CN111166306A

CN111166306A - Physiological signal acquisition method, computer device and storage medium

Info

Publication number: CN111166306A
Application number: CN202010076825.7A
Authority: CN
Inventors: 赵起超; 杨苒; 李召
Original assignee: Kingfar International Inc
Current assignee: Kingfar International Inc
Priority date: 2020-01-23
Filing date: 2020-01-23
Publication date: 2020-05-19

Abstract

The invention provides a physiological signal acquisition method, computer equipment and a storage medium, wherein the method comprises the following steps: synchronously acquiring physiological signals of a subject and acceleration information acquired by an acceleration sensor; collecting the impedance of a conductive closed loop formed by the contact of the two detection electrodes and the skin of the subject, and marking the time period when the impedance is out of the range of a set value range as an invalid time period of the wearing state of the detection equipment; marking the time period when the acceleration recorded in the acceleration information exceeds a set threshold as a motion time period; and deleting or marking the part of the physiological signal in the invalid wearing state period, and correcting the physiological signal in the exercise period by adopting a Kalman filtering method to obtain an effective physiological signal. The physiological signals collected in the invalid time period are deleted or marked, Kalman filtering processing is carried out on the physiological characteristic data collected in the movement time period, and the influence of external interference factors is effectively reduced so as to obtain the physiological signals with higher accuracy.

Description

Physiological signal acquisition method, computer device and storage medium

Technical Field

The present invention relates to the field of physiological signal acquisition technologies, and in particular, to a physiological signal acquisition method, a computer device, and a storage medium.

Background

In the prior art, two scenes for acquiring and monitoring physiological signals are provided, one is to detect vital signs of a subject through professional medical detection equipment in a medical environment, and the equipment in the application environment has high accuracy, but is larger in size and cannot be applied to other use environments; the other type is that under the living environment, the vital signs of the testee are detected through the wearable intelligent detection equipment, the environment scene is complex and changeable, and the wearable intelligent detection equipment is small in size and simple in wearing mode, so that the wearable intelligent detection equipment is easily interfered by external environment factors to cause inaccuracy of collected signals.

Wearable intelligent detection equipment in the prior art can cause invalid or distorted acquired physiological signals due to equipment slippage, sliding or interference of other external factors on a sensor in the process of various activities of a testee, influences the acquisition quality of the physiological signals and reduces the detection reliability.

Disclosure of Invention

In view of this, embodiments of the present invention provide a physiological signal acquisition method, a computer device, and a storage medium, so as to solve the problem of signal acquisition misalignment caused by device slippage or other interference factors during a movement process of a subject.

The technical scheme of the invention is as follows:

in one aspect, the present invention provides a physiological signal acquisition method, including:

synchronously acquiring physiological signals of a subject and acceleration information acquired by an acceleration sensor, wherein the physiological signals at least comprise: PPG heart rate signal, blood oxygen signal;

acquiring the impedance of a conductive closed loop formed by the contact of two detection electrodes and the skin of the subject, acquiring a time period of the impedance outside a set value range, and marking the time period as an invalid time period of the wearing state of the detection equipment;

marking the time period when the acceleration recorded in the acceleration information exceeds a set threshold as a motion time period;

deleting or marking the part of the physiological signal in the invalid wearing state time period, and correcting the physiological signal in the motion time period by adopting a Kalman filtering method to obtain an effective physiological signal.

In some embodiments, collecting the impedance of a conductive closed loop formed by two detection electrodes in contact with the skin of the subject, and marking a time period when the impedance is out of a set value range as a detection device wearing state invalid period comprises:

respectively adding positive and negative voltages to the two detection motors, collecting the current of a conductive closed loop formed by the contact of the two detection electrodes and the skin of the subject according to a set frequency, and calculating the impedance of the conductive closed loop;

recording the exceeding time point T of the Kth exceeding of the set value range of the impedance_k1And the regression time point T_k2And will T_k1To T_k2The period is marked as the K-th wearing state invalid period.

In some embodiments, after synchronously acquiring the physiological signal of the subject and the acceleration information acquired by the acceleration sensor, the method further comprises:

performing fast Fourier transform on a PPG heart rate signal in a time domain to obtain the PPG heart rate signal in a frequency domain;

and removing the signal of the interference light wave from the PPG heart rate signal on the frequency domain according to the signal frequency corresponding to the interference light wave.

and performing band-pass filtering processing on the PPG heart rate signal, wherein the bandwidth is 0.1 HZ-20 HZ, so as to remove interference signals outside the bandwidth frequency.

