WO2020133052A1 - 一种监测用户生命体征的方法和装置 - Google Patents

一种监测用户生命体征的方法和装置 Download PDF

Info

Publication number
WO2020133052A1
WO2020133052A1 PCT/CN2018/124305 CN2018124305W WO2020133052A1 WO 2020133052 A1 WO2020133052 A1 WO 2020133052A1 CN 2018124305 W CN2018124305 W CN 2018124305W WO 2020133052 A1 WO2020133052 A1 WO 2020133052A1
Authority
WO
WIPO (PCT)
Prior art keywords
sampling
low
signal
frequency
sensor
Prior art date
Application number
PCT/CN2018/124305
Other languages
English (en)
French (fr)
Inventor
胡咪咪
蒋浩宇
叶文宇
何先梁
Original Assignee
深圳迈瑞生物医疗电子股份有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 深圳迈瑞生物医疗电子股份有限公司 filed Critical 深圳迈瑞生物医疗电子股份有限公司
Priority to CN201880099069.0A priority Critical patent/CN112930138B/zh
Priority to PCT/CN2018/124305 priority patent/WO2020133052A1/zh
Publication of WO2020133052A1 publication Critical patent/WO2020133052A1/zh
Priority to US17/361,262 priority patent/US20210321927A1/en

Links

Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]
    • A61B5/339—Displays specially adapted therefor
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/74—Details of notification to user or communication with user or patient ; user input means
    • A61B5/746—Alarms related to a physiological condition, e.g. details of setting alarm thresholds or avoiding false alarms
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/0002—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network
    • A61B5/0004—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network characterised by the type of physiological signal transmitted
    • A61B5/0006—ECG or EEG signals
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]
    • A61B5/346—Analysis of electrocardiograms
    • A61B5/347—Detecting the frequency distribution of signals
    • 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
    • A61B5/7225—Details of analog processing, e.g. isolation amplifier, gain or sensitivity adjustment, filtering, baseline or drift compensation
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]
    • A61B5/346—Analysis of electrocardiograms
    • A61B5/349—Detecting specific parameters of the electrocardiograph cycle

