Self-adaptive vomit stopping device and control method thereof

Abstract

The invention discloses a self-adaptive vomiting stopping device and a control method thereof.The device comprises a shell, an electrode plate, a pulse wave collecting unit and a driving control unit, and the two ends of the shell are connected with wrist straps; the two electrode plates are arranged on the inner side of the wrist strap at an interval; the pulse wave acquisition unit acquires pulse wave information of a user in real time; and a microcontroller of the driving control unit is connected with the electrode plate through a discharging circuit. During use, the device is worn on the wrist of a user, and the electrode plates are tightly attached to the two sides of the Neiguan point of the wrist of the human body; the microcontroller sets the current of the discharge circuit according to the detected and analyzed pulse wave information, and controls the stimulation intensity of the electrode slice on the Neiguan point; in addition, the microcontroller analyzes the occurrence interval time of each wave crest according to historical data and latest sampled data in real time to obtain the heart rate change rate, and adjusts the stimulation intensity of the electrode slice on the Neiguan point according to the heart rate change rate. The device is convenient to operate and adapts to the physical state of a user to adjust the stimulation intensity.

Description

Technical Field

[0001] The invention relates to an antiemetic device, and in particular to an adaptive antiemetic device and a control method thereof. Background Art

[0002] Nausea and vomiting caused by pregnancy, motion sickness, seasickness, VR vertigo, surgery, cardiovascular and cerebrovascular diseases, chemotherapy drugs, etc. are common clinical symptoms. These vomiting mechanisms are very complicated, but some scholars believe that the whole process is mainly regulated and controlled by the vomiting center. The vomiting center located in the brainstem is responsible for regulating the vomiting reaction. This area receives stimulation information from multiple neural pathways, including stimulation of the throat, gastrointestinal tract, mediastinum and higher cortical centers, visceral signals, visual and vestibular system signals, and on the other hand, there is stimulation of the chemoreceptor excitation area. These pathways can stimulate the center to cause vomiting reflexes, leading to nausea and vomiting. According to the theory of traditional Chinese medicine acupuncture, the "Neiguan" point is a special acupoint for relieving nausea and vomiting. Neiguan point is an acupoint of the pericardium meridian, located on the inner side of the forearm, about 2 inches on the horizontal coordinate of the wrist. According to the theory of traditional Chinese medicine, Neiguan point has the following mechanisms and effects in relieving nausea and vomiting: the stimulation of Neiguan point can help harmonize the spleen and stomach, enhance digestive function, and thus reduce nausea and vomiting caused by spleen and stomach disorders. Acupuncture or massage of Neiguan acupoint can dredge the pericardium meridian, improve the circulation of qi and blood, and relieve physical discomfort. Stimulation of Neiguan acupoint helps calm the mind, relieve anxiety and tension, and thus reduce the impact of emotions on nausea and vomiting. Stimulation of Neiguan acupoint can promote local and systemic blood circulation and enhance the body's ability to adapt to discomfort. Stimulation of Neiguan acupoint can effectively relieve nausea and vomiting caused by various factors, such as vomiting during pregnancy and nausea caused by chemotherapy. Clinically, many patients can clearly feel the reduction of nausea and vomiting frequency after receiving acupuncture or acupoint massage. In short, the mechanism of vomiting is complex, and Chinese medicine can relieve the symptoms of nausea and vomiting to a certain extent by regulating Neiguan acupoint, which has good clinical application prospects.

[0003] Although there are related electronic antiemetic devices on the market, which can stimulate the acupuncture points of the human body periodically to relieve vomiting symptoms by simulating bioelectric signals, they are complicated to use and inconvenient to wear by one person, and there are few gears to choose from. In addition, the stimulation intensity cannot be adjusted according to the user's personal situation, and it may be counterproductive. Moreover, after long-term use, the wearer will become numb to the unchanged stimulation intensity, and the expected effect cannot be achieved. Summary of the invention

[0004] Based on this, the present invention provides an adaptive antiemetic device and a control method thereof, which are convenient for wearing and adjustment, and can adjust the stimulation according to changes in the user's pulse wave and other conditions, thereby improving the stimulation effect and reducing the occurrence of discomfort reactions.

