WO2020190332A1

WO2020190332A1 - Meridian energy analyzing system and analyzing method thereof

Info

Publication number: WO2020190332A1
Application number: PCT/US2019/053311
Authority: WO
Inventors: Ji-Li CHUNG
Original assignee: Potential Techs, Llc
Priority date: 2019-03-21
Filing date: 2019-09-26
Publication date: 2020-09-24
Also published as: TW202037331A

Abstract

A meridian energy analyzing system directly detects meridian acupoints on different meridian to collect multiple bio-signals of meridian acupoints on different meridians in human body and then analyzes the bio-signals in frequency domain to have the accurate meridian energies. Therefore, the present invention does not require complex surmises to calculate the meridian energies of all meridians in the human body, but the results of the present invention are more accurate than attempting to detecting all meridians' energy from one single point. In addition, the meridian energies are further processed to meridian energy ratios as meridian relative power. According to meridian relative power, the present invention easily provides correct training plan to help people have meridian normal pattern.

Description

M ERIDIAN ENERGY ANALYZIN' G SYSTEM AND ANALYZING

METHOD THEREOF

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of United States provisional application filed on March 21, 2019 and having application Set No

62/821.456, the entire contents of which are hereby incorporated herein by reference.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention is related to a meridian energy analyzing technology, and more particularly to a meridian energy analyzing system and an analyzing method thereof,

2. Description of the Prior Ails

Traditional Chinese doctor diagnoses patient’s diseases according to pulse diagnosis results. Since the conventional pulse diagnosis is done manually and subjectively, an accuracy and objectivity of the pulse diagnosis results are hard to be confirmed- Accordingly, people attempt to develop some machines to analyze meridian energy to accurately diagnosis patient's diseases.

One of the conventional machines of analyzing meridian energy provides analysis results of the meridian energy by analyzing resistance or micro-current of each meridian acupoint (or also called as acupuncture point). However, the conventional machine lacks mechanisms to manage noises that may impact the accuracy of meridian energy measurement. Another

conventional machine of analyzing meridian energy detects a pulse-wave signal from one meridian acupoint and analyzes the pulse-wave signal in the frequency domain to obtain all meridian energies of the human body. Since the pulse- wave signal from one meridian acupoint usually contains body noises and/or environment noises and the conventional machine requires a lot of assumptions regarding which frequency relates to which meridian, the analysis results of all meridian energies are still inaccurate.

To overcome inaccurate analysis results of all meridian energies, the present invention provides a meridian energy analyzing system and an analyzing method thereof to mitigate or obviate the aforementioned problems.

SUMMARY OF THE INVENTION

An ob_jecti ve of the present invention is to provide a meridian energy analyzin system analyzing method thereof

To achieve the ob_jective as mentioned above, the meridian energy analyzing system has:

a sensing module having multiple bio-signal detectors, wherein each bio-signal detector is adapted to detect a meridian acupoint and outputs a bio-signal of the meridian acupoint;

an analyzing module connected to the sensing module through a signal processin module to convert each bio-signal to a frequency distribution and having an analysis procedure, wherein the analysis procedure comprises steps of:

(a) calculating power features of each meridian according to the corresponding frequency distribution;

(b) calculating power feature ratios according to the power features; an

(e) comparing the power feature ratios with corresponding normal power feature ratios respectively to have first differences between the power feature ratios and the corresponding normal power feature ratios; and

an output module connected to the analyzing module to output the first differences.

Based on the foregoing description, the meridian energy analyzing system directly detects meridian acupoints on different meridian to collect multiple bio-signals of meridian acupoints on different meridians in human body and then analyzes the bio-signals in frequency domain to have the accurate meridian energies. Therefore, the present invention does not require complex surmises to calculate the meridian energies of all meridians in the human body.

To achieve the objective as mentioned above, the meridian energ analyzing method has steps of;

(a) collecting multiple bio-signals for different eridian acupoints of different meridians of a human body;

(b) converting each of the bio-signals to a frequency distribution; wherein the bio-signals are respectively converted to the frequency

distributions by the Fourier transform;

(c) calculating power features of each meridian according to the corresponding frequency distribution;

(d) calculating power feature ratios according to the power features;

(f) outputting the first differences between the power feature ratios and corresponding normal power feature ratios.

Based on the foregoing description, the meridian energy analyzing system directly detects meridian acupoints on different meridian to collect multiple bio-signals of meridian acupoints on different meridians in human body and then analyzes the bio-signals in frequency domain to have the accurate meridian energies. Therefore_» the present invention does not require complex surmises to calculate the meridian energies of all meridians in the human body.

Other objectives, advantages and novel features of the invention will become more apparent: from the following detailed description when takers in con_junction with the accompanying drawings.