Definitions

  • the invention relates to a method and device for monitoring user vital signs.
  • Existing devices for monitoring user signs such as monitors, generally use a fixed signal sampling rate, resolution, bandwidth, and number of bits to collect physiological signals of patients in a physiological signal collection method. This is for a reason: in conventional monitoring applications, such as telemetry monitoring scenarios, patients need to carry a telemetry monitor with them. In this case, long-term continuous monitoring of physiological parameters such as the patient’s ECG is required, so the power consumption of the monitor is required It is relatively high, and in general monitoring applications, only basic monitoring information such as heart rate and arrhythmia is generally concerned, and the requirements for physiological signal acquisition accuracy are not high.
  • the above low-power acquisition method is not suitable for detailed analysis of physiological signals, because its acquisition accuracy is relatively low; but for telemetry monitoring, if a fixed higher signal sampling rate, resolution, bandwidth, and number of bits are used, although this kind of long-term continuous collection of high-precision physiological signals can be used for detailed analysis, it will cause great power consumption, excessive data storage capacity and higher chip computing power consumption for the monitor, which is not suitable for clinical long-term Time real-time monitoring application.
  • the present invention mainly provides a method and device for monitoring user vital signs.
  • an embodiment provides a method for monitoring user vital signs, including:
  • the method for collecting and processing the sensor signal includes: a method for sampling the sensor signal, and/or a method for processing the data obtained after sampling the sensor signal.
  • an embodiment provides a method for monitoring user vital signs, including:
  • the method for collecting and processing the ECG signal includes: a method for sampling the ECG signal, and/or a method for processing the data obtained after sampling the ECG signal.
  • an embodiment provides an apparatus for monitoring user vital signs, including:
  • At least one sensor connected to the user to output sensor signals related to vital signs
  • a signal acquisition circuit is used to sample the sensor signal to obtain data related to vital signs
  • the processor is configured to adjust the manner in which the signal acquisition circuit collects and processes sensor signals in response to key events.
  • the manner in which the processor adjusts the signal acquisition circuit to collect and process the sensor signal includes: adjusting the manner in which the signal acquisition circuit samples the sensor signal, and/or obtained after sampling the sensor signal The way the data is processed again.
  • an embodiment provides an apparatus for monitoring user vital signs, including:
  • ECG sensor used to connect to the user to output ECG signals
  • a signal acquisition circuit is used to sample the ECG signal to obtain ECG data
  • the processor is configured to adjust the manner in which the signal acquisition circuit collects and processes the electrocardiogram signal in response to a key event.
  • the manner in which the processor adjusts the signal acquisition circuit to collect and process the ECG signal includes: adjusting the manner in which the signal acquisition circuit samples the ECG signal, and/or The method of processing the data obtained after sampling.
  • an embodiment provides a computer-readable storage medium, including a program, which can be executed by a processor to implement the method described in any of the embodiments herein.
  • the method, device and computer-readable storage medium for monitoring vital signs of a user dynamically change the manner in which sensor signals such as ECG signals are collected and processed by responding to key events, including, for example, ECG signals, etc.
  • the way of sampling and post-sampling data processing can realize the switching of one or more modes such as different power consumption, different calculation amount, different data amount, different sampling rate, different resolution, different bandwidth, different number of bits and so on.
  • FIG. 1 is a schematic structural diagram of an apparatus for monitoring user vital signs according to an embodiment
  • FIG. 2 is a schematic structural diagram of another embodiment of an apparatus for monitoring vital signs of a user
  • Fig. 3 is a schematic structural diagram of a monitor networking system used in a hospital
  • FIG. 4 is a schematic diagram of two other types of structures of an apparatus for monitoring vital signs of a user according to an embodiment
  • FIG. 5 is an explanatory diagram of the working principle of an apparatus for monitoring vital signs of a user according to an embodiment
  • FIG. 6 is another schematic structural diagram of an apparatus for monitoring vital signs of a user according to an embodiment
  • FIG. 7 is a schematic structural diagram of an apparatus for monitoring user vital signs according to another embodiment
  • FIG. 8 is a schematic diagram of another two types of structures of an apparatus for monitoring vital signs of a user according to another embodiment
  • FIG. 9 is another schematic structural diagram of an apparatus for monitoring vital signs of a user according to another embodiment.
  • FIG. 10 is a flowchart of a method for monitoring user vital signs according to an embodiment
  • 11 is another flowchart of a method for monitoring user vital signs according to an embodiment
  • FIG. 13 is a flowchart of a method for monitoring user vital signs according to another embodiment
  • 15 is another flowchart of a method for monitoring user vital signs according to another embodiment.
  • connection and “connection” mentioned in this application, unless otherwise specified, include direct and indirect connection (connection).
  • routine monitoring applications such as telemetry monitoring
  • routine monitoring applications in order to balance the requirements of power consumption, noise, data storage capacity and chip computing power, on the basis of meeting the clinical routine monitoring needs and algorithm requirements, generally use a fixed lower signal Sampling rate/resolution/bandwidth/digits for physiological signal acquisition.
  • the amount of patient status information provided by conventional basic monitoring to users is limited, and it has been unable to meet the needs of high-end clinical monitoring.
  • users need monitors to provide more detailed patient physiology Status analysis to assist clinical decision-making, such as ECG diagnosis analysis and ECG high frequency component analysis.
  • the physiological signal acquisition accuracy of conventional basic monitoring applications can no longer meet more detailed
  • the needs of the patient's physiological state analysis need to improve the accuracy of the physiological signal acquisition at the data acquisition end to have application value, but on the other hand, if the data acquisition end directly adopts a fixed high signal sampling rate/resolution/bandwidth/digit number acquisition method It will bring higher power consumption, data storage capacity and chip computing consumption to the monitor, and is not suitable for clinical long-term real-time monitoring applications.
  • the present invention designs a technical solution for dynamically changing physiological signal acquisition and processing methods, such as automatic, semi-automatic, or manual adjustment of physiological signal acquisition and processing methods, including dynamic Change the signal sampling rate, signal resolution, signal bandwidth and/or number of signal bits, according to the application requirements of clinical detailed analysis, to achieve different power consumption, different calculation amount, different data amount, different sampling rate, different resolution, different bandwidth, Switch between one or more modes such as different digits.
  • physiological signal acquisition and processing methods such as automatic, semi-automatic, or manual adjustment of physiological signal acquisition and processing methods, including dynamic Change the signal sampling rate, signal resolution, signal bandwidth and/or number of signal bits, according to the application requirements of clinical detailed analysis, to achieve different power consumption, different calculation amount, different data amount, different sampling rate, different resolution, different bandwidth, Switch between one or more modes such as different digits.
  • an embodiment provides a device for monitoring vital signs of a user.
  • the device includes at least one sensor 10, a signal acquisition circuit 30, and a processor 50, which will be described in detail below.
  • the sensor 10 is used to connect to a user to acquire and output sensor signals related to vital signs.
  • the sensor 10 may include one or more of an electrocardiogram electrode, a blood oxygen probe, a blood pressure sensor, an electroencephalogram sensor, a respiratory electrode, a temperature sensor, and a motion sensor.
  • the sensor signal includes an electrocardiogram signal , One or more of blood oxygen signal, blood pressure signal, electroencephalogram signal, respiratory signal, body temperature signal and exercise signal; in other words, ECG electrodes are used to connect users to obtain and output ECG signal, blood oxygen
  • the probe is used to connect users to obtain and output blood oxygen signals
  • the blood pressure sensor is used to connect users to obtain and output blood pressure signals
  • the EEG sensor is used to connect users to obtain and output EEG signals
  • the breathing electrode pads are used to connect users to obtain And output breathing signals
  • temperature sensors are used to connect users to obtain and output body temperature signals
  • motion sensors are used to connect users to obtain and output motion signals.
  • the above-mentioned sensor signal is a front-end signal obtained directly from the patient, which may be an analog signal or a digital signal.
  • the signal acquisition circuit 30 is used to sample the sensor signal to obtain data related to vital signs.
  • the signal acquisition circuit 30 samples the sensor signal, and uses the sampled digital signal as data related to the vital signs.
  • the signal acquisition circuit 30 samples the sensor signal according to a preset sampling rate, bandwidth, resolution, and/or number of bits to obtain a digital signal.
  • the sampling rate is also called sampling speed or sampling frequency, which defines the number of samples that are extracted from the signal per second and form a discrete signal
  • the bandwidth of the signal acquisition circuit 30 refers to the bandwidth of its sampling, That is, the frequency range of signals that can be collected, for example, the bandwidth of the signal sampling circuit 30 is 0 Hz to 350 Hz, it means that the signal sampling circuit 30 can collect signals of 0 Hz to 350 Hz
  • the resolution of the signal collection circuit 30 is defined as the minimum value of the input signal value Variation, that is, the ability to resolve the smallest quantized signal
  • the number of bits of the signal acquisition circuit 30 is also called the data width or data bit width, which defines the dynamic range of the input signal value, that is, the maximum signal range that can be quantified.
  • the signal acquisition circuit 30 can also process the data obtained by sampling the sensor, for example, the signal acquisition circuit 30 samples the sensor signal to obtain the data, and then processes the data, including variable sampling of the data , And/or filtering, and/or data interception, and/or changing the number of digits, etc.
  • the processor 50 may adjust the manner in which the signal acquisition circuit 30 samples the sensor signal by changing one or more of the sampling rate, bandwidth, resolution, and number of bits of the signal acquisition circuit 30.
  • the processor 50 may also change the manner in which the signal acquisition circuit 30 processes the data obtained by sampling, such as variable sampling, and/or filtering, and/or data interception, and/or changing the number of bits Wait for processing to change the sampling rate, and/or bandwidth, and/or resolution, and/or number of bits of the collected data, so that the processor 50 does not need too high data storage when re-analyzing the processed data, and/or Or chip computing power.
  • the present application provides a system framework diagram of an apparatus for monitoring user vital signs.
  • the device for monitoring the vital signs of the user includes at least a parameter measurement circuit 1112.
  • the parameter measuring circuit 1112 includes at least one parameter measuring circuit 1112 corresponding to physiological parameters.
  • the parameter measuring circuit 1112 includes at least an electrocardiographic signal parameter measuring circuit, a respiratory parameter measuring circuit, a body temperature parameter measuring circuit, a blood oxygen parameter measuring circuit, a non-invasive blood pressure parameter measuring circuit , At least one parameter measurement circuit in the invasive blood pressure parameter measurement circuit, etc., each parameter measurement circuit 1112 is connected to the externally inserted sensor accessory 1111 through a corresponding sensor interface.
  • the sensor accessory 1111 includes a sensor 10 for detecting physiological parameters such as electrocardiographic respiration, blood oxygen, blood pressure, and body temperature.
  • the parameter measurement circuit 1112 is mainly used to connect the sensor accessory 1111 to obtain the collected physiological parameter signal, and may include at least two or more physiological parameter measurement circuits.
  • the parameter measurement circuit 1112 may be, but not limited to, a physiological parameter measurement circuit (module) , Human physiological parameter measurement circuit (module) or sensor to collect human physiological parameters and so on.
  • the parameter measurement circuit 1112 is connected to an external physiological parameter sensor through an extended interface to obtain physiological sampling signals about the patient, and after processing, physiological data is obtained for alarm and display.
  • the extended interface can also be used to output the control signal about how to collect physiological parameters output by the main control circuit to the external physiological parameter monitoring accessory through the corresponding interface to realize the monitoring and control of the patient's physiological parameters.
  • the device for monitoring vital signs of a user of the present application may further include a main control circuit 1113.
  • the main control circuit 1113 needs to include at least one processor 50 and at least one memory.
  • the main control circuit 1113 may also include a power management module, a power IP module and At least one of an interface conversion circuit and the like.
  • the power management module is used to control the power on/off of the whole machine, the pre-power-up sequence of each power supply inside the board and the battery charge and discharge.
  • the power IP module refers to correlating the schematic diagram of the power circuit unit that is frequently called repeatedly and the PCB layout, and curing into a separate power module, that is, converting an input voltage into an output voltage through a predetermined circuit, wherein the input voltage and The output voltage is different.
  • the power IP module may be single-channel or multi-channel.
  • the power IP module can convert an input voltage to an output voltage.
  • the power IP module can convert one input voltage to multiple output voltages, and the voltage values of the multiple output voltages can be the same or different, so as to meet the needs of multiple electronic components at the same time. Voltage demand, and the module has few external interfaces, working in the system is a black box decoupled from the external hardware system, improving the reliability of the entire power system.
  • the interface conversion circuit is used to convert the signal output by the main control minimum system module (that is, at least one processor and at least one memory in the main control circuit) into the input standard signal required by the actual external device, for example, supporting external VGA display
  • the function is to convert the RGB digital signal output from the main control CPU to a VGA analog signal, support external network functions, and convert the RMII signal to a standard network differential signal.
  • the device for monitoring the vital signs of the user may further include one or more of an alarm circuit 1116, an input interface circuit 1117, an external communication, and a power interface 1115.
  • the main control circuit 1113 is used to coordinate and control the various cards, circuits and devices in the multi-parameter monitor or module assembly.
  • the main control circuit 1113 is used to control the data interaction between the parameter measurement circuit 1112 and the communication interface circuit, as well as the transmission of control signals, and send the physiological data to the display 1114 for display, or it can also be received from the touch screen Or user control commands input by physical input interface circuits such as keyboards and keys, of course, can also output control signals on how to collect physiological parameters.
  • the alarm circuit 1116 may be an audible and visual alarm circuit.
  • the main control circuit 1113 completes the calculation of physiological parameters, and can send the calculation results and waveforms of the parameters to the host (such as the host with a display, PC, central station, etc.) through external communication and power interface 1115, external communication and power interface 115 may be one or a combination of a LAN interface composed of Ethernet (Token), Token Ring (Token Ring), Token Bus (Token Bus), and the Optical Fiber Distributed Data Interface (FDDI) as the backbone of the three networks It can also be one or a combination of wireless interfaces such as infrared, Bluetooth, wifi, and WMTS communication, or one or a combination of wired data connection interfaces such as RS232 and USB.
  • wireless interfaces such as infrared, Bluetooth, wifi, and WMTS communication
  • wired data connection interfaces such as RS232 and USB.
  • the external communication and power interface 115 may also be one or a combination of two of a wireless data transmission interface and a wired data transmission interface.
  • the host computer can be any computer equipment such as the monitor's host computer, electrocardiogram machine, ultrasonic diagnostic equipment, computer, etc., and install the matching software to form a monitoring device.
  • the host can also be a communication device, such as a mobile phone, a multi-parameter monitor, or a module component, which sends data to a mobile phone that supports Bluetooth communication through a Bluetooth interface, so as to realize remote transmission of data.
  • the device for monitoring the vital signs of the user can be set outside the monitor casing, as an independent extrapolation parameter module, which can be inserted into the monitor host (including the main control board) to form a plug-in monitor as part of the monitor, or It can also be connected to the host of the monitor (including the main control board) through a cable, and the external parameter module is used as an external accessory of the monitor.
  • parameter processing can also be built into the housing, integrated with the main control module, or physically separated within the housing to form an integrated monitor.
  • a bedside monitor 1212 may be provided for each bed, and the bedside monitor 1212 may be the aforementioned device for monitoring vital signs of the user.
  • each bedside monitor 1212 can also be paired with a portable monitoring device 1213.
  • the portable monitoring device 1213 provides a simple and portable multi-parameter monitor or module assembly, but it can be worn on the patient's body to move the patient.
  • the physiological data generated by the mobile monitoring can be transmitted to the bedside monitor 1212 for display, or transmitted through the bedside monitor 1212 to the central station 1211 is for viewing by the doctor or nurse, or transmitted to the data server 1215 through the bedside monitor 1212 for storage.
  • the portable monitoring device 1213 can also directly transmit the physiological data generated by the mobile monitoring to the central station 1211 through the wireless network node 1214 provided in the hospital for storage and display, or the mobile monitoring can be transmitted through the wireless network node 214 provided in the hospital The generated physiological data is transmitted to the data server 1215 for storage.
  • the data corresponding to the physiological parameters displayed on the bedside monitor 1212 can be derived from the sensor accessory 1111 directly connected to the monitor, or from the portable monitoring device 1213, or from the data server .
  • the sampling method of the signal sampling circuit 30 will be described in detail below.
  • the signal sampling circuit 30 samples the sensor signal by a low-precision sampling method and a high-precision sampling method, where the low-precision sampling method can be the default sampling method, of course, the high-precision sampling method can also be set to the default Sampling method.
  • the sampling rate of the low-precision sampling method, the highest frequency of the bandwidth, the resolution, and the number of bits are not greater than the sampling rate, the highest frequency of the bandwidth, the resolution, and the number of bits of the high-precision sampling method, and at least one Those are not equal.
  • the sampling rate of the high-precision sampling method can be greater than that of the low-precision sampling method; for example, the resolution of the high-precision sampling method can be greater than the resolution of the low-precision sampling method, that is, the ability of the high-precision sampling method to resolve the quantized minimum signal is greater than the low-precision sampling method.
  • Ability to distinguish the smallest quantized signal for example, the number of data bits in high-precision sampling can be greater than that in low-precision, that is, the maximum signal dynamic range that high-precision sampling can quantize is greater than the maximum signal dynamics that low-precision sampling can quantify Range; for example, the highest frequency of the bandwidth of the high-precision sampling method may be greater than the highest frequency of the bandwidth of the low-precision sampling method.
  • the bandwidth of the high-precision sampling method may include the low-precision bandwidth, or only partially overlap, or completely Non-overlapping, for example, the bandwidth of high-precision sampling in an example is 0 to 350 Hz, and the bandwidth of low-precision sampling is 0 to 150 Hz; for example, the bandwidth of high-precision sampling is 100 to 350 Hz, and the bandwidth of low-precision sampling is 0 to 150 Hz; for example In one example, the bandwidth of high-precision sampling is 150 to 350 Hz, and the bandwidth of low-precision sampling is 0 to 150 Hz.
  • the signal acquisition circuit 30 may have various solutions for implementing a high-precision sampling method and a low-precision sampling method.
  • the signal acquisition circuit 30 may include a low-precision sampling circuit 31 and a high-precision sampling circuit 33 respectively connected to the sensor 10.
  • the sampling rate and bandwidth of the low-precision sampling circuit 31 are the highest.
  • the four of frequency, resolution, and number of digits are not greater than the sampling rate, the highest frequency of the bandwidth, the resolution, and the number of digits of the high-precision sampling circuit 33, respectively, and at least one of them is not equal.
  • the low-precision sampling mode only the low-precision sampling circuit 31 in the signal acquisition circuit 30 is enabled to sample the sensor signal; while in the high-precision sampling mode, the high-precision sampling circuit 33 in the signal sampling circuit only samples the sensor signal .
  • the signal sampling circuit 30 includes a first processing circuit 35, a low-precision sampling circuit 31, and a high-precision sampling circuit 33.
  • the first processing circuit 35 is used to process the sensor signal into the same two signals, one signal is input to the low-precision sampling circuit 31, and the other signal is input to the high-precision sampling circuit 33; the low-precision sampling circuit 31
  • the sampling rate, the highest frequency of the bandwidth, the resolution, and the number of bits are not greater than the sampling rate, the highest frequency of the bandwidth, the resolution, and the number of bits of the high-precision sampling circuit 33, respectively, and at least one of them is not equal;
  • the processor 50 adjusts the way of sampling the sensor signal by turning on and off the low-precision sampling circuit 31 and the high-precision sampling circuit 33.
  • the processor 50 controls to turn on the low-precision sampling circuit 31 and turn off the high-precision sampling circuit 33.
  • the processor 50 controls to turn on the low-precision sampling circuit 31 and the high-precision sampling circuit 33.
  • the method for sampling the sensor signal by the signal acquisition circuit 30 includes a low-precision sampling method and a high-precision sampling method; wherein the low-precision sampling of the sensor signal includes: sampling low-frequency components in the sensor signal to obtain vital sign correlation Low-frequency data of the sensor; high-precision sampling of the sensor signal includes: sampling low-frequency components and high-frequency components in the sensor signal to obtain low-frequency data and high-frequency data related to vital signs.
  • the bandwidth of the low-accuracy sampling method of the signal acquisition circuit 30 is the preset low-frequency bandwidth
  • the bandwidth of the high-accuracy sampling method includes not only the above-mentioned preset low-frequency bandwidth, but also the preset high-frequency bandwidth. Frequency bandwidth.
  • the low-precision sampling method of the ECG signal by the signal acquisition circuit 30 includes: sampling low-frequency components in the ECG signal to obtain low-frequency data of the ECG; the signal acquisition circuit 30 is The high-precision sampling method of the ECG signal includes: sampling low-frequency components and high-frequency components in the ECG signal to obtain low-frequency data and high-frequency data of the ECG.
  • the low-precision sampling method of the ECG signal by the signal acquisition circuit 30 has a sampling rate no greater than 1 kHz, and/or a bandwidth no greater than 0-250 Hz, and/or a resolution no greater than 1 uV/LSB; and/or
  • the high-precision sampling method of the ECG signal by the signal acquisition circuit 30 has a sampling rate of not less than 1 kHz, and/or a bandwidth of not less than 0-250 Hz, and/or a resolution of at least 1 uV/LSB.
  • the above are some descriptions of the manner in which the signal acquisition circuit 30 samples.
  • the following describes how the processor 50 adjusts the signal acquisition circuit 30 to acquire and process the sensor signal.
  • the processor 50 adjusts the manner in which the signal sampling circuit 30 samples the sensor signal in response to a key event.
  • the key events include one or more of the input of related instructions for the user's physiological state, the user's movement state, and the sampling and processing mode adjustment, which are described below.
  • the key event is the change of the user's physiological state
  • the processor 50 is further configured to analyze the data related to the vital signs to determine the change in the user's physiological state, for example, to determine whether the user's physiological state is normal or abnormal. It should be noted that the processor 50 can determine the user's physiological state changes according to real-time, short-term, or long-term vital sign-related data.
  • the processor 50 can obtain ECG indexes such as heart rate, heart rhythm, P wave shape, QRS shape, and/or ST-T shape by analyzing the ECG data obtained by sampling the ECG signal , You can determine whether the user's physiological state is normal or abnormal according to one or more of these ECG indicators.
  • ECG indexes such as heart rate, heart rhythm, P wave shape, QRS shape, and/or ST-T shape.
  • the user's physiological state becomes abnormal; for example, when the user is judged When the arrhythmia is abnormal, it is judged that the user's physiological state becomes abnormal; for example, when the user's P-wave form is different from the normal P-wave form, the user's physiological state becomes abnormal; for example, when the user's QRS form is different from the normal QRS form
  • QRS wave shape is abnormal or its width is abnormal
  • it is judged that the user's physiological state becomes abnormal for example, when it is judged that the ST-T shape of the user is significantly different from the normal ST-T shape-such as ST segment depression or T
  • the wave is inverted, it is determined that the user's physiological state has become abnormal.
  • the processor 50 can analyze the blood oxygen data sampled from the blood oxygen signal to obtain blood oxygen indexes such as blood oxygen saturation and/or perfusion index. According to one of these blood oxygen indexes Or more can judge whether the user's physiological state is normal or abnormal.
  • the blood pressure signal is also similar.
  • the processor 50 can analyze the blood pressure data sampled from the blood pressure signal to obtain blood pressure indicators such as systolic pressure, diastolic pressure and average pressure. According to more than one of these blood pressure indicators, the user's physiology can be determined Whether the status is normal or abnormal.
  • the respiration signal is also similar.
  • the processor 50 can analyze the respiration data sampled from the respiration signal to obtain respiration indicators such as respiration rate.
  • respiration indicators such as respiration rate
  • the body temperature signal is also similar.
  • the processor 50 can analyze the body temperature data sampled from the body temperature signal to obtain body indexes such as body temperature, and can also determine whether the user's physiological state is normal or abnormal according to the body temperature.
  • the processor 50 when the processor 50 determines that the physiological state of the user has changed from normal to abnormal, the processor 50 adjusts the signal sampling circuit 30 to sample the sensor signal to a sampling method with higher accuracy than the current one. And/or, in one embodiment, when the processor 50 determines that the user's physiological state has changed from abnormal to normal, the processor 50 adjusts the way in which the signal acquisition circuit 30 samples the sensor signal to a sampling mode with lower accuracy than the current one, or The data obtained by sampling the sensor signal is then subjected to variable sampling, and/or filtering, and/or data interception, and/or changing the number of bits to reduce the data sampling rate, and/or bandwidth, and/or resolution, and /Or the number of digits to get data with lower accuracy than the current one.
  • the processor 50 may set the signal sampling circuit 30 to sample the sensor signal to a low-precision sampling method.
  • the processor 50 collects the signal The circuit 30 is adjusted from a low-precision sampling mode to a high-precision sampling mode; in the high-precision sampling mode, when the processor 50 determines that the user's physiological state has changed from abnormal to normal, the processor 50 samples the signal acquisition circuit 30 from high-precision sampling.
  • the method is adjusted back to the low-precision sampling mode, or the data obtained by sampling the sensor signal is then subjected to variable sampling, and/or filtering, and/or data interception, and/or changing the number of bits to reduce the data sampling rate, and/or Or bandwidth, and/or resolution, and/or number of bits, to obtain low-precision data.