In some embodiments, after deleting a portion of the physiological signal in the invalid wearing state period and modifying the physiological signal in the exercise period by using a kalman filtering method to obtain an effective physiological signal, the method further includes:

and sending the effective physiological signal to a mobile terminal device for storage and display feedback.

when the impedance is judged to be higher than the upper limit of the set value range, marking the corresponding time period as an absolute invalid time period;

when the impedance is judged to be lower than the lower limit of the set threshold value, marking the corresponding time period as an interference time period;

deleting a portion of the physiological signal within the absolute null period;

and marking the part of the physiological signal in the interference time period, and performing Kalman filtering processing.

In some embodiments, acquiring the impedance of a conductive closed loop formed by two detection electrodes contacting with the skin of the subject, and marking the impedance at a time period outside a set value range as a detection device wearing state invalid period, further comprises:

generating acousto-optic alarm information to prompt the subject to adjust the wearing state of the detection equipment so as to acquire the effective physiological signal.

In some embodiments, before synchronously acquiring the physiological signal of the subject and the acceleration information acquired by the acceleration sensor, the method further comprises:

and carrying out baseline calibration of a first set duration on the physiological signal and the acceleration information.

In another aspect, the present invention also provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method when executing the program.

In another aspect, the present invention also provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the above method.

According to the physiological signal acquisition method, the computer equipment and the storage medium, the impedance of a conductive closed loop formed by the contact of the detection electrode and the skin of the subject is detected, the equipment wearing state invalid time period of the impedance outside the set value range is judged, and the physiological signal acquired in the invalid time period is deleted or marked; meanwhile, acceleration information is collected through an acceleration sensor, the time period when the acceleration is larger than a set threshold value is marked as a movement time period, Kalman filtering processing is carried out on physiological characteristic data collected in the movement time period, the influence of external interference factors is effectively reduced, and a physiological signal with higher accuracy is obtained.

Additional advantages, objects, and features of the invention will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.

It will be appreciated by those skilled in the art that the objects and advantages that can be achieved with the present invention are not limited to the specific details set forth above, and that these and other objects that can be achieved with the present invention will be more clearly understood from the detailed description that follows.

Drawings

The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the principles of the invention. The components in the figures are not necessarily to scale, emphasis instead being placed upon illustrating the principles of the invention. For purposes of illustrating and describing some portions of the present invention, corresponding parts of the drawings may be exaggerated, i.e., may be larger, relative to other components in an exemplary apparatus actually manufactured according to the present invention. In the drawings:

FIG. 1 is a flowchart illustrating a physiological signal acquisition method according to an embodiment of the present invention;

fig. 2 is a schematic flow chart of a procedure for eliminating an interference optical signal in the physiological signal acquisition method according to another embodiment of the present invention;

fig. 3 is a schematic flow chart illustrating a process of detecting a wearing state invalid period in the physiological signal acquisition method according to an embodiment of the present invention;

fig. 4 is a schematic flow chart illustrating a procedure of detecting a wearing state absolute invalid period and an interference period in the physiological signal acquisition method according to another embodiment of the present invention;

fig. 5 is a schematic structural diagram of a wearable intelligent detection device used in the physiological signal acquisition method according to an embodiment of the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail with reference to the following embodiments and accompanying drawings. The exemplary embodiments and descriptions of the present invention are provided to explain the present invention, but not to limit the present invention.

It should be noted that, in order to avoid obscuring the present invention with unnecessary details, only the structures and/or processing steps closely related to the scheme according to the present invention are shown in the drawings, and other details not so relevant to the present invention are omitted.

It should be emphasized that the term "comprises/comprising" when used herein, is taken to specify the presence of stated features, elements, steps or components, but does not preclude the presence or addition of one or more other features, elements, steps or components.

It is also noted herein that the term "coupled," if not specifically stated, may refer herein to not only a direct connection, but also an indirect connection in which an intermediate is present.

