CN109189232A - A kind of capacitance data acquisition device and its gesture identification method for gesture identification - Google Patents

Abstract

The invention discloses a kind of capacitance data acquisition devices and its gesture identification method for gesture identification.Existing gesture identifying device is generally existing expensive, and the device is complicated, to the demanding problem of light.A kind of capacitance data acquisition device for gesture identification of the present invention, including capacitance signal collector and Acquisition Circuit.Capacitance signal collector includes metal foil, substrate and isolation board.Metal foil is fixed between substrate and isolation board.Acquisition Circuit includes main control module, power module and capacitance sensing module.The power module is master control module for power supply by voltage stabilizing chip.Main control module includes single-chip microcontroller, the first key switch, the first crystal oscillator and the second crystal oscillator.Capacitance sensing module includes capacitance sensor.The present invention can be realized to stone, scissors, cloth, and the gestures such as number 1,2,3,4,5 accurately identify.

Description

A capacitive data acquisition device for gesture recognition and a gesture recognition method thereof

technical field

The invention belongs to the technical field of gesture recognition, and in particular relates to a capacitance data acquisition device for gesture recognition and a gesture recognition method thereof.

Background technique

With the rapid development of computers, people and computers have become inseparable. And human-computer interaction, as an important step, is no longer satisfied with the use of common peripheral devices such as mouse and keyboard. Although, these methods are widely used and well known. However, people are still pursuing a simpler, more comfortable and human-computer interaction method suitable for human habits. Therefore, gesture recognition came into being.

Gesture, as one of the ways of human-to-human communication, has the characteristics of diversity and specificity, which provides the possibility for the further development of human-computer interaction. In terms of traffic safety, operating various functions and data inside the car through gestures can fully concentrate the driver's attention on the current road situation in front of him and reduce traffic accidents. In the development of the Internet of Things, gesture recognition can fully improve the interaction between people and various things. It also provides the possibility for the realization of virtual reality technology. However, the existing gesture recognition devices, such as data gloves, infrared recognition devices, or camera recognition devices, generally have the problems of high price, complicated equipment and high requirements on light. This defeats the original purpose of people interacting naturally without contact and with the help of mechanical devices. Therefore, it is necessary to consider establishing a non-contact gesture recognition interactive device system with simple equipment, high resolution, strong anti-noise performance, and economical application.

SUMMARY OF THE INVENTION

The purpose of the present invention is to provide a capacitance data acquisition device for gesture recognition and a gesture recognition method thereof.

The present invention is a capacitive data acquisition device for gesture recognition, comprising a capacitive signal acquisition device and a acquisition circuit. The capacitive signal collector includes metal foil, substrate and isolation plate. The metal foil is fixed between the base plate and the isolation plate. The acquisition circuit includes a main control module, a power supply module and a capacitive sensing module. The power supply module supplies power to the main control module through a voltage regulator chip.

The main control module includes a single-chip microcomputer, a first capacitor C1, a second capacitor C2, a third capacitor C3, a fourth capacitor C4, a fifth capacitor C5, a first resistor R1, a second resistor R2, a first key switch S1, The first crystal oscillator Y1 and the second crystal oscillator Y2. The reset pin of the single-chip microcomputer is connected to one end of the first capacitor C1, the first resistor R1 and the first key switch S1. The other ends of the first capacitor C1 and the first key switch S1 are both grounded. The other end of the first resistor R1 is connected to the power supply output end of the power supply module. The VDD pin of the microcontroller is connected to the power supply output end of the power supply module, and the VSS pin is grounded. The two external crystal pins of the single-chip microcomputer are respectively connected to two ends of the first crystal oscillator Y1, and are respectively connected to one end of the second capacitor C2 and the third capacitor C3. The other ends of the second capacitor C2 and the third capacitor C3 are both grounded. The two second external crystal oscillator pins of the microcontroller are respectively connected to two ends of the second resistor R2, respectively connected to both ends of the second crystal oscillator, and respectively connected to one end of the fourth capacitor C4 and the fifth capacitor C5. The other ends of the fourth capacitor C4 and the fifth capacitor C5 are both grounded.

The capacitive sensing module includes a capacitive sensor. The SCL pin of the capacitive sensor is connected to one end of the fourth resistor R4, and the SDA pin is connected to one end of the third resistor R3. The other end of the third resistor R3 is connected to the first I/O port of the microcontroller. The other end of the fourth resistor R4 is connected to the second I/O port of the microcontroller. The PAD, GND, ADDR, SD and CLKIN pins of the capacitive sensor are all grounded, and the VDD pin is connected to one end of the sixth capacitor C6, the seventh capacitor C7 and the external input +5V voltage. The other ends of the sixth capacitor C6 and the seventh capacitor C7 are both grounded. The IN0A pin of the capacitive sensor is connected to one end of the first inductor L1 and the eighth capacitor C8, and the IN0B pin is connected to the other end of the first inductor L1 and the eighth capacitor C8. The IN0A pin of the capacitive sensor is used as the signal input end of the capacitive sensing module and is electrically connected to the metal foil.