[0005] In order to achieve the above-mentioned purpose, in the first aspect, the present invention provides an adaptive antiemetic device, comprising a housing, an electrode sheet, a pulse wave acquisition unit and a drive control unit. A wristband is connected to both ends of the housing; the electrode sheet comprises two electrodes which are arranged at intervals on the inner side of the wristband; the pulse wave acquisition unit is configured to collect the pulse wave information of the user in real time; the drive control unit comprises a microcontroller and a discharge circuit arranged in the housing, the microcontroller is connected to the electrode sheet through the discharge circuit, and the microcontroller is configured to receive and control the current of the discharge circuit according to the pulse wave information, and control the stimulation intensity of the electrode sheet on the wrist acupoints.

[0006] Furthermore, the inner surface of the drive control unit is connected to the electrode sheet through a spring pin, and the drive control unit includes a microcontroller, a lithium battery, a power supply circuit, a charging circuit, a boost circuit, a voltage detection circuit, a discharge circuit, a pulse wave acquisition unit and a data storage chip.

[0007] Furthermore, the pulse wave acquisition unit is provided with an original pulse wave signal processing circuit, including a filtering part, a signal amplifying part and a waveform shaping part. The single chip microcomputer is connected to the original pulse wave signal processing circuit and is configured to perform digital signal processing on the data after filtering, signal amplification and waveform shaping to reduce the influence of ambient light.

[0008] In order to achieve the above object, in a second aspect, the present invention provides an adaptive anti-emetic control method, using the adaptive anti-emetic device, comprising:

[0009] The adaptive antiemetic device is worn on the wrist of the user, and the electrode sheets are closely attached to both sides of the Neiguan acupoints of the wrist through the action of the wristband;

[0010] The pulse wave acquisition unit detects the user's pulse wave and analyzes the peaks and troughs. The microcontroller sets the current of the discharge circuit according to the detected and analyzed information, and controls the stimulation intensity of the electrode sheet on the Neiguan acupoint.

[0011] During use, the pulse wave acquisition unit samples the pulse wave, and the microcontroller analyzes the interval time of each wave peak in real time through historical data and the latest sampled data to obtain the heart rate change rate, and adjusts the stimulation intensity of the electrode sheet to the Neiguan acupoint according to the heart rate change rate;

[0012] When the user's heart rate change rate and heartbeat completion time change rate exceed 10% of the set threshold, the microcontroller controls the electrode sheet to stop stimulating the Neiguan acupoint.

[0013] Furthermore, gear selection is performed during use: the microcontroller controls the boost circuit to pre-charge the capacitor, and through the voltage feedback of the voltage detection circuit, the capacitor and voltage are stabilized at the target value, and the driving control unit controls the discharge circuit to control the frequency and width of the pulse.

[0014] Furthermore, during use, the pulse wave acquisition unit samples the pulse wave and analyzes the peaks and troughs, which are stored in the data storage chip. The microcontroller compares the historical data and the latest sampled data in real time, analyzes the interval time between each peak, and obtains the heart rate change rate: the time from adjacent peaks to troughs is determined as the time it takes for a heartbeat to complete, and the time it takes to complete each heartbeat is analyzed to obtain the heartbeat completion time change rate.

[0015] Furthermore, by obtaining the user's heart rate change rate and heartbeat completion time change rate in real time, the microcontroller controls the pulse change in real time:

[0016] When the heart rate change rate exceeds its upper threshold, the pulse frequency is reduced in steps of 5% of the original pulse frequency;

[0017] When the heart rate variation rate exceeds its lower threshold, the pulse frequency is increased by 5% of the original pulse frequency until the heart rate variation rate is within the normal range;

[0018] When the heartbeat completion time change rate exceeds its upper threshold, the pulse width is reduced in steps of 5% of the original pulse width;

[0019] When the heartbeat completion time change rate exceeds its lower threshold, the pulse width is increased in steps of 5 percent of the original pulse width until the heartbeat completion time change rate is within a normal range.

