CN111012328A - Biofeedback device and method - Google Patents
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- A61B5/0004—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network characterised by the type of physiological signal transmitted
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Abstract
The invention provides a biofeedback device and a method, wherein the device comprises: the system comprises a collector, a transmitter and a processor; the collector, the transmitter and the processor are connected in sequence; the collector is used for collecting electrocardiosignals of a user; the transmitter is used for transmitting the electrocardiosignal to the processor; the processor is used for carrying out time domain analysis and frequency domain analysis on the electrocardiosignals and feeding back analysis results to a user so that the user can autonomously adjust the physical and mental states through breathing according to the analysis results; the analysis results include a plurality of HRV time domain plots, HRV frequency domain power spectral density plots, cumulative score change plots, and HRV frequency domain distribution histograms. According to the invention, the time domain analysis and the frequency domain analysis are carried out on the electrocardiosignals of the user through the heart rate variability, so that the analysis accuracy of the biofeedback technology is improved, and the biofeedback training can be effectively guided.
Description
Technical Field
The invention relates to the technical field of biological training, in particular to a biofeedback device and a biofeedback method.
Background
With the continuous acceleration of life rhythm, the pressure brought to people from various aspects such as working and life is more and more, psychological pressure and bad emotion can cause heart rhythm disorder, and the normal exertion of physiological functions is not facilitated, most sensitive reaction indexes are found by observing the changes of myoelectricity, skin conductance, finger tip skin dampness, blood pressure and the like in the conventional biofeedback training, and then corresponding measures are taken to adjust the psychological pressure according to the indexes, however, a plurality of indexes are required to be monitored in the actual training process, and the condition that the biofeedback result is inaccurate due to unreasonable index selection or unreasonable index analysis exists, so that the effectiveness of the biofeedback training is poor, and the biofeedback training cannot be effectively guided.
Disclosure of Invention
In view of the above, the present invention is directed to a biofeedback apparatus and method for improving the analysis accuracy of a biofeedback technique, so as to effectively guide the biofeedback training.
In a first aspect, an embodiment of the present invention provides a biofeedback device, where the device includes: the system comprises a collector, a transmitter and a processor; the collector, the transmitter and the processor are connected in sequence; the collector is used for collecting electrocardiosignals of a user; the transmitter is used for transmitting the electrocardiosignal to the processor; the processor is used for carrying out time domain analysis and frequency domain analysis on the electrocardiosignals and feeding back analysis results to a user so that the user can autonomously adjust the physical and mental states through breathing according to the analysis results; the analysis results include a plurality of HRV time domain plots, HRV frequency domain power spectral density plots, cumulative score change plots, and HRV frequency domain distribution histograms.
With reference to the first aspect, an embodiment of the present invention provides a first possible implementation manner of the first aspect, where the collector includes a physiological parameter recording detector, and the physiological parameter recording detector is connected to the transmitter; the physiological parameter recording detector is used for collecting electrocardiosignals and sending the electrocardiosignals to the transmitter.
With reference to the first aspect, an embodiment of the present invention provides a second possible implementation manner of the first aspect, where the transmitter includes a bluetooth device, and the bluetooth device is connected to the physiological parameter recording detector and is configured to send the electrocardiographic signal to the processor.
With reference to the first aspect, an embodiment of the present invention provides a third possible implementation manner of the first aspect, where the transmitter includes a bluetooth adapter; the Bluetooth adapter is in wireless communication connection with the Bluetooth equipment and is used for receiving electrocardiosignals; the Bluetooth adapter is also connected with the processor through a USB interface and used for sending the received electrocardiosignals to the processor.
With reference to the third possible implementation manner of the first aspect, an embodiment of the present invention provides a fourth possible implementation manner of the first aspect, where the processor is further configured to control a virtual serial port to be established between the bluetooth device and the bluetooth adapter for connection.
With reference to the first aspect, an embodiment of the present invention provides a fifth possible implementation manner of the first aspect, where the processor is further configured to: obtaining an HRV time domain curve graph according to the electrocardiosignals; obtaining an HRV frequency domain power spectral density graph according to an HRV time domain curve graph; and obtaining an HRV frequency domain distribution histogram according to the HRV frequency domain power spectrum density graph, and obtaining an accumulation score change curve graph according to the HRV frequency domain power spectrum density graph and the HRV frequency domain distribution histogram.
