TWI671706B - Biological status feedback system and operating method thereof - Google Patents

Abstract

The invention provides a biological feedback system and an operation method thereof, using streaming technology, real-time analysis of physiological signals, and instant feedback to an operating device or display device (hereinafter referred to as a device), so that the device can make a real-time response based on the feedback information. Or adjust. With such a positive loop of continuous feedback and adjustment, it helps users gradually achieve their health goals and enhances the health value of physiological testing.

Description

Biological feedback system and its operation method

A biological feedback system and its operation method, especially a biological feedback system and its operation method that use streaming technology to analyze physiological signals in real time, convert them into control instructions, and provide instant feedback to users or devices.

In traditional physiological tests, users get static result charts, but in fact, physiological states can be changed all the time. For example, people's heart rate, blood pressure, or nerve activity will be affected by various external environments, day, night, Changes in diet, schedule, illness or psychological factors.

The static physiological detection method lacks observation and also ignores the information of the measurement process. The overly simplified static data and planar images can easily cause blind spots in interpretation.

In the field of sub-health, the health or physiological test report obtained by ignoring the time factor can only inform the user of the result in one direction, and cannot achieve the purpose of immediate feedback and immediate adjustment of the health management.

For automated health equipment, the test results cannot be used as the basis for adjusting the strength or mode of the equipment, making the functions of health auxiliary equipment unable to effectively play.

In order to solve the problems mentioned in the prior art, the present invention provides a biological feedback system and an operation method thereof.

The biological feedback system includes a detection module, a database, an analysis module, an analysis control module, and at least one execution module.

The database is connected to the detection module, the analysis module is connected to the detection module and the database, and the analysis module analyzes the original signal stream from the detection module or one of the databases in real time, And converted into a physiological signal corresponding to one of the original signals.

The analysis control module is connected to the analysis module, the analysis control module receives the physiological signal and converts it into a control instruction, the at least one execution module is connected to the analysis control module, and the at least one execution module The control instruction stream from the analysis control module is executed.

The operating method of the present invention includes the following steps. First, step (a) is performed by a detection module to detect an original signal generated by a user, and then step (b) is performed. The detection module transmits the original signal to a data at the same time. Database and a parsing module, the database stores the original signal.

Step (c) is executed, the analysis module analyzes the original signal stream in real time, converts the original signal into a physiological signal, and transmits it to an analysis control module, and then executes step (d), the analysis control module analyzes the The physiological signal is streamed and converted into a control instruction, and the control instruction is transmitted to at least one execution module.

Finally, step (e) is executed, the at least one execution module executes the control instruction stream.

1‧‧‧Detection Module

2‧‧‧Database

3‧‧‧ Resolution Module

4‧‧‧analysis control module

5‧‧‧Execution Module

C‧‧‧ coach

L1‧‧‧First Learner

L2‧‧‧Second Learner

D‧‧‧ EEG

AS‧‧‧ Sleep EEG

S1‧‧‧ has not fallen asleep

S2‧‧‧ shallow sleep

S3‧‧‧ Deep Sleep

MD‧‧‧Maximum drawing diameter

SD‧‧‧Homogeneous user diameter

TD‧‧‧ Tai Chi

PD‧‧‧ Taijiyang

ND‧‧‧Tai Chi Yin

F‧‧‧Experimental group

NF‧‧‧Control Group

T1‧‧‧First means of influence

T2‧‧‧Second influence means

A‧‧‧First user

B‧‧‧Second User

(a) ~ (f) ‧‧‧step

FIG. 1 is a system structure diagram of the biological feedback system of the present invention.

Figure 2 (a) is a schematic diagram of a static inter-heartbeat scatter diagram.

FIG. 2 (b) is a schematic diagram of the inter-heartbeat scatter diagram of the present invention.

FIG. 3 is a schematic diagram of the present invention applied to yoga teaching.

FIG. 4 (a) is a schematic diagram of the present invention applied to sleep brain wave detection.

Fig. 4 (b) is another schematic diagram of the present invention applied to sleep brain wave detection.

FIG. 5 (a) is a schematic representation of the dynamic Taiji diagram of the present invention.

Fig. 5 (b) is a schematic diagram of the application of the present invention to the influence means.