The method for acquiring physiological signals in daily life environment mainly adopts wearable intelligent detection equipment, combines a biosensor, a motion sensor and an environment sensor, and acquires physiological signals, motion states and environment index information of a subject; wherein the physiological signal may include: heart rate signals, blood oxygen signals, electrodermal signals, cortisol data, and the like. Compared with a professional detection instrument in a medical environment, the physiological sensor in the wearable intelligent detection device has defects in hardware detection precision and wearing mode, so that the precision of the acquired data is not high in some scenes, for example, when the wearable intelligent detection device slips, the acquired signal data has no reference value; in the process of movement, as the wearable intelligent detection equipment is simple in wearing mode, the biosensor cannot be stably attached to the body of a subject, and the acquired signals have deviation; or, in the process of movement, external light triggers the biosensor to generate a scrambled signal due to sliding of the wearable intelligent detection device, so that data distortion is caused.

In order to solve the above problems, the present invention provides a physiological signal acquisition method, a computer device, and a storage medium, which can detect a wearing state and a motion state of a device, and adjust a corresponding data signal according to a specific situation, so as to ensure that an acquired physiological signal is more accurate and effective.

The wearable intelligent detection device to which the physiological signal acquisition method is applied can comprise a biosensor 101 for acquiring physiological characteristic information, two detection electrodes 102 for detecting wearing states, an acceleration sensor 103, a signal acquisition processing module 104 and a power supply assembly 105 for supplying power. The biosensor 101 may comprise a photosensor, an infrared light reflecting diode and a visible light emitting diode for acquiring PPG heart rate signals and blood oxygen signals, electrodes for acquiring picosignals, a motion sensor for acquiring motion data, etc.

Fig. 1 is a flow chart of a physiological signal acquisition method according to an embodiment of the present invention, and although the present application provides the method operation steps or device structure shown in the following embodiments or the attached drawings, more or less operation steps or module units may be included in the method or device based on the conventional or non-inventive labor. In the case of steps or structures which do not logically have the necessary cause and effect relationship, the execution sequence of the steps or the module structure of the apparatus is not limited to the execution sequence or the module structure described in the embodiments and shown in the drawings of the present application. When the described method or module structure is applied in an actual device or end product, the method or module structure according to the embodiments or shown in the drawings can be executed sequentially or executed in parallel (for example, in a parallel processor or multi-thread processing environment, or even in a distributed processing environment).

The physiological signal acquisition method of the present invention is described below with reference to fig. 1, and as shown in the figure, the method may include steps S101 to S104:

step S101: synchronously acquiring physiological signals of a subject and acceleration information acquired by an acceleration sensor, wherein the physiological signals at least comprise: PPG heart rate signal, blood oxygen signal.

Step S102: and acquiring the impedance of a conductive closed loop formed by the contact of the two detection electrodes and the skin of the subject, acquiring the time period of the impedance outside the range of a set value range, and marking as a period of invalid wearing state of the detection equipment.

Step S103: and marking the time period when the acceleration recorded in the acceleration information exceeds a set threshold as a motion period.

Step S104: deleting or marking the part of the physiological signal in the invalid wearing state time period, and correcting the physiological signal in the motion time period by adopting a Kalman filtering method to obtain an effective physiological signal.

In step S101, based on the physiological signals of the subject acquired by the biosensor, the change of blood volume in the living tissue can be detected by photo-electric means, for example, by Photoplethysmography (PPG), and when a light beam with a certain wavelength is irradiated on the surface of the finger tip skin, the contraction and expansion of the blood vessel affect the transmission of light (for example, in the case of transmission PPG, light passing through the finger tip) or the reflection of light (for example, in the case of reflection PPG, light from the vicinity of the surface of the wrist) each time the heart beats. When light is transmitted through the skin tissue and then reflected to the light sensitive sensor, there is some attenuation of the light. The absorption of light by the tissues like muscles, bones, veins and other connections is substantially constant (provided that there is no substantial movement of the measurement site), but the arteries will be different and naturally also vary due to the pulsation of the blood in the arteries. Wherein the light beam is typically an infrared light beam. When we convert light into an electrical signal, it is because the absorption of light by arteries changes and the absorption of light by other tissues is basically unchanged, and the resulting signal can be divided into a Direct Current (DC) signal and an Alternating Current (AC) signal. The AC signal is extracted to reflect the characteristics of blood flow and thereby indicate the heart rate status of the subject.