With reference to the first aspect, an embodiment of the present invention provides a sixth possible implementation manner of the first aspect, where the processor includes a display screen, the processor is configured to feed back the analysis result to the user through the display screen, and a display form of the analysis result includes a graphic, a text, a sound, and an animation.
With reference to the first aspect, an embodiment of the present invention provides a seventh possible implementation manner of the first aspect, and the processor is further configured to perform backup storage on the electrocardiographic signal and the analysis result, so as to obtain backup storage data.
With reference to the seventh possible implementation manner of the first aspect, an embodiment of the present invention provides an eighth possible implementation manner of the first aspect, where the processor is further configured to perform statistical analysis on multiple backup saving data of the same user, and create a biofeedback training scheme for the user according to a result of the statistical analysis.
In a second aspect, an embodiment of the present invention further provides a biofeedback method, where the method is applied to the biofeedback device in the first aspect, and the method includes: the collector collects electrocardiosignals of a user; the transmitter transmits the electrocardiosignals to the processor; the processor performs time domain analysis and frequency domain analysis on the electrocardiosignals, and feeds back analysis results to a user so that the user can autonomously adjust the physical and mental states through breathing according to the analysis results; the analysis results include a plurality of HRV time domain plots, HRV frequency domain power spectral density plots, cumulative score change plots, and HRV frequency domain distribution histograms.
The embodiment of the invention has the following beneficial effects:
the invention provides a biofeedback device and a method, wherein the device comprises: the system comprises a collector, a transmitter and a processor; the collector, the transmitter and the processor are connected in sequence; the collector is used for collecting electrocardiosignals of a user; the transmitter is used for transmitting the electrocardiosignal to the processor; the processor is used for carrying out time domain analysis and frequency domain analysis on the electrocardiosignals and feeding back analysis results to a user so that the user can autonomously adjust the physical and mental states through breathing according to the analysis results; the analysis results include a plurality of HRV time domain plots, HRV frequency domain power spectral density plots, cumulative score change plots, and HRV frequency domain distribution histograms. According to the invention, the time domain analysis and the frequency domain analysis are carried out on the electrocardiosignals of the user through the heart rate variability, so that the analysis accuracy of the biofeedback technology is improved, and the biofeedback training can be effectively guided.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the invention as set forth above.
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a schematic structural diagram of a biofeedback device according to an embodiment of the present invention;
FIG. 2 is a HRV time domain graph under an ideal condition according to the embodiment of the present invention;
FIG. 3 is a diagram of the HRV frequency domain power spectral density under an ideal condition according to an embodiment of the present invention;
FIG. 4 is a schematic structural diagram of another biofeedback device provided in an embodiment of the present invention;
fig. 5 is a data flow diagram of a biofeedback method according to an embodiment of the present invention.
Icon: 101-a collector; 102-a transmitter; 103-a processor; 1011-physiological parameter record detector; 1021-a bluetooth device; 1022-Bluetooth adapter.
Detailed Description
To make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
At present, the balance of an autonomic nervous system can be well described by heart rate variability, the ability of a person to effectively cope with stress and bad emotion can be reflected, however, the application of a heart rate variability analysis technology in a biofeedback technology is very few, evaluation indexes related to the heart rate variability are used in some biofeedback products, but the evaluation indexes are limited to simple time domain indexes and hardly relate to indexes on frequency domain transformation, and corresponding technical principle research is not deep and detailed.
Based on this, the biofeedback device and the method provided by the embodiment of the invention can be applied to scenes in which biofeedback training is required.
To facilitate understanding of the present embodiment, a biofeedback device disclosed in the present embodiment will be described in detail first.
Referring to fig. 1, a schematic structural diagram of a biofeedback device is shown, wherein the device comprises: a collector 101, a transmitter 102 and a processor 103; the collector 101, the transmitter 102 and the processor 103 are connected in sequence;
the collector 101 is used for collecting electrocardiosignals of a user;
specifically, the collector 101 is worn on the body of the user, collects the electrocardiosignals of the user and sends the electrocardiosignals to the transmitter, so that the convenience and the comfort of the user in using the device can be improved.