Fig. 6 (a) is a schematic diagram showing the performance of the present invention applied to mental training.

Fig. 6 (b) is another schematic diagram of the present invention applied to mental training.

FIG. 7 is a flowchart of an operation method of the biological feedback system of the present invention.

In order to understand the technical features and practical effects of the present invention, and can be implemented in accordance with the contents of the description, the preferred embodiment shown in the drawings is further described in detail as follows:

First, please refer to FIG. 1. FIG. 1 is a system structure diagram of the biological feedback system of the present invention.

As shown in FIG. 1, the biological feedback system according to the present invention includes a detection module 1, a database 2, an analysis module 3, an analysis control module 4, and at least one execution module 5.

The database 2 is connected to the detection module 1, the analysis module 3 is connected to the detection module 1 and the database 2, respectively, and the analysis module 3 parses from the original of one of the detection module 1 or the database 2. The signal is streamed and converted into a physiological signal corresponding to one of the original signals.

The analysis control module 4 is connected to the analysis module 3, and at least one execution module 5 is connected to the analysis control module 4. The analysis control module 4 can receive the physiological signal stream from the analysis module 3, analyze and convert it into After a control instruction, the stream is sent to the execution module 5. The execution module 5 receives a control instruction from the analysis control module 4 and executes the control instruction.

The detection module 1 is a device having the functions of electrocardiography (ECG) measurement, electromyography measurement, eye movement measurement, electroencephalogram measurement, or pulse measurement (Photoplethysmography, PPG), such as electrocardiograph, pulse meter, electroencephalograph, The present invention is not limited to the physiological measuring instrument of myoelectric wave or eye movement wave, and the analysis and control module 4 may include a microcontroller (MCU), a microprocessor (Microprocessor, MPU), and a display. Card, or any device, instrument, or combination of Programmable Logic Controller (PLC) used to issue control instructions to the execution module 5, the present invention is not limited to this; the execution module 5 is any Software and hardware that can accept control instructions, such as TVs, smartphones, smart watches, bracelets, computers, tablets, or other devices equipped with displays, and can also be used as health aids such as massage tables, massage chairs, and treadmills Or other health equipment, medical equipment or sports equipment with regulatory functions. In addition, if the above-mentioned execution modules 5 include APP, email, instant messaging software or other Function Zheyi the like included within the scope of the present invention, the present invention is not limited thereto.

When the execution module 5 is any device equipped with a display, the execution module 5 can display the control instructions it receives as an animation. The animation can be a dynamic statistical graph, a dynamic analysis graph, a dynamic physiological waveform graph, and a dynamic power. Power Spectral Density (PSD) graph, dynamic heartbeat interval scatter graph (RRI Scatter), dynamic Tai Chi graph, dynamic character graph, or a combination thereof, wherein the dynamic statistical graph may be a trend graph, bar graph, or pie chart ; The dynamic analysis chart may be a five-force analysis chart, a radar analysis chart, and the dynamic physiological waveform chart may be an electrocardiogram, an electroencephalogram, or other waveform charts showing physiological states, and the present invention is not limited thereto.

The present invention can be used in a variety of physiological detection methods, so that the detection results can be immediately returned to the user or the device in a display, adjustment, and control manner. The user or device makes corresponding adjustments based on the feedback results, and then obtains new detection results through the detection device to form an instant feedback and adjustment The entire cyclic process, and in this embodiment, the device is the execution module 5.

First, the user accepts the detection of the detection module 1. As mentioned earlier, the detection module 1 can be quite a variety of detection instruments or equipment. After detecting the user's physiological state, the detection module 1 will obtain an original signal. The original signal may be electrocardiogram data, electromyogram data, eye movement data, brain wave data, pulse data, or a combination thereof.

The data content of the original signal can be in various forms, usually based on the unit signal strength per unit time interval, such as the signals related to nerve activity such as electrocardiogram, myoelectric wave, eye movement wave, brain wave, etc. Primitive signals with intermittent regular motion characteristics, such as pulse.

Then, the detection module 1 sends the original signal to the database 2 storage and analysis module 3 for parsing at the same time, and the database 2 can be stored in a stand-alone manner or the cloud huge storage of the original signal. The present invention does not This is the limit.