Furthermore, when the infrared light beam is used for detecting the PPG heart rate signal of the subject, visible red light can be added for detecting the blood oxygen content. Because the oxyhemoglobin HbO2 and the hemoglobin Hb contained in the blood have a certain proportion, namely the oxygen content; the spectral detection can find that the oxygenated hemoglobin HbO2 has an absorption peak in the light with the wavelength of 800-1000 nm, and the hemoglobin Hb has an absorption peak in the light with the wavelength of 600-800 nm, so that the blood oxygen content can be converted by detecting the ratio of the absorption rates of the light beams of the human body to the two regions. In some embodiments, the PPG heart rate signal and the blood oxygen signal are acquired at the ear by sensors.

In other embodiments, the change in cardiac potential may also be collected and recorded by Electrocardiography (ECG or EKG), and the results of the ECG are typically displayed in a wave pattern consisting essentially of P-waves, QRS-waves, and T-waves. The P wave represents atrial contraction, the QRS wave group ventricular contraction, and the T wave ventricular relaxation. The measurement or evaluation of the heart rate is represented by the interval between the R-wave and the R-wave. The larger the RR interval is, the lower the heart rate is, and the smaller the RR interval is, the higher the heart rate is. And acquiring body temperature information by a temperature sensor, acquiring cortisol information by a cortisol sensor, and the like.

In the embodiment of the invention, the acceleration sensor can adopt a three-axis acceleration sensor, and is not only used for collecting the integral motion acceleration, but also used for collecting the acceleration information of three axial directions in a calibrated coordinate system.

In some embodiments, as shown in fig. 2, after step S101, that is, after synchronously acquiring the physiological signal of the subject and the acceleration information acquired by the acceleration sensor, step S1011 to step S1012 are further included:

step S1011: and carrying out fast Fourier transform on the PPG heart rate signal in the time domain to obtain the PPG heart rate signal in the frequency domain.

Step S1012: and removing the signal of the interference light wave from the PPG heart rate signal on the frequency domain according to the signal frequency corresponding to the interference light wave.

In this case, the PPG heart rate signal is detected by the photosensor, and in the detection process, due to the influence of the external interference light beam, there is a clutter signal in the PPG heart rate signal detected by the photosensor. The signal detected by the photoelectric sensor is a time-domain signal, and the spurious signal is difficult to remove. In this case, through carrying out fast Fourier transform with the discrete cycle PPG heart rate signal of sampling on the time domain and obtaining the PPG heart rate signal on the frequency domain, clutter signal and the infrared light wave signal alternate segregation that is used for detecting can be according to corresponding frequency with clutter filtering.

In some embodiments, after step S101, after synchronously acquiring the physiological signal of the subject and the acceleration information acquired by the acceleration sensor, the method further includes:

In this embodiment, in order to prevent the influence of other signals, combine human heartbeat frequency, be 0.1HZ ~ 20HZ through the bandwidth that sets up band-pass filtering, on the basis of guaranteeing effectively to remain heart rate signal waveform, with the clutter signal filtering of other frequencies to promote and detect the effect.

In step S102, in order to prevent the distortion of the collected related physiological signals or data information caused by the slipping of the wearable intelligent detection device, or even the failure to collect the related data information, the wearable intelligent detection device detects the wearing state by providing two detection electrodes. Specifically, in an effective wearing state, two detection electrodes and the skin of the subject form a conductive closed loop, and the conductive closed loop forms relatively uniform impedance due to the similar structure of the skin of the human, and the variation range of the conductive closed loop is limited. By adding stable voltage on the two detection electrodes, when the impedance of the conductive closed loop is detected to be in a set value range, the wearing state of the physiological signal acquisition device can be judged to be effective. When the impedance of the conductive closed loop is higher than the upper limit of the set threshold, the conductive closed loop is broken, and the physiological signal acquisition device can be judged to slide off, and the data acquired and generated in the period is invalid. When the impedance of the conductive closed loop is lower than the lower limit of the set threshold value, the subject can be judged to be in a sweat or damp environment, and the vital sign signal collected in the state can be interfered.