BRIEF DESCRIPTION OF TH DRAWINGS

Fig. 1. is a functional block diagram of an analyzing system in accordance with the present invention;

Fig. 2 is a schematic view of a first meridian definition including 12 meridians and 12 end acupoints thereof in accordance with the present invention;

Fig. 3 is a schematic view of a second meridian definition including 1.2 meridians and 12 end acupoints thereof in accordance with the present invention;

Fig. 4 is a schematic view of a third meridian definition including 12 meridians and 12 end acupoints thereof in accordance with the present invention;

Fig. 5 is a schematic view of a fourth meridian definition including 12 meridians and 12 end acupoints thereof in accordance with the present invention;

Fig. 6 is a pulse-wave diagram in time domain showing four pulse-wave signals from corresponding meridian acupoints in accordance with the present invention;

Fig. 7.4 to 7D are frequency distributions corresponding to four pulse-wave signals of Fig, 6;

Fig. 8A is another pulse-wave diagram in time domain showing a pulse- wave signal including muscle noise in accordance with the present invention;

Fig 8B is a frequency distribution diagram corresponding to the pulse-wave signal of Fig 8 A;

Fig. 8C is another pulse-wave diagram in time domain showing a pulse- wave signal including 60Hz noise in accordance with the present invention;

Fig 8D is a frequency distribution diagram corresponding to the pulse-wave signal of Fig. 8C;

Fig. 8E is another pulse-wave diagram in time domain showing a pulse- wave signal including heartbeat noise in accordance with the present invention;

Fig. 8F is a frequency distribution diagram corresponding to the pulse-wave signal of Fig 8E;

Fig. 9A is a bar graph showing normalized first differences between the power feature ratios and corresponding normal power feature ratios in six different frequency bands, wherein four of them are not shown since they are close to 0%;

Fig. 9B is a bar graph showing normalized first differences between the power feature ratios and corresponding normal power feature ratios for four different meridians in the same frequency band, wherein two of them are not shown since they are close to 0%;

Fig. 9C is a bar graph showing normalized second difference between the meridian energy ratios and corresponding normal meridian energ ratios for first to fourth meridians;

Fig. 10A is a flow chart of a first embodiment of an analyzing method in accordance with the present invention;

Fig. lOB is a flow chart of a second embodiment of an analyzing method in accordance with the present invention;

Fig. IOC is a flow chart of a third embodiment of an analyzing method in accordance with the present i vention;

Fig. I I A is a perspective view of a conductive 3D sponge in

accordance with the present invention;

Fig. I I SB is an enlarge view of Fig. 11 A;

Figs. I 1C to 1 IF are perspective views of different sponges in accordance with the present: invention;

Fig. 12A is a to view of a first embodiment of a clipper in accordance with the present invention, wherein the clipper is closed;

Fig. 1.2B is a side view of Fig. 12 A;

Fig. 12C is another top view of a clipper in accordance with the present invention, wherein the clipper is opened;

Fig. 12D is a side view of Fig, 12C;

Fig. 1.2E is a side view of a second embodiment of a clipper in

accordance with the present invention, wherein the clipper is closed;

Fig. 12F is a top view of Fig. 12E;

Fig, 13A is a glove on which the bio-signal detectors are mounted in accordance with the present invention;

Fig. 1.3B is another view of the glove of Fig 13 A in accordance with the present invention;

Fig. 14A is a top view of a mesh cap on which the bio-signal detectors are mounted in accordance with the present invention;

Fig. 14B is an operational view of a sensor carrier of Fig. 14 A;

Fig. 1.4C is a perspective view of a hat on which the bio-signal detectors are mounted in accordance with the present invention;

Fig. 14D is an enlarged and operational view of a sensor carrier mounted on the hat of Fig. I4C;

Fig. 15 A is a front view of a first embodiment of a shoulder strap o which the bio-signal detectors are mounted in accordance with the present invention;

Fig. 15B is a perspecti ve view of a second embodiment of a shoulder strap on which the bio-signal detectors are mounted in accordance with the present invention; and

Figs, 16.4 to 16F are perspective views of different fixing devices on which the bio-signal detectors are mounte in accordance with the present invention.

DETAI LED DESCRIPTION OF THE EMBODIMENTS

The present invention provides a meridian energy analyzing system analyzing method thereof to have accurate analysis results of meridian energy in human body. With embodiments and drawings thereof the features of the present invention are described in detail as follow.

Fig 1 shows a functional block diagram of a meridian energy analyzing system in accordance with the present invention. The meridian energy analyzing system has a sensing module 10, a signal processing module 20, a data storage device 30 and an analyzing module 40 and an output module 50.