[0020] Further, the pulse wave measurement and analysis process includes:

[0021] First, pulse wave data were obtained by photoplethysmography;

[0022] Then, the pulse wave data is converted from the time domain to the frequency domain and the noise is filtered out by a bandpass filter;

[0023] Then, the frequency domain data is converted into time domain data through inverse Fourier transform;

[0024] Finally, the scale-invariant feature transform is used to obtain the local features of the pulse wave data and find the peak and trough positions;

[0025] Furthermore, in the process of finding the peak and trough positions, a multi-scale space of pulse wave data is constructed, and the process includes:

[0026] First, the signal data is sampled so that the resolution of the data is gradually reduced. The sampling is performed three times to obtain four sets of data including the original data.

[0027] Then, the four sets of data are smoothed by using Gaussian filtering, where σ is a smoothing factor, and σ is multiplied by a proportional coefficient k to obtain a new smoothing factor k*σ.

[0028]

[0029] Repeat the above steps four times to obtain 4*5 groups of data. The original four groups of data are increased to five layers each, and each group has five layers of scale space:

[0030] Then, for each group of five-layer scale spaces, a Gaussian difference scale space is constructed: five layers of adjacent scale spaces are subtracted to obtain four layers of Gaussian difference scale space;

[0031] Finally, the positions where the signal strength changes significantly in the Gaussian difference scale space are selected to obtain the positions of the peak and trough feature points.

[0032] Further, at each data position in the Gaussian difference scale space, the value of the position is compared with its two adjacent values ​​in the current layer and its six values ​​in the upper and lower layers; if the value is greater than all adjacent values, the position is a peak, and if the value is less than all adjacent values, the position is a trough; or,

[0033] Normalize the eigenvalue position vectors of each scale space to obtain four groups of normalized signal data eigenvalue position vectors, and divide the four groups of vectors equally by weight to obtain the positions of the peaks and troughs.

[0034] Compared with the prior art, the adaptive anti-emetic device and control method provided by the present invention have the following technical advantages:

[0035] 1. The wristband assembly is convenient for a single person to wear. The tightening adjustment of the wristband also makes the electrode sheet close to the acupuncture points. The electrical signals generated by the electrode sheet periodically stimulate the acupuncture points of the human body to relieve vomiting symptoms. It is easy to wear and easy to operate. The five-speed setting is convenient for adjustment and operation. The stimulation intensity can be adjusted according to the user's personal situation to obtain a suitable adjustment effect.

[0036] 3. Use the pulse wave acquisition unit to detect the user's status and select the appropriate stimulation intensity. In addition, the user's pulse wave will be detected during long-term use to obtain the user's heart rate information and adjust the stimulation intensity in real time to achieve the expected effect, avoiding the problem of numbness to the unchanged stimulation intensity after long-term use by the wearer;

[0037] 3. The pulse wave acquisition unit samples the pulse wave, constructs a Gaussian difference multi-scale space of the pulse wave data, accurately obtains the peaks and troughs, and obtains the heart rate change rate by analyzing the interval time of each peak in real time through historical data and the latest sampled data according to the microcontroller, and adjusts the stimulation intensity of the electrode to the Neiguan acupoint according to the heart rate change rate, thereby improving the accuracy and adjustability of the electrode stimulation and enhancing the antiemetic effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0039] Figure 1 is a structural block diagram of an embodiment of the provided adaptive antiemetic device;

[0040] Figure 2 is a flowchart of an antiemetic control method of the provided adaptive antiemetic device;

[0041] Figure 3 It is a block diagram of the charge and discharge control process of the provided adaptive antiemetic device.

[0042] Description of the accompanying drawings:

[0043] 1-electrode sheet, 2-microcontroller, 3-discharging circuit, 4-boosting circuit, 5-pulse wave acquisition unit, 6-data storage chip, 7-power supply circuit, 8-charging circuit. DETAILED DESCRIPTION

[0044] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. The following description of at least one exemplary embodiment is actually only illustrative and is by no means intended to limit the present invention and its application or use. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0045] like Figure 1 As shown, the present invention provides an adaptive anti-emetic device, including a housing, an electrode sheet 1, a pulse wave acquisition unit 5, and a drive control unit. Wristbands are connected to both ends of the housing; the electrode sheet 1 includes two electrodes spaced apart and arranged inside the wristband; the pulse wave acquisition unit 5 is configured to collect the pulse wave information of the user in real time; the drive control unit includes a microcontroller 2 and a discharge circuit 3 arranged in the housing, the microcontroller 2 is connected to the electrode sheet 1 through the discharge circuit 3, and the microcontroller 2 is configured to receive and control the current of the discharge circuit 3 according to the pulse wave information, so as to control the stimulation intensity of the electrode sheet 1 on the wrist acupoints.