  • the processor 50 may set the signal sampling circuit 30 to sample the sensor signal to a high-precision sampling method.
  • the signal acquisition circuit 30 samples the low-frequency component of the electrocardiogram signal to obtain low-frequency data of the electrocardiogram.
  • the processor 50 judges that the user's heart state changes from normal to abnormal according to the low-frequency data of the electrocardiogram, the process is processed.
  • the device 50 adjusts the signal sampling circuit 30 to sample the low-frequency component and the high-frequency component of the ECG signal; and/or, the signal acquisition circuit 30 samples the low-frequency component and the high-frequency component of the ECG signal to obtain the low frequency of the ECG Data and high-frequency data, when the processor 50 judges that the user's heart state has changed from abnormal to normal according to the low-frequency data and/or high-frequency data of the electrocardiogram, the processor 50 adjusts the signal acquisition circuit to perform low-frequency components in the electrocardiogram signal Sampling, or, the data obtained by sampling the low-frequency component and the high-frequency component of the electrocardiogram signal is then subjected to variable sampling, and/or filtering, and/or data interception, and/or changing the number of bits.
  • the signal acquisition unit 30 can adopt the default low-precision sampling mode. This can ensure lower power consumption, smaller data storage capacity, and lower chip computing power consumption; when judging the user’s When the physiological state changes from normal to abnormal, the signal acquisition unit 30 switches to a high-precision sampling mode to further obtain some subdivided components of the sensor signal, which is helpful for further diagnosis of the user's physiological state; When returning to normal, the signal sampling unit 30 can switch back to the low-precision sampling mode and so on.
  • the processor 50 is further configured to analyze the data related to the vital signs to determine the change of the user's movement state.
  • the processor 50 can analyze the motion data obtained by sampling the motion signal to obtain relevant motion indicators, such as speed, acceleration, and angle of motion.
  • the motion indicators can be used to determine the user’s motion status.
  • the degree of intensification for example, when the speed becomes faster, the acceleration becomes larger, and the movement angle becomes larger in a short time, etc., the degree of the user's movement state can be judged to be intensified, otherwise, the user's movement state can be maintained at the current level or slowed down; specifically during implementation, You can set one or more thresholds to divide the exercise into different levels. The higher the level, the more intense the exercise status. When the exercise status changes from a low level to a high level, the user's exercise status is judged to increase. On the contrary, when the exercise When the state changes from a high level to a low level, it is judged that the degree of the user's motion state is slowed.
  • the processor 50 when the processor 50 judges that the degree of the user's motion state is intensified, the processor 50 adjusts the way in which the signal acquisition circuit 30 samples the sensor signal to a sampling method with higher accuracy than the current one. And/or, in one embodiment, when the processor 50 judges that the degree of the user's motion state is slow, the processor 50 adjusts the way the signal acquisition circuit 30 samples the sensor signal to a sampling method with lower accuracy than the current, or the sensor signal.
  • the data obtained by sampling is then subjected to variable sampling, and/or filtering, and/or data interception, and/or changing the number of bits, etc., to obtain data with lower accuracy than the current one.
  • the processor 50 judges that the degree of the user's movement state is intensified, a higher-precision sampling method is needed, and the obtained sampled data is credible, reducing the interference of the movement on the data; when the processor 50 judges that the degree of the user's movement state is slow, then It can be switched to a sampling method with lower accuracy than the current, or the data obtained by sampling the sensor signal can be subjected to variable sampling, and/or filtering, and/or data interception, and/or changing the number of bits, etc.
  • the data with low accuracy is because on the one hand, due to the slowness of the motion state, the high-precision sampling method is unnecessary, and the reduction to a sampling method with lower accuracy can also ensure the reliability of the data; on the other hand, it is also reduced.
  • the device's power consumption, data storage and chip computing power consumption make the device work longer and save energy.
  • the key events in (1) above are changes in the user's physiological state and (2) the key events are changes in the user's motion state.
  • the processor 50 can automatically adjust the manner in which the signal acquisition circuit 30 collects and processes sensor signals.
  • the processor 50 is used to analyze the data related to the vital signs, determine the change of the user's physiological state, and generate a control for inputting relevant instructions for adjusting the collection and processing mode according to the change of the user's physiological state.
  • the generated control includes a confirmation key for adjusting the precision, which is used to collect the signal when the click information on the confirmation key is received. The way in which the circuit 30 samples the sensor signal is adjusted to a sampling method with higher accuracy than the current one.
  • the generated control when the processor 50 determines that the user's physiological state has changed from abnormal to normal, includes a confirmation key with lowered precision, which is used to receive the click information on the confirmation key. Adjusting the way the signal acquisition circuit 30 samples the sensor signal to a sampling method with lower accuracy than the current, or the data obtained by sampling the sensor signal is subjected to variable sampling, and/or filtering, and/or data interception, and/or Processing such as changing the number of digits results in data with lower accuracy than the current one.
  • the processor 50 may determine the physiological state of the user by analyzing the electrocardiogram data obtained by sampling the electrocardiogram signal. For example, the signal acquisition circuit 30 samples the low-frequency components of the electrocardiogram signal to obtain low-frequency data of the electrocardiogram.
  • the generated controls include adjusting the high precision
  • the confirmation key of is used to adjust the signal acquisition circuit 30 to sample the low-frequency component and the high-frequency component of the electrocardiogram signal when the click information of the confirmation key is received.
  • the signal acquisition circuit 30 samples the low-frequency component and the high-frequency component of the electrocardiogram signal to obtain low-frequency data and high-frequency data of the electrocardiogram.
  • the high-frequency data determines that the user's heart state has changed from abnormal to normal, and the generated control includes a confirmation key with reduced accuracy, which is used to adjust the signal acquisition circuit 30 to the electrocardiographic signal when receiving click information on the confirmation key Sampling the mid- and low-frequency components, or sampling the low-frequency and high-frequency components of the electrocardiogram signal for variable sampling, and/or filtering, and/or data interception, and/or changing the number of bits.
  • the above is an example of a control in which the processor 50 generates related instructions for input collection and processing mode adjustment according to the change of the user's physiological state. Similarly, the processor 50 can also generate the input collection and processing mode adjustment according to the change in the user's motion state.
  • the control of related commands is described in detail below.
  • the processor 50 is further used to analyze the vital sign-related data, determine the user's movement state change, and generate a control for inputting relevant instructions for adjusting the collection and processing mode according to the user's movement state change.
  • the generated control includes a high-precision confirmation key, which is used to control the signal acquisition circuit 30 when receiving click information on the confirmation key.
  • the method of sampling the sensor signal is adjusted to a sampling method with higher accuracy than the current one.
  • the processor 50 judges that the degree of the user's movement state is slow, and the generated control includes a confirmation key with lowered precision, which is used to signal when the click information on the confirmation key is received.
  • the acquisition circuit 30 adjusts the sampling method of the sensor signal to a sampling method with lower accuracy than the current one, or the data obtained by sampling the sensor signal is subjected to variable sampling, and/or filtering, and/or data interception, and/or bit change Data processing, etc., to obtain data with lower accuracy than the current.
  • the processor 50 can determine the change of the user's state—for example, the physiological state and/or the movement state, and then determine whether to generate a control for inputting and adjusting the related instructions of the processing mode according to the determination result, so that the medical staff can The generated control is combined with its own experience to determine whether to adjust the manner in which the signal acquisition circuit 30 collects and processes the sensor signal.
  • the device for monitoring the vital signs of the user may also include an input unit (not shown in the figure)-for example, a keyboard, a mouse, and a touch screen, etc., used for inputting and adjusting relevant instructions for processing methods;
  • the processor 50 is used to adjust the method of collecting and processing the sensor signal by the signal collection circuit to the corresponding method of collection and processing when receiving the relevant instructions of the collection and processing mode adjustment through the input unit.
  • the medical staff can manually determine whether to adjust the manner in which the signal acquisition circuit 30 collects and processes the sensor signal, giving the medical staff greater autonomy and authority.
  • the processor 50 herein adjusts the way the signal acquisition circuit 30 samples the sensor signal to a sampling method with higher accuracy than the current, including: increasing the sampling rate of the signal acquisition circuit 30, increasing the bandwidth, and increasing the resolution and Increase one or more of the signal digits; for example, the processor 50 adjusts the signal acquisition circuit 30 to sample the sensor signal to a sampling method with higher accuracy than the current, including: adjusting the signal acquisition circuit 30 to the sensor signal
  • the low-frequency and high-frequency components are sampled to obtain low-frequency and high-frequency data related to vital signs.
  • the processor 50 adjusts the way the signal acquisition circuit 30 samples the sensor signal to a sampling method with lower accuracy than the current, including: reducing the sampling rate of the signal acquisition circuit 30, reducing the bandwidth, reducing the resolution, and reducing the signal bit One or more of the numbers; for example, the processor 50 adjusts the signal acquisition circuit 30 to sample the sensor signal to a sampling method with lower accuracy than the current, including: adjusting the signal acquisition circuit 30 to the low-frequency component of the sensor signal Perform sampling to obtain low frequency data related to vital signs.
  • the processor 50 adjusts the way in which the signal acquisition circuit 30 samples the sensor signal to be higher than the current accuracy
  • the sampling method is to switch the signal acquisition circuit 30 from the low-accuracy sampling method to the high-accuracy sampling method; the processor 50 adjusts the signal acquisition circuit 30 to sample the sensor signal to a sampling method with a lower accuracy than the current, that is, the signal acquisition
  • the circuit 30 is switched from a high-precision sampling method to a low-precision sampling method.
  • the processor 50 adjusts the sampling method of the signal acquisition circuit 30 to sample the sensor signal to a sampling method with higher precision than the current, some more detailed signals can be obtained.
  • 30 Adjust the sampling method of the sensor signal to a sampling method with higher accuracy than the current.
  • the vital signs related data are analyzed to determine whether the user's physiological state is abnormal. When the user's physiological state is abnormal, an alarm is issued.
  • the processor 50 analyzes the high frequency data related to vital signs to determine whether the user's physiological state is abnormal; when the analysis result of the high frequency data related to vital signs indicates that the user's physiological state is abnormal, an alarm is issued.
  • the processor 50 analyzes the low-frequency data and high-frequency data related to vital signs to determine whether the user's physiological state is abnormal; only when the analysis results of the high-frequency data and low-frequency data related to vital signs All indicate that the user's physiological state is abnormal, and then the alarm is issued.
  • the device for monitoring vital signs of a user may further include a display 70 for displaying data related to the vital signs.
  • the display 70 displays a graph of the data related to the vital signs, and/or displays the results of analyzing the data related to the vital signs.
  • the display 70 displays a graph of vital sign-related data, which can be a trend waveform that displays vital sign-related data in real time, or can display only a few historical typical moment waveforms, and can also display high precision in real time next to the waveform. Analysis of indicator values or changes. Take the ECG signal as an example. Sampling the ECG signal can obtain the ECG data.
  • the display 70 can display the ECG or the results of the analysis of the ECG data, such as heart rate and heart rhythm, and P wave shape. , QRS form and/or ST-T form, etc. are the result of judgment. Further, the display 70 can also be used to display an alarm prompt or an abnormal prompt.
  • the display 70 after the processor 50 adjusts the signal acquisition circuit 30 to sample the sensor signal to a sampling method with higher accuracy than the current one—for example, after adjusting from the low-accuracy sampling method to the high-accuracy sampling method, the display 70 only displays Data obtained by sampling the high-frequency component of the sensor signal, or synchronously and separately displaying the data obtained by sampling the high-frequency component and the low-frequency component of the sensor signal; when the processor 50 adjusts the way that the signal acquisition circuit 30 samples the sensor signal
  • the display 70 hides the data obtained by sampling the high-frequency components of the sensor signal, and only displays the data obtained by sampling the low-frequency components of the sensor signal.
  • the display 70 can also display the signal sampling mode in real time, for example, after adjusting from the low-precision sampling mode to the high-precision sampling mode, the display 70 can display in real time "high-precision signal acquisition or related function analysis” or "high-precision sampling” Prompt statements such as "method" are used to prompt the signal sampling method being adopted by the device monitoring the vital signs of the user.
  • an apparatus for monitoring vital signs of a user in an embodiment includes an electrocardiographic sensor 11, a signal acquisition circuit 30 and a processor 50.
  • the ECG sensor 11 is used to connect to a user to output an ECG signal;
  • the signal acquisition circuit 30 is used to sample the ECG signal to obtain ECG data;
  • the processor 50 is used to adjust the signal acquisition circuit in response to a key event The way to collect and process ECG signals.
  • the manner in which the processor 50 adjusts the signal acquisition circuit 30 to collect and process the ECG signal includes: adjusting the manner in which the signal acquisition circuit 30 samples the ECG signal, and/or after sampling the ECG signal The method of processing the obtained data. The following explains one by one.
  • the ECG sensor includes an ECG electrode pad for connecting to a user to obtain and output an ECG signal.
  • the signal acquisition circuit 30 samples the signal output by the ECG sensor 11 and uses the sampled digital signal as the ECG data.
  • the signal acquisition circuit 30 samples the signal output by the ECG sensor 11, including: sampling the signal output by the ECG sensor 11 according to a preset sampling rate, bandwidth, resolution, and/or number of signal bits, to obtain Digital signal.
  • the processor 50 adjusts the signal acquisition circuit 30 to sample the signal output by the electrocardiographic sensor 11 by changing one or more of the sampling rate, bandwidth, resolution, and number of signal bits of the signal acquisition circuit 30 the way.
  • the signal acquisition circuit 30 samples the signal output by the electrocardiogram sensor 11 including a low-precision sampling mode and a high-precision sampling mode, where the low-precision sampling mode is the default sampling mode; the low-precision sampling
  • the sampling rate of the method, the highest frequency of the bandwidth, the resolution, and the number of bits are not greater than the sampling rate, the highest frequency of the bandwidth, the resolution, and the number of bits, respectively, and at least one of them is not equal.
  • the sampling rate of the high-precision sampling method can be greater than that of the low-precision sampling method; for example, the resolution of the high-precision sampling method can be greater than the resolution of the low-precision sampling method, that is, the ability of the high-precision sampling method to resolve the smallest quantized signal is greater than that of the low-precision sampling method.
  • the number of data bits in high-precision sampling can be greater than that in low-precision sampling, that is, the maximum signal dynamic range that high-precision sampling can quantize is greater than the maximum signal dynamics that low-precision sampling can quantify Range; for example, the highest frequency of the bandwidth of the high-precision sampling method may be greater than the highest frequency of the bandwidth of the low-precision sampling method.
  • the bandwidth of the high-precision sampling method may include the low-precision bandwidth, or only partially overlap, or completely Non-overlapping, for example, the bandwidth of high-precision sampling in an example is 0 to 350 Hz, and the bandwidth of low-precision sampling is 0 to 150 Hz; for example, the bandwidth of high-precision sampling is 100 to 350 Hz, and the bandwidth of low-precision sampling is 0 to 150 Hz; for example In one example, the bandwidth of high-precision sampling is 150 to 350 Hz, and the bandwidth of low-precision sampling is 0 to 150 Hz.
  • the signal acquisition circuit 30 may have various solutions for implementing a high-precision sampling method and a low-precision sampling method.
  • the signal acquisition circuit 30 may include a low-precision sampling circuit 31 and a high-precision sampling circuit 33 respectively connected to the electrocardiographic sensor 11.
  • the sampling rate and bandwidth of the low-precision sampling circuit 31 are The four highest frequencies, the resolution, and the number of digits are not greater than the highest frequency, resolution, and number of digits of the sampling rate and bandwidth of the high-precision sampling circuit 33, respectively, and at least one of them is not equal.
  • the low-precision sampling mode only the low-precision sampling circuit 31 in the signal acquisition circuit 30 is enabled to sample the signal output by the electrocardiographic sensor 11; in the high-precision sampling mode, only the high-precision sampling circuit 33 in the signal sampling circuit is Enable to sample the signal output by ECG sensor 11.
  • the signal sampling circuit 30 includes a first processing circuit 35, a low-precision sampling circuit 31, and a high-precision sampling circuit 33.
  • the first processing circuit 35 is used to process the signal output by the electrocardiographic sensor 11 into the same two signals, one signal is input to the low-precision sampling circuit 31, and the other signal is input to the high-precision sampling circuit 33;
  • the sampling rate of the low-precision sampling circuit 31, the highest frequency of the bandwidth, the resolution, and the number of bits are not greater than the sampling rate, the highest frequency of the bandwidth, the resolution, and the number of bits of the high-precision sampling circuit 33, respectively, and at least One is not equal; the processor 50 adjusts the way of sampling the sensor signal by turning on and off the low-precision sampling circuit 31 and the high-precision sampling circuit 33.
  • the processor 50 controls The low-precision sampling circuit 31 is turned on and the high-precision sampling circuit 33 is turned off. In the high-precision sampling mode, the processor 50 controls to turn on the low-precision sampling circuit 31 and the high-precision sampling circuit 33.
  • the signal acquisition circuit 30 samples the signal output by the ECG sensor 11 includes a low-precision sampling method and a high-precision sampling method; wherein the low-precision sampling of the signal output by the ECG sensor 11 includes: 11.
  • the low-frequency components of the signal output by 11 are sampled to obtain low-frequency data of the ECG;
  • the high-precision sampling of the signal output by the ECG sensor 11 includes: sampling the low-frequency components and high-frequency components of the signal output by the ECG sensor 11, To obtain low-frequency data and high-frequency data of ECG.
  • the low-precision sampling method of the ECG signal by the signal acquisition circuit 30 has a sampling rate no greater than 1 kHz, and/or a bandwidth no greater than 0-250 Hz, and/or a resolution no greater than 1 uV/LSB; and/or
  • the high-precision sampling method of the ECG signal by the signal acquisition circuit 30 has a sampling rate of not less than 1 kHz, and/or a bandwidth of not less than 0-250 Hz, and/or a resolution of at least 1 uV/LSB.
  • the above are some descriptions of the manner in which the signal acquisition circuit 30 samples.
  • the following describes how the processor 50 adjusts the signal acquisition circuit 30 to acquire and process the sensor signal.
  • the processor 50 can adjust the manner in which the signal sampling circuit 30 samples the sensor signal in response to a critical event.
  • the key events include one or more of the input of relevant commands for the change of the user's physiological state and the adjustment of the collection and processing modes, which are described separately below.
  • the key event is the change of the user's physiological state
  • the processor 50 is used to analyze the electrocardiographic data to determine the change in the user's heart state. Specifically, in an embodiment, the signal acquisition circuit 30 samples the low-frequency components of the signal output by the electrocardiogram sensor 11 to obtain low-frequency data of the electrocardiogram. When the processor 50 judges that the user's heart state is normal according to the low-frequency data of the electrocardiogram If it becomes abnormal, the processor 50 adjusts the signal acquisition circuit 30 to sample the low-frequency component and the high-frequency component of the signal output by the electrocardiographic sensor; in one embodiment, the signal acquisition circuit 30 processes the signal output by the electrocardiographic sensor 11 Sampling low-frequency components and high-frequency components to obtain low-frequency data and high-frequency data of the ECG.
  • the process is processed.
  • the device 50 adjusts the signal acquisition circuit 30 to sample the low-frequency component of the signal output by the electrocardiographic sensor, or to sample the data obtained by sampling the low-frequency component and the high-frequency component of the signal output by the electrocardiographic sensor, and/or Or filtering, and/or data interception, and/or changing the number of digits, etc.
  • the processor 50 analyzes the electrocardiographic data to determine the user's heart state, thereby automatically adjusting the manner in which the signal acquisition circuit 30 collects and processes the electrocardiographic signal.
  • the processor 50 is used to analyze the electrocardiographic data to determine the change in the user's heart state, and according to the change in the user's heart state, generate a control for inputting related instructions for adjusting the collection and processing mode.
  • the signal acquisition circuit 30 samples the low-frequency components of the signal output by the electrocardiogram sensor 11 to obtain low-frequency data of the electrocardiogram.
  • the generated control includes a high-precision confirmation key, which is used to adjust the signal acquisition circuit 30 to the low-frequency component and high-frequency component of the signal output by the electrocardiogram sensor when receiving the click information on the confirmation key Sampling; in one embodiment, the signal acquisition circuit 30 samples the low-frequency components and high-frequency components of the signal output by the electrocardiogram sensor 11 to obtain low-frequency data and high-frequency data of the electrocardiogram.
  • Low-frequency data and/or high-frequency data determine that the user's heart state has changed from abnormal to normal, and the generated control includes a confirmation key with lowered precision, which is used to adjust the signal acquisition circuit 30 when receiving click information on the confirmation key
  • the generated control includes a confirmation key with lowered precision, which is used to adjust the signal acquisition circuit 30 when receiving click information on the confirmation key
  • the processor 50 analyzes the electrocardiographic data to determine the user's heart state, and then determines whether to generate a control of the relevant instructions for input collection and processing mode adjustment according to the judgment result, so that the medical staff can combine their own controls according to the generated control Experience to determine whether to adjust the signal acquisition circuit 30 to collect and process the ECG signal.
  • the device for monitoring the vital signs of the user may also include an input unit (not shown in the figure)-such as a keyboard, a mouse, and a touch screen, etc., for inputting relevant instructions for the collection and processing mode adjustment; processing
  • the device 50 is used to adjust the method of sampling the signal output by the electrocardiographic sensor 11 by the signal acquisition circuit 30 to the corresponding method of acquisition and processing when receiving the relevant instruction for the adjustment of the acquisition and processing method through the input unit.
  • the medical staff can manually determine whether to adjust the manner in which the signal acquisition circuit 30 collects and processes the ECG signal, giving the medical staff greater autonomy and authority.
  • the processor 50 adjusts the sampling method of the signal acquisition circuit 30 to the sensor signal to a sampling method with higher accuracy than the current, some more detailed signals can be obtained, so in one embodiment, the processor 50 outputs the electrocardiographic sensor 11
  • the low-frequency component and the high-frequency component of the signal are sampled, and the processor 50 analyzes the sampled data to determine whether the user's heart state is abnormal, and issues an alarm when the user's heart state is abnormal.
  • the processor 50 analyzes the high-frequency data of the ECG to determine whether the user's heart state is abnormal; when the analysis result of the high-frequency data of the ECG indicates that the user's heart state is abnormal, an alarm is issued; or, for example, the processor 50
  • the low-frequency data and high-frequency data of the ECG are analyzed to determine whether the user's heart state is abnormal; only when the analysis results of the high-frequency data and the low-frequency data of the ECG indicate that the user's physiological state is abnormal, the alarm is issued.
  • you can get ECG indicators such as heart rhythm, P-QRS-ST-T morphology, and ST trend changes.
  • HF-RMS high-frequency root mean square
  • HF-RAZ high-frequency reduction zone
  • other ECG indicators can be comprehensively judged by these ECG indicators of low-frequency and high-frequency data of the ECG, for example, giving HFQRS change abnormality, ST abnormality, ST change Abnormality, or give hints that the myocardial condition may be abnormal or myocardial ischemia may be given.
  • the device for monitoring the vital signs of the user may further include a display 70 for displaying the ECG data.
  • the display 70 is used to display a graph of electrocardiographic data.
  • the display 70 is used to display the results of analyzing the electrocardiographic data, such as heart rate and heart rhythm, as well as the determination result of whether the P wave form, QRS form, and/or ST-T form are abnormal. Further, the display 70 can also be used to display an alarm prompt or an abnormal prompt.
  • the display 70 displays only the data obtained by sampling the high-frequency component of the signal output by the electrocardiographic sensor. In an embodiment, when the signal acquisition circuit 30 samples the low-frequency component and the high-frequency component of the signal output by the ECG sensor 11, the display 70 can simultaneously and display the high-frequency component and the low-frequency component of the signal output by the ECG sensor 11, respectively. The data obtained.
  • the display 70 can prompt " Similar text prompts such as "high-frequency electrocardiographic analysis is in progress" can also be prompted by shape identification or color.
  • the display 70 is adjusted from displaying only the ECG low-frequency data waveform in the low-precision sampling mode to synchronizing the ECG low-frequency data waveform and the ECG high-frequency data waveform in real-time display in the high-precision sampling mode.
  • the waveform display mode can be real-time display of the complete high-frequency data waveform, or real-time display of high-frequency indicators obtained by analyzing high-frequency data (such as the above-mentioned high-frequency root mean square (HF-RMS) and high-frequency reduction area (HF-RAZ) and other ECG indicators), or it can be a waveform that displays only high-frequency data at a few critical moments. Further, the real-time status values or changes of high-frequency indicators (such as the aforementioned high-frequency root mean square (HF-RMS) and high-frequency reduction zone (HF-RAZ) ECG indicators) can also be displayed on the display interface value.
  • high-frequency indicators obtained by analyzing high-frequency data
  • HF-RAZ high-frequency reduction area
  • other ECG indicators can be a waveform that displays only high-frequency data at a few critical moments.
  • the real-time status values or changes of high-frequency indicators can also be displayed on the display interface value.
  • the processor 50 judges the high-frequency index of the ECG (such as the above-mentioned high-frequency root mean square (HF-RMS) and high-frequency reduction zone (HF-RAZ) and other low-frequency indexes (such as When the above mentioned heart rhythm, P-QRS-ST-T morphology, ST trend changes and other ECG indicators), and other parameter indicators (such as the above mentioned blood oxygen indicators, blood pressure indicators, respiratory indicators and body temperature indicators) appear abnormal