Therefore, in the embodiment of the invention, the wearing state of the wearable intelligent detection device is judged by detecting the impedance of the conductive closed loop, and the wearing state is determined to be valid only when the impedance of the conductive closed loop is within the range of the set value range, otherwise, the wearing state is invalid. And marks the corresponding detection device wearing state invalid period.

In some embodiments, a detection electrode may be provided on a detection device adapted for use in the ear that forms an electrically conductive closed loop with the skin. According to the physiological structure characteristics of the human body, the swing amplitude of the head of the human body is relatively small in the motion process, the wearable intelligent detection equipment is worn tightly, and the interference in the physiological signal acquisition process is small. Specifically, two detection electrodes are arranged on the side surface of the detection device, and after the detection device is worn on the ear, the detection electrodes and the ear or skin around the ear form a closed conductive loop. Only when the impedance of the conductive closed loop is within a set value range, the wearing state is determined to be effective, otherwise, the wearing state is not effective.

In some embodiments, as shown in fig. 3, the step S102, namely, acquiring the impedance of the conductive closed loop formed by the two detection electrodes contacting with the skin of the subject, and marking the time period when the impedance is out of the range of the set value range as the invalid time period of the wearing state of the detection device, includes steps S1021 to S1022:

step S1021: and respectively adding positive and negative voltages to the two detection motors, collecting the current of a conductive closed loop formed by the contact of the two detection electrodes and the skin of the testee according to a set frequency, and calculating the impedance of the conductive closed loop.

Step S1022: recording the exceeding time point T of the Kth exceeding of the set value range of the impedance_k1And the regression time point T_k2And will T_k1To T_k2Time period markThe K-th wearing state invalid period.

In step S1021, the set frequency should be higher than the sampling frequency of the physiological signal to ensure that the wearing state corresponding to each sampling point can be effectively detected. In step S1022, by recording the start time and the end time when the impedance of the conductive closed loop exceeds the set value range each time, the invalid time period of the wearing state is calibrated in detail each time, and the invalid time period is used for performing the screening process after deleting or marking the physiological signals in the corresponding time period in the subsequent processing process.

In some embodiments, as shown in fig. 4, the step S102 of acquiring the impedance of the conductive closed loop formed by the two detection electrodes contacting with the skin of the subject and marking the time period when the impedance is out of the range of the set value range as the invalid period of the wearing state of the detection device includes steps S201 to S204:

step S201: and when the impedance is judged to be higher than the upper limit of the set value range, marking the corresponding time period as an absolute invalid time period.

Step S202: and when the impedance is judged to be lower than the lower limit of the set threshold, marking the corresponding time period as an interference time period.

Step S203: the portion of the physiological signal within the absolute null period is deleted.

Step S204: and marking the part of the physiological signal in the interference period, and performing Kalman filtering processing.

Since in the case of an impedance of the conductive closed circuit exceeding the set value range, it is further differentiated between the case of an impedance higher than the upper limit of the set value range due to the device falling off and the case of an impedance lower than the lower limit of the set value range due to the device in a humid environment. In the present embodiment, the case where the setting value range is exceeded is further divided and marked as an absolute invalid period and an interference period in step S201 and step S202, respectively. Physiological signals generated in the absolute invalid period are irrelevant to the vital signs of the subject and cannot be used as reference, so that deletion processing is carried out. And the physiological signals generated in the interference period can be corrected due to uncertain interference factors, and the accuracy of the physiological signals in the interference period is improved after Kalman filtering processing.

In some embodiments, the step S102, namely, acquiring the impedance of the conductive closed loop formed by the two detection electrodes contacting the skin of the subject, and marking the time period when the impedance is out of the range of the set value range as the invalid period of the wearing state of the detection device, further includes:

generating acousto-optic alarm information to prompt the subject to adjust the wearing state of the detection equipment so as to acquire effective physiological signals.

In the embodiment, when the slippage, the sliding or the interference of the wearable intelligent detection device worn by the subject is detected, the prompt is given by generating audible and visual alarm information. The audible and visual alarm can be directly executed by the wearable intelligent detection device or sent to the mobile terminal device for execution.