[0046] The inner surface of the driving control unit is connected to the electrode sheet 1 through a spring pin. The driving control unit includes a microcontroller 2, a lithium battery, a power supply circuit 7, a charging circuit 8, a boost circuit 4, a voltage detection circuit, a discharge circuit 3, a pulse wave acquisition unit 5 and a data storage chip 6. The pulse wave acquisition unit 5 is provided with an original pulse wave signal processing circuit, including a filtering part, a signal amplification part and a waveform shaping part. The single chip microcomputer is connected to the original pulse wave signal processing circuit and is configured to perform digital signal processing on the data after filtering, signal amplification and waveform shaping to reduce the influence of ambient light.

[0047] Based on the above embodiments, the provided adaptive anti-emetic device is convenient for a single person to wear through the setting of the wristband assembly. The tightening adjustment of the wristband also makes the electrode sheet close to the acupoints. The electrical signals generated by the electrode sheet periodically stimulate the acupoints of the human body to relieve vomiting symptoms. It is easy to wear and simple to operate. The five-speed setting facilitates the adjustment operation, and the stimulation intensity can be adjusted according to the user's personal situation to obtain a suitable adjustment effect.

[0048] like Figure 2 and Figure 3 As shown, at the same time, the present invention provides a control method for adaptive anti-emetic, using the adaptive anti-emetic device, comprising:

[0049] The adaptive antiemetic device is worn on the wrist of the user, and the electrode sheet 1 is closely attached to both sides of the Neiguan acupoints of the wrist through the action of the wristband;

[0050] The pulse wave acquisition unit 5 detects the user's pulse wave and analyzes the peaks and troughs. The microcontroller 2 sets the current of the discharge circuit 3 according to the detected and analyzed information, and controls the stimulation intensity of the electrode sheet 1 on the Neiguan acupoint.

[0051] During use, the pulse wave acquisition unit 5 samples the pulse wave, and the microcontroller 2 analyzes the interval time of each wave peak in real time through the historical data and the latest sampled data to obtain the heart rate change rate, and adjusts the stimulation intensity of the electrode sheet 1 to the Neiguan acupoint according to the heart rate change rate;

[0052] When the user's heart rate change rate and heartbeat completion time change rate exceed 10% of the set threshold, the microcontroller 2 controls the electrode sheet 1 to stop stimulating the Neiguan acupoint.

[0053] A pulse wave acquisition unit is used to detect the user's status and select the appropriate stimulation intensity. The user's pulse wave is also detected during long-term use to obtain the user's heart rate information and adjust the stimulation intensity in real time to achieve the desired effect, avoiding numbness problems caused by unchanged stimulation intensity after long-term use by the wearer.

[0054] The gear is selected during use: the microcontroller 2 controls the boost circuit 4 to pre-charge the capacitor, and through the voltage feedback of the voltage detection circuit, the capacitor and voltage are stabilized at the target value, and the driving control unit controls the discharge circuit 3 to control the frequency and width of the pulse.

[0055] During use, the pulse wave acquisition unit 5 samples the pulse wave and analyzes the peaks and troughs, and stores them in the data storage chip 6. The microcontroller 2 compares the historical data with the latest sampled data in real time, analyzes the interval time of each peak, and obtains the heart rate change rate: the time from the adjacent peak to the trough is determined as the time for a heartbeat to complete, and the time for each heartbeat to complete is analyzed to obtain the heartbeat completion time change rate. By obtaining the user's heart rate change rate and heartbeat completion time change rate in real time, the microcontroller 2 controls the pulse change in real time:

[0056] When the heart rate change rate exceeds its upper threshold, the pulse frequency is reduced in steps of 5% of the original pulse frequency;

[0057] When the heart rate variation rate exceeds its lower threshold, the pulse frequency is increased by 5% of the original pulse frequency until the heart rate variation rate is within the normal range;

[0058] When the heartbeat completion time change rate exceeds its upper threshold, the pulse width is reduced in steps of 5% of the original pulse width;

[0059] When the heartbeat completion time change rate exceeds its lower threshold, the pulse width is increased in steps of 5 percent of the original pulse width until the heartbeat completion time change rate is within a normal range.