As described above, the analysis module 3 analyzes the original signal stream from the detection module 1 or the database 2 in real time, and converts it into a physiological signal corresponding to the original signal.

Compared with the original signal, the parsed physiological signal contains a lot of physiological information, which is more convenient for analysis and use. For different types of physiological signals, the present invention corresponds to different signal formats. This embodiment will provide a variety of physiological detection data for explanation.

First, please refer to Table 1. Table 1 is the signal format of time interval physiological signals, such as the heart rate variabilitv (HRV) analysis of the heartbeat interval (RR-interval) signal.

Each signal in Table 1 sends the heartbeat interval data accumulated to that point in time. It can be used to represent the process of RRI Scatter.

Since this embodiment involves signal transmission and stream processing, the standard JavaScript Object Notation (JSON) format is used for data transmission processing and analysis. If Table 1 above is taken as an example, the implementation of Table 1 The adopted JSON format is as follows: [{TimeSpan: float, Data: [{ms: float}, ...]}, ...]

Table 2 is the signal format of the power spectral density physiological signal. It is used to transmit the power spectral density (PSD) obtained by Fourier transform of the time interval physiological signal and applied to PSD-like detection data.

For example, each signal in Table 2 represents the power spectrum density obtained by Fourier transformation of the time interval data accumulated up to that time point; for example, a signal of time sequence 100 is the time interval data accumulated up to time point 100, using Fourier Power spectral density results obtained after conversion.

Similarly, the JSON format adopted in the implementation of Table 3 is as follows: [{TimeSpan: float, Data: [{{Hz: float}, {PSD: float}}, ...]}, ...]

Table 3-1 is a physiological signal format of physiological parameters based on heart rate variability (HRV) analysis as an example, and is used to transmit various physiological parameters.

Each signal in Table 3-1 represents the value of various physiological parameters accumulated up to that time point. For the definition of each physiological parameter, please refer to the description in Table 3-2 below.

For Table 3-1, the JSON format of its physiological signals is as follows: [{TimeSpan: float, Data: [{{Lf: float}, {Hf: float}, {LfHf: float}, {VLf: float}, { Tp: float}, {Sdnn: float}}, ...]}, ...]

Although the present invention can utilize and present the results of heart rate variability (HRV) analysis, it can still be used for other physiological tests. It is only necessary to adjust the parameters in its JSON format according to the values of physiological tests, such as blood pressure measurement. When the parameter is changed to the value and unit (mm / Hg) of systolic and diastolic blood pressure, all the physiological tests that are commonly used should belong to the scope of the present invention, and the invention is not limited thereto. The original signals and physiological signals in Tables 1 to 3-2 above are all transmitted in JSON format. Therefore, the data receiving part such as database 2, analysis module 3, or analysis control module 4 can provide API (Application Programming Interface).

After the analysis module 3 successfully parses the original signal into a physiological signal, it transmits the physiological signal stream to the analysis control module 4. After the analysis control module 4 receives the physiological signal stream, it analyzes it and sends control based on the analysis result. The instruction stream is transmitted to the execution module 5.

The analysis and control module 4 can issue control instructions based on the analysis results, such as drawing real-time animation instructions, regulating device instructions, sending warning message instructions, or a combination thereof, which can be based on the user. Demand design, the present invention is not limited to this, and the execution module 5 executes the control instruction after receiving the control instruction.

After the execution module 5 executes the control instruction, the user or the execution module 5 can make corresponding adjustments in motion. For example, the user views the scatter diagram of the real-time dynamic heartbeat interval, adjusts the action posture in time, and for example, increases the intensity of the health equipment. The detection module 1 can detect the adjusted physiological signal, and then execute it according to the foregoing implementation steps to form a loop of real-time dynamic feedback.

Next, practical examples will be used to explain how the present invention improves the existing physiological detection methods.

Example 1

This embodiment 1 uses the analysis of heart rhythm variation as an example to explain how the present invention uses process information to solve the errors caused by ignoring the time sequence in the traditional static data and 2D images. Table 4 below shows samples of the heartbeat interval (RRI) of a first user A and a second user B. The values of the two groups of samples are exactly the same, only the order is different.