In step S103, in a daily use environment, the state of the subject can be summarized as a motion state and a static state, wherein in the large-amplitude motion state, the detection effect of the wearable intelligent detection device is affected by hardware factors such as a wearing manner, and data is inaccurate and distorted due to poor contact with the body of the subject or interference caused by external light entering, and needs to be further corrected; and under the static state and during the small-amplitude motion, the detection effect of wearable intelligent detection equipment is stable, and the credibility is higher, and the excessive processing and correction to data lead to the deviation of output signal and true value on the contrary.

In the embodiment of the invention, according to the motion state of the subject reflected by the acceleration information, marking the time interval in the state of larger motion amplitude; specifically, when the acceleration information reaction acceleration is higher than a set threshold value, it is judged that the corresponding motion amplitude can affect the detection accuracy of the wearable intelligent detection device, and then the corresponding time period is marked as a motion time period. The size of the threshold value can be specifically set according to the detection precision and the wearing mode of the wearable intelligent detection equipment.

In step S104, the acquired physiological sign information is corrected according to the wearing state invalid period and the exercise period marked in step S102 and step S103. The data collected in the period of invalid wearing state can be directly deleted or marked to be used as standby data for processing due to large deviation. And for the data in the motion period, Kalman filtering is adopted for processing so as to obtain a better detection effect.

Kalman filtering is a means for eliminating random interference to improve detection accuracy, and is a linear filter derived based on a minimum variance criterion. Kalman filtering is a time domain recursive algorithm that derives an optimized current state from an estimated value of the previous state and an observed value (measured value) of the current state.

Illustratively, for a certain kind of signals, such as PPG heart rate signals, a system of discrete control processes is introduced, which can be described by a linear random differential equation:

X(k)＝AX(k-1)+BU(k)+W(k).......................................(1)

at the same time, the measurements taken in the system:

Z(k)＝HX(k)+V(k)................................................(2)

wherein, X (k) is the system state at the moment k, namely the predicted value of the PPG heart rate signal; u (k) is the amount of control over the system at time k. A and B are system parameters, and for a multi-model system, A and B are matrices; z (k) is the measured value at time k, H is a parameter of the measurement system, and H is a matrix for a multi-measurement system. W (k) and V (k) represent process and measured noise, respectively, assuming that W (k) and V (k) are white gaussian noise (whitegaussian noise) and their covariance differences are Q and R, respectively (assumed to be invariant to system state changes).

We use them in combination with their covariance to estimate the optimal output of the system, i.e. the optimal output of the PPG heart rate signal.

First, a process model of the system is used to predict the system for the next state. Assuming that the present system state is k, according to the model of the system, the present state can be predicted based on the last state of the system, i.e. the PPG heart rate signal in the k state is predicted from the PPG heart rate signal in the k-1 state:

X(k|k-1)＝AX(k-1|k-1)+BU(k)..................................(3)

where X (k | k-1) is the result predicted using the previous state, X (k-1| k-1) is the optimal result for the previous state, U (k) is the controlled variable for the current state, and U (k) may be 0 if there is no controlled variable.

Until now, the system prediction value has been updated, however, the covariance corresponding to X (k | k-1) has not been updated. Covariance is denoted by P:

P(k|k-1)＝AP(k-1|k-1)A’+Q....................................(4)

in the formula (4), P (k | k-1) is a covariance corresponding to X (k | k-1), P (k-1| k-1) is a covariance corresponding to X (k-1| k-1), A' represents a transposed matrix of A, and Q is a covariance of the system process. Equation 3, 4 is the prediction of the system by the kalman filter, i.e. the prediction value of the PPG heart rate signal.

Combining the predicted values and the measured values, we can obtain an optimized estimated value X (k | k) of the current state k:

X(k|k)＝X(k|k-1)+Kg(k)(Z(k)-HX(k|k-1)).......................(5)

wherein Kg is kalman gain (kalman gain):

Kg(k)＝P(k|k-1)H’/(HP(k|k-1)H’+R)...............................(6)

wherein H' is the transpose of H; to this end, an optimal estimated value X (k | k) in k-state is obtained, but in order to make the kalman filter continuously run until the system process is finished, we also update the covariance of X (k | k) in k-state:

P(k|k)＝(I-Kg(k)H)P(k|k-1).................................(7)

where I is a matrix of 1, I ═ 1 for single model single measurements.