  • the processor 50 may generate corresponding prompts or alarms, for example, suggesting that certain indexes are abnormal, indicating that the condition of the myocardium may be abnormal, indicating that the myocardium may be ischemic, and so on.
  • the ECG signal is a weak physiological signal on the body surface.
  • the signal bandwidth is distributed in the range of 0.05Hz-350Hz.
  • the P wave, QRS wave, and T wave are in different frequency bands.
  • Physiological state is relevant, it can provide different levels of detailed information, and the ECG signal acquisition requirements can be determined according to different clinical applications and algorithm requirements.
  • ECG monitoring signals For clinical routine ECG monitoring applications, such as heart rate and arrhythmia monitoring, ECG monitoring signals generally require a noise level of no more than 30uV within a bandwidth of 0.5Hz-40Hz, and a resolution of 5uV/LSB. A signal sampling rate of 500Hz is sufficient.
  • the ground signal sampling circuit 30 can reduce the system power consumption, data storage amount, and chip calculation consumption as much as possible under the allowable noise level, especially for telemetry monitoring.
  • heart disease especially myocardial disease, such as myocardial inflammation, ischemia, fibrosis, necrosis and other diseases, it may show changes in low-frequency components such as QRS wave morphology, ST segment morphology, T wave morphology (which can be recognized by the naked eye) ), may also be manifested as increased ventricular late potential, QRS high-frequency ECG and other high-frequency ECG components.
  • ECG low-frequency component analysis adding ECG high-frequency component analysis can effectively improve the sensitivity of clinical cardiomyopathy screening.
  • the characteristics of the high-frequency components of ECG are high frequency (150Hz-250Hz), low amplitude (uV level), and short duration (ms level). Because the high frequency components of ECG are relatively weak and high frequency, they are susceptible to external noise interference Therefore, the requirements for ECG signal acquisition performance are relatively high.
  • the ECG signal sampling unit 30 can adopt a low-power acquisition method that meets the monitoring requirements of low-frequency components of the ECG, such as the above-described low-precision sampling method;
  • high-precision acquisition methods that meet the needs of ECG high-frequency component monitoring are used, such as the above-mentioned high-precision sampling methods (such as sampling rate not less than 1kHz, bandwidth not less than 0-250Hz, and resolution of at least 1 uV/ LSB), this combined with the monitoring of low-frequency and high-frequency components, can assist clinical early warning or guide clinical decision-making or pay attention to changes in disease trends.
  • an embodiment of the present invention also discloses a method for monitoring user vital signs, which includes steps 100 to 120, which will be described in detail below.
  • Step 100 Acquire sensor signals related to vital signs.
  • step 100 acquiring sensor signals related to vital signs includes: acquiring signals output by one or more sensors connected to the user as the sensor signals.
  • the sensor includes one or more of an ECG electrode pad, a blood oxygen probe, a blood pressure sensor, an EEG sensor, a breathing electrode pad, a temperature sensor, and a motion sensor; the sensor signal includes: an ECG signal, One or more of blood oxygen signal, blood pressure signal, electroencephalogram signal, respiratory signal, body temperature signal and exercise signal.
  • Step 110 Sampling the sensor signal to obtain data related to vital signs.
  • step 110 samples the sensor signal to obtain vital sign related data, including: sampling the sensor signal output by one or more sensors, and using the sampled digital signal as the vital sign related data.
  • step 110 sampling the sensor signal includes: sampling the sensor signal according to a preset sampling rate, bandwidth, resolution, and/or number of bits to obtain a digital signal. Therefore, in one embodiment, the manner in which the sensor signal is sampled is adjusted by changing one or more of the sampling rate, bandwidth, resolution, and number of bits.
  • the method of sampling the sensor signal includes a low-precision sampling method and a high-precision sampling method, where the low-precision sampling method is the default sampling method; the sampling rate and bandwidth of the low-precision sampling method are the highest
  • the four of frequency, resolution, and number of bits are not greater than the sampling rate, the highest frequency of the bandwidth, resolution, and number of bits of the high-precision sampling method, respectively, and at least one of them is not equal. Therefore, a low-precision sampling method can be used by default, which can ensure low power consumption, low data storage and low chip computing consumption. When necessary, you can switch to a high-precision sampling method to provide more information.
  • a high-precision sampling method can also be adopted by default.
  • a low-precision sampling circuit can be used to implement the low-precision sampling mode.
  • the low The precision sampling circuit also enables a high-precision sampling circuit, and the sensor signal is sampled by the high-precision sampling circuit to realize a high-precision sampling mode, wherein the sampling rate, the highest frequency of the bandwidth, the resolution, The four digits are not greater than the sampling rate, the highest frequency of the bandwidth, the resolution, and the digits of the high-precision sampling circuit, respectively, and at least one of them is not equal; in another example, the sensor signal is processed into the same two Way, one way is connected to the low-precision sampling circuit, the other way is connected to the high-precision sampling circuit; the low-precision sampling circuit is used to realize the low-precision sampling mode, and when it is necessary to switch to the high-precision sampling mode, the high
  • the low-precision sampling circuit and the high-precision sampling circuit independently and simultaneously sample the sensor signal to achieve a high-precision sampling mode, wherein the low-precision sampling circuit has four sampling rates, the highest frequency of the bandwidth, the resolution, and the number of bits None of them are greater than the sampling rate, the highest frequency of the bandwidth, the resolution, and the number of bits of the high-precision sampling circuit, and at least one of them is not equal.
  • the method of sampling the sensor signal includes a low-precision sampling method and a high-precision sampling method; wherein the low-precision sampling of the sensor signal includes: sampling low-frequency components in the sensor signal to obtain low-frequency data related to vital signs; High-precision sampling of sensor signals includes: sampling low-frequency components and high-frequency components in sensor signals to obtain low-frequency and high-frequency data related to vital signs.
  • the low-precision sampling method for the ECG signal includes: sampling the low-frequency component of the ECG signal to obtain low-frequency data of the ECG; the high-precision sampling method for the ECG signal Including: sampling low-frequency components and high-frequency components in the ECG signal to obtain low-frequency data and high-frequency data of the ECG.
  • the sampling rate is not greater than 1 kHz, and/or the bandwidth is not greater than 0-250 Hz, and/or the resolution is not greater than 1 uV/LSB;
  • the high-precision sampling method of the signal is not less than 1kHz, and/or the bandwidth is not less than 0-250Hz, and/or the resolution is at least 1uV/LSB.
  • Step 120 Adjust the manner in which sensor signals are collected and processed in response to key events.
  • the method for collecting and processing the sensor signal includes: a method for sampling the sensor signal, and/or a method for processing the data obtained after sampling the sensor signal.
  • the key events include one or more of the user's physiological state changes, the user's motion state changes, and the input of related commands for the collection and processing mode adjustment, which will be described in the following cases.
  • the key event is the change of the user's physiological state
  • step 120 also analyzes the data related to the vital signs to determine the change of the user's physiological state.
  • the way of sampling the sensor signal is adjusted to be more accurate than the current High sampling method; in step 120 of an embodiment, when it is determined that the user's physiological state changes from abnormal to normal, the method of sampling the sensor signal is adjusted to a sampling method with lower accuracy than the current, or the data obtained by sampling the sensor signal Then perform variable sampling, and/or filtering, and/or data interception, and/or change the number of bits, etc. to obtain data with lower accuracy than the current one.
  • step 110 the low-frequency components of the ECG signal are sampled to obtain low-frequency data of the electrocardiogram.
  • step 120 when the user's heart state is judged from normal to abnormal according to the low-frequency data of the electrocardiogram, the The low-frequency and high-frequency components of the signal are sampled.
  • Step 110 samples the low-frequency and high-frequency components of the ECG signal to obtain low-frequency and high-frequency data of the ECG, and step 120 determines that the user's heart state changes from abnormal to abnormal according to the low-frequency and/or high-frequency data of the ECG.
  • the low frequency component of the ECG signal is sampled, or the data obtained by sampling the low frequency component and the high frequency component of the ECG is re-sampled, and/or filtered, and/or the data interception, and/or change Digit processing.
  • step 120 also analyzes the vital signs related data to determine the user's movement state.
  • the method of sampling the sensor signal is adjusted to be higher than the current accuracy.
  • Sampling method in one embodiment, step 120, when it is judged that the degree of the user's movement state is slow, then the method of sampling the sensor signal is adjusted to a sampling method with a lower accuracy than the current, or the data obtained by sampling the sensor signal is then sampled again , And/or filtering, and/or data interception, and/or changing the number of bits, etc., to obtain data with lower accuracy than the current one.
  • step 120 analyzes the data related to the vital signs to determine the change in the user's physiological state; and generates a control for inputting relevant instructions for adjusting the collection and processing mode according to the change in the user's physiological state.
  • the control for generating relevant instructions for input collection and processing mode adjustment according to the change of the user's physiological state includes: when it is determined that the user's physiological state changes from normal to abnormal, the generated control includes adjusting the precision
  • the confirmation key of is used to adjust the sampling method of the sensor signal to a sampling method with higher accuracy than the current when receiving the click information of the confirmation key.
  • the generated control when it is determined that the user's physiological state has changed from abnormal to normal, includes a confirmation key with lowered precision, which is used to perform a sensor signal upon receiving click information on the confirmation key.
  • the sampling method is adjusted to a sampling method with lower accuracy than the current one, or the data obtained by sampling the sensor signal is subjected to variable sampling, and/or filtering, and/or data interception, and/or changing the number of bits, etc. Data with low accuracy.
  • step 110 samples the low-frequency components of the ECG signal to obtain low-frequency data of the ECG.
  • step 120 determines that the user's heart state changes from normal to abnormal according to the low-frequency data of the ECG.
  • the generated control includes a high-precision confirmation key for sampling low-frequency components and high-frequency components in the electrocardiogram signal when receiving click information on the confirmation key.
  • step 110 samples the low-frequency and high-frequency components of the ECG signal to obtain low-frequency and high-frequency data of the ECG, and step 120 determines the user's heart state based on the low-frequency and/or high-frequency data of the ECG.
  • the generated control includes a low-precision confirmation key, which is used to sample the low-frequency component of the ECG signal or the low-frequency component of the ECG signal when receiving the click information on the confirmation key
  • the data obtained by sampling with the high-frequency component is then subjected to variable sampling, and/or filtering, and/or data interception, and/or changing the number of bits, etc.
  • step 120 generates related instructions for input collection and processing mode adjustment according to the change of the user's physiological state.
  • step 120 can also generate related instructions for input collection and processing mode adjustment according to the change in the user's movement state
  • the controls are described in detail below.
  • step 120 further includes analyzing the data related to the vital signs to determine the change in the user's movement state; and generating a control for inputting relevant instructions for adjusting the collection and processing mode according to the change in the user's movement state.
  • the control for generating relevant instructions for input collection and processing mode adjustment according to the change of the user's motion state includes: when the degree of judging the user's motion state is intensified, the generated control includes confirmation of adjusting the precision
  • the key is used to adjust the sampling method of the sensor signal to a sampling method with higher accuracy than the current when receiving the click information on the confirmation key.
  • the generated control when the degree of the user's movement state is judged to be slow, includes a confirmation key with reduced accuracy, which is used to sample the sensor signal when receiving click information on the confirmation key
  • the method is adjusted to a sampling method lower than the current accuracy, or the data obtained by sampling the sensor is then subjected to variable sampling, and/or filtering, and/or data interception, and/or changing the number of bits, etc. to obtain a lower accuracy than the current data.
  • the method of monitoring the vital signs of the user may also provide an input unit for inputting and adjusting related instructions of the collection and processing mode—such as a keyboard, a mouse, and a touch screen, etc., for receiving and processing
  • an input unit for inputting and adjusting related instructions of the collection and processing mode—such as a keyboard, a mouse, and a touch screen, etc., for receiving and processing
  • the relevant instruction of mode adjustment is adopted, the way of collecting and processing the sensor signal is adjusted to the corresponding mode of collection and processing.
  • step 120 adjusts the sampling method of the sensor signal to a sampling method with higher accuracy than the current one, including: one or more of increasing the sampling rate, increasing the bandwidth, increasing the resolution, and increasing the number of bits; and /Or, adjust the sampling method of the sensor signal to a sampling method with lower accuracy than the current one, including: one or more of reducing the sampling rate, reducing the bandwidth, reducing the resolution, and reducing the number of digits.
  • step 120 adjusts the sampling method of the sensor signal to a sampling method with higher accuracy than the current one, at least including increasing the bandwidth to achieve sampling of low-frequency components and high-frequency components in the sensor signal; and/or, Step 120 adjusts the sampling method of the sensor signal to a sampling method with lower accuracy than the current one, at least including reducing the bandwidth to only sample the low-frequency components in the sensor signal; in other words, step 120 will sample the sensor signal
  • the method is adjusted to a higher accuracy sampling method, including: sampling low-frequency components and high-frequency components in the sensor signal to obtain low-frequency data and high-frequency data related to vital signs; adjusting the method of sampling the sensor signal to Sampling methods with lower accuracy than current include: sampling low-frequency components in sensor signals to obtain low-frequency data related to vital signs.
  • step 120 adjusts the sensor signal sampling method to a sampling method with higher accuracy than the current one. That is, the method of sampling the sensor signal is switched from the low-precision sampling method to the high-precision sampling method; step 120 adjusts the sampling method of the sensor signal to a sampling method with lower accuracy than the current, that is, the method of collecting the sensor signal Switch from high-precision sampling to low-precision sampling.
  • the method for monitoring the vital signs of a user in an embodiment further includes step 130, analyzing data related to vital signs to determine whether an alarm of abnormal physiological state of the user is issued.
  • step 130 analyzes to determine whether the user's physiological state is abnormal. , An alarm is issued.
  • step 130 of an embodiment analyzes the high frequency data related to vital signs to determine whether the user's physiological state is abnormal; when the analysis result of the high frequency data related to vital signs indicates that the user's physiological state is abnormal, an alarm is issued.
  • the low-frequency data and high-frequency data related to vital signs are analyzed to determine whether the user's physiological state is abnormal; only when the analysis results of the high-frequency data related to vital signs and the low-frequency data both indicate the user's physiological state If it is abnormal, the alarm will be issued.
  • the method for monitoring user vital signs further includes step 140, displaying data related to the vital signs.
  • step 140 displays a graph of the data related to vital signs, and/or displays the results of analyzing the data related to vital signs.
  • the step 140 displays a graph of vital sign-related data, which may be a trend waveform that displays vital sign-related data in real time, or may only display a few historical typical moment waveforms.
  • step 140 after step 120 adjusts the sampling method of the sensor signal to a sampling method with higher accuracy than the current accuracy—for example, after adjusting from a low-precision sampling method to a high-precision sampling method, step 140 only displays the mid-to-high frequency of the sensor signal.
  • the method for monitoring vital signs in an embodiment includes steps 200 to 220, which will be described in detail below.
  • Step 200 Obtain an ECG signal.
  • the step 200 of acquiring the electrocardiographic signal includes: acquiring a signal output from an electrocardiographic sensor connected to the user as the electrocardiographic signal.
  • the ECG sensor includes an ECG electrode pad.
  • Step 210 Sampling the ECG signal to obtain ECG data.
  • step 210 samples the ECG signal to obtain ECG data, which includes: sampling the ECG signal output from the ECG sensor, and using the sampled digital signal as the ECG data. The following describes in detail the sampling of the ECG signal output by the ECG sensor in step 210.
  • step 210 sampling the signal output by the ECG sensor includes: sampling the signal output by the ECG sensor according to a preset sampling rate, bandwidth, resolution, and/or number of bits to obtain a digital signal. Therefore, in one embodiment, by changing one or more of the sampling rate, bandwidth, resolution, and number of bits, the manner of sampling the signal output by the electrocardiographic sensor is adjusted.
  • the method for sampling the signal output by the ECG sensor includes a low-precision sampling method and a high-precision sampling method, where the low-precision sampling method is the default sampling method; the sampling rate of the low-precision sampling method , The highest frequency of the bandwidth, the resolution, and the number of bits are not greater than the sampling rate of the high-precision sampling method, the highest frequency of the bandwidth, the resolution, and the number of bits, and at least one of them is not equal. Therefore, a low-precision sampling method can be adopted by default, which can ensure low power consumption and low chip computing consumption, and can be switched to a high-precision sampling method to provide more information when necessary.
  • a low-precision sampling circuit can be used to implement the low-precision sampling mode.
  • the low The precision sampling circuit also enables a high-precision sampling circuit, and the sensor signal is sampled by the high-precision sampling circuit to realize a high-precision sampling mode, wherein the sampling rate, the highest frequency of the bandwidth, the resolution, The four digits are not greater than the sampling rate, the highest frequency of the bandwidth, the resolution, and the number of digits of the high-precision sampling circuit, respectively, and at least one of them is not equal; for example, the signals output by the ECG sensor are processed into the same Two channels, one is connected to the low-precision sampling circuit and the other is connected to the high-precision sampling circuit; the low-precision sampling circuit is used to realize the low-precision sampling mode.
  • the high-precision sampling circuit When the high-precision sampling mode needs to be switched, the high-precision sampling circuit is also enabled.
  • the low-precision sampling circuit and the high-precision sampling circuit independently and simultaneously sample the ECG sensor signal to achieve a high-precision sampling method, wherein the low-precision sampling circuit has a sampling rate, a maximum frequency of the bandwidth, a resolution, and a bit
  • the four of these numbers are not greater than the sampling rate, the highest frequency of the bandwidth, the resolution, and the number of bits of the high-precision sampling circuit, respectively, and at least one of them is not equal.
  • the method for sampling the signal output by the ECG sensor includes a low-precision sampling method and a high-precision sampling method; wherein the low-precision sampling for the signal output by the ECG sensor includes: low-frequency components in the signal output by the ECG sensor Sampling to obtain low-frequency data of ECG; high-precision sampling of the signal output by the ECG sensor includes: sampling low-frequency components and high-frequency components of the signal output by the ECG sensor to obtain low-frequency data and high-frequency data of the ECG Frequency data.
  • the sampling rate is not greater than 1 kHz, and/or the bandwidth is not greater than 0-250 Hz, and/or the resolution is not greater than 1 uV/LSB;
  • the high-precision sampling method of the signal is not less than 1kHz, and/or the bandwidth is not less than 0-250Hz, and/or the resolution is at least 1uV/LSB.
  • Step 220 Adjust the manner in which ECG signals are collected and processed in response to key events.
  • the method for collecting and processing the ECG signal includes: a method for sampling the ECG signal, and/or a method for processing the data obtained after sampling the ECG signal.
  • the key event includes one or more of the input of related instructions for the user's heart state change and the collection and processing mode adjustment.
  • the key event is the change of the user's physiological state
  • step 220 also analyzes the ECG data to determine the user's heart state; for example, step 210 samples the low-frequency components of the signal output by the ECG sensor to obtain low-frequency ECG data.
  • Step 220 is According to the low-frequency data of the electrocardiogram to determine that the user's heart state has changed from normal to abnormal, the low-frequency component and the high-frequency component of the signal output by the electrocardiographic sensor are sampled; for example, step 210 compares the low-frequency component and the signal of the signal output by the electrocardiographic sensor High frequency components are sampled to obtain low-frequency data and high-frequency data of the ECG.
  • Step 220 When it is judged from the low-frequency data and/or high-frequency data of the ECG that the user's heart state changes from abnormal to normal, the signal output from the ECG sensor Sampling mid-low frequency components, or sampling the low-frequency components and high-frequency components of the signal output by the ECG sensor, and then performing variable sampling, and/or filtering, and/or data interception, and/or changing the number of bits, etc. deal with.
  • step 220 analyzes the electrocardiographic data to determine the user's heart state change; according to the user's heart state change, a control for generating relevant commands for input collection and processing mode adjustment is generated. Specifically, in an embodiment, step 210 samples the low-frequency components of the signal output by the electrocardiogram sensor to obtain low-frequency data of the electrocardiogram. Step 220 generates the low-frequency data of the electrocardiogram according to the low-frequency data of the electrocardiogram to determine that the user's heart state changes from normal to abnormal.
  • Controls include a high-precision confirmation key for sampling low-frequency components and high-frequency components in the signal output by the ECG sensor when receiving click information on the confirmation key; step 210 in one embodiment The low-frequency components and high-frequency components of the signal output by the sensor are sampled to obtain low-frequency data and high-frequency data of the ECG, and step 220 determines that the user's heart state changes from abnormal to normal according to the low-frequency data and/or high-frequency data of the ECG.
  • the generated control includes a confirmation key with lowered precision, which is used to sample the low-frequency component of the signal output from the electrocardiographic sensor when receiving the click information on the confirmation key, or the low-frequency component of the signal output from the electrocardiographic sensor.
  • the data obtained by sampling the components and high-frequency components are then subjected to variable sampling, and/or filtering, and/or data interception, and/or changing the number of bits, etc.
  • the method of monitoring the vital signs of the user may also provide an input unit for inputting and adjusting related instructions of the collection and processing mode—such as a keyboard, a mouse, and a touch screen, etc., for receiving and processing
  • an input unit for inputting and adjusting related instructions of the collection and processing mode—such as a keyboard, a mouse, and a touch screen, etc., for receiving and processing
  • the mode adjustment is relevant, the method of collecting and processing the signal output by the ECG sensor is adjusted to the corresponding method of collection and processing.
  • step 220 adjusts the sampling method of the signal output by the ECG sensor to a sampling method with higher accuracy than the current one, including: one or more of increasing the sampling rate, increasing the bandwidth, increasing the resolution, and increasing the number of digits And/or, adjust the sampling method of the signal output by the ECG sensor to a sampling method with lower accuracy than the current, including: one or more of reducing the sampling rate, reducing the bandwidth, reducing the resolution, and reducing the number of digits By.
  • step 220 adjusts the sampling method of the signal output by the ECG sensor to a sampling method with higher accuracy than the current one, at least including increasing the bandwidth to achieve sampling of the low-frequency component and the high-frequency component of the ECG signal ; And/or, step 220 adjusts the sampling method of the signal output by the ECG sensor to a sampling method with lower accuracy than the current one, at least including reducing the bandwidth to only sample the low-frequency components of the ECG signal; in other words
  • step 220 adjusts the sampling method of the signal output by the ECG sensor to a sampling method with higher accuracy than the current one-for example
  • the above-described high-precision sampling method includes: sampling low-frequency components and high-frequency components in the ECG signal , To obtain low-frequency data and high-frequency data of ECG; adjust the sampling method of ECG signal to a sampling method with lower accuracy than the current-for example, the above-mentioned low-precision sampling method includes: Perform sampling to obtain low-frequency data of ECG.
  • the method for monitoring the vital signs of the user in an embodiment further includes step 230, which analyzes the electrocardiographic data to determine whether to alert the user of abnormal physiological status.
  • step 230 performs analysis to determine the user's heart state. For example, when step 210 samples the low-frequency component and the high-frequency component of the signal output by the ECG sensor, step 230 analyzes the sampled data to determine whether the user's heart state is abnormal. alarm.
  • step 230 analyzes the high-frequency data of the electrocardiogram to determine whether the user's heart state is abnormal; when the analysis result of the high-frequency data of the electrocardiogram indicates that the user's heart state is abnormal, an alarm is issued; or, an implementation
  • step 230 analyzes the low-frequency data and high-frequency data of the ECG to determine whether the user's heart state is abnormal; only when the analysis results of the high-frequency data and the low-frequency data of the ECG indicate that the user's physiological state is abnormal, it is issued alarm.
  • the method for monitoring user vital signs further includes step 240 of displaying electrocardiographic data.
  • displaying ECG data in step 240 includes displaying a graph of the ECG data, and/or displaying the results of analyzing the ECG data.
  • the step 240 displays the graph of the ECG data, which may be a trend waveform that displays the ECG data in real time, or it may display only a few historical typical time waveforms.
  • step 240 when step 220 samples the low-frequency component and the high-frequency component of the signal output by the ECG sensor, step 240 only displays the data obtained by sampling the high-frequency component of the signal output by the ECG sensor, or displays it synchronously and separately Data obtained by sampling high-frequency components and low-frequency components in the signal output by the ECG sensor.
  • These computer program instructions can be loaded onto a general purpose computer, special purpose computer, or other programmable data processing equipment to form a machine, so that these instructions executed on a computer or other programmable data processing device can generate a device that implements a specified function.
  • These computer program instructions can also be stored in a computer-readable memory, which can instruct the computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory can form a piece Manufactured products, including implementation devices that implement specified functions.
  • Computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operating steps are performed on the computer or other programmable device to produce a computer-implemented process that allows the computer or other programmable device to execute Instructions can provide steps for implementing specified functions.

