据本发明的第三方面，提供了一种可穿戴电子设备，包括本发明第一方面提供的所述脉搏周期检测设备。
根据在下文中所描述的实施例，本发明的这些和其它方面将是显而易见的，并且将参考在下文中所描述的实施例而被阐明。
附图说明
图1示意性地图示了根据本发明的实施例的脉搏周期检测设备的框图；
图2(a)示意性地图示了根据本发明的实施例的采用反射式血氧传感器的脉搏周期检测设备在检测时的光路；
图2(b)示意性地图示了根据本发明的实施例的脉搏周期检测设备中的反射式血氧传感器的结构的俯视图；
图2(c)示意性地图示了根据本发明的实施例的脉搏周期检测设备中的反射式血氧传感器的另一种结构的俯视图；
图3图示了根据本发明的实施例的脉搏周期检测方法的流程图；
图4图示了示例性的脉搏波信号和相应的微分值序列的波形；
图5图示了如图3所示的方法中的计算脉搏周期的步骤中的操作；以及
图6图示了如图3所示的方法中的计算心率的步骤中的操作。
具体实施方式
以下结合附图对本发明的各实施例进行详细描述。
图1示意性地图示了根据本发明的实施例的脉搏周期检测设备100的框图。脉搏周期检测设备100可以包括传感器、处理器、电源以及通信接口和/或显示器。如图所示，传感器、处理器以及通信接口和/或显示器依次电连接，并且电源与各个部件电连接。传感器用于感测受检者的脉搏波信号。特别地，传感器可以是透射式血氧传感器或者反射式血氧传感器。处理器可以用于对血氧传感器感测的、经模数转换后的数字脉搏波信号进行处理以检测受检者的脉搏周期。处理器还可以用于基于受检者的脉搏周期来计算心率。在可穿戴式应用中，可以使用例如基于ARM核的处理器。显示器可以用于显示数字脉搏波信号、脉搏周期或心率中的至少一个。通信接口可以用于将数字脉搏波信号、脉搏周期或心率中的至少一个发送给其他接收设备，例如发送给智能终端进行显示和存储。通信接口可以是无线接口，诸如红外、蓝牙、Wi-Fi等，或者有线接口，诸如串行接口、通用串行总线(USB)、12C等。电源用于为检测设备100的各个部件供电。可以使用例如锂电池作为电源。
图2(a)示意性地图示了根据本发明的实施例的采用反射式血氧传感器200的脉搏周期检测设备在操作时的光路。如图所示，在反射 式传感器200的情况下，光源(LED 210)和光敏接收器件(光电二极管230)被布置在基板240的同一侧，其中LED 210和光电二极管230之间设置有遮挡物220。遮挡物220用于遮挡从LED 210发射的光，使得其不会直接照射到光电二极管230上。LED光源210所产生的入射光经过受检者皮下组织多次散射，一部分光重新返回皮肤表面。光电二极管230接收被受检者组织反射回来的光信号，并将其转换为电信号。
在一个实施例中，脉搏周期检测设备100可以包括隔绝软垫(图中未示出)，其环绕反射式血氧传感器200设置，可以起到隔绝环境光线的作用，从而减小外界光照条件对反射式血氧传感器200造成的干扰。这有利于进一步提高检测精度。取决于脉搏周期检测设备100的形状设计，隔绝软垫可以为回字形形状，或者可以为环形形状(未示出)。另外，在可穿戴应用中，隔绝软垫还可以改善使用者在佩戴可穿戴设备时的舒适性，例如，隔绝软垫可以与人体皮肤接触，同时将反射式血氧传感器200环绕在内，这样在提高检测精度的同时，还提高了佩戴者的舒适感。
图2(b)示意性地图示了根据本发明的实施例的脉搏周期检测设备中的反射式血氧传感器200的结构的俯视图。在该反射式血氧传感器200中，光电二极管230可以包括集成在一起的多个光电二极管单元230_1、230_2、230_3、230_4(在图中以示例的方式示出4个光电二极管单元)。在该图中，集成的光电二极管单元230_1、230_2、230_3和230_4被图示为以到LED 210的距离递增的方式并排布置在基板240上。
图2(c)示意性地图示了根据本发明的实施例的脉搏周期检测设备中的反射式血氧传感器200的另一种结构的俯视图，其中，集成的光电二极管单元230_1、230_2、230_3和230_4以到LED 210的距离相等的方式并排布置在基板240上。