The transmitter 102 is configured to transmit the electrocardiographic signal to the processor 103;
specifically, the transmitter 102 transmits the received electrocardiograph signal to the processor 103 in a wireless communication manner, and the wireless communication manner can effectively avoid the constraint feeling brought to the user by the traditional wired connection data transmission, so that the user can relax more freely in the feedback training.
The processor 103 is configured to perform time domain analysis and frequency domain analysis on the electrocardiosignal, and feed back an analysis result to the user, so that the user can autonomously adjust the physical and mental states through breathing according to the analysis result.
Specifically, the analysis result includes multiple kinds of HRV (Heart Rate Variability) time domain graphs, HRV frequency domain power spectral density graphs, cumulative score variation graphs, and HRV frequency domain distribution histograms.
Specifically, heart rate variability refers to the phenomenon that each heartbeat changes continuously with time. The time interval of each heartbeat corresponds to the instantaneous heart rate of a person, the instantaneous heart rate continuously fluctuates along with the change of the breathing, blood pressure and emotion of the person, the change is controlled by the autonomic nervous system of the human body, the heart rate variability analysis is a means for reflecting the powerful balance of the autonomic nervous system, and the autonomic nervous system adjusts the body operation to be in an ideal state by the deep breathing technology or focusing attention on the spirit, namely, the method for controlling the idea enables the autonomic balance to increase the activity of parasympathetic nerves, increase the synchronization of the heart and brain activities, enhance the resonance of the cardiovascular system and mutually draw other oscillation systems.
Specifically, the processor 103 performs time domain analysis and frequency domain analysis on the electrocardiosignal, and can effectively apply the heart rate variability analysis technology to the biofeedback technology, in the ideal state, the HRV time domain graph is similar to a sine wave on the waveform, and the HRV frequency domain power spectral density graph shows that the power spectrum is concentrated and the low-frequency power is greatly increased, especially around 0.1Hz (hertz), as shown in fig. 2 and 3, respectively, and conversely, the HRV time domain graph and the HRV frequency domain power spectral density graph are randomly distributed and have no obvious regularity.
Specifically, in the embodiment of the present invention, the processor 103 analyzes the cardiac electrical signal to obtain an analysis result, and feeds back the analysis result to the user, so that the user can adjust the breath or concentrate attention on the spirit according to the analysis result, and control the idea to increase the synchronization of cardiac and cerebral activities, etc. to adjust the analysis result fed back by the processor 103 in real time, so that the physical state of the user is gradually adjusted to an ideal state with the help of the analysis result, thereby improving the analysis accuracy of the biofeedback technology and improving the biofeedback training quality.
The embodiment of the invention provides a biofeedback device, wherein the device comprises a collector, a transmitter and a processor; the device collects electrocardiosignals of a user through the collector, sends the electrocardiosignals to the processor through the transmitter, carries out time domain analysis and frequency domain analysis on the electrocardiosignals through the processor, and feeds back the obtained analysis result to the user in real time, so that the user can automatically adjust the body and mind states of the user through breathing according to the analysis result fed back in real time, and the purpose of adjusting the body state by means of biofeedback training of the device is achieved. According to the embodiment of the invention, the time domain analysis and the frequency domain analysis are carried out on the electrocardiosignals of the user through the heart rate variability, so that the analysis accuracy of the biofeedback technology is improved, and the biofeedback training can be effectively guided.
Referring to the structural schematic diagram of another biofeedback device shown in fig. 4, the device is implemented on the basis of the device shown in fig. 1, corresponding to the above-mentioned device embodiment.
The collector 101 comprises a physiological parameter recording detector 1011, and the physiological parameter recording detector 1011 is connected with the transmitter 102; the physiological parameter recording detector 1011 is configured to collect an electrocardiographic signal and send the electrocardiographic signal to the transmitter 102.
The transmitter 102 includes a bluetooth device 1021, and the bluetooth device 1021 is connected to the physiological parameter recording detector 1011 for transmitting the electrocardiographic signal to the processor 103.
Specifically, the physiological parameter recording detector 1011 is connected to the bluetooth device 1021, and is worn by the user on the chest to collect the electrocardiographic signal and send the electrocardiographic signal to the processor 103 in real time.
The transmitter 103 further includes a bluetooth adaptor 1022; the bluetooth adapter 1022 is connected to the bluetooth device 1021 in a wireless communication manner, and is configured to receive the cardiac electrical signal.