The sensing module 10 has multiple bio-signal detectors 1 1 , a reference signal detector 12 and a ground signal detector 13. The bio-signal detectors 1 1 axe used to touch the skin and correspond to multiple acupoints of meridians in human body. With further reference to Figs. 2, 3, 4 and 5, four meridian acupoint definitions are shown. When the bio-signal detector 1 1 touches the skin and corresponds to the acupoint according to anyone of meridian acupoint definitions, the bio-signal detector 11 easily detects a bio-signal from the touched acupoint. In one embodiment, the bio-signal may be but not limited to a pulse-wave current signal or a pulse-wave voltage signal (hereinafter pulse-wave signal). The bio-signal detector 11 may detect bio-signals or other forms of activities (such as, but not limited to, heartbeat, S , temperature, pressure, and other information) in the human body (such as, but not limited to. twelve meridians, two centerline meridians, organ system, circulatory system, lymphatic system, and nervous system). The present invention may use anyone of the meridian acupoint definitions, but the first and second meridian acupoint definitions shown in Figs. 2 and 3 are more general. Here, the first meridian acupoin definition is selected to describe the present invention.

The signal processing module 20 is connected to the sensing module 10 and receives and processes the pulse-wave signal from each bio-signal detector 1 1. In one embodiment, the processing module 30 mainly has a selector 21 , an amplifier 22, a resistance detector 23, an analog signal processing unit 24 and an analog to digital converter 25 (hereinafter ADC), The resistance detector 23 is connected to sensing module 10 through the selector 1 i to obtain a resistance or a micro-current of the meridian acupoint. The amplifier 22 is connected between the selector 21 and the analog signal processing unit 24 The amplifier 22 amplifies the pulse- wave signal of each bio-signal detector 11 selected by the selector 21 and then outputs the amplified pulse- wave signal to the analog signal processing unit 24. In one embodiment, the analog signal processing unit 24 mainly has regulators, a low-pass filter, a high-pass filter, and a band-pass filter, so the analog signal processing unit 24 processes the amplified pulse-wave signal with such different frequency filters. The ADC 25 is

connected between the analog signal processing unit 24 and the analyzing module 40. The ADC 25 converts the pulse-wave signal to digital pulse data and then outputs to the analyzing module 40 and/or the data storage device 30. The storage device 30 may be integrated in the signal processing module 20, in the analyzing module 40 or be a cloud storage space linked to the signal processing module 20 or analyzing module 40.

The analyzing module 40 directly receives the digital poise data for each selected bio-signal detector 11 through the signal processing module 20 and then converts the digital pulse data in time domain to a digital pulse data in frequency domain. In one embodiment, the analyzing module 40 uses Fourier Transform to convert the digital pulse data in time domain to the digital pulse data in frequency domain Thai is, the puke data in frequency domain corresponding to the pulse-wave signal is distributed in a specific band

(ex:0-60Hz). The analyzing module 40 further executes an analysis procedure to analyze the digital pulse data in frequency domain to obtain analysis results of the meridian energy corresponding to the meridian acupoint on which the selected bio-signal detector 11 is. The analyzing module 40 has a database 41 storing diagnosis suggestions, treatment suggestions and training plans, so the analysis results may further have the training plan, the diagnosis suggestions or the treatment suggestions according to the analysis results of the meridian energy.

The output module 50 is connected to the analyzing module 40 to output the analysis result of the meridian energy. The analyzing module 40 and the output module 50 may be combined as a device, such as a computer, a smartphone, a cloud server or the like.

With reference to Fig 6, four pulse-wave signals Si, S2, S3, S4 in time domain are detected by four bio-signal detectors 11 on the skin corresponding to four different acupoints on different meridians, When the analyzing module 40 receives the digital pulse data corresponding to the pulse-wave signals, the digital pulse data are converted to the digital pulse data in frequency domain as shown in Figs. 7 A to 7D. However, the pulse-wave signal SI, S2, S3, S4 may include different noises. Using one of the pulse-wave signals S I as an example, the pulse-wave signal SI may include muscle noise Nl shown in Figs 8 A and 8B, 60Hz noise N2 shown in Figs. 8C and 8D or heartbeat noise N3 shown in Fig 8E and 8F In comparison with Figs. 6 and 7A, the pulse-wave signal S I having such noise Nl, N2 or 3 shown in Figs. 8 A to 8F is unstable. To have more accurate pulse- wave signal, such noises have to be eliminated.

The muscle noise N 1 may be minimized if the muscle close to the bio-signal detector 11 is relaxed. Therefore, people to be detected relaxes his or her muscles through observing a variation of the pulse-wave signal on the output module 50, as shown in Figs. 8A and SB, In addition, the signal processin module 20 further automatically eliminates the pulse-wave signal having muscle noise Nl when an amplitude of the pulse-wave signal exceeds a muscle noise threshold.