无论哪种情况，由于光电二极管单元230_1、230_2、230_3和230_4集成在一起，相互之间的距离可以忽略不计，所以它们可以接收来自从基本上同一处受检者皮下组织反射的光信号。这样，各个光电二极管单元230_x(x＝1，2，3，4…)构成单独的信号通道。每一路信号通道可以为处理器提供一路单独的脉搏波信号。在处理器执行的后续操作 (后面讨论)中，可以利用多个通道的数据(例如，取多个通道的数据的平均值)来提高脉搏周期的检测精度。另外，在本发明的实施例的应用中，优选地使用发射绿光(例如，500～560nm的波长)的LED器件作为LED 210。绿光可以提供良好的穿透性，并且因此提供具有良好信号强度和信噪比的脉搏波信号。
图3图示了根据本发明的实施例的脉搏周期检测方法的流程图。
在步骤S300处，血氧传感器感测受检者的脉搏波信号。如前所述，血氧传感器可以是透射式传感器或者反射式传感器。在一个实施例中，可以采用如前面描述的具有集成的多个光电二极管单元230_x的反射式传感器作为血氧传感器。
在步骤S310处，处理器对血氧传感器所感测的脉搏波信号进行预处理。预处理可以包括移动平均滤波和带通滤波中的至少一个。移动平均滤波例如为10点移动平均滤波。通过采用移动平均滤波，可以滤除脉搏波信号中的突变分量。带通滤波例如由通带为0.1Hz～10Hz的带通滤波器完成，从而降低噪声干扰。在如前面所述的集成的反射式传感器的情况下，预处理还可以包括首先取多通道数据的平均值。通过取多通道数据的平均值，可以提高脉搏波信号的采样精度，从而提高所检测到的脉搏周期的精度。还应当理解，在采样过程中需要将模拟信号转换为数字信号。模数转换例如可以由血氧传感器内置的A/D转换器完成。替换地，模数转换可以由处理器芯片内置的A/D转换器或与处理器芯片分立的A/D转换器完成。
在步骤S320处，处理器实时地计算经模数转换后的数字脉搏波信号的微分值。设S1是(经预处理的)脉搏波信号序列，则微分值序列S2计算如下
Figure PCTCN2015090278-appb-000003
其中，k为步长。
在一个实施例中，可以逐点地计算数字脉搏波信号的微分值，也即步长k＝1。这样，以计算量增大为代价，可以提高检测的精度。
在步骤S330处，处理器基于脉搏波信号的微分值序列diff的特性来计算脉搏周期(后面讨论)。
可选地，在步骤S340处，处理器还根据所计算的脉搏周期来计算 心率。
下面结合图4和5详细描述步骤S330的流程，其中图4图示了示例性的脉搏波信号(PPG)和相应的微分值序列(diff)的波形，并且图5图示了如图3所示的方法中的计算脉搏周期的步骤S330中的操作。
在本实施例中，基于改进的微分阈值法计算脉搏周期，其中利用微分值直接计算脉搏周期而不需要对脉搏波信号的微分值的进一步处理，例如，求微分值序列的微分值(二阶导)或者对于微分值进行下移等等。
如图5所示，在步骤S531处，设定一个动态微分阈值。所谓“动态”意指该阈值随着时间推移而变化(后面讨论)。
在步骤S532处，记录脉搏波信号到达极大值点时的时间值。由于脉搏波信号的极大值点对应于微分值的从正到负的转变(过零点)，所以可以通过检测微分值的该转变来确定脉搏波信号是否到达极大值点。如果检测到微分值的从正到负的转变，则记录对应的时间值。在图4中所示的示例脉搏波信号的T1、T2和T3的三个周期中，可以检测到6个极大值点，包括4个真正的峰值点p1、p2、p3和p4以及2个局部极大值点p1′和p2′。在检测过程中，利用前面提到的动态阈值来识别哪些极大值点是真正的峰值点。
在步骤S533处，判断当前的微分值是否满足动态阈值条件。微分值与动态阈值之间的关系实际上反映了关于脉搏波信号的陡峭下降沿的信息。从图4中可以看到，在脉搏波信号PPG的陡峭下降沿期间，脉搏波信号PPG的峰值点p1、p2、p3和p4(其对应于微分值的从正到负的转变)与微分值序列diff的最小值在时间上具有关联性。也即，对于峰值点p1、p2、p3和p4中的每一个，在微分值的从正到负的转变之后接着是微分值的一个最小值，而对于局部极大值点p1′和p2′并不是这样。因此，可以利用这样的时间关联性来识别真正的峰值点。
在步骤S534处，具体地，一旦当前微分值小于动态阈值，则识别过去时间内最近记录的极大值点为脉搏波信号的峰值点。例如，在图4中所示的示例波形中，在确定了脉搏波信号的极大值点p1之后，一旦检测到微分值小于动态阈值，则识别过去时间内最近记录的极大值点(即，p1)为峰值点。这样，在几十毫秒(从微分值从正到负的转变到小于动态阈值的时间段，如图4中所示)内就可以确定出一个峰值 点。