[0060] During use, the pulse wave measurement and analysis process includes:

[0061] First, pulse wave data were obtained by photoplethysmography;

[0062] Then, the pulse wave data is converted from the time domain to the frequency domain and the noise is filtered out by a bandpass filter;

[0063] Then, the frequency domain data is converted into time domain data through inverse Fourier transform;

[0064] Finally, the scale-invariant feature transform is used to obtain the local features of the pulse wave data and find the peak and trough positions;

[0065] Furthermore, in the process of finding the peak and trough positions, a multi-scale space of pulse wave data is constructed, and the process includes:

[0066] First, the signal data is sampled so that the resolution of the data is gradually reduced. The sampling is performed three times to obtain four sets of data including the original data.

[0067] Then, the four groups of data are smoothed, and the above steps are repeated four times to obtain 4*5 groups of data. The original four groups of data are increased to five layers each, and each group has five layers of scale space;

[0068] Then, for each group of five-layer scale spaces, a Gaussian difference scale space is constructed: five layers of adjacent scale spaces are subtracted to obtain four layers of Gaussian difference scale space;

[0069] Finally, the positions where the signal strength changes significantly in the Gaussian difference scale space are selected to obtain the positions of the peak and trough feature points.

[0070] At each data position in the Gaussian difference scale space, the value of the position is compared with its two adjacent values ​​in the current layer and its six values ​​in the upper and lower layers; if the value is greater than all adjacent values, the position is a peak; if the value is less than all adjacent values, the position is a trough; or,

[0071] Normalize the eigenvalue position vectors of each scale space to obtain four groups of normalized signal data eigenvalue position vectors, and divide the four groups of vectors equally by weight to obtain the positions of the peaks and troughs.

[0072] The pulse wave acquisition unit samples the pulse wave, constructs a Gaussian difference multi-scale space of the pulse wave data, accurately obtains the peaks and troughs, and obtains the heart rate change rate by analyzing the interval time of each peak in real time through historical data and the latest sampled data according to the microcontroller, and adjusts the stimulation intensity of the electrode on the Neiguan acupoint according to the heart rate change rate, thereby improving the accuracy and adjustability of the electrode stimulation and enhancing the antiemetic effect.

[0073] An adaptive antiemetic device and a control method thereof according to the present invention are described below in conjunction with specific embodiments to make the solution clearer.

[0074] like Figure 1 , Figure 2 and Figure 3As shown, in the specific implementation process, the provided adaptive antiemetic device includes a shell, which is divided into an upper shell and a lower shell. There is a cavity in the middle of the shell for placing a drive control unit. The upper shell and the lower shell are fixed by ultrasonic welding, and the two ends of the shell are respectively connected with a detachable wristband assembly. The outer surface of the upper shell is provided with a display interface and buttons of five gear indicator lights, a charging indicator light, and a status indicator light, and the inner surface of the upper shell is provided with a limit card slot and a screw hole for fixing the drive control unit. The drive control unit is used to control the operation of the wristband, which is fixed to the inner surface of the upper shell by screws. The drive control unit includes a microcontroller 2 (MCU, Micro Controller Unit), a lithium battery, a power supply circuit 7, a charging circuit 8, a boost circuit 4, a voltage detection circuit, a discharge circuit 3, a pulse wave acquisition unit 4, a data storage chip 6, a gear indicator light, a charging indicator light, and a status indicator light. The lower shell has two semicircular electrode sheets 1 with convex points connected to the drive control unit by a spring ejector pin, a charging interface for magnetic charging, and a photoelectric capacitance pulse wave acquisition unit 4. The electrode sheet 1 is connected to the discharge circuit 3, acts on the acupuncture points of the human body, and stimulates through an adjustable pulse current. In addition, the electrode sheet 1 is closely attached to the acupuncture points on the wrist of the human body by adjusting the tightening of the magnetic wristband.