Landscapes

  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • General Health & Medical Sciences (AREA)
  • Public Health (AREA)
  • Veterinary Medicine (AREA)
  • Animal Behavior & Ethology (AREA)
  • Surgery (AREA)
  • Physics & Mathematics (AREA)
  • Molecular Biology (AREA)
  • Biophysics (AREA)
  • Pathology (AREA)
  • Biomedical Technology (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Medical Informatics (AREA)
  • Cardiology (AREA)
  • Physiology (AREA)
  • Signal Processing (AREA)
  • Psychiatry (AREA)
  • Power Engineering (AREA)
  • Artificial Intelligence (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Measurement And Recording Of Electrical Phenomena And Electrical Characteristics Of The Living Body (AREA)
  • Measuring And Recording Apparatus For Diagnosis (AREA)

Abstract

一种监测用户生命体征的方法和装置，包括：获取生命体征相关的传感器信号；对所述传感器信号进行采样，得到生命体征相关的数据；响应于关键事件调整对传感器信号进行采集及处理的方式。

Description

一种监测用户生命体征的方法和装置 技术领域
本发明涉及一种监测用户生命体征的方法和装置。
 背景技术
现有监测用户体征的装置例如监护仪，其生理信号采集方式一般采用固定的信号采样率、分辨率、带宽和位数对病人的生理信号进行采集。这是有原因的：在常规监护应用中，如遥测监护场景，病人需要随身携带遥测监护仪，在这种情况下要求长时间连续监测病人心电等生理参数，因此对监护仪功耗的要求较高，而常规监护应用中一般只关注心率和心律失常等基本监护信息，对生理信号采集精度的要求并不高，即在权衡功耗、噪声、数据存储量和芯片计算能力的情况下，一般在监护需求可允许的噪声水平内，会最大程度地降低功耗、数据存储量和芯片计算消耗，因此监护仪大多采用固定的且较低的信号采样率、分辨率、带宽和位数进行采集，一方面保证低功耗、低数据存储量和低芯片计算消耗，另一方面又可以满足常规监护的信号精度需求。
但上述低功耗的采集方式不适用于生理信号细节分析， 因为其采集的精度比较低；但是对于遥测监护来说，如果采用固定的较高的信号采样率、分辨率、带宽和位数，虽然这种长时间持续采集高精度的生理信号可以用于细节分析，又会给监护仪造成很大的功耗、过大的数据存储量和更高的芯片计算力消耗，不适用于临床长时间实时监护应用。
 技术问题
考虑到上述问题，本发明主要提供一种监测用户生命体征的方法和装置。
 技术解决方案
根据第一方面，一种实施例中提供一种监测用户生命体征的方法，包括：
获取生命体征相关的传感器信号；
对所述传感器信号进行采样，得到生命体征相关的数据；
响应于关键事件调整对传感器信号进行采集及处理的方式。
一实施例中对传感器信号进行采集及处理的方式包括：对传感器信号进行采样的方式，和/或，对传感器信号进行采样后得到的数据再进行处理的方式。
根据第二方面，一种实施例中提供一种监测用户生命体征的方法，包括：
获取心电信号；
对所述心电信号进行采样，得到心电数据；
响应于关键事件调整对心电信号进行采集及处理的方式。
一实施例中对心电信号进行采集及处理的方式包括：对心电信号进行采样的方式，和/或，对心电信号进行采样后得到的数据再进行处理的方式。
根据第三方面，一种实施例中提供一种监测用户生命体征的装置，包括：
至少一个传感器，连接于用户以输出生命体征相关的传感器信号；
信号采集电路，用于对所述传感器信号进行采样，得到生命体征相关的数据；
处理器，用于响应于关键事件调整所述信号采集电路对传感器信号进行采集及处理的方式。
一实施例中所述处理器调整所述信号采集电路对传感器信号进行采集及处理的方式包括：调整所述信号采集电路对传感器信号进行采样的方式，和/或，对传感器信号进行采样后得到的数据再进行处理的方式。
根据第四方面，一种实施例中提供一种监测用户生命体征的装置，包括：
心电传感器，用于连接于用户以输出心电信号；
信号采集电路，用于对所述心电信号进行采样，得到心电数据；
处理器，用于响应于关键事件调整所述信号采集电路对心电信号进行采集及处理的方式。
一实施例中所述处理器调整所述信号采集电路对心电信号进行采集及处理的方式包括：调整所述信号采集电路对心电信号进行采样的方式，和/或，对心电信号进行采样后得到的数据再进行处理的方式。
根据第五方面，一种实施例中提供一种计算机可读存储介质，包括程序，所述程序能够被处理器执行以实现本文中任一实施例中所述的方法。
 有益效果
依据上述实施例的监测用户生命体征的方法、装置和计算机可读存储介质，通过响应关键事件，来动态改变对传感器信号例如心电信号等进行采集及处理的方式，例如包括对心电信号等进行采样和采样后数据处理的方式，能够实现不同功耗、不同运算量、不同数据量、不同采样率、不同分辨率、不同带宽、不同位数等一种或者多种模式的切换。
 附图说明
图1为一种实施例的监测用户生命体征的装置的一种结构示意图；
图2为一种实施例的监测用户生命体征的装置的另一种结构示意图；
图3为一种院内使用的监护仪联网系统的结构示意图；
图4为一种实施例的监测用户生命体征的装置的又两种一种结构示意图；
图5为一种实施例的监测用户生命体征的装置的工作原理说明图；
图6为一种实施例的监测用户生命体征的装置的又一种结构示意图；
图7为另一种实施例的监测用户生命体征的装置的一种结构示意图；
图8为另一种实施例的监测用户生命体征的装置的另两种一种结构示意图；
图9为另一种实施例的监测用户生命体征的装置的又一种结构示意图；
图10为一种实施例的监测用户生命体征的方法的一种流程图；
图11为一种实施例的监测用户生命体征的方法的另一种流程图；
图12为一种实施例的监测用户生命体征的方法的又一种流程图；
图13为另一种实施例的监测用户生命体征的方法的一种流程图；
图14为另一种实施例的监测用户生命体征的方法的另一种流程图；
图15为另一种实施例的监测用户生命体征的方法的又一种流程图。
 本发明的最佳实施方式
在此处键入本发明的最佳实施方式描述段落。
 本发明的实施方式
具体实施方式
下面通过具体实施方式结合附图对本发明作进一步详细说明。其中不同实施方式中类似元件采用了相关联的类似的元件标号。在以下的实施方式中，很多细节描述是为了使得本申请能被更好的理解。然而，本领域技术人员可以毫不费力的认识到，其中部分特征在不同情况下是可以省略的，或者可以由其他元件、材料、方法所替代。在某些情况下，本申请相关的一些操作并没有在说明书中显示或者描述，这是为了避免本申请的核心部分被过多的描述所淹没，而对于本领域技术人员而言，详细描述这些相关操作并不是必要的，他们根据说明书中的描述以及本领域的一般技术知识即可完整了解相关操作。
另外，说明书中所描述的特点、操作或者特征可以以任意适当的方式结合形成各种实施方式。同时，方法描述中的各步骤或者动作也可以按照本领域技术人员所能显而易见的方式进行顺序调换或调整。因此，说明书和附图中的各种顺序只是为了清楚描述某一个实施例，并不意味着是必须的顺序，除非另有说明其中某个顺序是必须遵循的。
本文中为部件所编序号本身，例如“第一”、“第二”等，仅用于区分所描述的对象，不具有任何顺序或技术含义。而本申请所说“连接”、“联接”，如无特别说明，均包括直接和间接连接（联接）。
在常规监护应用中，如遥测监护，为了权衡功耗、噪声、数据存储量和芯片计算能力的要求，在满足临床常规监护需求与算法要求的基础上，一般采用固定不变的较低的信号采样率/分辨率/带宽/位数进行生理信号采集。但随着监护应用的智能化高端化发展，常规基础监护给用户提供的病人状态信息量有限，已经无法满足临床高端监护需求，在一些特殊场景下，用户需要监护仪提供更细节化的病人生理状态分析情况去辅助临床决策，比如心电诊断分析和心电高频成分分析等。具体地，在一些特殊场景下，如果要提供可辅助病人生理状态判断的细节化分析功能，如心室晚电位、高频心电等可用于心肌缺血的辅助决策的技术，那么就需尽可能地保留病人的生理信息，才有可能进行更细节化的分析应用；但是这些技术依赖于更高的信号采样率/分辨率/带宽/位数；而对于遥测监护来说，如果采用固定的较高的信号采样率/分辨率/带宽/位数，长时间持续采集高精度的生理信号用于细节分析，又会给监护仪造成更大的功耗、更大的数据存储量和更高的芯片计算力消耗，不适用于临床长时间实时监护应用。
综上所述，当病人生理状态发生变化，需要更高的信号采样率/分辨率/带宽/位数进行细节分析时，一方面常规基础监护应用的生理信号采集精度已经无法满足更细节化的病人生理状态分析需求，需要提升数据采集端的生理信号采集精度才有应用价值，但另一方面如果数据采集端直接采用固定不变的高信号采样率/分辨率/带宽/位数的采集方式又会给监护仪带来较高的功耗、数据存储量和芯片计算消耗，不适用于临床长时间实时监护应用。因此为了满足不同临床监护场景下的监护数据精度需求，本发明设计一种动态改变生理信号采集及处理方式的技术方案，例如可以自动、半自动或手动地动态调整生理信号采集及处理方式，包括动态改变信号采样率、信号分辨率、信号带宽和/或信号位数，根据临床细节分析的应用需求，实现不同功耗、不同运算量、不同数据量、不同采样率、不同分辨率、不同带宽、不同位数等一种或者多种模式的切换。
请参照图1，一实施例提供一种监测用户生命体征的装置，该装置包括至少一个传感器10、信号采集电路30和处理器50，下面具体说明。
传感器10用于连接于用户以获取并输出生命体征相关的传感器信号。例如一实施例中传感器10可以包括心电电极片、血氧探头、血压传感器、脑电传感器、呼吸电极片、温度传感器和运动传感器的一者或多者，相应地，传感器信号包括心电信号、血氧信号、血压信号、脑电信号、呼吸信号、体温信号和运动信号中的一者或多者；换句说话，心电电极片用于连接用户以获取并输出心电信号，血氧探头用于连接用户以获取并输出血氧信号，血压传感器用于连接用户以获取并输出血压信号，脑电传感器用于连接用户以获取并输出脑电信号，呼吸电极片用于连接用户以获取并输出呼吸信号，温度传感器用于连接用户以获取并输出体温信号，运动传感器用于连接用户以获取并输出运动信号。上述传感器信号是从病人处直接获取的前端信号，其可以是模拟信号，也可以是数字信号。
信号采集电路30用于对传感器信号进行采样，得到生命体征相关的数据。一实施例中信号采集电路30对传感器信号进行采样，将采样得到的数字信号作为所述生命体征相关的数据。一实施例中信号采集电路30根据预设的采样率、带宽、分辨率和/或位数对传感器信号进行采样，得到数字信号。本领域技术人员可以理解，采样率也称为采样速度或者采样频率，其定义了每秒从信号中提取并组成离散信号的采样个数；信号采集电路30的带宽指的是其采样的带宽，即可以采集的信号的频率范围，例如信号采样电路30的带宽为0Hz到350Hz，则说明信号采样电路30可以采集0Hz到350Hz的信号；信号采集电路30的分辨率被定义为输入信号值的最小变化，即能够分辨量化的最小信号的能力；信号采集电路30的位数也称为数据宽度或数据位宽，其定义了输入信号值的动态范围，即能够量化的最大信号范围。一实施例中信号采集电路30还可以对传感器进行采样得到的数据再进行处理，例如信号采集电路30先对传感器信号进行采样得到数据，然后再对该数据进行处理，包括对该数据进行变采样，和/或滤波，和/或数据截取，和/或改变位数等处理。
本申请中通过动态地改变信号采集电路30对传感器信号进行采样的方式，来解决低功耗、低数据存储量、低芯片计算能力和高精度采样的矛盾。例如，一实施例中处理器50可以通过改变信号采集电路30的采样率、带宽、分辨率和位数中的一者或多者来调整信号采集电路30对传感器信号进行采样的方式。例如，一实施例中处理器50还可以通过改变信号采集电路30对其采样得到的数据进行处理的方式，比如进行变采样，和/或滤波，和/或数据截取，和/或改变位数等处理来改变采集数据的采样率、和/或带宽，和/或分辨率，和/或位数等，使得处理器50再分析处理过的数据时可以不需要太高的数据存储，和/或芯片计算能力。
结合图1，参见图2所示，本申请提供一种监测用户生命体征的装置的系统框架图。监测用户生命体征的装置至少包括参数测量电路1112。参数测量电路1112至少包括一个生理参数对应的参数测量电路1112，参数测量电路1112至少包含心电信号参数测量电路、呼吸参数测量电路、体温参数测量电路、血氧参数测量电路、无创血压参数测量电路、有创血压参数测量电路等等中的至少一个参数测量电路，每个参数测量电路1112分别通过相应的传感器接口与外部插入的传感器附件1111连接。传感器附件1111包括用于心电呼吸、血氧、血压、体温等生理参数检测所对应的传感器10。参数测量电路1112主要是用来连接传感器附件1111以获得采集的生理参数信号的，可以包括至少两种以上生理参数的测量电路，参数测量电路1112可以是但不局限于生理参数测量电路(模块)，人体生理参数测量电路(模块)或传感器采集人体生理参数等。具体的，参数测量电路1112通过扩展接口连接外部生理参数传感器获得有关病人的生理采样信号，并经过处理后得到生理数据，用以报警和显示。扩展接口还可用于将主控电路输出的关于如何采集生理参数的控制信号通过相应接口输出至外部生理参数监测附件，实现对病人生理参数的监测控制。
本申请的监测用户生命体征的装置还可以包括主控电路1113，主控电路1113需要包括至少一个处理器50和至少一个存储器，当然，主控电路1113还可以包括电源管理模块、电源IP模块和接口转换电路等中的至少之一。电源管理模块用于控制整机开关机、板卡内部各电源预上电时序和电池充放电等。电源IP模块是指把经常重复调用的电源电路单元的原理图和PCB版图相关联，固化成单独的电源模块，即，将一输入电压通过预定的电路转换为一输出电压，其中，输入电压和输出电压不同。例如，将15V的电压转换为1.8V、3.3V或3.8V等。可以理解的是，电源IP模块可以是单路的，还可以是多路的。当电源IP模块为单路时，电源IP模块可以将一个输入电压转换为一个输出电压。当电源IP模块为多路时，电源IP模块可以将一个输入电压转换为多个输出电压，且多个输出电压的电压值可以相同，也可以不相同，从而能够同时满足多个电子元件的不同电压需求，并且模块对外接口少，在系统中工作呈黑盒与外界硬件系统解耦，提高了整个电源系统的可靠性。接口转换电路用于将主控最小系统模块（即主控电路中的至少一个处理器和至少一个存储器）输出的信号，转换为实际外部设备所要求接收的输入标准信号，例如，支持外接VGA显示功能，是将主控CPU输出的RGB数字信号转换为VGA模拟信号，支持对外网络功能，是将RMII信号转换为标准的网络差分信号。
此外，监测用户生命体征的装置还可以包括报警电路1116、输入接口电路1117、对外通讯和电源接口1115中的一个或多个。主控电路1113用于协调、控制多参数监护仪或模块组件中的各板卡、各电路和设备。在本实施例中，主控电路1113用于控制参数测量电路1112和通讯接口电路之间的数据交互、以及控制信号的传输，并将生理数据输送到显示器1114上进行显示，也可以接收来自触摸屏或者键盘、按键等物理输入接口电路输入的用户控制指令，当然还可以输出的关于如何采集生理参数的控制信号。报警电路1116可以是声光报警电路。主控电路1113完成生理参数的计算，并通过对外通讯和电源接口1115可将参数的计算结果和波形发送到主机（如带显示器的主机、PC机、中央站等等），对外通讯和电源接口115可以是以太网（Ethernet）、令牌环（Token Ring）、令牌总线(Token Bus)以及作为这三种网的骨干网光纤分布数据接口（FDDI）构成的局域网接口中的一个或其组合，还可以是红外、蓝牙、wifi、WMTS通讯等无线接口中的一个或其组合，或者还可以是RS232、USB等有线数据连接接口中的一个或其组合。对外通讯和电源接口115也可以是无线数据传输接口和有线数据传输接口中的一种或两种的组合。主机可以是监护仪的主机、心电图机，超声诊断仪，计算机等任何一个计算机设备，安装配合的软件， 就能够组成一个监护设备。主机还可以是通讯设备，例如手机，多参数监护仪或模块组件通过蓝牙接口将数据发送到支持蓝牙通讯的手机上，实现数据的远程传输。
监测用户生命体征的装置可以设置在监护仪外壳之外，作为独立的外插参数模块，可以通过插入到监护仪的主机（包含主控板）形成插件式监护仪，作为监护仪的一部分，或者也可以通过电缆与监护仪的主机（包含主控板）连接，外插参数模块作为监护仪外置的一个配件。当然，参数处理还可以内置于外壳之内，与主控模块集成，或物理分离设置在外壳之内，形成集成监护仪。
如图3所示，提供一种院内使用的监护仪联网系统，利用该系统可以将监护仪的数据进行整体保存，集中管理病人信息和看护信息，两者进行关联存储，便于进行历史数据的保存和关联报警。如图3所示的系统，在本申请的一优选实施例中，针对病床均可以提供一个床边监护仪1212，该床边监护仪1212可以是前述监测用户生命体征的装置。另外，每个床边监护仪1212还可以与一个便携式监护设备1213进行配对传输，便携式监护设备1213提供简便、可携带的多参数监护仪或模块组件，可是穿戴在病人身体上对应病人进行移动式监护，通过便携式监护设备1213与床边监护仪1212进行有线或无线通讯后可以将移动式监护产生的生理数据传输到床边监护仪1212上进行显示，或通过床边监护仪1212传输到中央站1211供医生或护士查看，或通过床边监护仪1212传输到数据服务器1215进行存储。另外，便携式监护设备1213还可以直接通过设置在院内的无线网络节点1214将移动式监护产生的生理数据传输到中央站1211进行存储和显示，或者通过设置在院内的无线网络节点214将移动式监护产生的生理数据传输到数据服务器1215进行存储。结合图2，参见图3可见，床边监护仪1212上显示的生理参数对应的数据可以是源自直接连接到监护仪上的传感器附件1111，或者源自便携式监护设备1213，或者源自数据服务器。
下面对信号采样电路30的采样方式进行一个详细的说明。
一实施例中信号采集电路30对传感器信号进行采样的方式包括低精度采样方式和高精度采样方式，其中低精度采样方式可以为默认的采样方式，当然也可以将高精度采样方式设置为默认的采样方式。低精度采样方式的采样率、带宽的最高频、分辨率、位数这四者都分别不大于高精度采样的方式的采样率、带宽的最高频、分辨率、位数，且至少有一者不相等。例如高精度采样方式的采样率可以大于低精度的采样率；例如高精度采样方式的分辨率可以大于低精度的分辨率，即高精度采样方式能够分辨量化的最小信号的能力大于低精度采样方式能够分辨量化的最小信号的能力；例如高精度采样方式的数据位数可以大于低精度的数据位数，即高精度采样方式能够量化的最大信号动态范围大于低精度采样方式能够量化的最大信号动态范围；例如高精度采样方式的带宽的最高频可以大于低精度的带宽的最高频，可以理解地，此时高精度采样方式的带宽可以包含低精度的带宽，或者仅部分重叠，或者完全不重叠，例如一个例子中高精度采样的带宽为0至350Hz，低精度采样的带宽为0至150Hz；例如一个例子中高精度采样的带宽为100至350Hz，低精度采样的带宽为0至150Hz；例如一个例子中高精度采样的带宽为150至350Hz，低精度采样的带宽为0至150Hz。一实施例中信号采集电路30实现高精度采样方式和低精度采样方式可以有多种方案。
例如请参照图4（a），一实施例中信号采集电路30可以包括分别与传感器10连接的低精度采样电路31和高精度采样电路33，低精度采样电路31的采样率、带宽的最高频、分辨率、位数这四者都分别不大于高精度采样电路33的采样率、带宽的最高频、分辨率、位数，且至少有一者不相等。低精度采样方式下，信号采集电路30中只有低精度采样电路31被启用来对传感器信号进行采样；而在高精度采样方式下，信号采样电路中只有高精度采样电路33来对传感器信号进行采样。
再例如请参照图4（b），信号采样电路30包括第一处理电路35、低精度采样电路31和高精度采样电路33。第一处理电路35用于将传感器信号处理成相同的两路信号，一路信号用于输入到低精度采样电路31，另一路信号用于输入到高精度采样电路33；所述低精度采样电路31的采样率、带宽的最高频、分辨率、位数这四者都分别不大于高精度采样电路33的采样率、带宽的最高频、分辨率、位数，且至少有一者不相等；所述处理器50通过开启和关闭所述低精度采样电路31和高精度采样电路33来调整对传感器信号进行采样的方式，在所述低精度采样方式下，处理器50控制开启低精度采样电路31和关闭高精度采样电路33，在所述高精度采样方式下，所述处理器50控制开启低精度采样电路31和高精度采样电路33。
一实施例中信号采集电路30对传感器信号进行采样的方式包括低精度采样方式和高精度采样方式；其中对于传感器信号的低精度采样包括：对传感器信号中低频成分进行采样，以得到生命体征相关的低频数据；对于传感器信号的高精度采样包括：对传感器信号中低频成分和高频成分进行采样，以得到生命体征相关的低频数据和高频数据。换句说话，在这种情况下信号采集电路30的低精度采样方式的带宽为预设的低频带宽，而高精度采样方式的带宽不仅包括上述预设的低频带宽，还额外包括预设的高频带宽。例如，以传感器信号包括心电信号为例，信号采集电路30对于心电信号的低精度采样方式包括：对心电信号中低频成分进行采样，以得到心电的低频数据；信号采集电路30对于心电信号的高精度采样方式包括：对心电信号中低频成分和高频成分进行采样，以得到心电的低频数据和高频数据。一实施例中信号采集电路30对于心电信号的低精度采样方式，其采样率不大于1kHz，和/或带宽不大于0-250Hz，和/或分辨率不高于1uV/LSB；和/或，信号采集电路30对心电信号的高精度采样方式，其采样率不小于1kHz，和/或带宽不小于0-250Hz，和/或分辨率至少1uV/LSB。
上面是对信号采集电路30进行采样的方式的一些说明。下面对处理器50如何调整信号采集电路30对传感器信号进行采集及处理的方式进行说明。
一实施例中处理器50响应于关键事件调整信号采样电路30对传感器信号进行采样的方式。一实施例中关键事件包括用户生理状态发生变化、用户运动状态发生变化和采样及处理方式调整的相关指令的输入中的一者或多者，下面分别说明。
（一）关键事件为用户生理状态发生变化
一实施例中处理器50还用于对所述生命体征相关的数据进行分析，以判断用户生理状态变化，例如判断用户生理状态是正常还是异常。需要说明的是，处理器50可以根据实时、短时或长时的生命体征相关的数据来判断用户生理状态变化。
不妨以心电信号为例，处理器50可以通过对由心电信号进行采样得到的心电数据进行分析，得到心率、心律、P波形态、QRS形态和/或ST-T形态等心电指标，可以根据这些心电指标中的一者或多者来判断用户生理状态是正常还是异常，例如当判断用户的心率过快或过慢时，则判断用户生理状态变为异常；例如当判断用户心律失常时，则判断用户生理状态变为异常；例如当判断用户P波形态与正常P波形态相差较大时，则判断用户生理状态变为异常；例如当判断用户QRS形态与正常QRS形态相差较大时——比如QRS波形态异常或其宽度异常，则判断用户生理状态变为异常；例如当判断用户ST-T形态与正常ST-T形态相差较大时——比如ST段压低或T波倒置等，则判断用户生理状态变为异常。不妨再以血氧信号为例，处理器50可以对由血氧信号采样得到的血氧数据进行分析，得到血氧饱和度和/或灌注指数等血氧指标，根据这些血氧指标中一者或多者就可以判断用户的生理状态是正常还是异常。血压信号也是类似地，处理器50可以对由血压信号采样得到的血压数据进行分析，得到收缩压、舒张压和平均压等血压指标，根据这些血压指标中一者多者就可以判断用户的生理状态是正常还是异常。呼吸信号也是类似地，处理器50可以对由呼吸信号采样得到呼吸数据进行分析，得到呼吸率等呼吸指标，根据呼吸率等呼吸指标就可以判断用户的生理状态是正常还是异常。体温信号也是类似地，处理器50可以对由体温信号采样得到体温数据进行分析，得到体温等人体指标，根据体温也可以判断用户的生理状态是正常还是异常。
请参照图5，一实施例中当处理器50判断用户生理状态由正常变为异常，则处理器50将信号采集电路30对传感器信号进行采样的方式调整为比当前精度高的采样方式。和/或，一实施例中当处理器50判断用户生理状态由异常变为正常，则处理器50将信号采集电路30对传感器信号进行采样的方式调整为比当前精度低的采样方式，或者对传感器信号进行采样得到的数据再进行变采样，和/或滤波，和/或数据截取，和/或改变位数等处理来降低数据的采样率，和/或带宽，和/或分辨率，和/或位数，得到比当前精度低的数据。具体地，默认状态下处理器50可以将信号采集电路30对传感器信号进行采样的方式设置为低精度采样方式，当处理器50判断用户生理状态由正常变为异常，则处理器50将信号采集电路30由低精度采样方式调整为高精度采样方式；在高精度采样方式下，当处理器50又判断用户生理状态由异常变为正常，则处理器50将信号采集电路30又由高精度采样方式调整回低精度采样方式，或者对传感器信号进行采样得到的数据再进行变采样，和/或滤波，和/或数据截取，和/或改变位数等处理来降低数据的采样率，和/或带宽，和/或分辨率，和/或位数，得到低精度数据。当然一实施例中处理器50可以将信号采集电路30对传感器信号进行采样的方式设置为高精度采样方式。
以心电信号为例，信号采集电路30对心电信号的低频成分进行采样，得到心电的低频数据，当处理器50根据心电的低频数据判断用户心脏状态由正常变为异常，则处理器50将信号采样电路30调整为对心电信号中低频成分和高频成分进行采样；和/或，信号采集电路30对心电信号的低频成分和高频成分进行采样，得到心电的低频数据和高频数据，当处理器50根据心电的低频数据和/或高频数据判断用户心脏状态由异常变为正常，则处理器50将信号采集电路调整为对心电信号中低频成分进行采样，或者，对心电信号的低频成分和高频成分进行采样得到的数据再进行变采样，和/或滤波，和/或数据截取，和/或改变位数等处理。
可以看到，在常规监护情况下，信号采集单元30可以采用默认的低精度采样方式这可以保证较小的功耗、较小的数据存储量和较低的芯片计算能力消耗；当判断用户的生理状态由正常变为异常时，信号采集单元30切换为高精度采样方式，来进一步获取传感器信号的一些细分成分，有助于进一步对用户的生理状态进行诊断；当判断用户的生理状态又恢复正常时，信号采样单元30又可以切换回到低精度采样方式等。
（二）关键事件为用户运动状态发生变化
一实施例中处理器50还用于对所述生命体征相关的数据进行分析，以判断用户运动状态变化。
不妨以运动信号为例，处理器50可以通过对由运动信号进行采样得到的运动数据进行分析，得到相关的运动指标，例如速度、加速度和运动角度等，可以根据这些运动指标判断用户运动状态的程度加剧，例如当速度变快、加速度变大、短时间内运动角度变大等，就可以判断用户运动状态的程度加剧，反之，则用户运动状态保持当前程度或减缓；具体在实施过程中，可以设置一个或多个阈值，来将运动分成不同等级，级别越高表明运动状态的程度越剧烈，当运动状态由低级别进入高级别时，则判断用户运动状态的程度加剧，反之，当运动状态由高级别进入低级别时，则判断用户运动状态的程度减缓。
一实施例中当处理器50判断用户运动状态的程度加剧，则处理器50将信号采集电路30对传感器信号进行采样的方式调整为比当前精度高的采样方式。和/或，一实施例中当处理器50判断用户运动状态的程度减缓，则处理器50将信号采集电路30对传感器信号进行采样的方式调整为比当前精度低的采样方式，或者对传感器信号进行采样得到的数据再进行变采样，和/或滤波，和/或数据截取，和/或改变位数等处理，得到比当前精度低的数据。当处理器50判断用户运动状态的程度加剧，则需要更高精度的采样方式，得到的采样数据才可信，减轻了运动对数据的干扰；当处理器50判断用户运动状态的程度减缓，则可以切换为比当前精度低的采样方式，或者，对传感器信号进行采样得到的数据再进行变采样，和/或滤波，和/或数据截取，和/或改变位数等处理，以得到比当前精度低的数据，这是因为一方面由于运动状态的程度减缓，可以不需要那么高精度的采样方式了，降低到比当前精度低的采样方式也可以保证数据的可靠性；另一方面也减轻了装置的功耗、数据存储和芯片计算能力的消耗，使得装置可以工作得更持久，且更加节能。
上述的（一）中关键事件为用户生理状态发生变化以及（二）中关键事件为用户运动状态发生变化，处理器50能够实现自动调整信号采集电路30对传感器信号进行采集及处理的方式。
（三）关键事件为采集及处理方式调整的相关指令的输入
一实施例中处理器50用于对所述生命体征相关的数据进行分析，判断用户生理状态变化，并根据用户生理状态变化，生成供输入采集及处理方式调整的相关指令的控件。具体地，一实施例中处理器50当判断用户生理状态由正常变为异常，所生成的控件包括调高精度的确认键，用于当接收到对该确认键的点击信息时，将信号采集电路30对传感器信号进行采样的方式调整为比当前精度高的采样方式。和/或，一实施例中所述处理器50当判断用户生理状态由异常变为正常，所生成的控件包括调低精度的确认键，用于当接收到对该确认键的点击信息时，将信号采集电路30对传感器信号进行采样的方式调整为比当前精度低的采样方式，或者对传感器信号进行采样得到的数据再进行变采样，和/或滤波，和/或数据截取，和/或改变位数等处理，得到比当前精度低的数据。
不妨以心电信号为例，处理器50可以通过对由心电信号进行采样得到的心电数据进行分析，来判断用户生理状态变化。例如信号采集电路30对心电信号的低频成分进行采样，得到心电的低频数据，处理器50当根据心电的低频数据判断用户心脏状态由正常变为异常，所生成的控件包括调高精度的确认键，用于当接收到对该确认键的点击信息时，将信号采集电路30调整为对心电信号中低频成分和高频成分进行采样。和/或，一实施例中信号采集电路30对心电信号的低频成分和高频成分进行采样，得到心电的低频数据和高频数据，处理器50当根据心电的低频数据和/或高频数据判断用户心脏状态由异常变为正常，所生成的控件包括调低精度的确认键，用于当接收到对该确认键的点击信息时，将信号采集电路30调整为对心电信号中低频成分进行采样，或者对心电信号的低频成分和高频成分进行采样得到的数据再进行变采样，和/或滤波，和/或数据截取，和/或改变位数等处理。
以上是处理器50根据用户生理状态变化来生成供输入采集及处理方式调整的相关指令的控件的例子，类似地，处理器50也可以根据用户运动状态变化来生成供输入采集及处理方式调整的相关指令的控件，下面具体说明。
一实施例中处理器50还用于对所述生命体征相关的数据进行分析，判断用户运动状态变化，并根据用户运动状态变化，生成供输入采集及处理方式调整的相关指令的控件。具体地，一实施例中处理器50当判断用户运动状态的程度加剧，所生成的控件包括调高精度的确认键，用于当接收到对该确认键的点击信息时，将信号采集电路30对传感器信号进行采样的方式调整为比当前精度高的采样方式。和/或，一实施例中所述处理器50当判断用户运动状态的程度减缓，所生成的控件包括调低精度的确认键，用于当接收到对该确认键的点击信息时，将信号采集电路30对传感器信号进行采样的方式调整为比当前精度低的采样方式，或者对传感器信号进行采样得到的数据再进行变采样，和/或滤波，和/或数据截取，和/或改变位数等处理，得到比当前精度低的数据。
需要说明的是，控件的实例有许多种，例如弹窗就是其中一种。
可以看到，处理器50能够判断用户的状态变化——例如生理状态和/或运动状态变化，再根据判断结果确定是否生成供输入采集及处理方式调整的相关指令的控件，使得医护人员可以根据所生成的控件再结合自己的经验来确定是否调整信号采集电路30对传感器信号进行采集及处理的方式。
当然，一些实施例中监测用户生命体征的装置也可以包括输入单元（图中未画出）——例如键盘、鼠标和触控屏等，用于供输入采集及处理方式调整的相关指令；所述处理器50用于当通过输入单元接收到采集及处理方式调整的相关指令时，将信号采集电路对传感器信号进行采集及处理的方式调整为相应的采集及处理的方式。在这种情况下，医护人员可以手动来确定是否调整信号采集电路30对传感器信号进行采集及处理的方式，给予了医护人员比较大的自主空间和权限。
一实施例中，本文中处理器50将信号采集电路30对传感器信号进行采样的方式调整为比当前精度高的采样方式，包括：提高信号采集电路30的采样率、增加带宽、提高分辨率和提高信号位数中的一者或多者；例如处理器50将信号采集电路30对传感器信号进行采样的方式调整为比当前精度高的采样方式，包括：将信号采集电路30调整为对传感器信号中低频成分和高频成分进行采样，以得到生命体征相关的低频数据和高频数据。一实施例中处理器50将信号采集电路30对传感器信号进行采样的方式调整为比当前精度低的采样方式，包括：降低信号采集电路30的采样率、减少带宽、降低分辨率和降低信号位数中的一者或多者；例如处理器50将信号采集电路30对传感器信号进行采样的方式调整为比当前精度低的采样方式，包括：将信号采集电路30调整为对传感器信号中低频成分进行采样，以得到生命体征相关的低频数据。
可以理解地，当信号采集电路30只包括上述的低精度采样方式和高精度采样方式这两种时，则处理器50将信号采集电路30对传感器信号进行采样的方式调整为比当前精度高的采样方式，就是将信号采集电路30由低精度采样方式切换为高精度采样方式；处理器50将信号采集电路30对传感器信号进行采样的方式调整为比当前精度低的采样方式，就是将信号采集电路30由高精度采样方式切换为低精度采样方式。
当处理器50将信号采集电路30对传感器信号进行采样的方式调整为比当前精度高的采样方式后，可以得到一些更细节的信号，因此在一实施例中处理器50对当将信号采集电路30对传感器信号进行采样的方式调整为比当前精度高的采样方式后所得到的生命体征相关的数据进行分析，以判断用户生理状态是否异常，当判断用户生理状态异常时，发出警报。例如一实施例中处理器50对生命体征相关的高频数据进行分析，以判断用户生理状态是否异常；当生命体征相关的高频数据的分析结果表明用户生理状态异常，则发出警报。或者，例如一实施例中处理器50对生命体征相关的低频数据和高频数据进行分析，以判断用户生理状态是否异常；只有当生命体征相关的高频数据的分析结果和低频数据的分析结果都表明用户生理状态异常，才发出警报。
为了方便医务人员例如医生等诊断，请参照图6，一实施例中监测用户生命体征的装置还可以包括显示器70，用于显示显示所述生命体征相关的数据。例如一实施例中显示器70显示所述生命体征相关的数据的曲线图，和/或，显示对所述生命体征相关的数据进行分析后的结果。需要说明的是，显示器70显示生命体征相关的数据的曲线图，可以是实时显示生命体征相关的数据的趋势波形，也可以只显示若干个历史典型时刻波形，还可以在波形旁实时显示高精度分析指标数值或变化值。不妨以心电信号为例，对心电信号进行采样可以得到心电的数据，显示器70可以显示心电图，也可以显示对心电的数据进行分析后的结果，比如心率和心律，以及P波形态、QRS形态和/或ST-T形态等是否异常的判断结果。进一步地，显示器70还可以用于显示警报提示或异常提示。