在一个实施例中，动态阈值可以为过去预定时间间隔内的最小微分值的1/2。例如，该预定时间间隔为4秒。每次计算得到一个微分值，则判断该微分值是否小于动态阈值，并且如果是，则触发峰值点的识别。在这种情况下，每次判断中都需要更新动态阈值，其中牵涉到查找(例如，使用本领域中已知的查找算法)从当前时刻起过去4秒内的最小微分值。这样查找和更新操作可能招致沉重的计算负担，尤其是在逐点计算微分值的情况下。
在另一个实施例中，动态阈值可以为上一个阈值更新周期内的最小微分值的1/2。阈值更新周期的方案是这样的：从开始检测的时刻起每隔一段固定的时间更新一次阈值。例如，可以针对阈值更新周期维持一个代表最小微分值的变量，并且在每个阈值更新周期内，每次计算得到一个微分值，则将其与该变量进行比较。如果所计算的微分值小于该变量的值，则利用所计算的微分值来更新该变量。在进入新的阈值更新周期时，使用上一个阈值更新周期内更新的阈值作为当前阈值更新周期内要使用的阈值。在图4的示例中，阈值更新周期被设定为4秒，因此在该图中所示的4秒的时间段内动态阈值保持恒定。这样，可以避免阈值的频繁更新，从而减轻计算负担。
前面讨论的两种动态阈值都是与特定的持续时间相关联，它们有可能不能与脉搏周期的剧烈变化(例如，在受检者从平静状态转变到运动状态的情况)相适应。
在又另一个实施例中，动态阈值可以为过去预定数目的脉搏周期内的最小微分值的1/2。这样的动态阈值与过去时间内的最近几个脉搏周期相关联，而不是特定的持续时间，因而其能够跟随脉搏周期的剧烈变化。
还应当理解，由于动态阈值的初始值通常被预设为零，所以在最初始的检测中会存在一段准备时间，在这期间由于正确的动态阈值尚未建立的原因脉搏周期的检测结果是错误的。有利地，对于前面提到的各动态阈值，所述预定时间间隔或阈值更新周期可以设定为小于等于2秒且大于等于1秒，或者所述预定数目可以例如为1、2或3。在一个供替换的实施例中，所述预定时间间隔或阈值更新周期可以在从检测开始时刻起预定时间段内被设置为小于等于2秒且大于等于1秒， 并且在所述预定时间段之后被设置为4秒。在该预定时间段期间，正确的动态阈值被建立。该预定时间段可以为例如2秒、3秒或甚至更多。由此，兼顾了检测设备开机后的快速投入使用和检测过程的稳定性。
在步骤S535处，计算相邻的两个峰值点之间的时间差以用于导出脉搏周期。在一个实施例中，可以在识别出多个峰值点后，再计算两个连续峰值点之间对应的时间差。这对于需要计算多个脉搏周期的平均值以提高检测精度的场合是有利的，然而，由于必须等待记录多个峰值点，这样的方案在实时性方面遭受损失。在一个供替换的实施例中，可以在每当连续识别出两个峰值点时，立即计算该两个峰值点对应的时间值之差。如前面描述的，由于在几十毫秒内就可以确定出一个峰值点，所以在一个脉搏周期结束后，最快在几十毫秒内就能够计算出脉搏周期(心率)。这大大增强了脉搏周期检测的实时性。
图6图示了如图3所示的方法中的计算心率的步骤中的操作。
在步骤S641处，比较最近测得的两个脉搏周期(即，当前测得的脉搏周期与上一次测得的脉搏周期)之间的时间差。在步骤S642处，判断该时间差是否小于预定阈值，并且如果是，则确定当前测得的脉搏周期为有效的数据；否则，确定当前测得的脉搏周期为无效的数据。医学研究表明，正常情况下相邻两次脉搏周期之间可能存在差异，其可能达到几十毫秒(对于人类而言)。如果这个差异超过一个预定阈值(例如100毫秒)，则可以推断所测得的脉搏周期受到了干扰并且因而为无效的数据。如果这个差异并不超过所述预定阈值，则在步骤S643处，根据有效的脉搏周期来计算瞬时心率。例如，如果测得的有效脉搏周期为0.8秒，则心率为60/0.8＝75次/分。可选地，在步骤S644处，在并非时间关键的应用中，可以取多个(例如5个)计算得到的心率的平均值作为最终的心率测量值。
还应当理解，步骤S641到S644并不是必需的。例如，可以根据在步骤S330处计算得到的脉搏周期来直接计算心率，这在一些低成本应用中是可以接受的。
根据本发明的实施例的脉搏周期检测设备和方法通过采用(可选的)集成的反射式血氧传感器和改进的微分阈值法，在信号采集和信号处理两个方面提高了脉搏周期(心率)检测的实时性和精度(误差在±2bpm)，并且可以降低计算量，从而为可穿戴的脉搏周期(心率) 检测设备提供了合期望的选项。