The bluetooth adapter 1022 is further connected to the processor 103 via a USB interface, and is configured to send the received electrocardiographic signal to the processor 103.
The processor 103 is further configured to control the bluetooth device 1021 and the bluetooth adapter 1022 to establish a virtual serial port for connection.
The processor is further configured to: obtaining an HRV time domain curve graph according to the electrocardiosignals; obtaining an HRV frequency domain power spectral density graph according to an HRV time domain curve graph; and obtaining an HRV frequency domain distribution histogram according to the HRV frequency domain power spectrum density graph, and obtaining an accumulation score change curve graph according to the HRV frequency domain power spectrum density graph and the HRV frequency domain distribution histogram.
Specifically, obtaining continuous energy accumulation of a specific frequency domain according to the HRV frequency domain power spectrum density graph and the HRV frequency domain distribution histogram; calculating to obtain a current biofeedback score through continuous energy accumulation of a specific frequency domain; calculating a biofeedback accumulation score and an accumulation score change curve chart according to the current biofeedback score and the continuous biofeedback score of the specific preamble; the better the biofeedback effect, the higher the cumulative score, and vice versa the lower the cumulative score.
The processor 103 comprises a display screen, the processor 103 is used for feeding back the analysis result to the user through the display screen, and the display form of the analysis result comprises graphics, characters, sound and animation.
Specifically, the processor designs a heart rate variability analysis algorithm in a software programming mode, the heart rate variability analysis algorithm comprises an HRV index calculation method, a feedback score algorithm and a feedback algorithm, the sub-algorithms are buckled with each other in a loop, the whole calculation process of real-time analysis of processor software is completed, an HRV time domain curve graph, an accumulated score change curve, an HRV frequency domain power spectral density graph and an HRV frequency domain distribution histogram are obtained according to the calculation result of each stage algorithm, the analysis result is used as a feedback result, a user is helped to better understand and grasp the change trend of the pitch-beat law in the biofeedback training process, and corresponding measures are taken according to the trend to enable the body state to gradually reach an ideal state.
The processor 103 is further configured to perform backup storage on the electrocardiographic signal and the analysis result to obtain backup storage data.
The processor 103 is further configured to perform statistical analysis on the multiple backup saved data of the same user, and formulate a biofeedback training scheme for the user according to a result of the statistical analysis.
Specifically, the processor 103 is further configured to record the identity information of the user, and backup and store each time of the electrocardiographic signal and the analysis result of the user, the user can play back each time of backup and storage data, so that the user can perform biofeedback training according to the playback, the processor can also perform statistical analysis on multiple times of backup and storage data of the same user, and feed back the statistical analysis result to the user, so that the user can observe the progress and effect of the whole biofeedback training, and the processor can also make a biofeedback training scheme for the user according to the statistical analysis result to help the user perform better training.
According to the embodiment of the invention, the physiological parameter recording detector is used for acquiring the electrocardiosignals of the user, the electrocardiosignals are sent to the processor through the wireless communication connection of the Bluetooth equipment and the Bluetooth adapter, the electrocardiosignals are analyzed by the processor, and the analysis result is fed back to the user so as to guide the user to carry out biofeedback training, and the body state of the user can be gradually improved by continuously regulating the body and mind states of the user through breathing by the aid of the analysis result fed back in real time. The time domain analysis and the frequency domain analysis are carried out on the electrocardiosignals of the user by utilizing the heart rate variability, so that the analysis accuracy of the biofeedback technology is improved, and the biofeedback training can be effectively guided to the user.
Corresponding to the above device embodiment, the embodiment of the present invention further provides a biofeedback method, wherein the method includes:
step (1), a collector collects electrocardiosignals of a user;
specifically, the data flow diagram corresponding to the biofeedback method shown in fig. 5 is obtained by the collector collecting the ecg signals of the user and sending the ecg signals to the transmitter.
Step (2), the transmitter sends the electrocardiosignals to the processor;
specifically, as shown in fig. 5, the electrocardiographic signal is transmitted to the processor via the transmitter.
Step (3), the processor performs time domain analysis and frequency domain analysis on the electrocardiosignals, and feeds back analysis results to a user so that the user can autonomously adjust the physical and mental states through breathing according to the analysis results; the analysis results include a plurality of HRV time domain plots, HRV frequency domain power spectral density maps, cumulative score change plots, and HRV frequency domain distribution histograms.
