TW201635233A - Biological status feedback system and operating method thereof - Google Patents

Abstract

This invention provides a biological status feedback system and an operating method thereof. It is able to perform users' information via real-time streaming analysis and feedbacks to the devices or the displays. Therefore, devices are able to adjust responses simultaneously. It helps people being healthier step by step and increasing the value of physiological detection via the loop of feedback and adjustment.

Description

Biological feedback system and its operation method

The invention relates to a biological feedback system and a method for operating the same, in particular to a biological feedback system and a method for operating the same by using a streaming technology to instantly analyze physiological signals, convert them into control commands, and instantly feed back to users or devices.

Traditional physiological testing, the user gets a static result chart, in fact, the physiological state can be changed all the time, such as the human heart rate, blood pressure or nerve activity, etc., due to various external environments, daytime, nighttime, Changes in diet, work, illness or psychological factors.

Static physiological detection methods, lack of observation, and neglect the information of the measurement process, too simplified static data and flat images, easily lead to blind spots in interpretation.

In the sub-health field, this kind of health or physiological test report that ignores the time factor has only one-way notification of the result to the user, and cannot achieve the purpose of immediate feedback and immediate adjustment of health management.

For automated health equipment, the test results cannot be applied as a basis for adjusting the strength or mode of the device, so that the function of the health aid cannot be effectively utilized.

In order to solve the problems mentioned in the prior art, the present invention provides a biological feedback system and a method of operating the same.

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

The data library is connected to the detection module, and the analysis module is respectively connected to the detection module and the database, and the analysis module instantly parses the original signal stream from the detection module or the database. And converted to a physiological signal corresponding to one of the original signals.

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

The operation method of the present invention comprises the following steps: firstly, step (a): detecting module detects a raw signal generated by a user, and then performing step (b), the detecting module simultaneously transmitting the original signal to a data The library and a parsing module store the original signal.

Step (c), the parsing 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 performs step (d), the analysis control module analyzes the The physiological signal stream is converted and converted into a control command, and the control command is transmitted to at least one execution module.

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

1‧‧‧Test module

2‧‧‧Database

3‧‧‧analysis module

4‧‧‧Analytical Control Module

5‧‧‧Execution module

C‧‧‧Coach

L1‧‧‧ first learner

L2‧‧‧ second learner

D‧‧‧ brain wave map

AS‧‧‧ sleep brainwave map

S1‧‧‧ has not yet fallen asleep

S2‧‧‧Small sleep

S3‧‧‧ Deep sleep

MD‧‧‧Maximum drawing diameter

SD‧‧‧Homogeneous user diameter

TD‧‧‧ Tai Chi

PD‧‧‧ Tai Chi Yang

ND‧‧‧ Tai Chi Yin

F‧‧‧Experimental Group

NF‧‧‧Control Group

T1‧‧‧ first means of influence

T2‧‧‧ second means of influence

A‧‧‧ first user

B‧‧‧Second user

(a)~(f)‧‧‧ steps

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

Figure 2 (a) is a schematic diagram of a static heartbeat interval scatter plot.

Fig. 2(b) is a schematic diagram of the present invention applied to a heartbeat interval scatter diagram.

Figure 3 is a schematic illustration of the teachings of the present invention for use in yoga teaching.

Figure 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 diagram showing the performance of the dynamic Taiji diagram of the present invention.

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

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

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

Figure 7 is a flow chart showing the 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 specification, the following further describes the preferred embodiment as shown in the following figure:

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

As shown in FIG. 1 , the biological feedback system of the present invention comprises 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 , and the analysis module 3 is respectively connected to the detection module 1 and the database 2 , and the analysis module 3 parses the original from the detection module 1 or the database 2 The signal stream is converted to 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 command, the stream is sent to the execution module 5. The execution module 5 receives a control command from the analysis control module 4 and executes the control command.

The detection module 1 is a device having electrocardiography (ECG) measurement, myoelectric wave measurement, eye movement measurement, brain wave measurement or photoplethysmography (PPG) function, such as an electrocardiograph, a pulse meter, a brain wave meter, The present invention is not limited to the physiological measurement instrument of the myoelectric wave or the eye movement wave, and the analysis control module 4 may include a microcontroller (Microcontroller Unit, MCU), a microprocessor (MPU), and a display. Any device, instrument, or combination thereof of a card or a programmable logic controller (PLC) for issuing a control command to the execution module 5, which is not limited thereto; the execution module 5 is any Software and hardware that can accept control commands, such as TVs, smart phones, smart watches, wristbands, computers, tablets or other devices equipped with displays, and health aids such as massage beds, massage chairs, treadmills Or other health equipment, medical equipment or sports equipment with control functions, in addition, the above 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 command received by the execution module 5 as an animation, and the animation can be a dynamic chart, a dynamic analysis chart, a dynamic physiological waveform chart, and dynamic power. a Power Spectral Density (PSD) map, a dynamic heartbeat scatter plot (RRI Scatter), a dynamic tai chi map, a dynamic character map, or a combination thereof, wherein the dynamic graph can be a trend graph, a bar graph, or a pie chart The dynamic analysis chart may be a five-force analysis chart or a radar analysis chart, and the dynamic physiological waveform chart may be an electrocardiogram, an electroencephalogram or other waveforms showing physiological states, and the invention is not limited thereto.