Further, the power supply module includes a voltage regulator chip, a ninth capacitor C9, a tenth capacitor C10, an eleventh capacitor C11 and a twelfth capacitor C12. The model of the voltage regulator chip is AMS111. The VCC pin of the voltage regulator chip is connected to the anode of the ninth capacitor C9, one end of the tenth capacitor C10 and the external input +5V voltage VCC, and the OUT pin is connected to the anode of the eleventh capacitor C11 and one end of the twelfth capacitor C12. The GND pin of the voltage regulator chip, the negative electrode of the ninth capacitor C9, the negative electrode of the eleventh capacitor C11, the other ends of the tenth capacitor C10 and the twelfth capacitor C12 are all grounded. The OUT pin of the voltage regulator chip is the power supply output end of the power supply module.

Further, the acquisition circuit also includes an LCD display screen. The model of the LCD display screen is LCD12864. The 1 and 20 pins of the LCD display are grounded, the 2 and 19 pins are connected to the external input 5V voltage, and the 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, and 17 pins It is connected with the third I/O port to the fifteenth I/O port of the microcontroller.

Further, the acquisition circuit further includes a key operation module. The key operation module includes a second key switch S2, a third key switch S3, a fourth key switch S4, a fifth key switch S5 and a sixth key switch S6. One end of the second key switch S2 is connected to one end of the ninth resistor R9 and the sixteenth I/O port of the microcontroller. One end of the third key switch S3 is connected to one end of the eighth resistor R8 and the seventeenth I/O port of the microcontroller. One end of the fourth key switch S4 is connected to one end of the seventh resistor R7 and the eighteenth I/O port of the microcontroller. One end of the fifth key switch S5 is connected to one end of the sixth resistor R6 and the nineteenth I/O port of the microcontroller. One end of the sixth key switch S6 is connected to one end of the fifth resistor R5 and the twentieth I/O port of the microcontroller. The other ends of the second key switch S2, the third key switch S3, the fourth key switch S4, the fifth key switch S5 and the sixth key switch S6 are all grounded. The other ends of the fifth resistor R5, the sixth resistor R6, the seventh resistor R7, the eighth resistor R8 and the ninth resistor R9 are connected to an external input voltage of +5V.

Further, the model of the capacitive sensor U2 is FDC2214.

Further, the model of the single-chip microcomputer is STM32F1.

Further, the metal foil is copper foil.

The gesture recognition method of the capacitive data acquisition device for gesture recognition is as follows:

Step 1: Establish a gesture recognition database, and the user enters each sample gesture that needs to be recognized into the database.

1.1. Assign 1 to i and j.

1.2. The user makes the i-th sampling gesture by hand and places it on the isolation board. The capacitive sensor collects m capacitance data output by the metal foil, and converts the collected m capacitance data into digital signal transmission main control module . The m capacitance data are respectively s ij1 , s _{ij2 ,} s _ij3 ,...,s _ijm . Proceed to step 1.3.

1.3. If i<l and j<n, increase j by 1, and execute step 1.2; if i<l and j=n, increase i by 1, assign 1 to j, and repeat Go to step 1.2; if i=l, and j=n, go to step 1.4. l is the number of gestures to be input, and n is the number of repetitions of each gesture 1≤n≤20.

1.4. Integrate the capacitance data obtained in steps 1.1 to 1.3 into a gesture sample dataset S.

Step 2: Normalize all elements in the gesture sample dataset S to obtain a normalized gesture dataset S _nor .

in, s _max is the element with the largest value in the gesture sample data set S; s _min is the element with the smallest value in the gesture sample data set S.

Step 3: Perform an averaging process on the elements in the normalized gesture data set S _nor to obtain an averaged gesture data set _Save .

S _ave = {{s _ave,11 ,s _ave,12 ,s _ave,13 ,......,s _ave,1m },{s _ave,21 ,s _ave,22 ,s _ave,23 ,. .....,s _ave,2m },...,{s _ave,l1 ,s _ave,l2 ,s _ave,l3 ,...,s _ave,lm }}

in,

Step 4: Sort the l·m elements in the normalized gesture dataset _Snor in order from small to large.

Step 5: Take the intermediate element of the normalized gesture dataset _Snor as the aggregation element. The middle element of a set of z elements is the th elements; The resulting value is rounded up to 0.5×z. The pooled element separates the normalized gesture dataset _Snor into two first intermediate sets. Assign 1 to a.

Step 6: Take all the intermediate elements of the a-th intermediate set as the a+1-th intermediate elements. The a+1-th intermediate element is called a child element of the corresponding a-th intermediate element. Two a+1-th intermediate elements in the same a-th intermediate set are siblings of each other.

If the number of elements in an a-th intermediate set is greater than or equal to 5, the corresponding a+1-th intermediate element divides the a-th intermediate set into two a+1-th intermediate sets.

If the number of elements in an a-th intermediate set is equal to 4, the corresponding a+1-th intermediate set divides the a-th intermediate set into a terminal element and a a+1-th intermediate set. The terminal element is a child element corresponding to the a+1-th intermediate element.