虽然前面的讨论包含若干特定的实现细节，但是这些不应解释为对任何发明或者可能要求保护的范围的限制，而应解释为对可能仅限于特定发明的特定实施例的特征的描述。在本说明书中不同的实施例中描述的特定特征也可以在单个实施例中以组合形式实现。与此相反，在单个实施例中描述的不同特征也可以在多个实施例中分别地或者以任何适当的子组合形式实现。此外，尽管前面可能将特征描述为以特定组合起作用，甚至最初也被如此要求保护，但是来自所要求保护的组合中的一个或多个特征在某些情况下也可以从该组合中排除(例如，就脉搏周期检测的功能而言，显示器和/或通信接口并不是检测设备100必需的)，并且该要求保护的组合可以被导向子组合或子组合的变型。
类似地，虽然各个操作在附图中被描绘为按照特定的顺序，但是这不应理解为要求这些操作必须以所示的特定顺序或者按顺行次序执行，也不应理解为要求必须执行所有示出的操作以获得期望的结果(例如，就基于脉搏波信号计算脉搏周期而言，数据采集步骤和数据预处理步骤等并不是必需的)。
本发明还提供了一种可穿戴电子设备，其包括如前面所描述的脉搏周期检测设备。该可穿戴电子设备可以采取例如手环、腕带、脖套、耳机等形式，从而可以佩戴在使用者的身上。这样，在佩戴期间，如前面描述的反射式血氧传感器可以采集脉搏波信号，而脉搏周期检测设备根据脉搏波信号计算脉搏或心率，并为该可穿戴电子设备提供相应的检测信息。
鉴于前面的描述并结合阅读附图，对前述本发明的示例性实施例的各种修改和改动对于相关领域的技术人员可以变得显而易见。任何和所有修改仍将落入本发明的非限制性和示例性实施例的范围内。此外，属于本发明的这些实施例所属领域的技术人员，在得益于前面的描述和相关附图所给出的教导后，将会想到在此描述的本发明的其他实施例。
因此，应当理解，本发明的实施例并不限于所公开的特定实施例，并且修改和其他的实施例也意图被包含在所附权利要求书的范围内。尽管此处使用了特定术语，但是它们仅在通用和描述性意义上使用，而非为了限制的目的。

Claims (37)

  1. 一种脉搏周期检测设备，包括：
    传感器，用于感测受检者的脉搏波信号；以及
    处理器，用于对所述传感器感测的、经模数转换后的数字脉搏波信号进行处理以检测所述受检者的脉搏周期，
    其中，所述处理器被配置成执行以下操作：
    随着时间的推移，计算所述数字脉搏波信号的微分值；
    每当所述微分值出现从正到负的转变，则确定所述脉搏波信号到达极大值点，并记录该极大值点对应的时间值；
    一旦所述微分值小于动态阈值，则识别过去时间内最近记录的所述极大值点为所述脉搏波信号的峰值点；以及
    计算两个连续峰值点对应的时间值之差以用于导出所述脉搏周期。
  2. 根据权利要求1所述的脉搏周期检测设备，其中，所述处理器被配置成每当连续识别出两个峰值点时计算该两个连续峰值点对应的时间值之差以用于导出所述脉搏周期。
  3. 根据权利要求1所述的脉搏周期检测设备，其中，所述传感器为反射式血氧传感器，该反射式血氧传感器包括：
    LED光源；以及
    集成的光电二极管，其包括集成在一起的多个光电二极管单元以用于提供多通道感测数据。
  4. 根据权利要求3所述的脉搏周期检测设备，其中，所述LED光源为绿光LED。
  5. 根据权利要求3所述的脉搏周期检测设备，其中，所述多个光电二极管单元以到所述LED光源的距离递增的方式并排布置，或者以到所述LED光源的距离相等的方式并排布置。
  6. 根据权利要求1所述的脉搏周期检测设备，其中，所述动态阈值为过去预定时间间隔内的最小微分值的1/2或上一个阈值更新周期内的最小微分值的1/2。
  7. 根据权利要求6所述的脉搏周期检测设备，其中，所述预定时间间隔或阈值更新周期为4秒。
  8. 根据权利要求6所述的脉搏周期检测设备，其中，所述预定时间间隔或阈值更新周期小于等于2秒且大于等于1秒。
  9. 根据权利要求6所述的脉搏周期检测设备，其中，所述预定时间间隔或阈值更新周期在从检测开始时刻起预定时间段内被设置为小于等于2秒且大于等于1秒，并且在所述预定时间段之后被设置为4秒。
  10. 根据权利要求1所述的脉搏周期检测设备，其中，所述动态阈值为过去预定数目的脉搏周期内的最小微分值的1/2。
  11. 根据权利要求1所述的脉搏周期检测设备，其中，所述动态阈值的初始值被预设为零。
  12. 根据权利要求1所述的脉搏周期检测设备，其中，所述处理器被配置成逐点地计算所述数字脉搏波信号的微分值。