In some embodiments, after step S104, namely deleting the part of the physiological signal in the invalid wearing state period, and modifying the physiological signal in the exercise period by using the kalman filtering method to obtain a valid physiological signal, the method further includes:

and sending the effective physiological signal to the mobile terminal equipment, storing the effective physiological signal and displaying feedback.

Because the wearable intelligent detection equipment has small volume and various wearing modes and is not beneficial to the feedback display of the physiological characteristic information, in the embodiment of the invention, the detected effective physiological signal is sent to the mobile terminal equipment for storage and display. In other embodiments, the mobile terminal device is further configured to connect to the cloud server, compare the physiological signal fed back in real time with data stored in the physiological characteristic database, and determine the physiological abnormal state of the subject.

In some embodiments, after step S101, before synchronously acquiring the physiological signal of the subject and the acceleration information acquired by the acceleration sensor, the method further includes:

and carrying out baseline calibration of a first set time length on the physiological signals and the acceleration information.

As response values of photoelectric sensors in the wearable intelligent detection device to different wavelengths are different, and in the using process, due to abrasion and stain residue of a light transmission window of the photoelectric sensors, the response values of the device to infrared beams and visible beams for detection are deviated, and the accuracy of the acquired physiological signals is reduced. Specifically, after the device is started, the device is worn by the subject to acquire the physiological signals and the acceleration signals in a static state. After data is obtained, a data baseline is obtained by mean filtering. The data baseline may determine thresholds for maximum and minimum values of the data. The data of the subsequent test is judged according to the threshold value.

In some embodiments, the steps of the physiological signal acquisition method include:

1. after the equipment is started, obtaining the impedance between two detection electrodes, detecting the impedance in a mode of sampling a resistor according to the principle of a current source, wherein the detected impedance is marked as z, and if z belongs to (2000, 10000000) ohm, the equipment is considered to be brought well; detecting impedance z at the frequency of 1Hz in the operation process of the whole equipment, correspondingly obtaining an impedance sequence z (x), wherein x is a continuous time sequence, if the system detects that z exceeds the range, marking a marking point M (i) by the system, wherein i is the accumulated number of z exceeding a set value domain, and recording M (i) as a first exceeding time point when the impedance i exceeds the set value domain; when the impedance returns to the set value range again, recording C (i) as a return time point when the impedance exceeds the set value range for the ith time; the time period between the time point and the regression time point is first exceeded, a time period T (x) is recorded, then T (x) ═ M (i), C (i) ], and the data recorded during this time period will be highlighted or deleted at the time of analysis.

2. And collecting data. The heart rate signal PPG adopts a band-pass filtering circuit in a hardware circuit, and the bandwidth is 0.1 Hz-20 Hz; and the signal collected by the photoelectric sensor is amplified by 120 times through a 2-stage amplification circuit. At this time, the interference of external infrared beams and visible beams is not eliminated by the equipment circuit, and a signal of the interference beams can exist in the bandwidth of 0.1 Hz-20 Hz of band-pass filtering, for example, the frequency of infrared scanning of the eye tracker is about 6-12 Hz, and if the eye tracker exists in a tested test, the signal acquisition of PPG and the acquisition of blood oxygen SPO2 are influenced.

Performing baseline calibration on the physiological signals and the acceleration signals, wherein after baseline test is performed, baseline acquisition is performed under the known condition without any interference;

collecting a PPG signal sequence P (x) during formal collection; x is a time series;

performing fast Fourier transform on the sequence P (x) to obtain a frequency domain signal sequence x { m }, and determining the frequency concentrated by energy according to the parteval theorem (Pasteval theorem); acquiring the frequency corresponding to the infrared clutter, and deleting to achieve the purpose of filtering the infrared clutter;