If the number of elements in an a-th intermediate set is equal to 3, the corresponding a+1-th intermediate element divides the a-th intermediate set into two terminal elements. The two terminal elements are sub-elements corresponding to the a+1-th intermediate element.

If the number of elements in an a-th intermediate set is equal to 2, the element in the a-th intermediate set except the a+1-th intermediate element is the terminal element. The terminal element is a child element corresponding to the a+1-th intermediate element.

Go to step seven.

Step 7: If the a+1th intermediate set exists, increase a by 1, and repeat step 6; otherwise, go to step 8.

Step 8: The user makes a hand gesture to be recognized, and attaches the hand to the placing board. A plurality of identified capacitance data output from the metal foil are averaged to obtain the identified capacitance average data x'.

Step 9: Calculate the normalized value x _nor of the recognized gesture detected in Step 4 .

Step 10: Take the aggregated element as the first target element g ₁ , and add it to the vertical screening set G. Assign 1 to b and go to step eleven.

Step 11: Compare the size of the b-th target element g _b with the normalized value x _nor of the recognized gesture. If x _nor is less than the value of the b-th target element g _b , the smaller of the two sub-elements of the b-th target element g _b is taken as the b+1-th target element g _b+1 ; otherwise, it will be taken as the b-th target element g b+1 ; The larger of the two sub-elements of the b target element g _b is the b+1-th target element g _b+1 .

Add the b+1 th target element g _b+1 to the vertical screening set G, and go to step 12.

Step 12. If the b+1 th target element g _b+1 has two sub-elements, increase b by 1 and execute step 11; if the b+1 th target element g _b+1 has one sub-element, then the first The child element of the b+1 target element g _b+1 is used as the b+2 target element g _b+2 , and is added to the vertical screening set G, and goes to step 13; if the b+1 target element g _b+1 does not have a child element, go directly to step thirteen.

Step 13: Calculate the Euclidean distance d _v between all elements in the vertical screening set G and the normalized value _xnor of the recognized gesture, v=1,2,...,c; c is the number of elements in the vertical screening set G.

Among them, g _v is the v-th element in the vertical screening set G.

Step 14: Take the minimum value _d ′ _min among d ₁ , d ₂ , . . . , dc . The element in the vertical screening set G corresponding to d' _min is used as the first candidate element. If the first candidate element has no sibling elements, the gesture to be recognized made by the user is the same as the sampling gesture corresponding to the first candidate element in the averaged gesture data set _Save , and the gesture recognition ends.

If the first candidate element has a sibling element, the sibling element of the first candidate element is used as the second candidate element, and the Euclidean distance d″ _min between the second candidate element and the normalized value x _nor of the recognized gesture is calculated; g' is the second candidate element; go to step fifteen.

Step 15. Compare d′ _min and d″ _min ; if d′ _min <d″ _min , the gesture to be recognized made by the user and the sample corresponding to the first candidate element in the averaged gesture dataset _Save If the gestures are the same, the gesture recognition ends; if d′ _min ≥ d″ _min , the gesture to be recognized made by the user is the same as the sampling gesture corresponding to the first candidate element in the averaged gesture dataset _Save , and the gesture recognition ends .

The beneficial effects that the present invention has are:

1. The present invention converts the movement of the human hand placed on the metal foil into an accurate capacitive signal through the combination of the capacitive sensor and the metal foil, thereby realizing the recognition of the gesture. And compared with the existing gesture recognition devices such as data gloves, infrared recognition devices, camera recognition devices, etc., it has the advantage of low cost.

2. The capacitive sensing technology applied in the present invention solves the problem of small signal amplification very well, thereby improving the accuracy of acquisition.

3. The present invention eliminates the influence of ambient light on the judgment, and improves the accuracy of gesture recognition.

4. The present invention makes the pairing of the recognized gesture and the data in the database through the Mesh network topology progressive search algorithm, so that the recognized gesture is compared with all the data in the database, and the data that is closest to the recognized gesture in the database can be found out, The amount of computation in the recognition process is greatly reduced.

5. The present invention can realize accurate recognition of gestures such as rock, scissors, cloth, numbers 1, 2, 3, 4, and 5.

Description of drawings

1 is a system block diagram of the present invention;

Fig. 2 is the circuit schematic diagram of the power module in the present invention;

Fig. 3 is the circuit schematic diagram of the main control module in the present invention;

4 is a schematic circuit diagram of a capacitive sensing module in the present invention;

Fig. 5 is the wiring diagram of LCD display screen in the present invention;

FIG. 6 is a circuit schematic diagram of a key operation module in the present invention.

Detailed ways

The present invention will be further described below with reference to the accompanying drawings.