  13. 根据权利要求1所述的脉搏周期检测设备，其中，所述处理器还被配置成在对所述数字脉搏波信号进行处理之前进行预处理。
  14. 根据权利要求13所述的脉搏周期检测设备，其中，所述预处理包括取多通道数据的平均值、移动平均滤波和带通滤波中的至少一个。
  15. 根据权利要求1所述的脉搏周期检测设备，其中，所述处理器还被配置成根据所述脉搏周期直接计算心率。
  16. 根据权利要求1所述的脉搏周期检测设备，其中，所述处理器还被配置成比较当前测得的脉搏周期与上一次测得的脉搏周期之间的时间差，如果该时间差小于预定阈值，则确定当前测得的脉搏周期为有效，否则，确定当前测得的脉搏周期为无效。
  17. 根据权利要求16所述的脉搏周期检测设备，其中，所述预定阈值为100毫秒。
  18. 根据权利要求16所述的脉搏周期检测设备，其中，所述处理器还被配置成根据有效的脉搏周期计算心率。
  19. 根据权利要求18所述的脉搏周期检测设备，其中，所述处理器还被配置成取多个计算得到的心率的平均值作为最终的心率测量值。
  20. 根据权利要求15、17或19所述的脉搏周期检测设备，还包括显示器和/或通信接口，其中，所述显示器用于显示数字脉搏波信号、 脉搏周期或心率中的至少一个，并且所述通信接口用于将数字脉搏波信号、脉搏周期或心率中的至少一个发送给其他接收设备。
  21. 一种脉搏周期检测方法，用于对数字脉搏波信号进行处理以检测受检者的脉搏周期，包括：
    随着时间的推移，计算所述数字脉搏波信号的微分值；
    每当所述微分值出现从正到负的转变，则确定所述脉搏波信号到达极大值点，并记录该极大值点对应的时间值；
    一旦所述微分值小于动态阈值，则识别过去时间内最近记录的所述极大值点为所述脉搏波信号的峰值点；以及
    计算两个连续峰值点对应的时间值之差以用于导出所述脉搏周期。
  22. 根据权利要求21所述的脉搏周期检测方法，其中，计算两个连续峰值点对应的时间值之差包括：每当连续识别出两个峰值点时计算该两个峰值点对应的时间值之差。
  23. 根据权利要求21所述的脉搏周期检测方法，其中，所述动态阈值为过去预定时间间隔内的最小微分值的1/2或上一个阈值更新周期内的最小微分值的1/2。
  24. 根据权利要求23所述的脉搏周期检测方法，其中，所述预定时间间隔或阈值更新周期为4秒。
  25. 根据权利要求23所述的脉搏周期检测方法，其中，所述预定时间间隔或阈值更新周期小于等于2秒且大于等于1秒。
  26. 根据权利要求21所述的脉搏周期检测方法，其中，所述动态阈值为过去预定数目的脉搏周期内的最小微分值的1/2。
  27. 根据权利要求23所述的脉搏周期检测方法，其中，所述预定时间间隔或阈值更新周期在从检测开始时刻起预定时间段内被设置为小于等于2秒且大于等于1秒，并且在所述预定时间段之后被设置为4秒。
  28. 根据权利要求21所述的脉搏周期检测方法，其中，所述动态阈值的初始值被预设为零。
  29. 根据权利要求21所述的脉搏周期检测方法，其中，逐点地计算所述数字脉搏波信号的微分值。
  30. 根据权利要求21所述的脉搏周期检测方法，还包括：在对所 述数字脉搏波信号进行处理之前，对所述数字脉搏波信号进行预处理。
  31. 根据权利要求30所述的脉搏周期检测方法，其中，所述预处理包括取多通道数据的平均值、移动平均滤波和带通滤波中的至少一个。
  32. 根据权利要求21所述的脉搏周期检测方法，还包括：根据所述脉搏周期直接计算心率。
  33. 根据权利要求21所述的脉搏周期检测方法，还包括：比较当前测得的脉搏周期与上一次测得的脉搏周期之间的时间差，如果该时间差小于预定阈值，则确定当前测得的脉搏周期为有效，否则，确定当前测得的脉搏周期为无效。
  34. 根据权利要求33所述的脉搏周期检测方法，其中，所述预定阈值为100毫秒。
  35. 根据权利要求33所述的脉搏周期检测方法，还包括：根据有效的脉搏周期计算心率。
  36. 根据权利要求35所述的脉搏周期检测方法，还包括：取多个计算得到的心率的平均值作为最终的心率测量值。
  37. 一种可穿戴电子设备，包括如权利要求1到20中任一项所述的脉搏周期检测设备。