Specifically, as shown in fig. 5, the processor analyzes the electrocardiosignal, and directly feeds back the analysis result to the user, so that the user can adjust the physical and mental states of the user in time.
The biofeedback method provided by the embodiment of the invention has the same technical characteristics as the biofeedback device provided by the embodiment, so that the same technical problems can be solved, and the same technical effects can be achieved.
The embodiment of the present invention further provides a machine-readable storage medium, where the machine-readable storage medium stores machine-executable instructions, and when the machine-executable instructions are called and executed by a processor, the machine-executable instructions cause the processor to implement the above biofeedback method.
The computer program product of the biofeedback apparatus and the method provided in the embodiments of the present invention includes a computer readable storage medium storing a program code, and instructions included in the program code may be used to execute the method described in the foregoing method embodiments, and specific implementation may refer to the method embodiments, and details are not described herein.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
Finally, it should be noted that: the above-mentioned embodiments are only specific embodiments of the present invention, which are used for illustrating the technical solutions of the present invention and not for limiting the same, and the protection scope of the present invention is not limited thereto, although the present invention is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the embodiments of the present invention, and they should be construed as being included therein. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A biofeedback device, comprising: the system comprises a collector, a transmitter and a processor;
the collector, the transmitter and the processor are sequentially connected;
the collector is used for collecting electrocardiosignals of a user;
the transmitter is used for sending the electrocardiosignals to the processor;
the processor is used for carrying out time domain analysis and frequency domain analysis on the electrocardiosignals and feeding back analysis results to the user so that the user can autonomously adjust the physical and mental states through breathing according to the analysis results; the analysis results include a plurality of HRV time domain plots, HRV frequency domain power spectral density maps, cumulative score change plots, and HRV frequency domain distribution histograms.
2. The device of claim 1, wherein the collector comprises a physiological parameter recording detector connected with the transmitter;
the physiological parameter recording detector is used for collecting the electrocardiosignals and sending the electrocardiosignals to the transmitter.
3. The apparatus according to claim 1, wherein the transmitter comprises a bluetooth device, and the bluetooth device is connected to the physiological parameter recording detector and is configured to transmit the ecg signal to the processor.
4. The apparatus of claim 1, wherein the transmitter comprises a bluetooth adapter;
the Bluetooth adapter is in wireless communication connection with the Bluetooth equipment and is used for receiving the electrocardiosignals;
the Bluetooth adapter is also connected with the processor through a USB interface and used for sending the received electrocardiosignals to the processor.
5. The apparatus of claim 4, wherein the processor is further configured to control the bluetooth device to establish a virtual serial port with the bluetooth adapter for connection.
6. The apparatus of claim 1, wherein the processor is further configured to:
obtaining the HRV time domain curve graph according to the electrocardiosignals;
obtaining the HRV frequency domain power spectral density map according to the HRV time domain graph;
obtaining the HRV frequency domain distribution histogram according to the HRV frequency domain power spectral density graph;
and obtaining the cumulative score change curve according to the HRV frequency domain power spectral density graph and the HRV frequency domain distribution histogram.
7. The apparatus of claim 1, wherein the processor comprises a display screen, and the processor is configured to feed back the analysis results to the user through the display screen, and the display forms of the analysis results comprise graphics, text, sound, and animation.
8. The apparatus of claim 1, wherein the processor is further configured to perform a backup saving of the cardiac electrical signal and the analysis result, thereby obtaining backup saving data.
9. The apparatus of claim 8, wherein the processor is further configured to perform a statistical analysis on the plurality of backup save data of the same user, and to formulate a biofeedback training regimen for the user according to the statistical analysis.
10. A biofeedback method applied to the biofeedback device according to any one of claims 1 to 9, the method comprising:
the collector collects electrocardiosignals of a user;
a transmitter sends the electrocardiosignals to the processor;
the processor performs time domain analysis and frequency domain analysis on the electrocardiosignals, and feeds back analysis results to a user so that the user can autonomously adjust the physical and mental states through breathing according to the analysis results; the analysis results include a plurality of HRV time domain plots, HRV frequency domain power spectral density maps, cumulative score change plots, and HRV frequency domain distribution histograms.
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