一实施例中当处理器50将信号采集电路30对传感器信号进行采样的方式调整为比当前精度高的采样方式后——例如由低精度采样方式调整为高精度采样方式后，显示器70只显示对传感器信号中高频成分采样得到的数据，或者同步且分别显示对传感器信号中高频成分和低频成分采样得到的数据；当处理器50将信号采集电路30对传感器信号进行采样的方式调整为比当前精度低的采样方式后——例如由高精度采样方式调整为低精度采样方式后，显示器70隐去对传感器信号中高频成分采样得到的数据，只显示对传感器信号中低频成分采样得到的数据。进一步地，显示器70还可以实时显示信号采样方式，例如，由低精度采样方式调整为高精度采样方式后，显示器70可实时显示“正在进行高精度信号采集或相关功能分析”或“高精度采样方式”等提示语句以提示监测用户生命体征的装置正在采用的信号采样方式。
以上就是本发明若干实施例的监测用户生命体征的装置的一些说明。下面通过将监测用户生命体征的装置用于监测心电来进一步说明。
请参照图7，一实施例中监测用户生命体征的装置，包括心电传感器11、信号采集电路30和处理器50。心电传感器11用于连接于用户以输出心电信号；信号采集电路30用于对所述心电信号进行采样得到心电数据；处理器50则用于响应于关键事件调整所述信号采集电路对心电信号进行采集及处理的方式。其中一实施例中处理器50调整信号采集电路30对心电信号进行采集及处理的方式包括：调整信号采集电路30对心电信号进行采样的方式，和/或，对心电信号进行采样后得到的数据再进行处理的方式。下面一一说明。
心电传感器包括心电电极片，用于连接用户以获取并输出心电信号。信号采集电路30则对所述心电传感器11输出的信号进行采样，将采样得到的数字信号作为所述心电数据。一实施例中信号采集电路30对心电传感器11输出的信号进行采样，包括：根据预设的采样率、带宽、分辨率和/或信号位数对心电传感器11输出的信号进行采样，得到数字信号。一实施例中处理器50则通过改变信号采集电路30的采样率、带宽、分辨率和信号位数中的一者或多者来调整信号采集电路30对心电传感器11输出的信号进行采样的方式。
例如一实施例中信号采集电路30对心电传感器11输出的信号进行采样的方式包括低精度采样方式和高精度采样方式，其中所述低精度采样方式为默认的采样方式；所述低精度采样方式的采样率、带宽的最高频、分辨率、位数这四者都分别不大于高精度采样方式的采样率、带宽的最高频、分辨率、位数，且至少有一者不相等。例如高精度采样方式的采样率可以大于低精度的采样率；例如高精度采样方式的分辨率可以大于低精度的分辨率，即高精度采样方式能够分辨量化的最小信号的能力大于低精度采样方式能够分辨量化的最小信号的能力；例如高精度采样方式的数据位数可以大于低精度的数据位数，即高精度采样方式能够量化的最大信号动态范围大于低精度采样方式能够量化的最大信号动态范围；例如高精度采样方式的带宽的最高频可以大于低精度的带宽的最高频，可以理解地，此时高精度采样方式的带宽可以包含低精度的带宽，或者仅部分重叠，或者完全不重叠，例如一个例子中高精度采样的带宽为0至350Hz，低精度采样的带宽为0至150Hz；例如一个例子中高精度采样的带宽为100至350Hz，低精度采样的带宽为0至150Hz；例如一个例子中高精度采样的带宽为150至350Hz，低精度采样的带宽为0至150Hz。一实施例中信号采集电路30实现高精度采样方式和低精度采样方式可以有多种方案。
例如请参照图8（a），一实施例中信号采集电路30可以包括分别与心电传感器11连接的低精度采样电路31和高精度采样电路33，低精度采样电路31的采样率、带宽的最高频、分辨率、位数这四者都分别不大于高精度采样电路33的采样率、带宽的最高频、分辨率、位数，且至少有一者不相等。低精度采样方式下，信号采集电路30中只有低精度采样电路31被启用来对心电传感器11输出的信号进行采样；而在高精度采样方式下，信号采样电路中只有高精度采样电路33被启用来对心电传感器11输出的信号进行采样。
再例如请参照图8（b），信号采样电路30包括第一处理电路35、低精度采样电路31和高精度采样电路33。第一处理电路35用于将心电传感器11输出的信号处理成相同的两路信号，一路信号用于输入到低精度采样电路31，另一路信号用于输入到高精度采样电路33；所述低精度采样电路31的采样率、带宽的最高频、分辨率、位数这四者都分别不大于高精度采样电路33的采样率、带宽的最高频、分辨率、位数，且至少有一者不相等；所述处理器50通过开启和关闭所述低精度采样电路31和高精度采样电路33来调整对传感器信号进行采样的方式，在所述低精度采样方式下，处理器50控制开启低精度采样电路31和关闭高精度采样电路33，在所述高精度采样方式下，所述处理器50控制开启低精度采样电路31和高精度采样电路33。
一实施例中信号采集电路30对心电传感器11输出的信号进行采样的方式包括低精度采样方式和高精度采样方式；其中对于心电传感器11输出的信号的低精度采样包括：对心电传感器11输出的信号中低频成分进行采样，以得到心电的低频数据；对于心电传感器11输出的信号的高精度采样包括：对心电传感器11输出的信号中低频成分和高频成分进行采样，以得到心电的低频数据和高频数据。
一实施例中信号采集电路30对于心电信号的低精度采样方式，其采样率不大于1kHz，和/或带宽不大于0-250Hz，和/或分辨率不高于1uV/LSB；和/或，信号采集电路30对心电信号的高精度采样方式，其采样率不小于1kHz，和/或带宽不小于0-250Hz，和/或分辨率至少1uV/LSB。
上面是对信号采集电路30进行采样的方式的一些说明。下面对处理器50如何调整信号采集电路30对传感器信号进行采集及处理的方式进行说明。
如上所述，处理器50可以响应于关键事件调整信号采样电路30对传感器信号进行采样的方式。一实施例中关键事件包括用户生理状态发生变化和采集及处理方式调整的相关指令的输入中的一者或多者，下面分别说明。
（一）关键事件为用户生理状态发生变化
一实施例中处理器50用于对心电数据进行分析，以判断用户心脏状态变化。具体地，一实施例中信号采集电路30对心电传感器11输出的信号的低频成分进行采样，得到心电的低频数据，当所述处理器50根据心电的低频数据判断用户心脏状态由正常变为异常，则处理器50将信号采集电路30调整为对心电传感器输出的信号中低频成分和高频成分进行采样；一实施例中，信号采集电路30对心电传感器11输出的信号的低频成分和高频成分进行采样，得到心电的低频数据和高频数据，当所述处理器50根据心电的低频数据和/或高频数据判断用户心脏状态由异常变为正常，则处理器50将信号采集电路30调整为对心电传感器输出的信号中低频成分进行采样，或者，对心电传感器输出的信号的低频成分和高频成分进行采样得到的数据再进行变采样，和/或滤波，和/或数据截取，和/或改变位数等处理。
处理器50通过对心电数据进行分析，判断用户的心脏状态，从而自动调整信号采集电路30对心电信号进行采集及处理的方式。
（二）关键事件为采集及处理方式调整的相关指令的输入
一实施例中处理器50用于对心电数据进行分析，以判断用户心脏状态变化，并根据用户心脏状态变化，生成供输入采集及处理方式调整的相关指令的控件。例如，一实施例中信号采集电路30对心电传感器11输出的信号的低频成分进行采样，得到心电的低频数据，所述处理器30当根据心电的低频数据判断用户心脏状态由正常变为异常，所生成的控件包括调高精度的确认键，用于当接收到对该确认键的点击信息时，将信号采集电路30调整为对心电传感器输出的信号中低频成分和高频成分进行采样；一实施例中信号采集电路30对心电传感器11输出的信号的低频成分和高频成分进行采样，得到心电的低频数据和高频数据，所述处理器30当根据心电的低频数据和/或高频数据判断用户心脏状态由异常变为正常，所生成的控件包括调低精度的确认键，用于当接收到对该确认键的点击信息时，将信号采集电路30调整为对心电传感器输出的信号中低频成分进行采样，或者，对心电传感器输出的信号的低频成分和高频成分进行采样得到的数据再进行变采样，和/或滤波，和/或数据截取，和/或改变位数等处理。处理器50通过对心电数据进行分析，判断用户的心脏状态，再根据判断结果确定是否生成供输入采集及处理方式调整的相关指令的控件，使得医护人员可以根据所生成的控件再结合自己的经验来确定是否调整信号采集电路30对心电信号进行采集及处理的方式。
当然，一些实施例中监测用户生命体征的装置也可以包括输入单元（图中未画出）——例如键盘、鼠标和触控屏等，用于供输入采集及处理方式调整的相关指令；处理器50用于当通过输入单元接收到采集及处理方式调整的相关指令时，将信号采集电路30对心电传感器11输出的信号进行采样的方式调整为相应的采集及处理的方式。在这种情况下，医护人员可以手动来确定是否调整信号采集电路30对心电信号进行采集及处理的方式，给予了医护人员比较大的自主空间和权限。
当处理器50将信号采集电路30对传感器信号进行采样的方式调整为比当前精度高的采样方式后，可以得到一些更细节的信号，因此在一实施例中处理器50对心电传感器11输出的信号的低频成分和高频成分进行采样，则处理器50对采样得到的数据进行分析，以判断用户心脏状态是否异常，当判断用户心脏状态异常时，发出警报。例如，处理器50对心电的高频数据进行分析，以判断用户心脏状态是否异常；当心电的高频数据的分析结果表明用户心脏状态异常，则发出警报；或者，例如，处理器50对心电的低频数据和高频数据进行分析，以判断用户心脏状态是否异常；只有当心电的高频数据的分析结果和低频数据的分析结果都表明用户生理状态异常，才发出警报。例如，对心电的低频数据进行分析，可以得到心律、P-QRS-ST-T形态和ST趋势变化等心电指标，对心电的高频数据进行分析，可以得到高频均方根（HF-RMS）和高频减少区域（HF-RAZ）等心电指标，可以心电的低频和高频数据的这些心电指示来综合进行判断，例如给出HFQRS变化异常、ST异常、ST变化异常等，或者给出心肌状况可能异常、可能心肌缺血等提示。
为了方便医务人员例如医生等诊断，请参照图9，一实施例中监测用户生命体征的装置还可以包括显示器70，用于显示所述心电数据。例如显示器70用于显示心电数据的曲线图。例如显示器70用于显示对心电数据进行分析后的结果，比如心率和心律，以及P波形态、QRS形态和/或ST-T形态等是否异常的判断结果。进一步地，显示器70还可以用于显示警报提示或异常提示等。
一实施例中信号采集电路30当对心电传感器11输出的信号的低频成分和高频成分进行采样，则显示器70只显示对心电传感器输出的信号的高频成分采样得到的数据。一实施例中信号采集电路30当对心电传感器11输出的信号的低频成分和高频成分进行采样，则显示器70可以同步且分别显示对心电传感器11输出的信号中高频成分和低频成分采样得到的数据。例如当信号采样电路30由对心电信号的低频成分进行采样的低精度采样方式，切换为对心电信号的低频成分和高频成分进行采样的高精度采样方式时，显示器70可以实时提示“正在进行高频心电分析”等类似的文字提示，还可以采用形状标识或颜色进行提示。显示器70由在低精度采样方式时只显示心电低频数据波形调整为在高精度采样方式时将心电低频数据的波形与心电高频数据的波形同步实时显示，其中心电高频数据的波形显示方式可以是实时显示完整的高频数据的波形，也可以是实时显示分析高频数据得到的高频指标（例如上述提及的高频均方根（HF-RMS）和高频减少区域（HF-RAZ）等心电指标），也可以是只显示若干个关键时刻的高频数据的波形。进一步地，在显示界面上还可以显示高频指标（例如上述提及的高频均方根（HF-RMS）和高频减少区域（HF-RAZ）等心电指标）的实时状态值或变化值。当处理器50判断心电的高频指标（例如上述提及的高频均方根（HF-RMS）和高频减少区域（HF-RAZ）等心电指标）、心电的低频指标（例如上述提及的心律、P-QRS-ST-T形态和ST趋势变化等心电指标）、其他参数指标（例如上述提及的血氧指标、血压指标、呼吸指标和体温指标）出现异常时，处理器50可以生成相应的提示或报警，例如提出某某指标出现异常，提示心肌状况可能异常，提示心肌可能缺血等。
下面举一个心电监护应用本发明的一个实例。
心电信号是一种微弱的体表生理信号，一般信号带宽分布在0.05Hz-350Hz范围内，其中P波、QRS波、T波均处于不同的频带范围，不同频带的心电信号与多种生理状态相关，能提供不同层次的细节信息，可根据不同临床应用和算法需求决定心电信号的采集需求。对于临床常规心电监护应用，如心率、心律失常监护，心电监护信号一般要求带宽0.5Hz-40Hz范围内噪声水平不大于30uV，且分辨率5uV/LSB，信号采样率500Hz就已足够，一般地信号采样电路30可在允许的噪声水平下，尽可能地降低系统功耗、数据存储量和芯片计算消耗，特别是遥测监护。但当心脏发生病变时，特别是心肌的病变，如心肌的炎症、缺血、纤维化、坏死等病变，可能表现为QRS波形态、ST段形态、T波形态等低频成分变化（肉眼能够识别的），也可能表现为心室晚电位、QRS高频心电等心电高频成分增加。在心电低频成分分析的基础上，增加心电高频成分分析，可以有效提高临床心肌病变筛查的敏感度。但是心电高频成分的特点表现为频率高（150Hz-250Hz）、幅度低（uV级）、时程短（ms级），由于心电高频成分比较微弱、频率高，易受外界噪声干扰，故对于心电信号的采集性能的要求比较高。所以在临床心电监护应用中，当病人生理状态稳定时，心电信号采样单元30可以采用满足心电低频成分监护需求的低功耗采集方式，例如上述的低精度采样方式；当病人发生心肌病变等生理状态变化时，采用满足心电高频成分监护需求的高精度采集方式，例如上述的高精度采样方式（比如采样率不小于1kHz，带宽不小于0-250Hz，分辨率至少1 uV/LSB），这样结合低频、高频成分监测情况，可辅助临床早期预警或指导临床决策或关注病情趋势变化。
请参照图10，本发明一实施例中还公开一种监测用户生命体征的方法，其包括步骤100到步骤120，下面具体说明。
步骤100：获取生命体征相关的传感器信号。一实施例中步骤100获取生命体征相关的传感器信号，包括：获取一个或多个连接于用户的传感器所输出的信号，作为所述传感器信号。一实施例中所述传感器包括心电电极片、血氧探头、血压传感器、脑电传感器、呼吸电极片、温度传感器和运动传感器的一者或多者；所述传感器信号包括：心电信号、血氧信号、血压信号、脑电信号、呼吸信号、体温信号和运动信号中的一者或多者。
步骤110：对所述传感器信号进行采样，得到生命体征相关的数据。一实施例中步骤110对所述传感器信号进行采样，得到生命体征相关的数据，包括：对一个或多个传感器所输出的传感器信号进行采样，将采样得到的数字信号作为所述生命体征相关的数据。
下面对步骤110对传感器信号进行采样进行详细说明。
一实施例中步骤110对传感器信号进行采样，包括：根据预设的采样率、带宽、分辨率和/或位数对传感器信号进行采样，得到数字信号。因此，一实施例中通过改变采样率、带宽、分辨率和位数中的一者或多者来调整对传感器信号进行采样的方式。
例如一实施例中对传感器信号进行采样的方式包括低精度采样方式和高精度采样方式，其中所述低精度采样方式为默认的采样方式；所述低精度采样方式的采样率、带宽的最高频、分辨率、位数这四者都分别不大于高精度采样方式的采样率、带宽的最高频、分辨率、位数，且至少有一者不相等。因此在默认情况下可以采用低精度采样方式，这可以保证低功耗、低数据存储量和低的芯片计算消耗，在需要时，可以切换到高精度采样方式，来提供更多的信息。当然在一些实施例中也可以在默认情况下采用高精度采样方式。实现高精度采样方式和低精度采样方式的切换可以有多种方案，例如一实施例中可以通过一低精度采样电路来实现低精度采样方式，当需要切换到高精度采样方式时，则关闭低精度采样电路并启用一高精度采样电路，通过所述高精度采样电路对传感器信号进行采样来实现高精度采样方式，其中所述低精度采样电路的采样率、带宽的最高频、分辨率、位数这四者都分别不大于高精度采样电路的采样率、带宽的最高频、分辨率、位数，且至少有一者不相等；再例如一实施例中将传感器信号处理成相同的两路，一路连接到低精度采样电路，另一路连接到高精度采样电路；通过低精度采样电路来实现低精度采样方式，当需要切换到高精度采样方式时，则还启用高精度采样电路，通过所述低精度采样电路和高精度采样电路独立且同时对传感器信号进行采样来实现高精度采样方式，其中所述低精度采样电路的采样率、带宽的最高频、分辨率、位数这四者都分别不大于高精度采样电路的采样率、带宽的最高频、分辨率、位数，且至少有一者不相等。
一实施例中对传感器信号进行采样的方式包括低精度采样方式和高精度采样方式；其中对于传感器信号的低精度采样包括：对传感器信号中低频成分进行采样，以得到生命体征相关的低频数据；对于传感器信号的高精度采样包括：对传感器信号中低频成分和高频成分进行采样，以得到生命体征相关的低频数据和高频数据。例如，以传感器信号包括心电信号为例，对于心电信号的低精度采样方式包括：对心电信号中低频成分进行采样，以得到心电的低频数据；对于心电信号的高精度采样方式包括：对心电信号中低频成分和高频成分进行采样，以得到心电的低频数据和高频数据。一实施例中对于心电信号的低精度采样方式，其采样率不大于1kHz，和/或带宽不大于0-250Hz，和/或分辨率不高于1uV/LSB；一实施例中对心电信号的高精度采样方式，其采样率不小于1kHz，和/或带宽不小于0-250Hz，和/或分辨率至少1uV/LSB。
步骤120：响应于关键事件调整对传感器信号进行采集及处理的方式。一实施例中对传感器信号进行采集及处理的方式包括：对传感器信号进行采样的方式，和/或，对传感器信号进行采样后得到的数据再进行处理的方式。
一实施例中关键事件包括用户生理状态发生变化、用户运动状态发生变化和采集及处理方式调整的相关指令的输入中的一者或多者，下面分情况进行说明。
（一）关键事件为用户生理状态发生变化
一实施例中步骤120还对所述生命体征相关的数据进行分析，以判断用户生理状态变化，当判断用户生理状态由正常变为异常，则将对传感器信号进行采样的方式调整为比当前精度高的采样方式；一实施例中步骤120当判断用户生理状态由异常变为正常，则将对传感器信号进行采样的方式调整为比当前精度低的采样方式，或者对传感器信号进行采样得到的数据再进行变采样，和/或滤波，和/或数据截取，和/或改变位数等处理，得到比当前精度低的数据。
不妨以心电信号为例，步骤110对心电信号的低频成分进行采样，得到心电的低频数据，步骤120当根据心电的低频数据判断用户心脏状态由正常变为异常，则对心电信号中低频成分和高频成分进行采样。步骤110对心电信号的低频成分和高频成分进行采样，得到心电的低频数据和高频数据，步骤120当根据心电的低频数据和/或高频数据判断用户心脏状态由异常变为正常，则对心电信号中低频成分进行采样，或者，对心电的低频成分和高频成分进行采样得到的数据再进行变采样，和/或滤波，和/或数据截取，和/或改变位数等处理。
（二）关键事件为用户运动状态发生变化
一实施例中步骤120还对所述生命体征相关的数据进行分析，以判断用户运动状态变化，当判断用户运动状态的程度加剧，则将对传感器信号进行采样的方式调整为比当前精度高的采样方式；一实施例中步骤120当判断用户运动状态的程度减缓，则将对传感器信号进行采样的方式调整为比当前精度低的采样方式，或者对传感器信号进行采样得到的数据再进行变采样，和/或滤波，和/或数据截取，和/或改变位数等处理，得到比当前精度低的数据。
（三）关键事件为采集及处理方式调整的相关指令的输入
一实施例中步骤120对所述生命体征相关的数据进行分析，判断用户生理状态变化；根据用户生理状态变化，生成供输入采集及处理方式调整的相关指令的控件。具体地，一实施例中所述根据用户生理状态变化，生成供输入采集及处理方式调整的相关指令的控件，包括：当判断用户生理状态由正常变为异常，所生成的控件包括调高精度的确认键，用于当接收到对该确认键的点击信息时，将对传感器信号进行采样的方式调整为比当前精度高的采样方式。和/或，一实施例中当判断用户生理状态由异常变为正常，所生成的控件包括调低精度的确认键，用于当接收到对该确认键的点击信息时，将对传感器信号进行采样的方式调整为比当前精度低的采样方式，或者对传感器信号进行采样得到的数据再进行变采样，和/或滤波，和/或数据截取，和/或改变位数等处理，得到比当前精度低的数据。
仍然不妨以心电信号为例，一实施例中步骤110对心电信号的低频成分进行采样，得到心电的低频数据，步骤120当根据心电的低频数据判断用户心脏状态由正常变为异常，所生成的控件包括调高精度的确认键，用于当接收到对该确认键的点击信息时，对心电信号中低频成分和高频成分进行采样。一实施例中步骤110对心电信号的低频成分和高频成分进行采样，得到心电的低频数据和高频数据，步骤120当根据心电的低频数据和/或高频数据判断用户心脏状态由异常变为正常，所生成的控件包括调低精度的确认键，用于当接收到对该确认键的点击信息时，对心电信号中低频成分进行采样，或者对心电信号的低频成分和高频成分进行采样得到的数据再进行变采样，和/或滤波，和/或数据截取，和/或改变位数等处理。
以上是步骤120根据用户生理状态变化来生成供输入采集及处理方式调整的相关指令的控件的例子，类似地，步骤120也可以根据用户运动状态变化来生成供输入采集及处理方式调整的相关指令的控件，下面具体说明。
一实施例中步骤120还包括对所述生命体征相关的数据进行分析，判断用户运动状态变化；根据用户运动状态变化，生成供输入采集及处理方式调整的相关指令的控件。具体地，一实施例中所述根据用户运动状态变化，生成供输入采集及处理方式调整的相关指令的控件，包括：当判断用户运动状态的程度加剧，所生成的控件包括调高精度的确认键，用于当接收到对该确认键的点击信息时，将对传感器信号进行采样的方式调整为比当前精度高的采样方式。和/或，一实施例中当判断用户运动状态的程度减缓，所生成的控件包括调低精度的确认键，用于当接收到对该确认键的点击信息时，将对传感器信号进行采样的方式调整为比当前精度低的采样方式，或者对传感器进行采样得到的数据再进行变采样，和/或滤波，和/或数据截取，和/或改变位数等处理，得到比当前精度低的数据。
需要说明的是，控件的实例有许多种，例如弹窗就是其中一种。
当然，一些实施例中监测用户生命体征的方法也可以提供用于供输入采集及处理方式调整的相关指令的输入单元——例如键盘、鼠标和触控屏等，用于当接收到采集及处理方式调整的相关指令时，将对传感器信号进行采集及处理的方式调整为相应的采集及处理方式。
一实施例中，步骤120将对传感器信号进行采样的方式调整为比当前精度高的采样方式，包括：提高采样率、增加带宽、提高分辨率和提高位数中的一者或多者；和/或，将对传感器信号进行采样的方式调整为比当前精度低的采样方式，包括：降低采样率、减少带宽、降低分辨率和降低位数中的一者或多者。例如，一实施例中步骤120将对传感器信号进行采样的方式调整为比当前精度高的采样方式，至少包括增加带宽，以实现对传感器信号中低频成分和高频成分的采样；和/或，步骤120将对传感器信号进行采样的方式调整为比当前精度低的采样方式，至少包括减少带宽，以仅实现对传感器信号中低频成分的采样；换话句说，步骤120将对传感器信号进行采样的方式调整为比当前精度高的采样方式，包括：对传感器信号中低频成分和高频成分进行采样，以得到生命体征相关的低频数据和高频数据；将对传感器信号进行采样的方式调整为比当前精度低的采样方式，包括：对传感器信号中低频成分进行采样，以得到生命体征相关的低频数据。
可以理解地，当对传感器信号的采集方式只包括上述的低精度采样方式和高精度采样方式这两种时，则步骤120将对传感器信号进行采样的方式调整为比当前精度高的采样方式，就是将对传感器信号进行采样的方式由低精度采样方式切换为高精度采样方式；步骤120将对传感器信号进行采样的方式调整为比当前精度低的采样方式，就是将对传感器信号进行采集的方式由高精度采样方式切换为低精度采样方式。
请参照图11，一实施例中监测用户生命体征的方法还包括步骤130，对生命体征相关的数据进行分析以判断是否发出用户生理状态异常的警报。针对当步骤120将对传感器信号进行采样的方式调整为比当前精度高的采样方式后所得到的生命体征相关的数据，步骤130进行分析，以判断用户生理状态是否异常，当判断用户生理状态异常时，发出警报。例如一实施例步骤130对生命体征相关的高频数据进行分析，以判断用户生理状态是否异常；当生命体征相关的高频数据的分析结果表明用户生理状态异常，则发出警报。例如一实施例中对生命体征相关的低频数据和高频数据进行分析，以判断用户生理状态是否异常；只有当生命体征相关的高频数据的分析结果和低频数据的分析结果都表明用户生理状态异常，才发出警报。
为了方便医务人员例如医生等诊断，请参照图12，一实施例的监测用户生命体征的方法还包括步骤140，显示所述生命体征相关的数据。例如一实施例中步骤140显示所述生命体征相关的数据的曲线图，和/或，显示对所述生命体征相关的数据进行分析后的结果。需要说明的是，步骤140显示生命体征相关的数据的曲线图，可以是实时显示生命体征相关的数据的趋势波形，也可以只显示若干个历史典型时刻波形。一实施例中当步骤120将对传感器信号进行采样的方式调整为比当前精度高的采样方式后——例如由低精度采样方式调整为高精度采样方式后，步骤140只显示对传感器信号中高频成分采样得到的数据，或者同步且分别显示对传感器信号中高频成分和低频成分采样得到的数据。
以上就是本发明若干实施例的监测用户生命体征的方法的一些说明。下面通过将监测用户生命体征的方法用于监测心电来进一步说明。
请参照图13，一实施例中监测用于生命体征的方法包括步骤200到步骤220，下面具体说明。
步骤200：获取心电信号。一实施例中步骤200获取心电信号包括：获取连接于用户的心电传感器输出的信号，作为所述心电信号。一实施例中所述心电传感器包括心电电极片。
步骤210：对所述心电信号进行采样，得到心电数据。一实施例中步骤210对所述心电信号进行采样得到心电数据，包括：对所述心电传感器输出的信号即心电信号进行采样，将采样得到的数字信号作为所述心电数据。下面对步骤210对心电传感器输出的信号即心电信号进行采样进行详细说明。
一实施例中步骤210对所述心电传感器输出的信号进行采样，包括：根据预设的采样率、带宽、分辨率和/或位数对心电传感器输出的信号进行采样，得到数字信号。因此，一实施例中通过改变采样率、带宽、分辨率和位数中的一者或多者来调整对心电传感器输出的信号进行采样的方式。
例如，一实施例中对心电传感器输出的信号进行采样的方式包括低精度采样方式和高精度采样方式，其中所述低精度采样方式为默认的采样方式；所述低精度采样方式的采样率、带宽的最高频、分辨率、位数这四者都分别不大于高精度采样方式的采样率、带宽的最高频、分辨率、位数，且至少有一者不相等。因此在默认情况下可以采用低精度采样方式，这可以保证低功耗和低的芯片计算消耗，在需要时，可以切换到高精度采样方式，来提供更多的信息。实现高精度采样方式和低精度采样方式的切换可以有多种方案，例如一实施例中可以通过一低精度采样电路来实现低精度采样方式，当需要切换到高精度采样方式时，则关闭低精度采样电路并启用一高精度采样电路，通过所述高精度采样电路对传感器信号进行采样来实现高精度采样方式，其中所述低精度采样电路的采样率、带宽的最高频、分辨率、位数这四者都分别不大于高精度采样电路的采样率、带宽的最高频、分辨率、位数，且至少有一者不相等；再例如，将心电传感器输出的信号处理成相同的两路，一路连接到低精度采样电路，另一路连接到高精度采样电路；通过低精度采样电路来实现低精度采样方式，当需要切换到高精度采样方式时，则还启用高精度采样电路，通过所述低精度采样电路和高精度采样电路独立且同时对心电传感器信号进行采样来实现高精度采样方式，其中所述低精度采样电路的采样率、带宽的最高频、分辨率、位数这四者都分别不大于高精度采样电路的采样率、带宽的最高频、分辨率、位数，且至少有一者不相等。
一实施例中对心电传感器输出的信号进行采样的方式包括低精度采样方式和高精度采样方式；其中对于心电传感器输出的信号的低精度采样包括：对心电传感器输出的信号中低频成分进行采样，以得到心电的低频数据；对于心电传感器输出的信号的高精度采样包括：对心电传感器输出的信号中低频成分和高频成分进行采样，以得到心电的低频数据和高频数据。一实施例中对于心电信号的低精度采样方式，其采样率不大于1kHz，和/或带宽不大于0-250Hz，和/或分辨率不高于1uV/LSB；一实施例中对心电信号的高精度采样方式，其采样率不小于1kHz，和/或带宽不小于0-250Hz，和/或分辨率至少1uV/LSB。
步骤220：响应于关键事件调整对心电信号进行采集及处理的方式。一实施例中对心电信号进行采集及处理的方式包括：对心电信号进行采样的方式，和/或，对心电信号进行采样后得到的数据再进行处理的方式。
一实施例中所述关键事件包括用户心脏状态发生变化和采集及处理方式调整的相关指令的输入中的一者或多者。
（一）关键事件为用户生理状态发生变化
一实施例中步骤220还对所述心电数据进行分析，以判断用户心脏状态变化；例如，步骤210对心电传感器输出的信号的低频成分进行采样，得到心电的低频数据，步骤220当根据心电的低频数据判断用户心脏状态由正常变为异常，则对心电传感器输出的信号中的低频成分和高频成分进行采样；例如，步骤210对心电传感器输出的信号的低频成分和高频成分进行采样，得到心电的低频数据和高频数据，步骤220当根据心电的低频数据和/或高频数据判断用户心脏状态由异常变为正常，则对心电传感器输出的信号中低频成分进行采样，或者，对心电传感器输出的信号的低频成分和高频成分进行采样得到的数据再进行变采样，和/或滤波，和/或数据截取，和/或改变位数等处理。
（二）关键事件为采集及处理方式调整的相关指令的输入
一实施例中步骤220对所述心电数据进行分析，判断用户心脏状态变化；根据用户心脏状态变化，生成供输入采集及处理方式调整的相关指令的控件。具体地，一实施例中步骤210对心电传感器输出的信号的低频成分进行采样，得到心电的低频数据，步骤220当根据心电的低频数据判断用户心脏状态由正常变为异常，所生成的控件包括调高精度的确认键，用于当接收到对该确认键的点击信息时，对心电传感器输出的信号中低频成分和高频成分进行采样；一实施例中步骤210对心电传感器输出的信号的低频成分和高频成分进行采样，得到心电的低频数据和高频数据，步骤220当根据心电的低频数据和/或高频数据判断用户心脏状态由异常变为正常，所生成的控件包括调低精度的确认键，用于当接收到对该确认键的点击信息时，对心电传感器输出的信号中低频成分进行采样，或者，对心电传感器输出的信号的低频成分和高频成分进行采样得到的数据再进行变采样，和/或滤波，和/或数据截取，和/或改变位数等处理。
要说明的是，控件的实例有许多种，例如弹窗就是其中一种。
当然，一些实施例中监测用户生命体征的方法也可以提供用于供输入采集及处理方式调整的相关指令的输入单元——例如键盘、鼠标和触控屏等，用于当接收到采集及处理方式调整的相关指令时，将对心电传感器输出的信号进行采集及处理的方式调整为相应的采集及处理的方式。
一实施例中步骤220将对心电传感器输出的信号进行采样的方式调整为比当前精度高的采样方式，包括：提高采样率、增加带宽、提高分辨率和提高位数中的一者或多者；和/或，将对心电传感器输出的信号进行采样的方式调整为比当前精度低的采样方式，包括：降低采样率、减少带宽、降低分辨率和降低位数中的一者或多者。例如，一实施例中步骤220将对心电传感器输出的信号进行采样的方式调整为比当前精度高的采样方式，至少包括增加带宽，以实现对心电信号中低频成分和高频成分的采样；和/或，步骤220将对心电传感器输出的信号进行采样的方式调整为比当前精度低的采样方式，至少包括减少带宽，以仅实现对心电信号中低频成分的采样；换话句说，步骤220将对心电传感器输出的信号进行采样的方式调整为比当前精度高的采样方式——例如上述的高精度采样方式，包括：对心电信号中低频成分和高频成分进行采样，以得到心电的低频数据和高频数据；将对心电信号进行采样的方式调整为比当前精度低的采样方式——例如上述的低精度采样方式，包括：对心电信号中低频成分进行采样，以得到心电的低频数据。
请参照图14，一实施例中监测用户生命体征的方法还包括步骤230，对心电数据进行分析以判断是否发出用户生理状态异常的警报。针对当步骤220将对心电信号进行采样的方式调整为比当前高的采样方式后所得到的心电的数据，步骤230进行分析，以判断用户心脏状态。例如，当步骤210对心电传感器输出的信号的低频成分和高频成分进行采样，则步骤230对采样得到的数据进行分析，以判断用户心脏状态是否异常，当判断用户心脏状态异常时，发出警报。具体地，一实施例中步骤230对心电的高频数据进行分析，以判断用户心脏状态是否异常；当心电的高频数据的分析结果表明用户心脏状态异常，则发出警报；或者，一实施例中步骤230对心电的低频数据和高频数据进行分析，以判断用户心脏状态是否异常；只有当心电的高频数据的分析结果和低频数据的分析结果都表明用户生理状态异常，才发出警报。
为了方便医务人员例如医生等诊断，请参照图15，一实施例的监测用户生命体征的方法还包括步骤240显示心电数据。例如一实施例中步骤240显示心电数据包括：显示心电数据的曲线图，和/或，显示对心电数据进行分析后的结果。需要说明的是，步骤240显示心电数据的曲线图，可以是实时显示心电数据的趋势波形，也可以只显示若干个历史典型时刻波形。一实施例中当步骤220对心电传感器输出的信号的低频成分和高频成分进行采样，则步骤240只显示对心电传感器输出的信号的高频成分采样得到的数据，或者同步且分别显示对心电传感器输出的信号中高频成分和低频成分采样得到的数据。
需要说明的是，本文中的各流程图并不是用于限定各步骤的时序顺序只能如此，而是用于说明其中的一个实施例，本领域技术人员可以理解地，本文中各实施的方法描述中的各步骤或者动作也可以按照本领域技术人员所能显而易见的方式进行顺序调换或调整，本文中各步骤或动作的时序关系由其内在的先后逻辑所限定。
本文参照了各种示范实施例进行说明。然而，本领域的技术人员将认识到，在不脱离本文范围的情况下，可以对示范性实施例做出改变和修正。例如，各种操作步骤以及用于执行操作步骤的组件，可以根据特定的应用或考虑与系统的操作相关联的任何数量的成本函数以不同的方式实现（例如一个或多个步骤可以被删除、修改或结合到其他步骤中）。
在上述实施例中，可以全部或部分地通过软件、硬件、固件或者其任意组合来实现。另外，如本领域技术人员所理解的，本文的原理可以反映在计算机可读存储介质上的计算机程序产品中，该可读存储介质预装有计算机可读程序代码。任何有形的、非暂时性的计算机可读存储介质皆可被使用，包括磁存储设备（硬盘、软盘等）、光学存储设备（CD-ROM、DVD、Blu Ray盘等）、闪存和/或诸如此类。这些计算机程序指令可被加载到通用计算机、专用计算机或其他可编程数据处理设备上以形成机器，使得这些在计算机上或其他可编程数据处理装置上执行的指令可以生成实现指定的功能的装置。这些计算机程序指令也可以存储在计算机可读存储器中，该计算机可读存储器可以指示计算机或其他可编程数据处理设备以特定的方式运行，这样存储在计算机可读存储器中的指令就可以形成一件制造品，包括实现指定功能的实现装置。计算机程序指令也可以加载到计算机或其他可编程数据处理设备上，从而在计算机或其他可编程设备上执行一系列操作步骤以产生一个计算机实现的进程，使得在计算机或其他可编程设备上执行的指令可以提供用于实现指定功能的步骤。
虽然在各种实施例中已经示出了本文的原理，但是许多特别适用于特定环境和操作要求的结构、布置、比例、元件、材料和部件的修改可以在不脱离本披露的原则和范围内使用。以上修改和其他改变或修正将被包含在本文的范围之内。
前述具体说明已参照各种实施例进行了描述。然而，本领域技术人员将认识到，可以在不脱离本披露的范围的情况下进行各种修正和改变。因此，对于本披露的考虑将是说明性的而非限制性的意义上的，并且所有这些修改都将被包含在其范围内。同样，有关于各种实施例的优点、其他优点和问题的解决方案已如上所述。然而，益处、优点、问题的解决方案以及任何能产生这些的要素，或使其变得更明确的解决方案都不应被解释为关键的、必需的或必要的。本文中所用的术语“包括”和其任何其他变体，皆属于非排他性包含，这样包括要素列表的过程、方法、文章或设备不仅包括这些要素，还包括未明确列出的或不属于该过程、方法、系统、文章或设备的其他要素。此外，本文中所使用的术语“耦合”和其任何其他变体都是指物理连接、电连接、磁连接、光连接、通信连接、功能连接和/或任何其他连接。具有本领域技术的人将认识到，在不脱离本发明的基本原理的情况下，可以对上述实施例的细节进行许多改变。因此，本发明的范围应仅由以下权利要求确定。