The invention can be applied to a plurality of physiological detection methods, so that the detection results are immediately fed back to the user or the device in a display, adjustment and control manner. The user or device makes corresponding adjustments according to the feedback result, and then obtains new detection results through the detection device to form an instant feedback and adjustment. The entire loop process, and in the present embodiment, the device is the execution module 5.

First, the user receives the detection of the detection module 1. As described above, the detection module 1 can be a plurality of detection instruments or devices. After detecting the physiological state of the user, the detection module 1 obtains an original signal. The original signal may be electrocardiogram data, myoelectric wave data, eye movement data, brain wave data, pulse data or a combination thereof.

The content of the original signal may be in various forms, and is usually based on the unit electrical signal intensity at a unit time interval, such as signals related to neural activity such as electrocardiogram, myoelectric wave, eye movement wave, and brain wave, and may also be It is the original signal 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 parse, and the database 2 can store the original signal in a stand-alone manner or use the cloud to store the original signal. This is limited to this.

As described above, the parsing module 3 immediately parses the original signal stream from the detection module 1 or the database 2 and converts it into a physiological signal corresponding to one of the original signals.

Compared with the original signal, the analyzed 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, and the present embodiment will cite various physiological detection data.

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

Each signal transmitted in Table 1 is the heartbeat spacing data accumulated to that point in time. Can be used to represent the process of heart rate scatter plot (RRI Scatter) changes.

Since the present embodiment relates to the part of signal transmission and stream processing, the data processing and analysis are performed by using a standard JavaScript object notation (JSON) format. If the above Table 1 is an example, the implementation of Table 1 The JSON format is as follows: [{TimeSpan:float,Data:[{ms:float},...]},...]

Table 2 shows the signal format of the power spectral density physiological signal for transmitting the Power Spectral Density (PSD) obtained after the Fourier transform of the time interval physiological signal, and is applied to the detection data of the PSD-like type.

For example, each of the signals in Table 2 indicates the power spectral density obtained by the Fourier transform of the time interval data accumulated until the time point; for example, the signal of the time sequence 100 is the time interval data accumulated up to the time point 100, with Fourier Power spectral density results obtained after conversion.

Similarly, the JSON format of 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 using heart rate variability (HRV) analysis as an example to transmit various physiological parameters.

Each signal in Table 3-1 indicates the value of each physiological parameter accumulated until the 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 the physiological signal is as follows: [{TimeSpan:float,Data:[{{Lf:float},{Hf:float},{LfHf:float},{VLf:float},{ Tp:float},{Sdnn:float}},...]},...]

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

After the parsing module 3 successfully parses the original signal into a physiological signal, the physiological signal stream is transmitted to the analysis control module 4, and the analysis control module 4 performs the analysis after receiving the physiological signal stream, and sends the control according to the analysis result. The instruction stream is transmitted to the execution module 5.

The analysis control module 4 can issue control commands according to the analysis result, such as drawing an instant animation instruction, regulating device instructions, sending a warning message instruction, or a combination thereof, according to the user. The present invention is not limited thereto, and the execution module 5 executes the control command after receiving the control command.

After the execution module 5 executes the control command, the user or the execution module 5 can make corresponding adjustments in the action. For example, the user views the instant dynamic heartbeat interval scatter map, adjusts the action posture in a timely manner, and, for example, the health device increases the intensity. The detection module 1 can detect the adjusted physiological signal, and then execute according to the foregoing implementation steps to form a loop of instant dynamic feedback.

Next, the actual embodiment will be used to explain how the present invention improves the existing physiological detection method.

Example 1

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

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 heartbeat interval scatter diagram after applying the time factor according to the present invention. A schematic diagram in which the direction of the arrows indicates the order of the points.

As shown in Fig. 2(a), if the traditional RRI Scatter is used as an example, the first user A and the second user B are different, but the interval is too short (heartbeat It is too fast, or the interval is too long (the heartbeat is too slow), so there is no difference in the interpretation of the two.