As shown in FIG. 1 , a capacitive data acquisition device for gesture recognition includes a capacitive signal acquisition device 1 and a acquisition circuit. The capacitive signal collector 1 includes a metal foil, a substrate and an isolation plate. The metal foil is fixed between the base plate and the spacer plate. The isolation plate is located above the base plate. The metal foil is copper foil. The acquisition circuit includes a main control module 2 , a power supply module 3 , a capacitive sensing module 4 , an LCD display screen U4 and a key operation module 5 . The power supply module 3 converts the externally input 5V voltage into a 3.3V voltage through a voltage regulator chip to supply power to the main control module 2 . The capacitance sensing module 4 converts the capacitance value analog signal between the metal foil of the capacitance signal collector 1 and the ground wire into a digital signal through the capacitance sensor and transmits it to the main control module 2 . When the user puts the isolation plate on, the capacitance value of the metal foil output changes. The LCD display screen U4 is connected to the main control module 2, and is used to display the result of gesture recognition and the current usage mode. The key operation module 5 sends the mode adjustment instruction to the main control module 2 through the key switch.

As shown in FIG. 2 , the power module 3 includes a voltage regulator chip U3 , a ninth capacitor C9 , a tenth capacitor C10 , an eleventh capacitor C11 and a twelfth capacitor C12 . The model of the voltage regulator chip U3 is AMS111. The VCC pin of the voltage regulator chip U3 is connected to the positive electrode of the ninth capacitor C9, one end of the tenth capacitor C10 and the external input +5V voltage VCC, and the OUT pin is connected to the positive electrode of the eleventh capacitor C11 and one end of the twelfth capacitor C12. The GND pin of the voltage regulator chip U3, the negative pole of the ninth capacitor C9, the negative pole of the eleventh capacitor C11, and the other ends of the tenth capacitor C10 and the twelfth capacitor C12 are all grounded. The OUT pin of the voltage regulator chip U3 is the power supply output terminal +3.3V of the power supply module 3 .

As shown in FIG. 3 , the main control module 2 includes a single-chip microcomputer U1, a first capacitor C1, a second capacitor C2, a third capacitor C3, a fourth capacitor C4, a fifth capacitor C5, a first resistor R1, a second resistor R2, a A key switch S1, a first crystal oscillator Y1 and a second crystal oscillator Y2. The model of the microcontroller U1 is STM32F1. The reset pin (pin 25) of the single-chip microcomputer U1 is connected to one end of the first capacitor C1, the first resistor R1 and the first key switch S1. The other ends of the first capacitor C1 and the first key switch S1 are both grounded. The other end of the first resistor R1 is connected to the power supply output terminal +3.3V of the power supply module 3 . The VDD pins (72, 108, 144, 39, 17, 52, 62, 84, 95, 121, 131 pins) of the microcontroller U1 are connected to the power supply output terminal +3.3V of the power supply module 3, and the VSS pins (71, 107 , 143, 38, 16, 51, 61, 83, 94, 120, 130 pins) to ground. The two external crystal oscillator pins (pins 7 and 8) of the single-chip microcomputer U1 are respectively connected to two ends of the first crystal oscillator Y1, and are respectively connected to one end of the second capacitor C2 and the third capacitor C3. The other ends of the second capacitor C2 and the third capacitor C3 are both grounded. The two second external crystal oscillator pins (pins 23 and 24) of the microcontroller U1 are respectively connected to both ends of the second resistor R2, respectively connected to both ends of the second crystal oscillator, and connected to the fourth capacitor C4 and the fifth capacitor C5. ends are connected respectively. The other ends of the fourth capacitor C4 and the fifth capacitor C5 are both grounded.

As shown in FIG. 4 , the capacitive sensing module 4 includes a capacitive sensor U2. The model of capacitive sensor U2 is FDC2214. The SCL pin (1 pin) of the capacitive sensor U2 is connected to one end of the fourth resistor R4, and the SDA pin (2 pin) is connected to one end of the third resistor R3. The other end of the third resistor R3 is connected to the first I/O port (pin 44) of the microcontroller U1. The other end of the fourth resistor R4 is connected to the second I/O port (pin 45) of the microcontroller U1. The PAD, GND, ADDR, SD and CLKIN pins of the capacitive sensor U2 are all grounded, and the VDD pin is connected to the sixth capacitor C6, one end of the seventh capacitor C7 and the external input +5V voltage. The other ends of the sixth capacitor C6 and the seventh capacitor C7 are both grounded. The IN0A pin of the capacitive sensor U2 is connected to one end of the first inductor L1 and the eighth capacitor C8, and the IN0B pin is connected to the other end of the first inductor L1 and the eighth capacitor C8. The IN0A pin of the capacitive sensor U2 is used as the signal input end of the capacitive sensing module 4 and is electrically connected to the metal foil. The remaining pins of capacitive sensor U2 are left floating.

As shown in Figure 5, the model of LCD display U4 is LCD12864. The 1 and 20 pins of the LCD display U4 are grounded, the 2 and 19 pins are connected to the external input 5V voltage VCC, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 17 The pins and the third I/O port to the fifteenth I/O port (114, 115, 117, 77, 78, 79, 80, 81, 82, 85, 86, 118, 119 pins) of the microcontroller U1 are respectively connected. The remaining pins of LCD display U4 are left floating.