Claims (97)

  1. 一种监测用户生命体征的方法,其特征在于，包括：
    获取生命体征相关的传感器信号；
    对所述传感器信号进行采样，得到生命体征相关的数据；
    响应于关键事件调整对传感器信号进行采集及处理的方式。
  2. 如权利要求1所述的方法，其特征在于，对传感器信号进行采集及处理的方式包括：对传感器信号进行采样的方式，和/或，对传感器信号进行采样后得到的数据再进行处理的方式。
  3. 如权利要求2所述的方法，其特征在于，所述获取生命体征相关的传感器信号，包括：获取一个或多个连接于用户的传感器所输出的信号，作为所述传感器信号。
  4. 如权利要求3所述的方法，其特征在于，所述传感器包括心电电极片、血氧探头、血压传感器、脑电传感器、呼吸电极片、温度传感器和运动传感器的一者或多者；所述传感器信号包括：心电信号、血氧信号、血压信号、脑电信号、呼吸信号、体温信号和运动信号中的一者或多者。
  5. 如权利要求3所述的方法，其特征在于，所述对所述传感器信号进行采样，得到生命体征相关的数据，包括：对一个或多个传感器所输出的传感器信号进行采样，将采样得到的数字信号作为所述生命体征相关的数据。
  6. 如权利要求5所述的方法，其特征在于，所述对传感器信号进行采样，包括：根据预设的采样率、带宽、分辨率和/或位数对传感器信号进行采样，得到数字信号。
  7. 如权利要求6所述的方法，其特征在于，通过改变采样率、带宽、分辨率和位数中的一者或多者来调整对传感器信号进行采样的方式。
  8. 如权利要求7所述的方法，其特征在于，对传感器信号进行采样的方式包括低精度采样方式和高精度采样方式，其中所述低精度采样方式或高精度采样方式为默认的采样方式；所述低精度采样方式的采样率、带宽的最高频、分辨率、位数这四者都分别不大于高精度采样方式的采样率、带宽的最高频、分辨率、位数，且至少有一者不相等。
  9. 如权利要求7所述的方法，其特征在于：通过低精度采样电路来实现低精度采样方式，当需要切换到高精度采样方式时，则关闭低精度采样电路并启用高精度采样电路，通过所述高精度采样电路对传感器信号进行采样来实现高精度采样方式，其中所述低精度采样电路的采样率、带宽的最高频、分辨率、位数这四者都分别不大于高精度采样电路的采样率、带宽的最高频、分辨率、位数，且至少有一者不相等；或者，
    将传感器信号处理成相同的两路，一路连接到低精度采样电路，另一路连接到高精度采样电路；通过低精度采样电路来实现低精度采样方式，当需要切换到高精度采样方式时，则还启用高精度采样电路，通过所述低精度采样电路和高精度采样电路独立且同时对传感器信号进行采样来实现高精度采样方式，其中所述低精度采样电路的采样率、带宽的最高频、分辨率、位数这四者都分别不大于高精度采样电路的采样率、带宽的最高频、分辨率、位数，且至少有一者不相等。
  10. 如权利要求7至9中任一项所述的方法，其特征在于，对传感器信号进行采样的方式包括低精度采样方式和高精度采样方式；其中对于传感器信号的低精度采样包括：对传感器信号中低频成分进行采样，以得到生命体征相关的低频数据；对于传感器信号的高精度采样包括：对传感器信号中低频成分和高频成分进行采样，以得到生命体征相关的低频数据和高频数据。
  11. 如权利要求10所述的方法，其特征在于，对于心电信号的低精度采样方式包括：对心电信号中低频成分进行采样，以得到心电的低频数据；对于心电信号的高精度采样方式包括：对心电信号中低频成分和高频成分进行采样，以得到心电的低频数据和高频数据。
  12. 如权利要求11所述的方法，其特征在于，对于心电信号的低精度采样方式，其采样率不大于1kHz，和/或带宽不大于0-250Hz，和/或分辨率不高于1uV/LSB；和/或，对心电信号的高精度采样方式，其采样率不小于1kHz，和/或带宽不小于0-250Hz，和/或分辨率至少1uV/LSB。
  13. 如权利要求1至12中任一项所述的方法，其特征在于，所述关键事件包括用户生理状态发生变化、用户运动状态发生变化和采集及处理方式调整的相关指令的输入中的一者或多者。
  14. 如权利要求13所述的方法，其特征在于，还包括：对所述生命体征相关的数据进行分析，以判断用户生理状态变化。
  15. 如权利要求14所述的方法，其特征在于，当判断用户生理状态由正常变为异常，则将对传感器信号进行采样的方式调整为比当前精度高的采样方式；和/或，当判断用户生理状态由异常变为正常，则将对传感器信号进行采样的方式调整为比当前精度低的采样方式，或者对传感器信号进行采样得到的数据再进行变采样，和/或滤波，和/或数据截取，和/或改变位数处理，得到比当前精度低的数据。
  16. 如权利要求15所述的方法，其特征在于，对心电信号的低频成分进行采样，得到心电的低频数据，当根据心电的低频数据判断用户心脏状态由正常变为异常，则对心电信号中低频成分和高频成分进行采样；和/或，对心电信号的低频成分和高频成分进行采样，得到心电的低频数据和高频数据，当根据心电的低频数据和/或高频数据判断用户心脏状态由异常变为正常，则对心电信号中低频成分进行采样，或者，对心电的低频成分和高频成分进行采样得到的数据再进行变采样，和/或滤波，和/或数据截取，和/或改变位数处理。
  17. 如权利要求13所述的方法，其特征在于，还包括：对所述生命体征相关的数据进行分析，以判断用户运动状态变化。
  18. 如权利要求17所述的方法，其特征在于，当判断用户运动状态的程度加剧，则将对传感器信号进行采样的方式调整为比当前精度高的采样方式；和/或，当判断用户运动状态的程度减缓，则将对传感器信号进行采样的方式调整为比当前精度低的采样方式，或者对传感器信号进行采样得到的数据再进行变采样，和/或滤波，和/或数据截取，和/或改变位数处理，得到比当前精度低的数据。
  19. 如权利要求13所述的方法，其特征在于，还包括：
    对所述生命体征相关的数据进行分析，判断用户生理状态变化；
    根据用户生理状态变化，生成供输入采集及处理方式调整的相关指令的控件。
  20. 如权利要求19所述的方法，其特征在于，所述根据用户生理状态变化，生成供输入采集及处理方式调整的相关指令的控件，包括：
    当判断用户生理状态由正常变为异常，所生成的控件包括调高精度的确认键，用于当接收到对该确认键的点击信息时，将对传感器信号进行采样的方式调整为比当前精度高的采样方式；和/或，
    当判断用户生理状态由异常变为正常，所生成的控件包括调低精度的确认键，用于当接收到对该确认键的点击信息时，将对传感器信号进行采样的方式调整为比当前精度低的采样方式，或者对传感器信号进行采样得到的数据再进行变采样，和/或滤波，和/或数据截取，和/或改变位数处理，得到比当前精度低的数据。
  21. 如权利要求20所述的方法，其特征在于，对心电信号的低频成分进行采样，得到心电的低频数据，当根据心电的低频数据判断用户心脏状态由正常变为异常，所生成的控件包括调高精度的确认键，用于当接收到对该确认键的点击信息时，对心电信号中低频成分和高频成分进行采样；和/或，对心电信号的低频成分和高频成分进行采样，得到心电的低频数据和高频数据，当根据心电的低频数据和/或高频数据判断用户心脏状态由异常变为正常，所生成的控件包括调低精度的确认键，用于当接收到对该确认键的点击信息时，对心电信号中低频成分进行采样，或者对心电信号的低频成分和高频成分进行采样得到的数据再进行变采样，和/或滤波，和/或数据截取，和/或改变位数处理。
  22. 如权利要求13所述的方法，其特征在于，还包括：
    对所述生命体征相关的数据进行分析，判断用户运动状态变化；
    根据用户运动状态变化，生成供输入采集及处理方式调整的相关指令的控件。
  23. 如权利要求22所述的方法，其特征在于，所述根据用户运动状态变化，生成供输入采集及处理方式调整的相关指令的控件，包括：
    当判断用户运动状态的程度加剧，所生成的控件包括调高精度的确认键，用于当接收到对该确认键的点击信息时，将对传感器信号进行采样的方式调整为比当前精度高的采样方式；和/或，
    当判断用户运动状态的程度减缓，所生成的控件包括调低精度的确认键，用于当接收到对该确认键的点击信息时，将对传感器信号进行采样的方式调整为比当前精度低的采样方式，或者对传感器进行采样得到的数据再进行变采样，和/或滤波，和/或数据截取，和/或改变位数处理，得到比当前精度低的数据。
  24. 如权利要求13所述的方法，其特征在于，还包括：提供用于供输入采集及处理方式调整的相关指令的输入单元，用于当接收到采集及处理方式调整的相关指令时，将对传感器信号进行采集及处理的方式调整为相应的采集及处理的方式。
     