If the cardimetric analysis commonly used to determine the autonomic activity of the SDNN indicator, the first user A and the second user B calculate the same SDNN value. That is, two users have the same autonomic nervous activity.

However, as shown in Fig. 2(b), using the RRI Scatter map drawn by the present invention, the individual formation process can be observed in time, and the heart rate of the first user A on the left image can be found in time. It is stable and gradually slows down, while the second user B on the right is an irregular change, highlighting the risk of a second user B's arrhythmia.

If you look at the static heartbeat scatter plot (RRI Scatter) as shown in Figure 2(a), the user will not know the order in which the detected values change over time (that is, the time sequence). Therefore, in the embodiment, as shown in FIG. 2(b), the original signal in the above Table 4 is displayed in an animation form on the execution module 5, and the heartbeat interval pattern (RRI Scatter) is formed. The process is sequentially presented on the execution module 5 in the order of the arrows as shown in Fig. 2(b).

Example 2

In the second embodiment, the heart rhythm variation analysis is taken as an example to illustrate how the present invention applies bio-feedback, and the stream is guided to the execution module 5 having the display device as a training aid.

Please refer to FIG. 3. FIG. 3 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 a sensing device with an attached or wearable type, that is, the detecting module 1.

The detection module 1 can instantly collect the original signal stream generated by the current coach C, the first learner L1 and the second learner L2 due to the yoga movement, and the autonomic nerve activity changes. The original signal is transmitted to the database 2 for storage, and is parsed in the parsing module 3. The original signal that is parsed is converted into a physiological signal and transmitted to the analysis control module 4. After the analysis control module 4 analyzes the signal, a control command can be issued to the execution module 5.

Taking the Power Spectral Density (PSD) map as an example, the execution module 5 will display the animation as shown in Figure 3. The coach C, the first learner L1 and the second learner L2 can see the present. Self-action real-time Dynamic Spectral Density (PSD) map.

Through the comparison of the coach's Power Spectral Density (PSD) diagram, the first learner L1 can know that his posture is a standard action, because the first learner L1 has its dynamic power spectral density (Power Spectral Density, The PSD) map is similar to the coach C.

On the contrary, the second learner L2 can learn that the dynamic power spectral density (PSD) map is different from the coach C through the execution module 5, and the embodiment can assist the second learner L2 to adjust its yoga posture autonomously until The performance of his physiological state 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 scene, the animation and self of the previous coach C can be played in other places through the network cloud and other technologies through the embodiment. The instant animation of the second learner L2 allows the second learner L2 to perform autonomous yoga practice anytime and anywhere.

Example 3

In the third embodiment, brainwave detection is taken as an example to illustrate how the present invention uses long-term monitoring and original signal recording as a diagnostic tool.

This embodiment is for users of long-term insomnia. Detection module 1 is a wearable The device is worn on the user to monitor the brain wave signal of the user for a long time, and the database 2 can record the brain wave signal. The execution module 5 can simultaneously display the dynamic brainwave D of FIG. 4(a) and the dynamic power spectral density map AS of FIG. 4(b) to instantly monitor the brainwave changes of the user during sleep.

When a person is in different sleep states, the power spectral density map reflected by the brain waves will be different. As shown in FIG. 4(b), when the user is in the unsleep state S1, the light sleep state S2, and the deep sleep state S3, the area of the region corresponding to the frequency corresponding to the α , β, γ, θ, and δ waves in the brain wave is shown. There are significant differences. By observing the dynamic power spectral density in real time, it can be seen that the physiological structure of the brain during the sleep period of the user is determined to determine whether the insomnia condition is caused by a neurophysiological state or a psychological factor.

The examination of brain wave can be used as a reference for diagnosing brain function. The normal result of one examination does not mean that there is no lesion in the brain. Therefore, it is necessary to pass the long-term examination more accurately, and it must be analyzed through multiple examinations. Comparison. The database 2 of the present invention can record the original signal of the detection for repeated use by the relevant personnel, and the analysis control module 4 can immediately use the analysis module 3 to immediately record the current brain wave signal and the brain wave signal recorded in the database 2. Analyze the comparison, or compare the multiple waveform records recorded in the database 2, and issue an alarm control command to the execution module 5 when the risk occurs, and the execution module 5 issues a warning, such as making a sound, to communicate The software sends a message, and the above-mentioned execution module 5 can be a portable or wearable device such as a smart phone or a wristband, and the invention is not limited thereto.