As shown in FIG. 6 , the key operation module 5 includes a second key switch S2, a third key switch S3, a fourth key switch S4, a fifth key switch S5 and a sixth key switch S6. One end of the second key switch S2 is connected to one end of the ninth resistor R9 and the sixteenth I/O port K2 (pin 10) of the microcontroller U1. One end of the third key switch S3 is connected to one end of the eighth resistor R8 and the seventeenth I/O port K3 (pin 11) of the microcontroller U1. One end of the fourth key switch S4 is connected to one end of the seventh resistor R7 and the eighteenth I/O port K4 (12 pins) of the microcontroller U1. One end of the fifth key switch S5 is connected to one end of the sixth resistor R6 and the nineteenth I/O port K5 (pin 13) of the microcontroller U1. One end of the sixth key switch S6 is connected to one end of the fifth resistor R5 and the twentieth I/O port K6 (pin 14) of the microcontroller U1. The other ends of the second key switch S2, the third key switch S3, the fourth key switch S4, the fifth key switch S5 and the sixth key switch S6 are all grounded. The other ends of the fifth resistor R5, the sixth resistor R6, the seventh resistor R7, the eighth resistor R8 and the ninth resistor R9 are connected to the external input +5V voltage VCC. The remaining pins of the microcontroller U1 are left floating.

The gesture recognition method of the capacitive data acquisition device for gesture recognition is as follows:

Step 1: Establishing a gesture recognition database, the user records each sample gesture to be recognized into the database, and the gestures that can be recognized by the present invention must be gestures that have been recorded in the database.

1.1. Assign 1 to i and j.

1.2. The user makes the i-th sampling gesture by hand and places it on the isolation board for T time, T=m/f, m≥10, and f is the data collection frequency of the capacitive sensor. The user's hand affects the capacitance value of the foil output. The capacitance sensor converts the collected m capacitance data into digital signals and transmits them to the main control module 2 . The m capacitance data are respectively s _{ij1 , s ij2 ,} s _ij3 ,...,s _ijm . Proceed to step 1.3.

1.3. If i<l and j<n, increase j by 1, and execute step 1.2; if i<l and j=n, increase i by 1, assign 1 to j, and repeat Go to step 1.2; if i=l, and j=n, go to step 1.4. l is the number of gestures to be input, and n is the number of repetitions of each gesture 1≤n≤20.

1.4. The gesture sample dataset S is obtained in steps 1.1 to 1.3.

Step 2: Normalize all elements in the gesture sample dataset S to obtain a normalized gesture dataset S _nor .

in, s _max is the element with the largest value in the gesture sample data set S; s _min is the element with the smallest value in the gesture sample data set S.

Step 3: Perform an averaging process on the elements in the normalized gesture data set S _nor to obtain an averaged gesture data set _Save .

S _ave = {{s _ave,11 ,s _ave,12 ,s _ave,13 ,......,s _ave,1m },{s _ave,21 ,s _ave,22 ,s _ave,23 ,. .....,s _ave,2m },...,{s _ave,l1 ,s _ave,l2 ,s _ave,l3 ,...,s _ave,lm }}

in,

Step 4: Sort the l·m elements in the normalized gesture dataset _Snor in order from small to large.

Step 5: Take the intermediate element of the normalized gesture dataset _Snor as the aggregation element. The middle element of a set of z elements is the th elements; The resulting value is rounded up to 0.5×z. The pooled element separates the normalized gesture dataset _Snor into two first intermediate sets. All elements in a first intermediate set are larger than the aggregated element or are smaller than the aggregated element. Assign 1 to a.

Step 6: Take all the intermediate elements of the a-th intermediate set as the a+1-th intermediate elements. The a+1-th intermediate element is called a child element of the corresponding a-th intermediate element. The a-th intermediate element is called the parent element of the corresponding a+1-th intermediate element. In the same a-th intermediate set, two a+1-th intermediate elements are mutually sibling elements (that is, two elements with the same parent element are mutually sibling elements).

If the number of elements in an a-th intermediate set is greater than or equal to 5, the corresponding a+1-th intermediate element divides the a-th intermediate set into two a+1-th intermediate sets. The elements in an a+1-th intermediate set are all larger than the a+1-th intermediate element or are all smaller than the a+1-th intermediate element.

If the number of elements in an intermediate set a is equal to 4, the corresponding intermediate element a+1 divides the intermediate set a into a terminal element and an intermediate set a+1 with the number of elements equal to 2. The terminal element is a child element corresponding to the a+1-th intermediate element.

If the number of elements in an a-th intermediate set is equal to 3, the a+1-th intermediate element divides the corresponding a-th intermediate set into two terminal elements. The two terminal elements are sub-elements corresponding to the a+1-th intermediate element.

If the number of elements in an a-th intermediate set is equal to 2, the element in the a-th intermediate set except the a+1-th intermediate element is the terminal element. The terminal element is a child element corresponding to the a+1-th intermediate element.