The 60Hz noise N2 is caused by electrical devices which are

electrically connected to a power loop provided to the analyzing system of the present invention. With reference to Figs. 8C and 8D, an operator of the analyzing system disconnects the electrical devices from po wer sockets of the power loop to remove the 60Hz noise N2 from the pulse-wave signal. In addition, the signal processing module 20 further has a first band reject filter to filter the 60 Hz noise. Since the heart beat noise M3 has a fixed frequency (about 1Hz), as shown in Figs. 8E and 8F_t the signal processing module 20 further have a second band reject filter to filter the IHz noise. In another solution to remove the heartbeat noise, the reference detector 12 and the ground detector 13 touches the skin and are close to the bio-signal detector 1 1 , the signal processing module 20 can receive the pulse-wave signal from the bio-signal detector 1 1 without heartbeat noise 3 in addition, when the pulse-wave signal having the noise with the fixed frequency (such as 6GHz or IHz) is converted to the pulse data in frequency domain, the analyzing module 40 further determines whether peaks of the pulse data at the fixed frequency exceed a noise threshold. If a determination result is positive, the peaks over the noise threshold are ignored. Means to remove the peaks over the noise threshold may be software programs, A Ϊ algorithm, machine learning or the like.

When the analyzing module 40 receives the pulse data in time domain corresponding to the pulse-wave signals without noise, the analyzing module 40 converts the digital pulse data in time domain to the digital pulse data in frequency domain as shown in Figs 7 A to 7D. And then, the analyzing module 40 executes the analysis procedure to analyze the digital pulse data in frequency domain. The digital pulse data in frequency domain corresponding to the pulse-wave signal is distributed in a specific band (ex:0-60Hz) and is shown as a frequency distribution in a bar graph. In the analysis procedure, the analyzing module 40 identifies multiple power features of each meridian and the power features of each meridian respectively correspond to different specific frequency bands or different specific peaks. Each of the power features is determined by calculating power of each selected frequency band or of each selected peak of frequency distribution according to a first equation ( ! }.

Power:

CO

Then, the power features are summed up according to a second equation (2) to calculate the meridian energy.

Energy:

ranges ..(2)

In the traditional Chinese medicine, the power features of each meridian energies can response human body’s specific health conditions.

Therefore, a great quantity of the analysis results of the power features of each meridian from different people in normal (or desired) health condition is collected to define a normal power feature pattern of each meridian in human body; For example, if a first to sixth power features corresponding to six frequency bands or six frequency peaks of the first meridian in human body’s left side are se lected, the related power feature ratios of the normal power feature pattern are around 1 :Q.5:0.8:0.7:1:0.5. When a patient is sensed, the first to sixth power feature ratios of the first meridian are calculated and should be 1 :0.6:0.8:0,7:0.5:0.5 in six different frequency bands. First differences between the power feature ratios and corresponding normal power feature ratios are (1-1 ) : (0.6- 0.5) : (0.8- 0.8) : (0.7-0.7) (0.5-1) : (0.5-0.5)-0:0.1 :0:0:-0.5:0.

After a normalization, the first differences for the first meridian are 0 : 20% : 0 :

0 : -50% : 0, as shown in Fig. 9 A.

In the traditional Chinese medicine, the power features of different meridians are related. The analyzing module 40 also identifies a normal related power feature pattern including multiple normal power feature ratios of the related meridians in the same frequency band. For example, the first power feature ratios of the first to fourth meridian are related and are 1 : 0.6: 0.8: 0.7.

If a patient is sensed, four power feature ratios of the first to fourth meridians in the same frequency band are calculated and should be

1 :0.9:0.6:0.7. The four feature strength ratios of the first to fourth meridians are further compared with the normal related power feature pattern. The first differences between the four power feature ratios and the normal related power feature pattern are (1 -1 ) : (0,9 0, 6) : (0.6-0.8) : (0.7-0.7)~0:0.3:-0 2:0. After the normalization, the normalized first differences for the first to fourth meridians are 0 : 50% : 25%: 0, shown in Fig. 9B.

Furthermore, in the traditional Chinese medicine, the whole meridian energies can respectively response human body's different health conditions. Therefore, a great quantity of the analysis results of the meridian energies from different people in normal (or desired) health condition is collected to define a normal meridian energy pattern of the first to twelfth meridians in human body. Therefore, the analyzing module 40 further sums up the powers of each meridian according to a second equation (2) to calculate the meridian energy.

Energy:

selected ranges . (2)

For example, if a first to twelfth meridian energy ratios for most healthy people are around i: 0.8 : 1.2 : 0.9 : i . i : 0.7 : i .05 : i .15 : 0.85 : 0.95 : 1 ,25 : 0.75 (÷/- particular ratio ranges), it can be define a meridian normal pattern 1 : 0.8 : 1/2 : 0 9 : 1 ,1 ; 0.7 ; 1.05 : 1.15 : 0,85 : 0 95 : 1,25 : 0.75 (+/- particular ratio ranges). The most healthy people are selected from a particular group, such as particular ages, genders, and/or ethnicities.