Example 4

In the fourth embodiment, an experiment of "the effect of obesity on the ability of autonomic regulation", which is often discussed in the academic field, is taken as an example to illustrate how the present invention uses biofeedback and stream to guide the execution module 5 having a display device as a development verification tool.

In this example, a dynamic taiji diagram is used as a display tool of the execution module 5. Referring to FIG. 5(a), FIG. 5(a) is a schematic diagram showing the performance of the dynamic taiji diagram of the present invention. In the present embodiment, the dynamic Taiji diagram shown in FIG. 5(a) mainly includes the maximum drawing diameter MD, the homogeneity user diameter SD, the Taiji TD (Tai Chi diameter), the Taiji Yang PD (Tai Chi Yang diameter), and the Tai Chi yin. ND (Tai Chi Yin diameter), Tai Chi color, and Tai Chi shade.

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

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

Rm=P×0.90 (Equation 1-2)

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

(The alpha value of the dynamic Taiji diagram indicates transparency, which reflects its Tai Chi depth)

For the above formula 1-1 to formula 1-7, please refer to the descriptions of Fig. 5 (a), Table 3-1, Table 3-2, Table 5 below and Table 6 below.

Therefore, the information of the table 3-1, the table 3-2, the table 5 and the table 6 and the description thereof, the dynamic taiji diagram in this embodiment, that is, the parts shown in FIG. 5(a), can be based on the original signal. The instantaneous change changes its size, proportion, area and depth (also can be color, such as the conversion of α to hue indicators), the immediate change of the original signal means that the physiological signal and control instructions can be changed at the same time, corresponding adjustment Execution module 5 brings information to the user.

Using the above-mentioned dynamic taiji diagram, the research and development personnel can immediately visualize, animate, and intuitively observe the detection module 1 to instantly detect the state change of the autonomic nerve activity between the experimental group and the control group.

Next, please refer to FIG. 5(b), and FIG. 5(b) is a schematic diagram of the effect of obesity on the ability of autonomic regulation by using the present invention. The subjects were divided into experimental group F and control group NF, assuming that experimental group F was a subject of obesity, and control group NF was a non-obese subject. At the same time, observe the dynamic taiji diagram, and apply the first influence means T1 (for example: acupuncture and acupoint massage) to the two groups according to the time series, and then observe the changes and differences of the dynamic taiji diagram immediately, and then apply the second influence means T2. At the time, the physiological state between the two groups will produce different changes, thereby serving as a method of verifying the first influencing means T1 and the second influencing means T2.

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

Example 5

In the fifth embodiment, the heart rhythm variation analysis is taken as an example to illustrate how the present invention applies the biological feedback and the stream to the execution module 5 having the display device as the evaluation tool.

Academically, heart rhythm variation analysis is commonly used to observe the concentration of the subject's attention. When the trained subject concentrates, the sympathetic activity is significantly enhanced and the parasympathetic activity is inhibited. The responses are expressed in power. In terms of spectral density, that is, LF energy rises rapidly.

Please refer to FIG. 6(a) and FIG. 6(b). FIG. 6(a) is a schematic diagram of 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. 6(a) shows the power spectral density of the subject, and Fig. 6(b) shows the power spectral density of the attention concentrator, and the dynamic observation subject changes from Fig. 6(a) to Fig. 6(b). It is possible to understand the speed and intensity of the subject's attention as a basis for evaluating the subject.

In addition to mental training, concentration training or movements related to physiological conditions such as shooting, the present invention can be utilized as an assessment tool or an autonomous training tool.

Example 6

In the sixth embodiment, the heart rhythm variation analysis is taken as an example to illustrate how the present invention further applies biofeedback to the execution module 5 such as a health care device.

Self-health managers often use health equipment to help with health management. Common equipment such as pressure-reducing chairs, decompression beds, massage chairs and other rolling equipment, or treadmills, flywheels and other sports equipment. These devices typically have regulatory functions such as strong or weak 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, and any device having a screen display function can be used as another execution module 5. When the user uses the detection device (equivalent to the detection module 1) and uses the health equipment at the same time (equivalent to execution) In the module 5), the detecting device (the detecting module 1) obtains the original signal of the user, and automatically analyzes the current physiological signal of the user through the analysis control module 4 and generates a corresponding control command, by the foregoing embodiment. The dynamic taiji diagram used in 4 is displayed on an execution module 5 having a screen display function device for instantly returning the autonomic nerve state change to the user. In addition, the analysis control module 4 simultaneously sends a control command signal to the health equipment. (Another execution module 5) performs regulation.

It can be seen from the present embodiment that the execution module 5 that can be used in the present invention is not limited to one type, and the analysis control module 4 can simultaneously connect a plurality of execution modules 5 and control the deployment between them according to user requirements.