Please refer to FIG. 2 (a) and FIG. 2 (b) at the same time. FIG. 2 (a) is a schematic diagram of a traditional heartbeat interval scatter diagram; FIG. 2 (b) is a diagram of a heartbeat interval scatter diagram after applying the time factor given by the present invention Schematic diagram, where the direction of the arrows indicates the order of the points.

As shown in Figure 2 (a), if the traditional RRI Scatter diagram is used as an example, although the first user A and the second user B are different, the interval is not too short (heartbeat Too fast), or the interval is too long (the heartbeat is too slow), so there is no difference in the interpretation of the two.

From the perspective of the SDNN index commonly used for judging the activity of the autonomic nerve by rhythm analysis, the SDNN values calculated by the first user A and the second user B are the same. That is, two users have the same autonomic nervous activity.

However, if we look at Figure 2 (b), using the real-time dynamic heartbeat scatter diagram (RRI Scatter) drawn by the present invention, and real-time observation of the individual formation process, we can find the heart rate of the first user A on the left in time. It is stable and gradually slowing down, while the second user B on the right is an irregular change, highlighting the risk of second user B's arrhythmia.

In the final analysis, if the static RRI Scatter is presented in the manner shown in Figure 2 (a), the user will not be able to know the order of the detected values over time (that is, chronological order). Therefore, when this embodiment is used, as shown in FIG. 2 (b), the original signals in the above table 4 are displayed on the execution module 5 in the form of animation, and the inter-heartbeat scatter diagram (RRI Scatter) is formed. The process will be sequentially presented on the execution module 5 in the order of arrows shown in FIG. 2 (b).

Example 2

This embodiment 2 uses a rhythm variation analysis as an example to explain how the present invention applies biological feedback, and the stream guides the execution module 5 with a display device as a training auxiliary tool.

Please refer to FIG. 3, which is a schematic diagram of the present invention applied to yoga teaching and autonomic nerve detection. As shown in FIG. 3, the coach C, the first learner L1, and the second learner L2 all wear an attached or wearable sensing device, that is, the detection module 1.

The detection module 1 can instantly collect the original signal stream generated by the coach C, the first learner L1, and the second learner L2 due to changes in their autonomic nervous activity due to yoga exercises. When the original signal is transmitted to the database 2 for storage, it is analyzed in the analysis module 3 together. The analyzed original signal is converted into a physiological signal and transmitted to the analysis control module 4. After the analysis and control module 4 analyzes the signal, it can issue a control instruction to the execution module 5.

Take the control instruction to draw a Power Spectral Density (PSD) chart as an example. At this time, the execution module 5 will display the animation shown in Figure 3. Coach C, the first learner L1 and the second learner L2 can see the current moment. Self-acting instant dynamic power spectral density (PSD) plot.

By comparing the coach's dynamic power spectral density (PSD) diagram with the teaching, the first learner L1 can know that his posture is a standard action, because the first learner L1's dynamic power spectral density (Power Spectral Density, PSD) is similar to coach C.

Conversely, the second learner L2 can learn that its dynamic power spectral density (PSD) map is different from the coach C by executing the module 5. This embodiment can assist the second learner L2 to independently adjust its yoga posture until Its physiological state performance is similar to that of coach C.

The original signal of the physiological test will be stored in the database 2. Therefore, after the second learner L2 leaves the yoga teaching site, he can still play the animation and self of the previous coach C in other places by using the technology of the Internet and cloud through this embodiment. (The second learner L2) real-time animation allows the second learner L2 to perform autonomous yoga practice anytime, anywhere.

Example 3

This embodiment 3 uses brain wave detection as an example to illustrate how the present invention uses long-term monitoring and original signal records as diagnostic tools.

This embodiment is intended for users with chronic insomnia. Detection module 1 is a wearable The device is worn on the user to monitor the user's brain wave signal for a long time, and the database 2 can record the brain wave signal. The execution module 5 can simultaneously display the dynamic brain wave D in FIG. 4 (a) and the dynamic power spectral density map AS in FIG. 4 (b), so as to monitor the changes of the brain wave when the user sleeps in real time.