3. and (5) judging the motion state. At the time of baseline testingThe coordinate value of the device after the tested device is determined is marked as a (x)₁，y₁，z₁) (ii) a Setting a set threshold value m of the set motion state;

assuming that the sequence of PPG signal acquisitions is P (x);

assume that the sequence of SPO2 oximetry signal acquisitions is S (x);

assuming that the sequence of EDA skin electrical signal acquisition is E (x);

wherein x is a time point on the corresponding time axis;

in the data acquisition process, all data acquisition is synchronous acquisition, when the acceleration exceeds a set threshold value M, data marking is carried out on PPG/SPO2/EDA when the acceleration exceeds the threshold value for the first time, a marking point is marked as M1, and when the threshold value returns to a normal range M, the marking point is marked as M2; the time points of M1 corresponding to the time point of M2 on the x axis are marked as t1 and t 2; heart rate PPG data between the intervals t1 and t2 are recorded as motion data P (m), t1 < m < t 2;

similarly, the blood oxygen SPO2 data is recorded as S (m), t1 < m < t 2;

similarly, the data of the skin electricity EDA are recorded as E (m), and t1 is more than m and less than t 2;

the data of the acceleration at this time is recorded as a (m), and t1 < m < t 2;

for data of a motion system, due to interference of the data, motion waves need to be filtered, and heart rate PPG data, blood oxygen SPO2 data and electrodermal EDA data in a time period from t1 to t2 are processed by Kalman filtering;

a new heart rate PPG sequence is thus available: p₁(m)，t1＜m＜t2；

Similarly, a new blood oxygen SPO2 data sequence S can be obtained₁(m)，t1＜m＜t2；

The same way can also obtain a new electrodeionization EDA data sequence E₁(m)，t1＜m＜t2；

And replacing the original sequence data with the new data and the filtered data to obtain a new sequence:

P′(x)；S′(x)；E′(x)。

at this point data acquisition and real-time analysis has been completed.

4. The physiological signals after analysis are sent to an upper computer or an APP terminal in a Bluetooth mode, and data collection and storage are completed. If no device is connected during the period, the ear clip sensor can perform internal storage of itself to ensure that data is not lost.

In summary, according to the physiological signal acquisition method, the computer device and the storage medium of the present invention, the impedance of the conductive closed loop formed by the contact between the detection electrode and the skin of the subject is detected to determine the invalid time period of the wearing state of the device in which the impedance is outside the range of the set value range, and the physiological signal acquired in the invalid time period is deleted or marked; meanwhile, acceleration information is collected through an acceleration sensor, the time period when the acceleration is larger than a set threshold value is marked as a movement time period, Kalman filtering processing is carried out on physiological characteristic data collected in the movement time period, the influence of external interference factors is effectively reduced, and a physiological signal with higher accuracy is obtained.

In the description herein, reference to the description of the terms "one embodiment," "a particular embodiment," "some embodiments," "for example," "an example," "a particular example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. The sequence of steps involved in the various embodiments is provided to schematically illustrate the practice of the invention, and the sequence of steps is not limited and can be suitably adjusted as desired.

As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are only exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.

Claims

1. A physiological signal acquisition method, comprising:

2. The physiological signal collection method according to claim 1, wherein collecting the impedance of a conductive closed loop formed by two detection electrodes contacting with the skin of the subject, marking the time period when the impedance is out of a set value range as a detection device wearing state invalid period comprises:

3. The method for acquiring physiological signals according to claim 1, further comprising, after synchronously acquiring the physiological signals of the subject and the acceleration information acquired by the acceleration sensor:

4. The method for acquiring physiological signals according to claim 1, further comprising, after synchronously acquiring the physiological signals of the subject and the acceleration information acquired by the acceleration sensor:

5. The method for acquiring physiological signals according to claim 1, wherein the step of deleting the part of the physiological signals in the invalid wearing state period and correcting the physiological signals in the exercise period by using a kalman filtering method to obtain valid physiological signals further comprises:

6. The physiological signal collection method according to claim 1, wherein collecting the impedance of a conductive closed loop formed by two detection electrodes contacting with the skin of the subject, marking the time period when the impedance is out of a set value range as a detection device wearing state invalid period comprises:

deleting a portion of the physiological signal within the absolute null period;

7. The method for acquiring physiological signals according to claim 1, wherein the method for acquiring the impedance of a conductive closed loop formed by the contact of two detection electrodes with the skin of the subject and marking the time period of the impedance outside the range of the set value range as the invalid period of the wearing state of the detection device further comprises the following steps:

8. The method for acquiring physiological signals according to claim 1, wherein before synchronously acquiring the physiological signals of the subject and the acceleration information acquired by the acceleration sensor, the method further comprises:

9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the steps of the method according to any of claims 1 to 8 are implemented when the program is executed by the processor.

10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 8.