Go to step seven.

Step 7. If there is an a+1-th intermediate set (that is, there is at least one a-th intermediate set whose number of elements is greater than or equal to 4), increase a by 1, and repeat step 6; otherwise, normalize the gesture data All elements in the set _Snor have become a kind of convergent elements, intermediate elements, and terminal elements, and go to step eight.

Step 8: The user makes a hand gesture to be recognized, and attaches the hand to the placing board. The user's hand affects the capacitance value of the foil output. The capacitance sensor converts the collected multiple identified capacitance data into digital signals and transmits them to the main control module 2 . The main control module 2 calculates the average value x' of the received multiple digital signals.

Step 9: Calculate the normalized value x _nor of the recognized gesture detected in Step 4 .

Step 10: Take the aggregated element as the first target element g ₁ , and add the vertical screening set G which is initially an empty set. Assign 1 to b and go to step eleven.

Step 11: Compare the size of the b-th target element g _b with the normalized value x _nor of the recognized gesture. If x _nor is less than the value of the b-th target element g _b , the smaller of the two sub-elements of the b-th target element g _b is taken as the b+1-th target element g _b+1 ; otherwise, it will be taken as the b-th target element g b+1 ; The larger of the two sub-elements of the b target element g _b is the b+1-th target element g _b+1 .

Add the b+1 th target element g _b+1 to the vertical screening set G, and go to step 12.

Step 12. If the b+1 th target element g _b+1 has two sub-elements, increase b by 1 and execute step 11; if the b+1 th target element g _b+1 has one sub-element, then the first The sub-elements of the b+1 target element g _b+1 are used as the b+2 target element g _b+2 , and are added to the vertical screening set G, and the process goes to step 13. At this time, there are b+2 elements in the vertical screening set G. Assign b+2 to c; if the b+1th target element g _b+1 has no sub-elements, go directly to step 13. At this time, there are b+1 elements in the vertical screening set G, and b+1 is assigned give c.

Step 13: Calculate the Euclidean distance d _v between all elements in the vertical screening set G and the normalized value _xnor of the recognized gesture, v=1,2,...,c; c is the number of elements in the vertical screening set G.

Among them, g _v is the v-th element in the vertical screening set G (ie, the v-th target element).

Step 14. Take the minimum value among d ₁ , d ₂ , ..., dc and record it as _d ' _min . The element in the vertical screening set G corresponding to d' _min is used as the first candidate element. If there is no sibling element in the first candidate element (that is, there is no element with the same parent element as the first candidate element in the averaged gesture dataset _Save ), the gesture to be recognized made by the user will be the same as the first candidate element. The sampling gesture corresponding to the averaged gesture dataset _Save is the same, and the gesture recognition ends.

If the first candidate element has sibling elements (that is, there is an element with the same parent element as the first candidate element in the averaged gesture dataset _Save ), the sibling element of the first candidate element is taken as the second candidate element, and the calculation Euclidean distance d″ _min between the second candidate element and the normalized value x _nor of the recognized gesture; g' is the value of the second candidate element. Go to step fifteen.

Step 15. Compare d′ _min and d″ _min ; if d′ _min <d″ _min , the gesture to be recognized made by the user and the sample corresponding to the first candidate element in the averaged gesture dataset _Save If the gestures are the same, the gesture recognition ends; if d′ _min ≥ d″ _min , the gesture to be recognized made by the user is the same as the sampling gesture corresponding to the first candidate element in the averaged gesture dataset _Save , and the gesture recognition ends .

Claims (8)

1. A capacitance data acquisition device for gesture recognition comprises a capacitance signal acquisition device and an acquisition circuit; the method is characterized in that: the capacitance signal collector comprises a metal foil, a substrate and an isolation plate; the metal foil is fixed between the substrate and the isolation plate; the acquisition circuit comprises a main control module, a power supply module and a capacitance sensing module; the power supply module supplies power to the main control module through the voltage stabilizing chip;

the main control module comprises a single chip microcomputer, a first capacitor C1, a second capacitor C2, a third capacitor C3, a fourth capacitor C4, a fifth capacitor C5, a first resistor R1, a second resistor R2, a first key switch S1, a first crystal oscillator Y1 and a second crystal oscillator Y2; the reset pin of the singlechip is connected with one end of a first capacitor C1, a first resistor R1 and a first key switch S1; the other ends of the first capacitor C1 and the first key switch S1 are grounded; the other end of the first resistor R1 is connected with the power supply output end of the power supply module; a VDD pin of the singlechip is connected with a power supply output end of the power module, and a VSS pin is grounded; two external crystal oscillator pins of the singlechip are respectively connected with two ends of a first crystal oscillator Y1 and are respectively connected with one ends of a second capacitor C2 and a third capacitor C3; the other ends of the second capacitor C2 and the third capacitor C3 are grounded; two second external crystal oscillator pins of the singlechip are respectively connected with two ends of a second resistor R2, connected with two ends of a second crystal oscillator, and respectively connected with one ends of a fourth capacitor C4 and a fifth capacitor C5; the other ends of the fourth capacitor C4 and the fifth capacitor C5 are grounded;