When people are in different sleep states, the power spectrum density maps reflected by brain waves will appear differently. As shown in FIG. 4 (b), when the user is in the sleepless state S1, the light sleep state S2, and the deep sleep state S3, the area of the frequency corresponding to the α , β, γ, θ, and δ waves in the brain waves There are significant differences. By observing the dynamic power spectral density in real time, we can see the changing structure of the physiological state of the brain during the sleep period of the user to determine whether the insomnia is caused by a neurophysiological state or a psychological factor.

An electroencephalogram test can be used as a reference for diagnosing brain function. A normal test result does not mean that there are no brain lesions. Therefore, it is more accurate through long-term tests, and multiple tests must be performed to analyze and analyze. Comparison. The database 2 of the present invention can record the detected original signals for repeated use by related personnel. The analysis and control module 4 can use the analysis module 3 to instantly analyze the current brainwave signals and the brainwave signals recorded in the database 2 as Analyze and compare, or compare multiple waveform records recorded in database 2 to analyze and compare, when there is a risk, you can issue a warning control instruction to the execution module 5, and the execution module 5 issues an alert, such as a sound, communication The software sends a message, and the above-mentioned execution module 5 may be a portable or wearable device such as a smart phone or a bracelet, which is not limited in the present invention.

Example 4

This embodiment 4 uses the experiment of "the influence of obesity on the autonomic nervous regulation ability" often discussed in the academic field as an example to illustrate how the present invention uses biological feedback and streaming to guide the execution module 5 with a display device as a research and development verification tool.

This example uses the dynamic Tai Chi chart as the display tool of the execution module 5. Please refer to FIG. 5 (a), which is a schematic diagram of the performance of the dynamic Tai Chi chart of the present invention. In this embodiment, the dynamic Tai Chi diagram shown in FIG. 5 (a) mainly includes the maximum drawing diameter MD, the homogeneous user diameter SD, Tai Chi TD (Tai Chi diameter), Tai Chi Yang PD (Tai Chi Yang diameter), and Tai Chi Yin. ND (Tai Chi Yin Diameter), Tai Chi color, and Tai Chi shades.

Among them, the size of Taiji TD represents the state of autonomic nerve activity of the user, Taiji Yang PD and Taiji Yin ND represent the state of autonomic nerve balance, and the color or shade of Taiji TD represents the state of autonomic nerve energy. The physiological parameters required for drawing the dynamic Tai Chi diagram are obtained after the detection module 1 detects the original signal of the user's autonomic nervous activity, and then converts it through the analysis module 3. For the parameter contents, refer to Table 3-1.

The drawing method is obtained by sequentially calculating the image signal according to the following formula 1-1 to formula 1-7: Rb = P × 0.95 (formula 1-1)

Rm = P × 0.90 (Equation 1-2)

If Ru> Rb Then Ru = Rb (Equation 1-4)

(The alpha value of the dynamic Tai Chi chart represents transparency, which can reflect the shade of Tai Chi)

For the above formulas 1-1 to 1-7, please refer to FIG. 5 (a), Table 3-1, Table 3-2, Table 5 and Table 6 at the same time.

Therefore, based on the information in Table 3-1, Table 3-2, Table 5 and Table 6 and their descriptions, the dynamic Tai Chi diagram in this embodiment is the parts shown in Figure 5 (a), which can be based on the original signal. The real-time change changes its size, proportion, area, and depth (also color, such as replacing α with a hue indicator for implementation). The instant change of the original signal means that the content of the physiological signal and control instructions can be changed at the same time, and adjusted accordingly. The information brought to the user by the execution module 5.

Using the above-mentioned dynamic Taiji diagram, the R & D personnel can instantly visualize the state change of the autonomic nerve activity of the experimental group and the control group in the detection module 1 in the manner of image, animation, and intuition.

Please refer to FIG. 5 (b). FIG. 5 (b) is a schematic diagram of using the present invention to study the effect of obesity on the ability of autonomic nerve regulation. The subjects were divided into experimental group F and control group NF. It was assumed that experimental group F was an obese subject, and control group NF was a non-obese subject. At the same time, observe the dynamic Tai Chi diagram, and apply the first influence means T1 (such as acupuncture and acupoint massage) to the two groups according to the time sequence. Then you can immediately observe the changes and differences of the dynamic Tai Chi diagram. If you apply the second influence means T2, At this time, what kind of changes will occur in the physiological state between the two groups is used as a method for verifying the first influence means T1 and the second influence means T2.