  25. 如权利要求7、15、18、20或23所述的方法，其特征在于，将对传感器信号进行采样的方式调整为比当前精度高的采样方式，包括：提高采样率、增加带宽、提高分辨率和提高位数中的一者或多者；和/或，将对传感器信号进行采样的方式调整为比当前精度低的采样方式，包括：降低采样率、减少带宽、降低分辨率和降低位数中的一者或多者。
  26. 如权利要求25所述的方法，其特征在于，所述将对传感器信号进行采样的方式调整为比当前精度高的采样方式，至少包括增加带宽，以实现对传感器信号中低频成分和高频成分的采样；和/或，所述将对传感器信号进行采样的方式调整为比当前精度低的采样方式，至少包括减少带宽，以仅实现对传感器信号中低频成分的采样。
  27. 如权利要求7、15、18、20或23所述的方法，其特征在于，将对传感器信号进行采样的方式调整为比当前精度高的采样方式，包括：对传感器信号中低频成分和高频成分进行采样，以得到生命体征相关的低频数据和高频数据；将对传感器信号进行采样的方式调整为比当前精度低的采样方式，包括：对传感器信号中低频成分进行采样，以得到生命体征相关的低频数据。
  28. 如权利要求1至27中任一项所述的方法，其特征在于，还包括：显示所述生命体征相关的数据。
  29. 如权利要求28所述的方法，其特征在于，显示所述生命体征相关的数据，包括：显示所述生命体征相关的数据的曲线图，和/或，显示对所述生命体征相关的数据进行分析后的结果。
  30. 如权利要求28所述的方法，其特征在于，当将对传感器信号进行采样的方式调整为比当前精度高的采样方式后：只显示对传感器信号中高频成分采样得到的数据，或者同步且分别显示对传感器信号中高频成分和低频成分采样得到的数据。
  31. 如权利要求30所述的方法，其特征在于，对当将对传感器信号进行采样的方式调整为比当前精度高的采样方式后所得到的生命体征相关的数据进行分析，以判断用户生理状态是否异常，当判断用户生理状态异常时，发出警报。
  32. 如权利要求31所述的方法，其特征在于，对生命体征相关的高频数据进行分析，以判断用户生理状态是否异常；当生命体征相关的高频数据的分析结果表明用户生理状态异常，则发出警报。
  33. 如权利要求31所述的方法，其特征在于，对生命体征相关的低频数据和高频数据进行分析，以判断用户生理状态是否异常；只有当生命体征相关的高频数据的分析结果和低频数据的分析结果都表明用户生理状态异常，才发出警报。
  34. 一种监测用户生命体征的方法，其特征在于，包括：
    获取心电信号；
    对所述心电信号进行采样，得到心电数据；
    响应于关键事件调整对心电信号进行采集及处理的方式。
  35. 如权利要求34所述的方法，其特征在于，对心电信号进行采集及处理的方式包括：对心电信号进行采样的方式，和/或，对心电信号进行采样后得到的数据再进行处理的方式。
  36. 如权利要求34所述的方法，其特征在于，所述获取心电信号，包括：获取连接于用户的心电传感器输出的信号，作为所述心电信号；所述对所述心电信号进行采样，得到心电数据，包括：对所述心电传感器输出的信号进行采样，将采样得到的数字信号作为所述心电数据。
  37. 如权利要求36所述的方法，其特征在于，所述心电传感器包括心电电极片。
  38. 如权利要求37所述的方法，其特征在于，对所述心电信号进行采样，包括：根据预设的采样率、带宽、分辨率和/或位数对心电传感器输出的信号进行采样，得到数字信号；其中对心电传感器输出的信号进行采样的方式包括低精度采样方式和高精度采样方式，其中所述低精度采样方式为默认的采样方式；所述低精度采样方式的采样率、带宽的最高频、分辨率、位数这四者都分别不大于高精度采样方式的采样率、带宽的最高频、分辨率、位数，且至少有一者不相等；通过改变采样率、带宽、分辨率和位数中的一者或多者来调整对心电传感器输出的信号进行采样的方式。
  39. 如权利要求38所述的方法，其特征在于，通过低精度采样电路来实现对心电传感器的低精度采样方式，当需要切换到对心电传感器的高精度采样方式时，则关闭低精度采样电路并启用高精度采样电路，通过所述高精度采样电路对心电传感器输出的信号进行采样来实现高精度采样方式，其中所述低精度采样电路的采样率、带宽的最高频、分辨率、位数这四者都分别不大于高精度采样电路的采样率、带宽的最高频、分辨率、位数，且至少有一者不相等；或者，
    将心电传感器输出的信号处理成相同的两路，一路连接到低精度采样电路，另一路连接到高精度采样电路；通过低精度采样电路来实现低精度采样方式，当需要切换到高精度采样方式时，则还启用高精度采样电路，通过所述低精度采样电路和高精度采样电路独立且同时对心电传感器信号进行采样来实现高精度采样方式，其中所述低精度采样电路的采样率、带宽的最高频、分辨率、位数这四者都分别不大于高精度采样电路的采样率、带宽的最高频、分辨率、位数，且至少有一者不相等。
  40. 如权利要求38或39所述的方法，其特征在于，对心电传感器输出的信号进行采样的方式包括低精度采样方式和高精度采样方式；其中对于心电传感器输出的信号的低精度采样包括：对心电传感器输出的信号中低频成分进行采样，以得到心电的低频数据；对于心电传感器输出的信号的高精度采样包括：对心电传感器输出的信号中低频成分和高频成分进行采样，以得到心电的低频数据和高频数据。
  41. 如权利要求40所述的方法，其特征在于，对于心电传感器输出的信号的低精度采样方式，其采样率不大于1kHz，和/或带宽不大于0-250Hz，和/或分辨率不高于1uV/LSB；和/或，对心电传感器输出的信号的高精度采样方式，其采样率不小于1kHz，和/或带宽不小于0-250Hz，和/或分辨率至少1uV/LSB。
  42. 如权利要求34至41中任一项所述的方法，其特征在于，所述关键事件包括用户心脏状态发生变化和采集及处理方式调整的相关指令的输入中的一者或多者。
  43. 如权利要求42所述的方法，其特征在于，还包括：对所述心电数据进行分析，以判断用户心脏状态变化；对心电传感器输出的信号的低频成分进行采样，得到心电的低频数据，当根据心电的低频数据判断用户心脏状态由正常变为异常，则对心电传感器输出的信号中的低频成分和高频成分进行采样；和/或，对心电传感器输出的信号的低频成分和高频成分进行采样，得到心电的低频数据和高频数据，当根据心电的低频数据和/或高频数据判断用户心脏状态由异常变为正常，则对心电传感器输出的信号中低频成分进行采样，或者，对心电传感器输出的信号的低频成分和高频成分进行采样得到的数据再进行变采样，和/或滤波，和/或数据截取，和/或改变位数处理；
    和/或，
    对所述心电数据进行分析，判断用户心脏状态变化，根据用户心脏状态变化，生成供输入采集及处理方式调整的相关指令的控件，包括：对心电传感器输出的信号的低频成分进行采样，得到心电的低频数据，当根据心电的低频数据判断用户心脏状态由正常变为异常，所生成的控件包括调高精度的确认键，用于当接收到对该确认键的点击信息时，对心电传感器输出的信号中低频成分和高频成分进行采样；和/或，对心电传感器输出的信号的低频成分和高频成分进行采样，得到心电的低频数据和高频数据，当根据心电的低频数据和/或高频数据判断用户心脏状态由异常变为正常，所生成的控件包括调低精度的确认键，用于当接收到对该确认键的点击信息时，对心电传感器输出的信号中低频成分进行采样，或者，对心电传感器输出的信号的低频成分和高频成分进行采样得到的数据再进行变采样，和/或滤波，和/或数据截取，和/或改变位数处理；
    和/或，
    提供用于供输入采集及处理方式调整的相关指令的输入单元，用于当接收到采集及处理方式调整的相关指令时，将对心电传感器输出的信号进行采集及处理的方式调整为相应的采集及处理的方式。
  44. 如权利要求34至43中任一项所述的方法，其特征在于，还包括：显示所述心电数据。
  45. 如权利要求44所述的方法，其特征在于，显示所述心电数据包括：显示心电数据的曲线图，和/或，显示对心电数据进行分析后的结果。
  46. 如权利要求44所述的方法，其特征在于，当对心电传感器输出的信号的低频成分和高频成分进行采样，则只显示对心电传感器输出的信号的高频成分采样得到的数据，或者同步且分别显示对心电传感器输出的信号中高频成分和低频成分采样得到的数据。
  47. 如权利要求46所述的方法，其特征在于，当对心电传感器输出的信号的低频成分和高频成分进行采样，则对采样得到的数据进行分析，以判断用户心脏状态是否异常，当判断用户心脏状态异常时，发出警报。
  48. 权利要求47所述的方法，其特征在于，对心电的高频数据进行分析，以判断用户心脏状态是否异常；当心电的高频数据的分析结果表明用户心脏状态异常，则发出警报。
  49. 权利要求47所述的方法，其特征在于，对心电的低频数据和高频数据进行分析，以判断用户心脏状态是否异常；只有当心电的高频数据的分析结果和低频数据的分析结果都表明用户生理状态异常，才发出警报。
  50. 一种监测用户生命体征的装置，其特征在于，包括：
    至少一个传感器，连接于用户以输出生命体征相关的传感器信号；
    信号采集电路，用于对所述传感器信号进行采样，得到生命体征相关的数据；
    处理器，用于响应于关键事件调整所述信号采集电路对传感器信号进行采集及处理的方式。
  51. 如权利要求50所述的装置，其特征在于，所述处理器调整所述信号采集电路对传感器信号进行采集及处理的方式包括：调整所述信号采集电路对传感器信号进行采样的方式，和/或，对传感器信号进行采样后得到的数据再进行处理的方式。
  52. 如权利要求50所述的装置，其特征在于，所述传感器包括心电电极片、血氧探头、血压传感器、脑电传感器、呼吸电极片、温度传感器和运动传感器的一者或多者；所述传感器信号包括：心电信号、血氧信号、血压信号、脑电信号、呼吸信号、体温信号和运动信号中的一者或多者。
  53. 如权利要求50所述的装置，其特征在于，所述信号采集电路对传感器信号进行采样，将采样得到的数字信号作为所述生命体征相关的数据。
  54. 如权利要求53所述的装置，其特征在于，所述信号采集电路根据预设的采样率、带宽、分辨率、和/或位数对传感器信号进行采样，得到数字信号。
  55. 如权利要求50所述的装置，其特征在于，所述处理器通过改变信号采集电路的采样率、带宽、分辨率和位数中的一者或多者来调整信号采集电路对传感器信号进行采样的方式。
  56. 如权利要求55所述的装置，其特征在于，所述信号采集电路对传感器信号进行采样的方式包括低精度采样方式和高精度采样方式，其中所述低精度采样方式为默认的采样方式；所述低精度采样方式的采样率、带宽的最高频、分辨率、位数这四者都分别不大于高精度采样方式的采样率、带宽的最高频、分辨率、位数，且至少有一者不相等。
  57. 如权利要求56所述的装置，其特征在于，所述信号采集电路包括分别与所述传感器连接的低精度采样电路和高精度采样电路，所述低精度采样电路的采样率、带宽的最高频、分辨率、位数这四者都分别不大于高精度采样电路的采样率、带宽的最高频、分辨率、位数，且至少有一者不相等；所述处理器通过开启和关闭所述高精度采样电路来调整对传感器信号进行采样的方式，在所述低精度采样方式下，所述处理器控制开启低精度采样电路和关闭高精度采样电路，在所述高精度采样方式下，所述处理控制关闭低精度采样电路和开启高精度采样电路；或者，
    所述信号采样电路包括第一处理电路、低精度采样电路和高精度采样电路，所述第一处理电路用于将传感器信号处理成相同的两路信号，一路信号用于输入到低精度采样电路，另一路信号用于输入到高精度采样电路；所述低精度采样电路的采样率、带宽的最高频、分辨率、位数这四者都分别不大于高精度采样电路的采样率、带宽的最高频、分辨率、位数，且至少有一者不相等；所述处理器通过开启和关闭所述低精度采样电路和高精度采样电路来调整对传感器信号进行采样的方式，在所述低精度采样方式下，处理器控制开启低精度采样电路和关闭高精度采样电路，在所述高精度采样方式下，所述处理器控制开启低精度采样电路和高精度采样电路。
  58. 如权利要求56或57中任一项所述的装置，其特征在于，所述信号采集电路对传感器信号进行采样的方式包括低精度采样方式和高精度采样方式；其中对于传感器信号的低精度采样包括：对传感器信号中低频成分进行采样，以得到生命体征相关的低频数据；对于传感器信号的高精度采样包括：对传感器信号中低频成分和高频成分进行采样，以得到生命体征相关的低频数据和高频数据。
  59. 如权利要求58所述的装置，其特征在于，所述信号采集电路对于心电信号的低精度采样方式包括：对心电信号中低频成分进行采样，以得到心电的低频数据；所述信号采集电路对于心电信号的高精度采样方式包括：对心电信号中低频成分和高频成分进行采样，以得到心电的低频数据和高频数据。
  60. 如权利要求59所述的装置，其特征在于，所述信号采集电路对于心电信号的低精度采样方式，其采样率不大于1kHz，和/或带宽不大于0-250Hz，和/或分辨率不高于1uV/LSB；和/或，所述信号采集电路对心电信号的高精度采样方式，其采样率不小于1kHz，和/或带宽不小于0-250Hz，和/或分辨率至少1uV/LSB。
  61. 如权利要求50至60中任一项所述的装置，其特征在于，所述关键事件包括用户生理状态发生变化、用户运动状态发生变化和采集及处理方式调整的相关指令的输入中的一者或多者。
  62. 如权利要求61所述的装置，其特征在于，所述处理器还用于对所述生命体征相关的数据进行分析，以判断用户生理状态变化。
  63. 如权利要求62所述的装置，其特征在于，所述处理器当判断用户生理状态由正常变为异常，则将所述信号采集电路对传感器信号进行采样的方式调整为比当前精度高的采样方式；和/或，所述处理器当判断用户生理状态由异常变为正常，则将所述信号采集电路对传感器信号进行采样的方式调整为比当前精度低的采样方式，或者对传感器信号进行采样得到的数据再进行变采样，和/或滤波，和/或数据截取，和/或改变位数处理，得到比当前精度低的数据。
  64. 如权利要求63所述的装置，其特征在于，所述信号采集电路对心电信号的低频成分进行采样，得到心电的低频数据，所述处理器当根据心电的低频数据判断用户心脏状态由正常变为异常，则将信号采样电路调整为对心电信号中低频成分和高频成分进行采样；和/或，所述信号采集电路对心电信号的低频成分和高频成分进行采样，得到心电的低频数据和高频数据，所述处理器当根据心电的低频数据和/或高频数据判断用户心脏状态由异常变为正常，则将信号采集电路调整为对心电信号中低频成分进行采样，或者，对心电信号的低频成分和高频成分进行采样得到的数据再进行变采样，和/或滤波，和/或数据截取，和/或改变位数处理。
  65. 如权利要求61所述的装置，其特征在于，所述处理器还对所述生命体征相关的数据进行分析，以判断用户运动状态变化。
  66. 如权利要求65所述的装置，其特征在于，所述处理器当判断用户运动状态的程度加剧，则将信号采集电路对传感器信号进行采样的方式调整为比当前精度高的采样方式；和/或，所述处理器当判断用户运动状态的程度减缓，则将信号采集电路对传感器信号进行采样的方式调整为比当前精度低的采样方式，或者对传感器信号进行采样得到的数据再进行变采样，和/或滤波，和/或数据截取，和/或改变位数处理，得到比当前精度低的数据。
  67. 如权利要求61所述的装置，其特征在于，所述处理器还用于对所述生命体征相关的数据进行分析，判断用户生理状态变化，并根据用户生理状态变化，生成供输入采集及处理方式调整的相关指令的控件。
  68. 如权利要求67所述的装置，其特征在于，所述处理器当判断用户生理状态由正常变为异常，所生成的控件包括调高精度的确认键，用于当接收到对该确认键的点击信息时，将信号采集电路对传感器信号进行采样的方式调整为比当前精度高的采样方式；和/或，所述处理器当判断用户生理状态由异常变为正常，所生成的控件包括调低精度的确认键，用于当接收到对该确认键的点击信息时，将信号采集电路对传感器信号进行采样的方式调整为比当前精度低的采样方式，或者对传感器信号进行采样得到的数据再进行变采样，和/或滤波，和/或数据截取，和/或改变位数处理，得到比当前精度低的数据。
  69. 如权利要求68所述的装置，其特征在于，所述信号采集电路对心电信号的低频成分进行采样，得到心电的低频数据，所述处理器当根据心电的低频数据判断用户心脏状态由正常变为异常，所生成的控件包括调高精度的确认键，用于当接收到对该确认键的点击信息时，将信号采集电路调整为对心电信号中低频成分和高频成分进行采样；和/或，所述信号采集电路对心电信号的低频成分和高频成分进行采样，得到心电的低频数据和高频数据，所述处理器当根据心电的低频数据和/或高频数据判断用户心脏状态由异常变为正常，所生成的控件包括调低精度的确认键，用于当接收到对该确认键的点击信息时，将信号采集电路调整为对心电信号中低频成分进行采样，或者对心电信号的低频成分和高频成分进行采样得到的数据再进行变采样，和/或滤波，和/或数据截取，和/或改变位数处理。
  70. 如权利要求61所述的装置，其特征在于，所述处理器还用于对所述生命体征相关的数据进行分析，判断用户运动状态变化，并根据用户运动状态变化，生成供输入采集及处理方式调整的相关指令的控件。
  71. 如权利要求70所述的装置，其特征在于，所述处理器当判断用户运动状态的程度加剧，所生成的控件包括调高精度的确认键，用于当接收到对该确认键的点击信息时，将信号采集电路对传感器信号进行采样的方式调整为比当前精度高的采样方式；和/或，所述处理器当判断用户运动状态的程度减缓，所生成的控件包括调低精度的确认键，用于当接收到对该确认键的点击信息时，将信号采集电路对传感器信号进行采样的方式调整为比当前精度低的采样方式，或者对传感器信号进行采样得到的数据再进行变采样，和/或滤波，和/或数据截取，和/或改变位数处理，得到比当前精度低的数据。
  72. 如权利要求61所述的装置，其特征在于，还包括输入单元，用于供输入采集及处理方式调整的相关指令；所述处理器用于当通过输入单元接收到采集及处理方式调整的相关指令时，将信号采集电路对传感器信号进行采集及处理的方式调整为相应的采集及处理的方式。
  73. 如权利要求63、66、68、71或72所述的装置，其特征在于，所述处理器将信号采集电路对传感器信号进行采样的方式调整为比当前精度高的采样方式，包括：提高信号采集电路的采样率、增加带宽、提高分辨率和提高位数中的一者或多者；和/或，将信号采集电路对传感器信号进行采样的方式调整为比当前精度低的采样方式，包括：降低信号采集电路的采样率、减少带宽、降低分辨率和降低位数中的一者或多者。
  74. 如权利要求73所述的装置，其特征在于，所述处理器将信号采集电路对传感器信号进行采样的方式调整为比当前精度高的采样方式，至少包括增加信号采集电路的带宽，以实现对传感器信号中低频成分和高频成分的采样；和/或，所述处理器将信号采集电路对传感器信号进行采样的方式调整为比当前精度低的采样方式，至少包括减少信号采集电路的带宽，以仅实现对传感器信号中低频成分的采样。
  75. 如权利要求63、66、68、71或72所述的装置，其特征在于，所述处理器将信号采集电路对传感器信号进行采样的方式调整为比当前精度高的采样方式，包括：将信号采集电路调整为对传感器信号中低频成分和高频成分进行采样，以得到生命体征相关的低频数据和高频数据；所述处理器将信号采集电路对传感器信号进行采样的方式调整为比当前精度低的采样方式，包括：将信号采集电路调整为对传感器信号中低频成分进行采样，以得到生命体征相关的低频数据。
  76. 如权利要求50至75中任一项所述的装置，其特征在于，还包括显示器，用于显示所述生命体征相关的数据。
  77. 如权利要求76所述的装置，其特征在于，所述显示器显示所述生命体征相关的数据的曲线图，和/或，显示对所述生命体征相关的数据进行分析后的结果。
  78. 如权利要求76所述的装置，其特征在于，所述处理器当将信号采集电路对传感器信号进行采样的方式调整为比当前精度高的采样方式后：所述显示器只显示对传感器信号中高频成分采样得到的数据，或者同步且分别显示对传感器信号中高频成分和低频成分采样得到的数据。
  79. 如权利要求78所述的装置，其特征在于，所述处理器对当将信号采集电路对传感器信号进行采样的方式调整为比当前精度高的采样方式后所得到的生命体征相关的数据进行分析，以判断用户生理状态是否异常，当判断用户生理状态异常时，发出警报。
  80. 如权利要求79所述的装置，其特征在于，所述处理器对生命体征相关的高频数据进行分析，以判断用户生理状态是否异常；当生命体征相关的高频数据的分析结果表明用户生理状态异常，则发出警报。
  81. 如权利要求79所述的装置，其特征在于，所述处理器对生命体征相关的低频数据和高频数据进行分析，以判断用户生理状态是否异常；只有当生命体征相关的高频数据的分析结果和低频数据的分析结果都表明用户生理状态异常，才发出警报。
  82. 一种监测用户生命体征的装置，其特征在于，包括：
    心电传感器，用于连接于用户以输出心电信号；
    信号采集电路，用于对所述心电信号进行采样，得到心电数据；
    处理器，用于响应于关键事件调整所述信号采集电路对心电信号进行采集及处理的方式。
  83. 如权利要求82所述的装置，其特征在于，所述处理器调整所述信号采集电路对心电信号进行采集及处理的方式包括：调整所述信号采集电路对心电信号进行采样的方式，和/或，对心电信号进行采样后得到的数据再进行处理的方式。
  84. 如权利要求82所述的装置，其特征在于，所述心电传感器包括心电电极片。
  85. 如权利要求82所述的装置，其特征在于，所述信号采集电路对所述心电信号进行采样，包括：根据预设的采样率、带宽、分辨率和/或位数对心电传感器输出的信号进行采样，得到数字信号；所述信号采集电路对心电传感器输出的信号进行采样的方式包括低精度采样方式和高精度采样方式，其中所述低精度采样方式为默认的采样方式；所述低精度采样方式的采样率、带宽的最高频、分辨率、位数这四者都分别不大于高精度采样方式的采样率、带宽的最高频、分辨率、位数，且至少有一者不相等；所述处理器通过改变信号采集电路的采样率、带宽、分辨率和位数中的一者或多者来调整信号采集电路对心电传感器输出的信号进行采样的方式。
  86. 如权利要求85所述的装置，其特征在于，所述信号采集电路包括分别与所述心电传感器连接的低精度采样电路和高精度采样电路，所述低精度采样电路的采样率、带宽的最高频、分辨率、位数这四者都分别不大于高精度采样电路的采样率、带宽的最高频、分辨率、位数，且至少有一者不相等；所述处理器通过开启和关闭所述高精度采样电路来调整对心电传感器输出的信号进行采样的方式，在所述低精度采样方式下，所述处理器控制开启低精度采样电路和关闭高精度采样电路，在所述高精度采样方式下，所述处理器控制关闭低精度采样电路和开启高精度采样电路；或者，
    所述信号采样电路包括第一处理电路、低精度采样电路和高精度采样电路，所述第一处理电路用于将心电传感器输出的信号处理成相同的两路信号，一路信号用于输入到低精度采样电路，另一路信号用于输入到高精度采样电路；所述低精度采样电路的采样率、带宽的最高频、分辨率、位数这四者都分别不大于高精度采样电路的采样率、带宽的最高频、分辨率、位数，且至少有一者不相等；所述处理器通过开启和关闭所述低精度采样电路和高精度采样电路来调整对传感器信号进行采样的方式，在所述低精度采样方式下，处理器控制开启低精度采样电路和关闭高精度采样电路，在所述高精度采样方式下，所述处理控制开启低精度采样电路和高精度采样电路。
  87. 如权利要求85或86所述的装置，其特征在于，所述信号采集电路对心电传感器输出的信号进行采样的方式包括低精度采样方式和高精度采样方式；其中对于心电传感器输出的信号的低精度采样包括：对心电传感器输出的信号中低频成分进行采样，以得到心电的低频数据；对于心电传感器输出的信号的高精度采样包括：对心电传感器输出的信号中低频成分和高频成分进行采样，以得到心电的低频数据和高频数据。
  88. 如权利要求87所述的装置，其特征在于，所述信号采集电路对于心电传感器输出的信号的低精度采样方式，其采样率不大于1kHz，和/或带宽不大于0-250Hz，和/或分辨率不高于1uV/LSB；和/或，所述信号采集电路对心电传感器输出的信号的高精度采样方式，其采样率不小于1kHz，和/或带宽不小于0-250Hz，和/或分辨率至少1uV/LSB。
  89. 如权利要82至88中作一项所述的装置，其特征在于，所述关键事件包括用户心脏状态发生变化和采集及处理方式调整的相关指令的输入中的一者或多者。
  90. 如权利要求89所述的装置，其特征在于，所述处理器还用于对所述心电数据进行分析，以判断用户心脏状态变化；所述信号采集电路对心电传感器输出的信号的低频成分进行采样，得到心电的低频数据，所述处理器当根据心电的低频数据判断用户心脏状态由正常变为异常，则将信号采集电路调整为对心电传感器输出的信号中低频成分和高频成分进行采样；和/或，所述信号采集电路对心电传感器输出的信号的低频成分和高频成分进行采样，得到心电的低频数据和高频数据，所述处理器当根据心电的低频数据和/或高频数据判断用户心脏状态由异常变为正常，则将信号采集电路调整为对心电传感器输出的信号中低频成分进行采样，或者，对心电传感器输出的信号的低频成分和高频成分进行采样得到的数据再进行变采样，和/或滤波，和/或数据截取，和/或改变位数处理；
    和/或，
    所述处理器对所述心电数据进行分析，判断用户心脏状态变化，并根据用户心脏状态变化，生成供输入采集及处理方式调整的相关指令的控件，包括：所述信号采集电路对心电传感器输出的信号的低频成分进行采样，得到心电的低频数据，所述处理器当根据心电的低频数据判断用户心脏状态由正常变为异常，所生成的控件包括调高精度的确认键，用于当接收到对该确认键的点击信息时，将信号采集电路调整为对心电传感器输出的信号中低频成分和高频成分进行采样；和/或，所述信号采集电路对心电传感器输出的信号的低频成分和高频成分进行采样，得到心电的低频数据和高频数据，所述处理器当根据心电的低频数据和/或高频数据判断用户心脏状态由异常变为正常，所生成的控件包括调低精度的确认键，用于当接收到对该确认键的点击信息时，将信号采集电路调整为对心电传感器输出的信号中低频成分进行采样，或者，对心电传感器输出的信号的低频成分和高频成分进行采样得到的数据再进行变采样，和/或滤波，和/或数据截取，和/或改变位数处理；
    和/或，
    所述装置还包括输入单元，用于提供用于供输入采集及处理方式调整的相关指令的输入单元；所述处理器用于当通过输入单元接收到采集及处理方式调整的相关指令时，将信号采集电路对心电传感器输出的信号进行采集及处理的方式调整为相应的采集及处理的方式。
  91. 如权利要求82至90中任一项所述的装置，其特征在于，还包括显示器，用于显示所述心电数据。
  92. 如权利要求91所述的装置，其特征在于，所述显示器用于显示心电数据的曲线图，和/或，显示对心电数据进行分析后的结果。
  93. 如权利要求91所述的装置，其特征在于，所述信号采集电路当对心电传感器输出的信号的低频成分和高频成分进行采样，则显示器只显示对心电传感器输出的信号的高频成分采样得到的数据，或者同步且分别显示对心电传感器输出的信号中高频成分和低频成分采样得到的数据。
  94. 如权利要求93所述的装置，其特征在于，当所述信号采集电路对心电传感器输出的信号的低频成分和高频成分进行采样，则处理器对采样得到的数据进行分析，以判断用户心脏状态是否异常，当判断用户心脏状态异常时，发出警报。
  95. 如权利要求94所述的装置，其特征在于，所述处理器对心电的高频数据进行分析，以判断用户心脏状态是否异常；当心电的高频数据的分析结果表明用户心脏状态异常，则发出警报。
  96. 如权利要求94所述的装置，其特征在于，所述处理器对心电的低频数据和高频数据进行分析，以判断用户心脏状态是否异常；只有当心电的高频数据的分析结果和低频数据的分析结果都表明用户生理状态异常，才发出警报。
  97. 一种计算机可读存储介质，其特征在于，包括程序，所述程序能够被处理器执行以实现如权利要求1至49中任一项所述的方法。
PCT/CN2018/124305 2018-12-27 2018-12-27 一种监测用户生命体征的方法和装置 WO2020133052A1 (zh)

Priority Applications (3)

Application Number Priority Date Filing Date Title
CN201880099069.0A CN112930138B (zh) 2018-12-27 2018-12-27 一种监测用户生命体征的方法和装置
PCT/CN2018/124305 WO2020133052A1 (zh) 2018-12-27 2018-12-27 一种监测用户生命体征的方法和装置
US17/361,262 US20210321927A1 (en) 2018-12-27 2021-06-28 Method and device for monitoring vital sign of user

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/CN2018/124305 WO2020133052A1 (zh) 2018-12-27 2018-12-27 一种监测用户生命体征的方法和装置

Related Child Applications (1)

Application Number Title Priority Date Filing Date
US17/361,262 Continuation US20210321927A1 (en) 2018-12-27 2021-06-28 Method and device for monitoring vital sign of user

Publications (1)

Publication Number Publication Date
WO2020133052A1 true WO2020133052A1 (zh) 2020-07-02

Family

ID=71125873

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2018/124305 WO2020133052A1 (zh) 2018-12-27 2018-12-27 一种监测用户生命体征的方法和装置

Country Status (3)

Country Link
US (1) US20210321927A1 (zh)
CN (1) CN112930138B (zh)
WO (1) WO2020133052A1 (zh)

Families Citing this family (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116264967A (zh) * 2021-12-17 2023-06-20 上海微创生命科技有限公司 降低血糖监测信号噪声的方法、可读存储介质及管理系统
CN116509360B (zh) * 2023-06-25 2023-09-12 苏州维伟思医疗科技有限公司 心律监控系统、方法及医疗设备
CN117958824B (zh) * 2024-03-29 2024-06-11 大连清东科技有限公司 一种肾脏疾病人员状态监测分析方法

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101802881A (zh) * 2007-09-19 2010-08-11 皇家飞利浦电子股份有限公司 检测异常情况的设备和方法
CN102098961A (zh) * 2008-05-14 2011-06-15 埃斯潘美国控股有限责任公司 身体活动监测器和数据收集单元
CN103632055A (zh) * 2013-11-29 2014-03-12 华为技术有限公司 数据采集方法和装置
CN105662356A (zh) * 2014-11-20 2016-06-15 中兴通讯股份有限公司 一种生理体征监测方法及装置

Family Cites Families (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2000025668A1 (en) * 1998-11-05 2000-05-11 Medhkour Adel M System and method for long-term recording of neural activity
US7876251B2 (en) * 2008-10-22 2011-01-25 Siemens Medical Solutions Usa, Inc. System for processing patient monitoring signals
JP2010194167A (ja) * 2009-02-26 2010-09-09 Higashi Nippon Gijutsu Kenkyusho:Kk 脈波測定方法及び脈波測定装置
US8891713B2 (en) * 2011-04-06 2014-11-18 Siemens Medical Solutions Usa, Inc. System for adaptive sampled medical signal interpolative reconstruction for use in patient monitoring
KR101745684B1 (ko) * 2013-05-31 2017-06-09 나이키 이노베이트 씨.브이. 동적 샘플링
US10512407B2 (en) * 2013-06-24 2019-12-24 Fitbit, Inc. Heart rate data collection
WO2015129411A1 (ja) * 2014-02-27 2015-09-03 株式会社村田製作所 個人識別装置、及び、個人識別方法
WO2016038585A1 (en) * 2014-09-12 2016-03-17 Blacktree Fitness Technologies Inc. Portable devices and methods for measuring nutritional intake
US9690361B2 (en) * 2014-12-24 2017-06-27 Intel Corporation Low-power context-aware control for analog frontend
US9826940B1 (en) * 2015-05-26 2017-11-28 Verily Life Sciences Llc Optical tracking of heart rate using PLL optimization
US9397685B1 (en) * 2015-07-23 2016-07-19 Texas Instruments Incorporated Sensor with low power model based feature extractor
WO2017059569A1 (zh) * 2015-10-08 2017-04-13 深圳迈瑞生物医疗电子股份有限公司 起搏信号处理方法、系统和心电监护仪

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101802881A (zh) * 2007-09-19 2010-08-11 皇家飞利浦电子股份有限公司 检测异常情况的设备和方法
CN102098961A (zh) * 2008-05-14 2011-06-15 埃斯潘美国控股有限责任公司 身体活动监测器和数据收集单元
CN103632055A (zh) * 2013-11-29 2014-03-12 华为技术有限公司 数据采集方法和装置
CN105662356A (zh) * 2014-11-20 2016-06-15 中兴通讯股份有限公司 一种生理体征监测方法及装置

Also Published As

Publication number Publication date
CN112930138A (zh) 2021-06-08
US20210321927A1 (en) 2021-10-21
CN112930138B (zh) 2023-04-11

Similar Documents

Publication Publication Date Title
US20210321927A1 (en) Method and device for monitoring vital sign of user
CN104363824B (zh) 心电图中实时qrs持续时间的测量
CN105496400A (zh) 便捷式多导联无线心电监测设备及方法
Rotariu et al. Telemedicine system for remote blood pressure and heart rate monitoring
WO2020132813A1 (zh) 针对颅脑损伤的生理体征监测方法和医疗监护设备
WO2020132899A1 (zh) 血压脉象检测系统及其检测方法、检测装置
WO2020132799A1 (zh) 一种监护设备的报警限值设置方法及装置
CN103169479A (zh) 血氧测量系统及其生理测量装置与其脉波分析方法
WO2020133347A1 (zh) 一种对患者的监护方法及装置
KR20230088668A (ko) 원격진료 서비스 제공 방법
US9486154B2 (en) Device and method for recording physiological signal
Tzavaras et al. Development of a low-cost wireless monitoring System supporting the Continuity of Medical Care of the Patient at home
KR20060031837A (ko) 이동통신 단말기의 심박변동율을 이용한 바이오유니트
WO2021108950A1 (zh) 监护方法及监护装置、监护设备、计算机可读存储介质
CN113080983A (zh) 利用低功耗长距离通信网的心电图测定装置
CN105919586A (zh) 一种脉搏心率协同监测分类系统
RU174590U1 (ru) Монитор многофункциональный компьютеризированный
WO2020133429A1 (zh) 监护方法、监护仪及计算机存储介质
KR20140092997A (ko) 생체 정보 측정 장치 및 생체 정보 측정 방법
KR20030074520A (ko) 이동통신 단말기를 이용한 바이오유니트
US20220122444A1 (en) Monitoring apparatus and method for operating same, monitor and computer storage medium
CN116602644B (zh) 血管信号采集系统、人体特征监测系统
US20220117561A1 (en) Monitoring device, method for setting reference baseline and readable storage medium
CN103027663A (zh) 电子生理监测装置及电子生理监测系统
WO2020258333A1 (zh) 一种监护处理方法及装置、存储介质

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 18944422

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

32PN Ep: public notification in the ep bulletin as address of the adressee cannot be established

Free format text: NOTING OF LOSS OF RIGHTS PURSUANT TO RULE 112(1) EPC (EPO FORM1205 DATED 19.11.2021)

122 Ep: pct application non-entry in european phase

Ref document number: 18944422

Country of ref document: EP

Kind code of ref document: A1