[0075] During use, long press the button for 3s to turn on or off, and the gear can be set by pressing the button after turning on. In the turned-on state, the MCU obtains the user's valid data through the pulse wave acquisition unit 4 and selects the appropriate stimulation intensity through the set calibration range. The pulse wave acquisition unit 4 is used to measure the peak and trough of the pulse wave, and its data is saved in the data storage chip 6. The housing is fixed to the user's wrist with a wristband so that the two electrodes are located on both sides of the Neiguan acupoint. Long press the button for 3s to turn on the MCU, and the gear can be set by pressing the button after turning on.

[0076] The status indicator light on the right side of the button will light up whenever the button is pressed, and will go out when the button is released. The indicator light on the left side of the button will stay on during the startup state. The drive control unit will periodically detect the lithium battery power. When the lithium battery power is low, the indicator light on the left side of the button will flash to remind the user to charge and the device will not work. During the charging process, the charging indicator light will light up red to indicate that it is charging, and will light up green after charging is completed to indicate that the lithium battery is fully charged.

[0077] There are five gear indicator lights on the display screen. The number of gear indicator lights that light up corresponds to gears 1 to 5, and the five gears correspond to five stimulation voltage values. The gear flag is set to Flag, and the initial value of Flag is 0. Click the button once to increase the gear, and Flag will increase by one. Double-click the button to decrease the gear, and Flag will decrease by one. Flag will be set to zero when upshifting at gear 5 and downshifting at gear 1.

[0078] After the gear selection is completed, the MCU will control the boost circuit 4 through the PWM_BOOST signal waveform to pre-charge the capacitor and stabilize the capacitor voltage at the target value through the voltage feedback of the voltage detection circuit. The MCU can control the discharge circuit 3 through the PWM_1 and PWM_2 signals to complete the frequency and width control of the pulse.

[0079] During use, the device samples the pulse wave and analyzes the positions of the peaks and troughs and records and stores them in the data storage chip 6. The MCU analyzes the interval time of N1 peaks in real time through historical data and the latest sampled data to obtain the heart rate change rate A. The time from the adjacent peak to the trough can be equivalent to the time for one heartbeat to complete. The time for N2 heartbeats to complete is analyzed to obtain the heartbeat completion time change rate B.

[0080] The user's heart rate change rate A and heartbeat completion time change rate B are obtained in real time through the data storage. When the heart rate change rate A exceeds its upper threshold value A1, the pulse frequency is reduced by 5% of the original pulse frequency. When the heart rate change rate A exceeds its lower threshold value A2, the pulse frequency is increased by 5% of the original pulse frequency until the heart rate change rate A is within the normal range. When the heartbeat completion time change rate B exceeds its upper threshold value B1, the pulse width is reduced by 5% of the original pulse width. When the heartbeat completion time change rate B exceeds its lower threshold value B2, the pulse width is increased by 5% of the original pulse width until the heartbeat completion time change rate B is within the normal range.

[0081] When the user's heart rate change rate A and heartbeat completion time change rate B exceed 10% of the set threshold, the MCU will stop outputting the PWM_BOOST signal, PWM_1 signal and PWM_2 signal, and the device stops working.

[0082] Pulse wave measurement is to detect the changes in blood caused by heartbeat through photoelectric volumetric pulse wave scanning (PPG), generate different LED light reflection signals, use photoelectric sensors to convert the pulse wave beats into electrical signals, and then amplify, shape and filter them, and finally send them to the single-chip microcomputer for processing. The original pulse wave signal processing circuit mainly includes three parts: signal amplification, filtering, and waveform shaping. The single-chip microcomputer then performs digital signal processing on the data processed by the hardware to reduce the influence of ambient light. In the digital signal processing process, the one-dimensional pulse wave signal is sampled at 256 points so that it can be calculated by FFT (Fast Fourier Transform), and the pulse wave data is converted from time domain to frequency domain for processing. Since the frequency of the pulse wave signal is about 0.7Hz-3.0Hz, the frequency outside this frequency range can be regarded as noise, so a bandpass filter is used to filter out the noise. The frequency domain data is converted to time domain data through inverse Fourier transform.

[0083] The peak of PPG reflects the state after a heart contraction, and the trough reflects the state after a heart diastole.