For the convenience of research, the original signal of the control group can also be stored in database 2 for subsequent use in the same experiment, saving experimental resources.

Example 5

This embodiment 5 uses a rhythm variation analysis as an example to explain how the present invention uses biological feedback and streaming to guide the execution module 5 with a display device as an assessment tool.

The analysis of rhythm variation is commonly used in academics to observe the concentration of the test subject. When the trainee is focused, the activity of the sympathetic nerve will be significantly increased, and the activity of the parasympathetic nerve will be inhibited. These reactions are expressed in power In terms of spectral density, the LF energy increases rapidly.

Please refer to FIG. 6 (a) and FIG. 6 (b). FIG. 6 (a) is a schematic diagram of performance of the present invention applied to mental training; FIG. 6 (b) is another schematic diagram of performance of the present invention applied to mental training.

Figure 6 (a) shows the power spectrum density of the subject, and Figure 6 (b) shows the power spectrum density of the concentrator. Dynamically observe the process of the subject's change from Figure 6 (a) to Figure 6 (b). You can understand the speed and intensity of the subject's concentration, as a basis for evaluating the subject.

Except for mental training, concentration training, or sports related to physiological conditions such as shooting, the invention can be used as an assessment tool or an autonomous training tool.

Example 6

This embodiment 6 uses a rhythm variation analysis as an example to explain how the present invention further applies biological feedback to, for example, an execution module 5 for regulating health equipment.

Autonomous health managers often use health equipment to help with health management. Common equipment such as pressure-relief chairs, decompression beds, massage chairs, and other relief equipment, or treadmills, flywheels and other sports equipment. These devices often have regulatory functions, such as strength changes or mode changes.

When the present invention is combined with a health device, the health device can be regarded as an execution module 5. In addition, any device with a screen display function can be used as another execution module 5. When the user uses the detection equipment (equivalent to the detection module 1) and simultaneously uses the health equipment (equivalent to the implementation of Module 5), the detection device (detection module 1) obtains the real-time original signal of the user, and automatically analyzes the current physiological signal of the user through the analysis and control module 4 and generates corresponding control instructions. The dynamic Taiji chart used in 4 is displayed on an execution module 5 of the device with a screen display function in order to feed back changes in the state of the autonomic nerve to the user in real time. In addition, the analysis control module 4 also sends control command signals to the health equipment at the same time (Another execution module 5).

It can be known from this embodiment that the execution module 5 that can be used in the present invention is not limited to one type, and the analysis and control module 4 can be connected to multiple execution modules 5 at the same time, and control the deployment and use in accordance with user needs.

Through the above-mentioned cycle of detection and regulation, the health equipment can be adjusted to the most suitable state for the user, helping the user to achieve health purposes.

Finally, please refer to FIG. 7, which is a flowchart of an operation method of the biological feedback system of the present invention. First execute step (a), the detection module 1 detects the original signal generated by a user, and then execute step (b). The detection module 1 transmits the original signal to the database 2 and the analysis module 3 at the same time. The database 2 stores the original signal.

In step (b), the original signal detected by the detection module 1 needs to be transmitted to the analysis module 3 if it needs to be displayed to the user for viewing in real time, otherwise it can be stored in the database 2 according to the user's needs. Yes, to facilitate users to query and read in the future.

Then step (c) is performed. The analysis module 3 parses the original signal stream in real time, converts the original signal into a physiological signal, and transmits the physiological signal to an analysis control module 4 by streaming.

In step (c), the original signal pointed by the analysis module 3 can come from the detection module 1. Or database 2, namely electrocardiogram data, electromyogram data, eye movement data, brain wave data, pulse data, or a combination thereof.

Then, step (d) is executed. The analysis and control module 4 analyzes the physiological signal stream and sends a control instruction stream to the execution module 5.

Finally, step (e) is executed, and the execution module 5 executes the control instruction. After step (e) is performed, the present invention may further include step (f), the user or the execution module 5 adjusts the action.