the capacitance sensing module comprises a capacitance sensor; the SCL pin of the capacitance sensor is connected with one end of a fourth resistor R4, and the SDA pin is connected with one end of a third resistor R3; the other end of the third resistor R3 is connected with a first I/O port of the singlechip; the other end of the fourth resistor R4 is connected with a second I/O port of the singlechip; pins PAD, GND, ADDR, SD and CLKIN of the capacitance sensor are all grounded, and a pin VDD is connected with one end of a sixth capacitor C6 and one end of a seventh capacitor C7 and +5V voltage of external input; the other ends of the sixth capacitor C6 and the seventh capacitor C7 are grounded; the pin IN0A of the capacitive sensor is connected with one end of the first inductor L1 and one end of the eighth capacitor C8, and the pin IN0B is connected with the other end of the first inductor L1 and the other end of the eighth capacitor C8; the IN0A pin of the capacitive sensor serves as a signal input end of the capacitive sensing module and is electrically connected with the metal foil.

2. The capacitive data acquisition device for gesture recognition according to claim 1, wherein: the power supply module comprises a voltage stabilizing chip, a ninth capacitor C9, a tenth capacitor C10, an eleventh capacitor C11 and a twelfth capacitor C12; the model of the voltage stabilizing chip is AMS 111; a VCC pin of the voltage stabilizing chip is connected with the anode of the ninth capacitor C9, one end of a tenth capacitor C10 and an external input +5V voltage VCC, and an OUT pin is connected with the anode of the eleventh capacitor C11 and one end of a twelfth capacitor C12; the GND pin of the voltage stabilizing chip, the ninth capacitor C9, the negative electrode of the eleventh capacitor C11, the tenth capacitor C10 and the twelfth capacitor C12 are all grounded; and an OUT pin of the voltage stabilizing chip is a power supply output end of the power supply module.

3. The capacitive data acquisition device for gesture recognition according to claim 1, wherein: the acquisition circuit also comprises an LCD display screen; the model of the LCD display screen is LCD 12864; pins 1 and 20 of the LCD screen are grounded, pins 2 and 19 are connected with an external input voltage of 5V, and pins 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 and 17 are respectively connected with a third I/O port to a fifteenth I/O port of the singlechip.

4. The capacitive data acquisition device for gesture recognition according to claim 1, wherein: the acquisition circuit further comprises a key operation module; the key operation module comprises a second key switch S2, a third key switch S3, a fourth key switch S4, a fifth key switch S5 and a sixth key switch S6; one end of the second key switch S2 is connected with one end of the ninth resistor R9 and the sixteenth I/O port of the single chip microcomputer; one end of the third key switch S3 is connected with one end of the eighth resistor R8 and a seventeenth I/O port of the singlechip; one end of a fourth key switch S4 is connected with one end of a seventh resistor R7 and an eighteenth I/O port of the singlechip; one end of a fifth key switch S5 is connected with one end of a sixth resistor R6 and a nineteenth I/O port of the single chip microcomputer; one end of a sixth key switch S6 is connected with one end of a fifth resistor R5 and a twentieth I/O port of the singlechip; the other ends of the second key switch S2, the third key switch S3, the fourth key switch S4, the fifth key switch S5 and the sixth key switch S6 are all grounded; the other ends of the fifth resistor R5, the sixth resistor R6, the seventh resistor R7, the eighth resistor R8 and the ninth resistor R9 are connected with an external input +5V voltage.

5. The capacitive data acquisition device for gesture recognition according to claim 1, wherein: the capacitive sensor U2 is model FDC 2214.

6. The capacitive data acquisition device for gesture recognition according to claim 1, wherein: the model of the single chip microcomputer is STM32F 1.

7. The capacitive data acquisition device for gesture recognition according to claim 1, wherein: the metal foil is copper foil.

8. The gesture recognition method of the capacitive data acquisition device for gesture recognition according to claim 1, characterized in that: step one, establishing a gesture recognition database, and inputting each sampling gesture to be recognized into the database by a user;

1.1, assigning 1 to i and j;

1.2, a user makes an ith sampling gesture with a hand and places the sampling gesture on an isolation plate, a capacitance sensor collects m capacitance data output by a metal foil, and the collected m capacitance data are converted into a digital signal transmission main control module; m pieces of capacitance data are s_ij1,s_ij2,s_ij3,......,s_ijm(ii) a Entering step 1.3;

1.3, if i is less than l and j is less than n, increasing j by 1 and executing the step 1.2; if i is less than l and j is equal to n, increasing i by 1, assigning 1 to j, and repeatedly executing the step 1.2; if i ═ l and j ═ n, then proceed to row step 1.4; l is the number of gestures to be input, n is the repeated placement frequency of each gesture, n is more than or equal to 1 and less than or equal to 20;

1.4, integrating the capacitance data obtained in the steps 1.1 to 1.3 into a gesture sample data set S;

step two, normalizing all elements in the gesture sample data set S to obtain a normalized gesture data set S_nor；