[0084] The scale-invariant feature transform (SIFT) is used to obtain the local features of the pulse wave data and find the locations of the PPG peaks and troughs within the range.

[0085] First, we construct a multi-scale space for pulse wave data, which helps detect features at different scales: First, we downsample the signal data so that the resolution of the data is gradually reduced. We sample three times and finally get four sets of data including the original data. We smooth the four sets of data using Gaussian filtering. Here, σ is the smoothing factor. Multiply σ by a proportional coefficient k to get a new smoothing factor k*σ.

[0086]

[0087] After repeating this process four times, we can finally get 4*5 sets of data, and each of the original four sets of data has been increased to five layers. This is the scale space with four sets of five layers in each set.

[0088] Then, a Gaussian difference scale space is constructed for each group of five layers, and the four-layer Gaussian difference scale space can be obtained by subtracting the five adjacent scale spaces.

[0089] Then select the location where the signal strength changes significantly in the Gaussian difference scale space, that is, the location that may be the peak or trough feature point. At each data location in the differential scale, compare the value of the location with its two adjacent values ​​in the current layer and its six values ​​in the upper and lower layers. Since the comparison is to be made at adjacent scales, a Gaussian difference layer with four layers in each group can only perform extreme point detection at two scales in the middle two layers. If the value is greater than all its adjacent values, the location is selected as a peak. If the value is less than all its adjacent values, the location is selected as a trough.

[0090] When a continuous function is sampled, its true maximum or minimum value may actually be between the sample points. Therefore, it is necessary to fit an interpolation function to the discrete number, and then find the extreme value position with improved accuracy. After the above steps, it has been found that the eigenvalues ​​exist at different scales, but it is necessary to combine the eigenvalues ​​at multiple scales. Since this is a one-dimensional data, it is only necessary to determine the position of the eigenvalue point in the entire sample. Normalize the eigenvalue position vectors at each scale. You can get four sets of normalized signal data eigenvalue position vectors, and after weighting and dividing the four sets of vectors equally, you can get the positions of the peaks and troughs in the PPG.

[0091] When the user presses the button for a long time, the MCU will stop outputting the PWM_BOOST signal, PWM_1 signal, and PWM_2 signal, and the device will stop working.

[0092] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein, but these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An adaptive antiemetic device, characterized in that: include: A housing, with wrist straps connected to both ends; The electrode sheets (1) include two electrodes which are arranged at intervals on the inner side of the wristband; A pulse wave collection unit (5) is configured to collect the user's pulse wave information in real time; and The drive control unit comprises a microcontroller (2) and a discharge circuit (3) arranged in a housing, wherein the microcontroller (2) is connected to an electrode sheet (1) via the discharge circuit (3), and the microcontroller (2) is configured to receive and control the current of the discharge circuit (3) according to pulse wave information, so as to control the stimulation intensity of the electrode sheet (1) on the wrist acupuncture points.

2. The adaptive antiemetic device according to claim 1, characterized in that: The inner surface of the drive control unit is connected to the electrode sheet (1) via a spring pin, and the drive control unit comprises a microcontroller (2), a lithium battery, a power supply circuit (7), a charging circuit (8), a boost circuit (4), a voltage detection circuit, a discharge circuit (3), a pulse wave acquisition unit (5) and a data storage chip (6).

3. The adaptive antiemetic device according to claim 1, characterized in that: The pulse wave acquisition unit (5) is provided with an original pulse wave signal processing circuit, including a filtering part, a signal amplifying part and a waveform shaping part. The single chip microcomputer is connected to the original pulse wave signal processing circuit and is configured to perform digital signal processing on the data after filtering, signal amplification and waveform shaping processing, so as to reduce the influence of ambient light.