When the user or the execution module 5 adjusts the action in step (f), it will return to and execute step (a), and the detection module 1 will immediately obtain the brand new generated after the user or the execution module 5 adjusts the action. The original signal is then executed in the same steps (b) to (f) in order to achieve the effect of biological feedback until the user finds the most suitable physiological state for himself.

The aforementioned "action" adjusted by the user is not limited to the movement of bones or muscles, but is actually a change in at least one physiological state, such as breathing, blood pressure, heartbeat, nerve activity, or mental state; The "action" adjusted by the group 5 is essentially a change in at least one operating condition, such as the pressing pressure path of a massage chair or the running speed of a treadmill, and the present invention is not limited thereto.

Through the application of the present invention, physiological testing can be introduced into the two-way communication level, which greatly improves the health value of physiological testing, can present more complete information, and establish a cycle of benign feedback, which shows the progress of the present invention.

However, the above are only the preferred embodiments of the present invention. When the scope of implementation of the present invention cannot be limited in this way, that is, simple equivalent changes and modifications made in accordance with the scope of the patent application and description of the present invention are still Within the scope of the invention.

Claims (9)

A biological feedback system includes: a detection module; a database connected to the detection module; and an analysis module connected to the detection module and the database, respectively, wherein the analysis module analyzes in real time from the detection The module or one of the original signal streams in the database, and converted into a physiological signal corresponding to the original signal; an analysis control module connected to the analysis module, the analysis control module receives the physiological signal and Conversion into a control instruction; and at least one execution module connected to the analysis control module, the at least one execution module executes the control instruction stream from the analysis control module; wherein the original signal is electrocardiogram data, EMG data, eye movement data, brain wave data, pulse data, or a combination thereof; the physiological signal includes time interval information, and the physiological signal having the time interval information is integrated into a power after Fourier transform Spectral Density (PSD). The biological feedback system according to claim 1, wherein the database stores the original signal from the detection module, and the original signal can be reused by the analysis module. The biological feedback system according to claim 1, wherein the detection module is a device having functions of electrocardiography (ECG) measurement, electromyography measurement, eye movement measurement, brain wave measurement, or pulse measurement (Photoplethysmography, PPG). The biological feedback system according to claim 1, wherein the control instruction is displayed as an animation, the animation is a dynamic statistical graph, a dynamic analysis graph, a dynamic physiological waveform graph, a dynamic power spectral density (PSD) graph, a dynamic Heartbeat interval scatter diagram (RRI Scatter), dynamic Tai Chi diagram, dynamic character diagram, or a combination thereof. The biological feedback system according to claim 4, wherein the dynamic Tai Chi diagram includes a maximum drawing diameter, a homogeneous user diameter, a Tai Chi diameter, a Tai Chi Yang diameter, a Tai Chi Yin diameter, Tai Chi color, and a Tai Chi shade. The biological feedback system according to claim 1, wherein the execution module is a television, a smart phone, a smart watch, a wristband, a computer, a tablet computer, a health auxiliary device, a sports device, a medical device, software, or a combination thereof. A method for operating a biological feedback system includes: (a) a detection module detects an original signal generated by a user; (b) the detection module transmits the original signal to a database and an analysis module at the same time, The database stores the original signal; (c) the analysis module analyzes the original signal stream in real time, and converts the original signal into a physiological signal and transmits it to an analysis control module; (d) the analysis control module analyzes The physiological signal stream is converted into a control instruction, and the control instruction is transmitted to at least one execution module; and (e) the at least one execution module executes the control instruction stream; wherein the original signal is electrocardiogram data, EMG data, eye movement data, brain wave data, pulse data, or a combination thereof; the physiological signal includes time interval information, and the physiological signal having the time interval information is integrated into a power after Fourier transform Spectral Density (PSD). The operation method of the biological feedback system as described in claim 7, wherein after performing step (e), perform: (f) the user or the execution module to adjust the action; re-execute the step after performing step (f) (a). According to the operating method of the biological feedback system described in claim 8, in step (f), the action adjusted by the user is at least one physiological state change, and the action adjusted by the execution module is at least one operating condition change.