Through the above-mentioned cycle of detection and regulation, the user can adjust the health equipment to the most suitable state to help the user achieve the health goal.

Finally, please refer to FIG. 7. FIG. 7 is a flow chart of the operation method of the biological feedback system of the present invention. First, step (a) is performed, and the detecting module 1 detects an original signal generated by a user, and then performs step (b), and the detecting module 1 simultaneously transmits the original signal to the data base 2 and the analyzing module 3, and the The database 2 stores the original signal.

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

Then, in step (c), the parsing module 3 analyzes the original signal stream and converts the original signal into a physiological signal, and then streams the physiological signal to an analysis control module 4.

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

Then, in step (d), the analysis control module 4 analyzes the physiological signal stream and issues a control command stream to the execution module 5.

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

When the user or the execution module 5 adjusts the action in step (f), the step (a) is returned to and executed, and the detection module 1 immediately obtains a new result generated by the user or the adjustment function of the execution module 5. The original signal is then executed in the same order (b) to (f) to achieve the biofeedback effect until the user finds the physiological state that is most suitable for him.

The "action" adjusted by the user is not limited to the movement of the bone or muscle, and is actually at least one physiological state change, such as breathing, blood pressure, heartbeat, nerve activity or mental state; and the execution mode The "action" of the group 5 adjustment is substantially a change of at least one of the operating conditions, such as the pressure rail of the massage chair or the running speed of the treadmill, etc., and the invention is not limited thereto.

Through the application of the invention, the physiological detection can be introduced into the level of two-way communication, the health value of the physiological detection can be greatly improved, the more complete information can be presented, and the cycle of benign feedback can be established, which shows the progress of the invention.

However, the above is only the preferred embodiment of the present invention, and the scope of the invention is not limited thereto, that is, the simple equivalent changes and modifications according to the scope and the description of the present invention remain. It is within the scope of the invention.

1‧‧‧Test module

2‧‧‧Database

3‧‧‧analysis module

4‧‧‧Analytical Control Module

5‧‧‧Execution module

Claims (10)

A bio-feedback system includes: a detection module; a database connected to the detection module; an analysis module respectively connected to the detection module and the database, wherein the analysis module is immediately analyzed from the detection The original signal stream of the module or the database is converted into a physiological signal corresponding to one of the original signals; an analysis control module is connected to the analysis module, and the analysis control module receives the physiological signal and Converting to a control command; and at least one execution module coupled to the analysis control module, the at least one execution module executing the control command stream from the analysis control module. The bio-feedback system of claim 1, wherein the database stores the original signal from the detection module, and the original signal is reused by the analysis module. The biological feedback system of claim 1, wherein the detection module is a device having an electrocardiography (ECG) measurement, a myoelectric wave measurement, an eye movement measurement, an electroencephalogram measurement, or a photoplethysmography (PPG) function. The biological feedback system of claim 1, wherein the original signal is electrocardiogram data, myoelectric wave data, eye movement data, brain wave data, pulse data, or a combination thereof. The biological feedback system of claim 1, wherein the control instruction is displayed as an animation, wherein the animation is a dynamic chart, a dynamic analysis chart, a dynamic physiological waveform chart, a Dynamic Power Spectral Density (PSD) map, and a dynamic Heart rate scatter plot (RRI Scatter), dynamic tai chi map, dynamic character map, or a combination thereof. The biological feedback system of claim 5, wherein the dynamic pylon diagram comprises a maximum drawing diameter, a homogenous user diameter, a tai chi diameter, a tai chi diameter, a tai chi diameter, a tai chi color, and a tai chi. The bio-feedback system of claim 1, wherein the execution module is a television, a smart phone, a smart watch, a wristband, a computer, a tablet, a health aid, a sports device, a medical device, a software, or a combination thereof. A method for operating a biological feedback system includes: (a) a detection module detecting a raw signal generated by a user; and (b) the detection module simultaneously transmitting the original signal to a database and an analysis module. The database stores the original signal; (c) the parsing module analyzes the original signal stream in real time, and converts the original signal into a physiological signal for transmission to an analysis control module; (d) analyzing the analysis control module The physiological signal stream is converted and converted into a control command, and the control command is transmitted to the at least one execution module; and (e) the at least one execution module executes the control command stream. The method for operating a biological feedback system according to claim 8, wherein after performing step (e), performing: (f) the user or the execution module adjusting action; performing step (f) and then performing the step again (a). The operation method of the biological feedback system according to claim 9, wherein the action adjusted by the user in the step (f) is at least one physiological state change, and the action of the execution module adjustment is at least one operating condition change.