Therefore, the analyzing module 40 may further calculate meridian energy ratios among the calculated meridian energies and then compares the calculated meridian energy ratios with the corresponding normal meridia energy ratios of the meridian normal pattern to obtain second differences shown in a meridian relative strength graph. Here e illustrate one example with four meridians. For example, the analyzing module 40 calculates the four meridian energy ratios according to the meridian energies for a people and the calculate first to fourth meridian energy' ratios are 1 : 0.65 : 1.2 : 0.9. In comparison with the corresponding normal meridian normal energy ratios, the second differences therebetween are 0:0 65:0:0 That is, the second meridian energy ratio is 0 65 and lower than the second normal meridian energy ratio 0 8 of the meridian normal pattern. Alter a normalization, the normalized second differences for the first to fourth meridians are 0%, -19%, 0% and 0%, as shown in Fig. 9€,

When the analyzing module 40 calculates the normalized first differences for one meridian of people, the normalized first differences for multiple related meridians of people, or the normalized second differences for all meridians of people, the normalized first differences or the normalized second differences which are not close to 0% are selected. The analyzing module 40 reads the database 41 to obtain a relative diagnosis suggestion. treatment suggestion or training plan according to the selected normalized power features or the selected normalized meridian energies. The training plan may include different bio-stimulating signals, such as suitable videos, music or electrotherapy, to stimulate people's brain areas and tries to adjust the selected normalized meridian energies to be close to 0%. That is, when people is tested and his or her normalized meridian energ of the second meridian is 19% lower than the normal pattern, the normalized meridian energy of the second meridian will be close to 0% or the second meridian energy ratio will be close to the second normal meridian energy ratio 0.8 in the meridian normal pattern after people accept the training plan. Therefore, the training plan is executed until the meridian energy ratio of the selected at least one meridian energy is close to the corresponding normal meridian energy ratio.

Based on the foregoing description, with reference to Fig. 11 A, the analyzing method has following steps of;

(a) collecting multiple bio-signals for different meridian acupoints of different meridians of a human bod (S10); wherein in one embodiment, the bio-signal may be but not limited to a pulse-wave signal;

(b) converting each of the bio-signals to a frequency distribution (Si 1); wherein in the one embodiment, the pulse-wave signal i converted to the frequency distribution by the Fourier transform;

(c) calculating multiple power features of each meridian according to the corresponding frequency distribution (SI 2); wherein in one embodiment, each meridian has multiple features shown in the frequency distribution and respectively correspond a specific frequency band or a specific peak, so each of the power features is determined by calculating power of each selected frequency band or of each selected peak of frequency distribution according to a first equation (

(d) calculating power feature ratios according to the power features

(SB);

(e) comparing the power feature ratios of each meridian with corresponding normal power feature ratios respectively to have first differences (SI 4); wherein in the embodiment, the first differences are calculated by comparing the power feature ratios of each meridian with the normal power feature ratios of corresponding meridian. In another embodiment, the first differences are calculated by comparing the power feature ratios of different meridians in the same frequency band with the normal power feature ratios of the corresponding meridians; wherein in one embodiment, the first differences are further normalized to obtain first percentage differences between the meridian energy ratios and corresponding normal meridian energy ratios; and

(f) outputting first differences between the power feature ratios and corresponding normal power feature ratios (SI 5); wherein in one embodiment, the first percentage differences are outputted.

Furthermore, the analyzing method of the present invention also has following steps of:

(g) calculating meridian energies according to the frequency distributions (Si 6); wherein in one embodiment, the powers are summed up according to a second equation (Ex the meridian energy;

(h) calculating meridian energy ratios according to the meridian energies (SI 7);

(i) comparing the meridian energy ratios with corresponding normal meridian energy ratios respectively to have second differences (SIS); wherein in one embodiment, the meridian energy ratios are further normalized to obtain second percentage differences between the meridian energy ratios and corresponding normal meridian energy ratios; and

(j) outputting the second differences between tire meridian energy ratios and corresponding normal meridian energy ratios (SI 9); wherein in one embodiment, the second percentage differences are outputted,

hi addition, with further reference to Fig. 10C, the analyzing method may further have following steps of:

(k) selecting at least one meridian energy, wherein the meridian energy ratio of the selected at least one meridian energy is not close to the

corresponding normal meridian energy ratio (S2G);

(l) obtaining a training plan according to the selected at least one meridian energy (S21 ); and

(m) executing the training plan until the meridian energy ratio of the selected at least one meridian energy is close to the corresponding normal meridian energy ratio (S22).