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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109833034A (zh) * 2017-11-24 2019-06-04 深圳市岩尚科技有限公司 一种脉搏波信号中提取血压数据的方法及装置

Families Citing this family (23)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP6594135B2 (ja) * 2015-09-16 2019-10-23 オムロンヘルスケア株式会社 生体情報測定装置、生体情報測定方法、及び生体情報測定プログラム
CN106214143B (zh) * 2016-10-12 2019-02-19 成都心吉康科技有限公司 瞬时运动干扰识别方法及心率置信度计算方法
CN106598107B (zh) * 2016-12-29 2020-07-24 杭州暖芯迦电子科技有限公司 一种基于反馈系统的可自动调节光电传感器信号电路
CN107296598B (zh) * 2017-06-22 2020-12-25 无锡力芯微电子股份有限公司 基于光电传感器的心率测定方法及装置
CN107669248B (zh) * 2017-09-29 2024-02-02 长春市万易科技有限公司 老人动态脉搏连续检测系统及方法
US11690520B2 (en) * 2018-06-20 2023-07-04 Samsung Electronics Co., Ltd. Apparatus and method for measuring bio-information
CN109189207B (zh) * 2018-06-27 2022-01-11 深圳市元征科技股份有限公司 一种可穿戴设备穿戴状态的检测方法及装置
CN108903931A (zh) * 2018-07-26 2018-11-30 深圳还是威健康科技有限公司 一种静息心率预警方法及装置
KR102655741B1 (ko) 2018-08-01 2024-04-05 삼성전자주식회사 생체정보 추정 장치 및 방법
TWM574470U (zh) * 2018-11-19 2019-02-21 眾里科技股份有限公司 血氧感測裝置
CN109498022A (zh) * 2018-12-29 2019-03-22 西安理工大学 一种基于光电容积脉搏波的呼吸频率提取方法
WO2020206661A1 (zh) * 2019-04-11 2020-10-15 深圳市柔宇科技有限公司 目标对象的特征参数获取方法、终端及存储介质
CN110477895B (zh) * 2019-07-24 2022-11-11 苏州国科医工科技发展(集团)有限公司 基于血液容积波的多光源探测器连续心率测量方法
KR102567952B1 (ko) * 2019-09-11 2023-08-16 삼성전자주식회사 생체정보 추정 장치 및 방법
CN112806972B (zh) * 2019-11-18 2023-04-07 Oppo广东移动通信有限公司 Ppg测量电路和方法、可穿戴电子设备
CN110974164B (zh) * 2019-12-05 2022-06-07 国网福建省电力有限公司检修分公司 一种基于肌电波形和脉搏频率的低压触电告警方法
JP2021186455A (ja) * 2020-06-03 2021-12-13 パナソニック株式会社 脈拍検出装置及び脈拍検出方法
US11688103B2 (en) * 2021-05-06 2023-06-27 Jenco Electronics, Ltd. System and method for color analysis
CN113100727B (zh) * 2021-05-12 2023-09-19 深圳市通久电子有限公司 实时分析识别脉搏波峰的方法
US12440110B1 (en) * 2021-09-29 2025-10-14 Amazon Technologies, Inc. Systems for determining physiological values based on signal characteristics
CN114403823A (zh) * 2022-01-20 2022-04-29 杭州纳境科技有限公司 心率血氧检测方法及装置、可穿戴设备