Wherein,i＝1,2,…,l；j＝1,2,…,n；k＝1,2,…,m；s_maxthe element with the largest numerical value in the gesture sample data set S is selected; s_minThe element with the minimum numerical value in the gesture sample data set S is selected;

step three, normalizing the gesture data set S_norThe inner elements are subjected to equalization processing to obtain an equalized gesture data set S_ave；

S_ave＝{{s_ave,11,s_ave,12,s_ave,13,......,s_ave,1m},{s_ave,21,s_ave,22,s_ave,23,......,s_ave,2m},......,{s_ave,l1,s_ave,l2,s_ave,l3,......,s_ave,lm}}

Wherein,i＝1,2,…,l；k＝1,2,…,m；

step four, normalizing the gesture data set S_norThe l.m elements in the sequence are sequentially ordered from small to large;

step five, taking a normalized gesture data set S_norAs a convergence element; an intermediate element of a set of z elements being the first element of the setAn element;the value obtained by rounding up in the 0.5 xz direction; the convergent elements will normalize the gesture data set S_norPartitioning into two first middle sets; assigning 1 to a;

taking all the intermediate elements of the a-th intermediate set as a + 1-th intermediate elements; the a +1 th intermediate element is called a sub-element of the corresponding a-th intermediate element; two a +1 intermediate elements in the same a intermediate set are brother elements;

if the number of elements in an a-th intermediate set is greater than or equal to 5, the corresponding a + 1-th intermediate element divides the a-th intermediate set into two a + 1-th intermediate sets;

if the number of elements in an a-th intermediate set is equal to 4, the corresponding a + 1-th intermediate element divides the a-th intermediate set into a terminal element and an a + 1-th intermediate set; the terminal element is a sub-element corresponding to the a +1 th intermediate element;

if the number of elements in an a-th intermediate set is equal to 3, the corresponding a + 1-th intermediate element divides the a-th intermediate set into two terminal elements; the two terminal elements are both sub-elements corresponding to the a +1 th intermediate element;

if the number of the elements in the a-th intermediate set is equal to 2, the element in the a-th intermediate set except the a + 1-th intermediate element is a terminal element; the terminal element is a sub-element corresponding to the a +1 th intermediate element;

entering a seventh step;

step seven, if the a +1 th intermediate set exists, increasing a by 1, and repeatedly executing the step six; otherwise, entering step eight;

step eight, making a hand into a gesture to be recognized by a user, and attaching the hand to the placing plate; averaging a plurality of identified capacitance data output by the metal foil to obtain identified capacitance average data x';

step nine, calculating the normalization value x of the recognized gesture detected in the step four_nor；

Step ten, using the convergent element as a first target element g₁Adding a longitudinal screening set G; assigning 1 to b and entering step eleven;

step eleven, comparing the target element g of the b_bNormalized to recognized gestureChange value x_norThe size of (d); if x_norLess than the b-th target element g_bIs then the b-th target element g_bThe smaller of the two sub-elements of (a) is taken as the (b + 1) th target element g_b+1(ii) a Otherwise, it will be the b-th target element g_bThe larger of the two sub-elements of (a) as the (b + 1) th target element g_b+1；

B +1 th target element g_b+1Adding a longitudinal screening set G, and entering the step twelve;

step twelve, if the b +1 th target element g_b+1If there are two sub-elements, then b is incremented by 1 and step eleven is performed; if the b +1 th target element g_b+1If there is a sub-element, the b +1 th target element g_b+1As the b +2 th target element g_b+2Adding a longitudinal screening set G and entering a step thirteen; if the b +1 th target element g_b+1If no sub-element exists, directly entering step thirteen;

thirteen, calculating all elements in the longitudinal screening set G and the normalization value x of the recognized gesture_norOf Euclidean distance d_vV ═ 1,2, …, c; c is the number of elements in the longitudinal screening set G;

wherein, g_vScreening the v element in the set G longitudinally;

step fourteen, get d₁、d₂、...、d_cOf d'_min；d′_minThe corresponding element in the longitudinal screening set G is used as a first candidate element; if the first candidate element does not have a brother element, the gesture to be recognized made by the user and the first candidate element are in the equalized gesture data set S_aveThe corresponding sampling gestures are the same, and the gesture recognition is finished;

if the first candidate element has the brother element, taking the brother element of the first candidate element as a second candidate element, and calculating the normalization value x of the second candidate element and the recognized gesture_norOfEuropean distance d'_m′_in；g' is a second candidate element; entering a step fifteen;

fifteen step, d 'comparison'_minAnd d ″)_min(ii) a If d'_min＜d″_minThe user' S gesture to be recognized and the first candidate element are averaged in a gesture data set S_aveThe corresponding sampling gestures are the same, and the gesture recognition is finished; if d'_min≥d″_minThe user' S gesture to be recognized and the first candidate element are averaged in a gesture data set S_aveThe corresponding sampling gesture is the same, and the gesture recognition is finished.