To obtain better bio-signal, the bio-signal detector may further have an inteiposer formed thereon. The interposer may be a conductive sponge, a conductive silicone pad or a conductive pressure sensitive adhesive

(hereinafter conductive PSA), in addition, salted water or conductive gel may be applied to the conductive sponge, the conductive poiymeric/fiber sponge or the conductive foam sponge to further enhance conductivity thereof.

With reference to Figs, 1 I A and IIB, the conductive sponge 110 may be a conductive 3D-structured sponge, metal sponge, conductive

poiymeric/fiber sponge, conductive foam sponge with big or small porous, or sponge 110 {conductive or not) with a conductive surface layer 1 11 (e.g., metal coating, metal mesh, conductive polymer coaling, etc.) as shown in Fig 1 1 C, Furthermore, in Fig. HD, another conductive sponge is ahown and has a non-cond active sponge 110, a conductive surface layer 1 11 , a snap bottom 112 and a fixing element 113. The snap button 1 12 is mounted on the fixing element 113, such as a tape, and the fixing element 113 is further mounted on the conductive surface layer 1 1 1. The fixing element is made of eondcutive material. The fixing element 113 could also wra the sides of the

non-condeutive sponge 110 to enhance stability, as shown in Figs. HE and 11 F. The conductive sponge could be connected to an electrode (such as a snap button or a pin) with other methods, such as soldering, cold soldering, conductive PSA, conductive glue (such as cold solder, no heat solder, Copper lock, Silverbearing Solder, Silver Epoxy Adhesive, etc.), conductive gel/paste, or butlons/elippers. Super glue can also he added to reinforce the connection strength between the electrode and the conductive sponge. The conductive 3D structured sponge provides a high compression tolerance with low (or preferred) compression force while providing stable conductivity. The conductive 3D structured sponge is consisted of cross-linked lines, cross-linked rings, polygon holes, diamond holes, or random-shaped holes, so has multiple end points extending around hairs to contact skin/scalp directly. Sponge porous sizes and sponge dimensions may be adjusted to optimize properties of compressibility, conductivity, comfortableness, durability, and cost.

The conductive silicone may contact skin repeatedly without losing its adhesions. Silicone compressibility may be adjusted to produce comfortable compression force and provide required sensor thickness tolerance in addition, silicone surface properties (e.g., softness, flexibility, profiles) may be adjusted to contact skin/scalp more firmly.

The conductive PSA does not solidify to form a solid material, but remain viscous. Bonds are made by applying pressure. PSA remains permanently tacky and has the ability to wet surfaces on contact. The conductive PSA can flow around hairs to adhere to scalp more firmly. The conductive PSA properties are adjusted so that when PSA is removed from scalp/skin, the conductive PSA will break internally in addition, the

compositions and/or percentages of the conductive PSA compositions are adjusted to optimize the sensor Properties (such as conductivity,

comfortableness, durability, cost, etc.). The conductive PSA may be replaced by a conductive double-sided tape.

In addition, the bio-signal detector may be a compressible sensor with pin. The compressible sensors are made of conductive fillers with silicone and/or rubber. For example, we can optimize sensor Properties and/or

Comfortableness by tuning Filler and Silicone or Rubber compositions, percentages, sizes, structure (e.g., doping nano/micro conductive particles for lower hardness, coating larger conductive particles for higher reliability), and pin's Shapes, numbers, diameters, lengths (e.g., outer pins can be longer than inner pins). We can have more than one region of Pins and have different regions connecting to different sensors and wires. We can have walls outside of each region to avoid conductive paste or PSA overflowing out of each region.

Since the bio-signal detector may be fixed on the body to touch the skin, different fixing devices are designed. With reference to Figs. 12 A. to 12D, one of the fixing devices is a clipper 100a. In Figs 12A and I2B, the clipper is closed in Figs. 12C and 12D, the dipper is opened. In addition, another clipper 100a is shown in Figs. 12E and 12F, the clipper 100a has two opposite snapping part 102 and two pressing parts 103 and a spring 104 mounted between the two pressing parts 103.

In Fig. 13 A, one of the fixing devices is a glove 100b having multiple finger clippers 101, As shown in Fig, 13B, one of the finger clippers is opened to show a finger F Since the finger clipper is easily opened and closed, the bio-signal detectors mounted thereon are easily firmly touched the meridian acupoints on the finger F. In addition, a male button and a female button are easily fastened through a mesh of a mesh glove, so the detector is also easily mounted on the glove by the male button or a female button. The male button or a female button are used as an electrode of the detector. In Figs. 14A and 14B, one of the fixing devices is a mesh cap 100c and the mesh cap 100c has multiple strips 102 on which the bio-signal detectors 11 axe mounted. When people wear the mesh cap 100c, the bio-signal detectors correspond the meridian acupoints on the head. In Figs 14C and 14C, a hat 100c has multiple sensor clipper 101a and each sensor clipper 101a fixes a sensor therein.