CN114711733B (zh) * 2022-06-07 2023-07-28 北京大学深圳研究生院 一种脉搏信号提取方法、装置、电子设备及存储介质
CN117919677A (zh) * 2023-12-15 2024-04-26 上海交通大学 一种射箭训练与比赛模拟系统

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1537508A (zh) * 2003-04-16 2004-10-20 ŷķ������ҽ����ҵ��ʽ���� 脉搏波测定装置和活体波分析程序产品
CN101703396A (zh) * 2009-11-06 2010-05-12 中国科学院合肥物质科学研究院 基于桡动脉脉搏波的心血管机能参数检测分析方法及检测装置
CN102307520A (zh) * 2009-02-03 2012-01-04 欧姆龙健康医疗事业株式会社 脉搏波分析装置以及脉搏波分析方法
US20120197140A1 (en) * 2009-10-19 2012-08-02 Murata Manufacturing Co., Ltd. Pulse Wave Detection Device and Pulse Wave Detection Method

Family Cites Families (17)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4889132A (en) * 1986-09-26 1989-12-26 The University Of North Carolina At Chapel Hill Portable automated blood pressure monitoring apparatus and method
JPH0747021B2 (ja) * 1987-06-15 1995-05-24 オムロン株式会社 電子血圧計
US6575912B1 (en) * 2001-10-16 2003-06-10 Pacesetter, Inc. Assessing heart failure status using morphology of a signal representative of arterial pulse pressure
KR100455289B1 (ko) * 2002-03-16 2004-11-08 삼성전자주식회사 빛을 이용한 진단방법 및 장치
US20040015091A1 (en) * 2002-04-01 2004-01-22 Aspect Medical Systems System and method of assessment of arousal, pain and stress during anesthesia and sedation
US7438686B2 (en) * 2003-01-10 2008-10-21 Medtronic, Inc. Apparatus and method for monitoring for disordered breathing
US8641635B2 (en) * 2006-08-15 2014-02-04 University Of Florida Research Foundation, Inc. Methods and devices for central photoplethysmographic monitoring methods
US20090287110A1 (en) * 2008-05-14 2009-11-19 Searete Llc Circulatory monitoring systems and methods
US8478538B2 (en) * 2009-05-07 2013-07-02 Nellcor Puritan Bennett Ireland Selection of signal regions for parameter extraction
US8509869B2 (en) * 2009-05-15 2013-08-13 Covidien Lp Method and apparatus for detecting and analyzing variations in a physiologic parameter