4. An adaptive antiemetic control method, using the adaptive antiemetic device according to any one of claims 1 to 3, characterized in that: include: The adaptive antiemetic device is worn on the wrist of a user, and the electrode sheets (1) are closely attached to both sides of the Neiguan acupoints on the wrist of the human body through the action of the wristband; The pulse wave acquisition unit (5) detects the pulse wave of the user and analyzes the peaks and troughs of the pulse wave, and the microcontroller (2) sets the current of the discharge circuit (3) according to the detected and analyzed information, and controls the stimulation intensity of the electrode sheet (1) on the Neiguan acupoint; During use, the pulse wave acquisition unit (5) samples the pulse wave, and the microcontroller (2) analyzes the interval time of each wave peak in real time through historical data and the latest sampled data to obtain the heart rate change rate, and adjusts the stimulation intensity of the electrode sheet (1) on the Neiguan acupoint according to the heart rate change rate; When the user's heart rate change rate and heartbeat completion time change rate exceed 10 percent of the set threshold value, the microcontroller (2) controls the electrode sheet (1) to stop stimulating the Neiguan acupoint.

5. The adaptive anti-emetic control method according to claim 1, characterized in that: The gear position is selected during use: the microcontroller (2) controls the boost circuit (4) to pre-charge the capacitor, and through the voltage feedback of the voltage detection circuit, the capacitor and the voltage are stabilized at the target value, and the driving control unit controls the discharge circuit (3) to control the frequency and width of the pulse.

6. The adaptive anti-emetic control method according to claim 1, characterized in that: The pulse wave acquisition unit (5) samples the pulse wave and analyzes the peaks and troughs, and stores them in the data storage chip (6). The microcontroller (2) compares the historical data with the latest sampled data in real time, analyzes the interval time of each peak, and obtains the heart rate change rate: the time from adjacent peaks to troughs is determined as the time for a heartbeat to be completed, and the time for each heartbeat to be completed is analyzed to obtain the heartbeat completion time change rate.

7. The adaptive anti-emetic control method according to claim 1, characterized in that: By acquiring the user's heart rate change rate and heartbeat completion time change rate in real time, the microcontroller (2) controls the pulse change in real time: When the heart rate change rate exceeds its upper threshold, the pulse frequency is reduced in steps of 5% of the original pulse frequency; When the heart rate variation rate exceeds its lower threshold, the pulse frequency is increased by 5% of the original pulse frequency until the heart rate variation rate is within the normal range; When the heartbeat completion time change rate exceeds its upper threshold, the pulse width is reduced in steps of 5% of the original pulse width; When the heartbeat completion time change rate exceeds its lower threshold, the pulse width is increased in steps of 5 percent of the original pulse width until the heartbeat completion time change rate is within a normal range.

8. The adaptive anti-emetic control method according to claim 1, characterized in that: The process of pulse wave measurement and analysis includes: First, pulse wave data were obtained by photoplethysmography; Then, the pulse wave data is converted from the time domain to the frequency domain and the noise is filtered out by a bandpass filter; Then, the frequency domain data is converted into time domain data through inverse Fourier transform; Finally, the scale-invariant feature transform is used to obtain the local features of the pulse wave data and find the peaks and troughs.

9. The adaptive anti-emetic control method according to claim 1, characterized in that: In the process of finding the peaks and troughs, a multi-scale space of pulse wave data is constructed. The process includes: First, the signal data is sampled so that the resolution of the data is gradually reduced. The sampling is performed three times to obtain four sets of data including the original data. Then, the four sets of data are smoothed by using Gaussian filtering, where σ is a smoothing factor, and σ is multiplied by a proportional coefficient k to obtain a new smoothing factor k*σ; Repeat the above steps four times to obtain 4*5 groups of data. The original four groups of data are increased to five layers each, and each group has five layers of scale space: Then, for each group of five-layer scale spaces, a Gaussian difference scale space is constructed: five layers of adjacent scale spaces are subtracted to obtain four layers of Gaussian difference scale space; Finally, the positions where the signal strength changes significantly in the Gaussian difference scale space are selected to obtain the positions of the peak and trough feature points.

10. The adaptive anti-emetic control method according to claim 1, characterized in that: At each data position in the Gaussian difference scale space, the value of the position is compared with its two adjacent values ​​in the current layer and its six values ​​in the upper and lower layers; if the value is greater than all adjacent values, the position is a peak; if the value is less than all adjacent values, the position is a trough; or, Normalize the eigenvalue position vectors of each scale space to obtain four groups of normalized signal data eigenvalue position vectors, and divide the four groups of vectors equally by weight to obtain the positions of the peaks and troughs.

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