In Fig. 15 A, the fixing device is a shoulder strap lOOd The shoulder strap 100d has multiple elastic bands 1 13 on which the bio-signal detectors 11 are mounted. When people wear shoulder strap 10Od, the bio-signal detectors correspond the meridian acupoints on the neck, the back and the chest.

In Fig. 16A to 16F, there are different head fixers 100, such as hat, different type kerchiefs, different headbands, different hairpins or the like.

Based on the foregoing description, the meridian energy analyzing system directly detects meridian acupoints on different meridian to collect multiple bio-signals of meridian acupoints on different meridians in human body and then analyzes the bio-signals in frequency domain to have the accurate meridian energies. Therefore, the present invention does not require complex surmises to calculate the meridian energies of all meridians in the human body, in addition, the meridian energies are further processed to meridian energy ratios as meridian relative power. According to meridian relative power, the present invention easily provides correct training plan to help people have meridian normal pattern.

Even though numerous characteristics and advantages of the present invention have been set forth in the foregoin description, together with details of the structure and features of the invention, the disclosure is illustrative only, Changes may be made in the details, especially in matters of shape, size, and arrangement of parts within the principles of the invention to the full extent indicated by the broad general meaning of the terms in which the appended claims are expressed.

Claims

WHAT IS CLAIMED IS:

I . A meridian energy analyzing system, comprising:

an analyzing module connected to the sensing module through a signal processing module to convert each bio-signal to a frequency distribution and having an analysis procedure, wherein the analysis procedure comprises steps of:

(b) calculating power feature ratios according to the power features; and

(c) comparing the power feature ratios with corresponding normal power feature ratios respectively to have first differences between the power feature ratios and the corresponding normal power feature ratios; and

2 The meridian energy analyzing system as claimed in claim 1 , wherein in the step (a), the power features of each meridian are determined by calculating power of each selected frequency band or of each selected peak of each frequency distribution according to a first equation, and the first equation

3 The meridian energy analyzing system as claimed hi claim 2, wherein in the step (c), the first differences are calculated by comparing the power feature ratios of each meridian with the normal power feature ratios of the corresponding meridian.

4 The meridian energy analyzing system as claimed in claim 2, wherein in the step (c), the first differences are calculated by comparing the power feature ratios of the related meridians in the same frequency band with the normal power feature ratios of the corresponding meridians.

5 The meridian energy analyzing system as claimed in claim 3.

wherein

in the step (c), the power feature ratios are further normalized to obtain first percentage differences between the power feature ratios of each meridian and corresponding normal power feature ratios of the corresponding meridian; and

the output module outputs the first percentage differences.

6 The meridian energy analyzing system as claimed in claim 4, wherein

in the step (c), the power feature ratios are further normalized to obtain first percentage differences between the power feature ratios of the related meridians in the same frequency band and corresponding normal power feature ratios of the corresponding meridian; and

the output module outputs the first percentage differences.

7 The meridian energy analyzing system as claimed in claim 2.

wherein in the step (a), the powers of each meridian are summed up according to a second equation to calculate a meridian energy of the corresponding meridian, wherein the second equation is Ex

selected ranges.

8. The meridian energy analyzing system as claimed in claim 7, the analysis procedure comprises steps of:

(e) calculating meridian energy ratios according to the meridian energies; and

( i i comparing the meridian energy ratios with corresponding normal meridian energy ratios respectively to have second differences between the meridian energy ratios and corresponding normal meridian energy ratios, wherein the output module outputs the second differences.

9. The meridian energy analyzing system as claimed in claim 8, wherein

in the step (f), the second differences are further normalized to obtain second percentage differences between the meridian energy ratios and corresponding normal meridian energy ratios; and

the output module outputs the second percentage differences.

10. The meridian energy analyzing system as claimed in claim 1, wherein sensing module further comprises a ref erence detector and a ground detector.

1 1. The meridian energy analyzing system as claimed in claim 10, wherein the signal processing module comprises:

a selector connected to the sensing module; a resistance detector connected to the selector

an analog signal processing unit connected to the selector through an amplifier; and

an analog to digital converter connected between the analog signal processing unit and the analyzing module, wherein the analog to digital converter converts each bio-signal to digital data in time domain

12. The meridian energy analyzing system as claimed in claim 1 1 , wherein the analyzing module uses Fourier Transform to convert the digital data in time domain to the digital data in frequency domain, wherein the digital data in frequency domain is the frequency distribution,

13. The meridian energy analyzing system as claimed in claim 1 , wherein the bio-signal detector further has an interposer formed thereon.