CN102247129B (zh) * 2011-06-15 2013-06-12 西安电子科技大学 脉搏波非典型波峰波谷的识别方法
US10219709B2 (en) * 2012-03-28 2019-03-05 Wayne State University Sensor and method for continuous health monitoring
US9241643B2 (en) * 2012-05-31 2016-01-26 Covidien Lp Methods and systems for power optimization in a medical device
TWI563969B (zh) * 2012-10-24 2017-01-01 財團法人工業技術研究院 生理資訊之計算機分析方法及裝置
US9687159B2 (en) * 2013-02-27 2017-06-27 Covidien Lp Systems and methods for determining physiological information by identifying fiducial points in a physiological signal
GB2519075B (en) * 2013-10-08 2017-12-13 Telefield Ltd Apparatus and method for measuring pulse rate
CN103565427B (zh) * 2013-11-19 2016-09-28 深圳邦健生物医疗设备股份有限公司 准周期生理信号特征点的检测

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1537508A (zh) * 2003-04-16 2004-10-20 ŷķ������ҽ����ҵ��ʽ���� 脉搏波测定装置和活体波分析程序产品
CN102307520A (zh) * 2009-02-03 2012-01-04 欧姆龙健康医疗事业株式会社 脉搏波分析装置以及脉搏波分析方法
US20120197140A1 (en) * 2009-10-19 2012-08-02 Murata Manufacturing Co., Ltd. Pulse Wave Detection Device and Pulse Wave Detection Method
CN101703396A (zh) * 2009-11-06 2010-05-12 中国科学院合肥物质科学研究院 基于桡动脉脉搏波的心血管机能参数检测分析方法及检测装置

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
YU , WEI: "Experimental Study on Non-invasive Reflectance Oxygen Saturation Measurement, CNKI", MEDICINE AND HEALTH, 15 January 2007 (2007-01-15), pages 13 , 14 , 38 - 46, XP009500364, ISSN: 1671-6779 *
ZHANG, XIN ET AL.: "Improvement of Pulse Waveform Dectection with Autoregressive Model In Blood Oxygen Saturation Measurement", JOURNAL OF BIOMEDICAL ENGINEERING, vol. 17, no. 3, 31 December 2000 (2000-12-31), XP009500226, ISSN: 1001-5551 *

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109833034A (zh) * 2017-11-24 2019-06-04 深圳市岩尚科技有限公司 一种脉搏波信号中提取血压数据的方法及装置

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