14. The meridian energy analyzing system as claimed in claim 13, the interposer is a 3D-struetured sponge, a conductive silicone pad, a conductive pressure sensitive adhesive, or a conductive double-sided tape,

15. The meridian energy analyzing system as claimed in claim 13, wherein the bio-signal detector is a compressible sensor with a pin.

16. The meridian energy analyzing system as claimed in claim I, wherein the bio-signal detector is further mounted on a fixing device.

17. The meridian energy analyzing system as claimed i claim 1 , wherein the fixing device is a clipper, a mesh cap, a shoulder strap, a hat, a kerchief, a headband, a glove, a mesh glove with a male button and a female butto or a hairpin.

18. The meridian energy analyzing system as claimed in claim 13, wherein the interposer is a conductive sponge comprising:

a conductive surface layer formed on a non-conductive sponge; and a snap button mounted on the conductive surface layer through a fixing element made of condcutive material.

19. A meridian energy analyzing method, comprising steps of:

(a) collecting multiple bio-signals for different meridian acupoints of different meridians of a human body;

(b) converting each of the bio-signais to a frequency distribution; wherein the bio-signals are respectively converted to the frequency

distributions by the Fourier transform;

(d) calculating power f eature ratios according to the meridian energies;

(f) outputting the first differences between tire power feature ratios and corresponding normal power feature ratios.

20. The meridian energy analyzing method as claimed in claim 19, wherein in the step (c ), the power features of each meridian are determined by' calculating power of each selected frequency band or of each selected peak of each frequ ncy distribution according to a first equation, and the first equation

21 The meridian energy analyzing method as claimed in claim 20, wherein in the step (e), the first differences are calculated by comparing the power feature ratios of each meridian with the normal power feature ratios of the corresponding meridian,

22 The meridian energy analyzing method as claimed in claim 20, wherein in the step (e), the first differences are calculated by comparing the power feature ratios of the related meridians in the same frequency band with the normal power feature ratios of the corresponding meridians.

23 The meridian energy analyzing method as claimed in claim 21, wherein:

in the step (e), the first differences are further normalized to obtain first percentage differences between the power feature ratios of each meridian and corresponding normal power feature ratios of the corresponding meridian; and in the step (f), the output module outputs the first percentage differences,

24 The meridian energy analyzing method as claimed in claim 22, wherein:

in the step (e), the first differences are further normalized to obtain first percentage differences between the power feature ratios of the related meridians in the same frequency band and corresponding normal power feature ratios of the corresponding meridian; and

in the step (f), the output module outputs the first percentage differences.

25 The meridian energy analyzing method as claimed in claim 20, further comprising a step of (g) summing up the power features of each meridian according to a second equation to calculate a meridian energy of the corresponding meridian, wherein the second equation is Ex

( , b) — ( ^. sc, os)

, or selected ranges.

26. The meridian energy analyzing method as claimed in claim 25, further comprising steps of:

(h) calculating meridian energy ratios according to the meridian energies;

(i) comparing the meridian energy ratios with corresponding normal meridian energy ratios respectively to have second differences between tire meridian energy ratios and corresponding normal meridian energy ratios; and

0) outputting the second differences.

27. The meridian energy analyzing method as claimed in claim 26, wherein:

In the step (i), the second differences are further normalized to obtain second percentage differences between the meridian energy ratios and corresponding normal meridian energy ratios; and

in the step (j), the second percentage differences are outputted.

28. The meridian energy analyzing method as claimed in claim 23, further comprising steps of:

(k) selecting at least one normalized first percentage difference, wherein the selected at least one first percentage difference is larger than a normal number; (!) obtaining a training plan according to the selected at least one first percentage difference; and

(m) executing the training plan until the selected at least one first percentage difference is decreased to the normal number.

29 The meridian energy analyzing method as claimed in claim 24, further comprising steps of:

(k) selecting at least one normalized first percentage difference, wherein the selected at least one first percentage difference is larger than the normal number;

(!) obtaining a training plan according to the selected at least one first percentage difference; and

30 The meridian energy analyzing method as claimed in claim 27, further comprising steps of:

(k) selecting at least one normalized second percentage difference, wherein the selected at least one second percentage difference is larger than the normal number;

(!) obtaining a training plan according to the selected at least one second percentage difference; and

(m) executing the training plan until the selected at least one second percentage difference is equal to the normal number

31 The meridian energy analyzing method as claimed in claim 28, wherein the training plan has different bio-stimulating signals.

32 The meridian energy analyzing method as claimed in claim 29, wherein the training plan has different bio-stimulating signals.

33. The meridian energy analyzing method as claimed in claim 30, wherein the training plan has different hio-stimulaiing signals.