A voice monitoring and analysis training device and method based on myoelectric current sensor

Abstract

The present invention discloses a voice monitoring and analysis training device and method based on galvanoelectric sensors, comprising: an galvanoelectric sensor array and at least one reference galvanoelectric sensor, the galvanoelectric sensor array being installed in the throat, oral cavity and chest of the human body, the reference galvanoelectric sensor being installed in a position where the muscles do not contract when the human body speaks, but not limited to the shoulders, arms or legs; a control and data processing unit, which is connected to each galvanoelectric sensor for data exchange; and a device terminal, which is connected to the control and data processing unit and implements command and information transmission. The device for voice monitoring and analysis training obtains muscle vibration data through galvanoelectric sensors, obtains power spectrum density of signals at different muscle positions through filtering and noise reduction processing, judges muscle contraction position, determines whether male or female voice is uttered, and trains the vocalization position. This technical solution uses galvanoelectric sensors for medical voice analysis and training, proposing an innovative path for the development of this technical field.

Description

Technical Field

[0001] The technical field of the present application belongs to the field of smart medical equipment, and in particular, to a device that combines signal processing and analysis methods in the field of medical equipment to monitor, analyze and train human body events with the help of traditional myoelectric sensors and data control processing modules used for cardiac monitoring. Background Art

[0002] Surface electromyography is the temporal and spatial superposition of bioelectric signals generated when multiple motor units are excited during muscle contraction. The human body controls muscle strength by adjusting the excitability of the muscles and the number of motor units involved in the contraction, and changes in both will cause changes in surface electromyography. In the diagnostic and treatment instruments for human biological characteristics, the most widely used application of surface electromyography is the electrocardiogram measurement process, which measures the tiny electrical signals generated by myocardial contraction during the heartbeat to obtain dynamic information of the heart. The measurement of myoelectric current usually uses skin surface electrodes, which are placed on the surface of the skin to record the electrical activity of the entire muscle, so as to obtain nerve conduction velocity, spinal cord reflexes, involuntary muscle movements, etc. The myoelectric current meter can distinguish neurogenic damage from myogenic damage by measuring the duration and amplitude of the motor unit potential, the presence or absence of spontaneous electrical activity in a quiet state, and the wave pattern and amplitude of strong muscle contraction, and diagnose acute and chronic damage to the anterior horn of the spinal cord (such as anterior poliomyelitis, motor neuron disease), nerve root and peripheral neuropathy (for example, electromyography can help determine the location, degree, range and prognosis of nerve damage). In addition, it also has diagnostic value for nerve compression lesions, neuritis, genetic metabolic disorder neuropathy, and various muscle diseases.

[0003] A careful analysis of the process of human body can reveal that three systems need to work together, namely, power system, vibration system and resonance system. The specific correspondence of each system in human organs is as follows: respiratory organs (including lungs, diaphragm and abdominal muscles) belong to the power system, larynx and vocal cords belong to the vibration system, oral cavity, pharynx, chest cavity, nasal cavity and head cavity belong to the resonance system, in addition, the lips, tongue, cheeks and teeth that produce speech in conjunction with the articulation and word parts. The work of these systems all requires muscle drive. Therefore, the characteristic parameters of voice, audio, sound quality, volume and other parameters are all determined by the state of the above three systems. When the human body is in a state of physiological disease, it is precisely because of the lesions in some parts of the above systems that the voice changes. In the existing treatment process, doctors obtain disease information through sound analysis and examination of related organs. With the application of big data technology, audio analysis methods have also begun to be used to determine voice diseases. In addition, for some people who are professionally engaged in vocal music, broadcasting and other industries, their vocal organs are the guarantee for the perfect presentation of their voices. In order to achieve the professional effect of the voice, these professionals need to conduct professional training on various vocal organs. In the training, the effect is usually obtained through hearing to adjust the working state of each organ to achieve the training purpose. It is precisely because the vocalization process is also a process in which the muscles of various organs participate in the contraction, so actively controlling the organ muscles can also achieve the quantitative calibration of the vocalization effect. However, there are no relevant instruments and devices to quantify the existing monitoring, measurement, and training of human voice with the help of other equipment measurements (non-sound detection). This application proposes technical innovations in the blank technical fields of sound detection, analysis, and training. Summary of the invention

[0004] The technical solution of this application is aimed at the limitation of the existing medical field in sound analysis measurement that focuses on the detection of the performance parameters of the sound emitted. It is a unique way to apply the myoelectric current measurement technology to the three major systems of human voice (power system, vibration system and resonance system), and to achieve the purpose of sound discrimination, disease diagnosis and professional vocal personnel training by measuring the myoelectric current signals generated by the muscle movement of each organ system, and processing and analyzing the signals. To achieve the above invention purpose, the technical solution adopted by this application is a voice monitoring and analysis training device based on myoelectric current sensor, which includes: an array of myoelectric current sensors for measurement and at least one myoelectric current sensor for reference, the array of myoelectric current sensors for measurement is installed in the throat, oral cavity and chest of the human body, and the reference myoelectric current sensor is installed in the position where the muscles of the human body do not contract when speaking, not limited to the shoulder, arm or leg; a control and data processing unit, the unit module is connected to each myoelectric current sensor to realize data exchange; a device terminal, the terminal is connected to the control and data processing unit and realizes command and information transmission, the myoelectric current sensor for measurement is applied to the surface of the muscle skin of the throat, oral cavity and chest of the human body, and measures and obtains the surface electromyographic signal (sEMG) during muscle contraction. This device innovatively places the myoelectric current sensor at the position of the organ muscles of the human body for vocalization for the first time, so as to directly obtain the electrical signals of the contraction of each muscle during the vocalization process, obtain the muscle working parameters of each position through data analysis, and use the terminal to display the acquired information to medical personnel or users in real time. In order to prevent the data during the vocalization process from being affected by noise signals from other movements, a reference myoelectric current sensor is specially set in the configuration of the myoelectric current sensor, and its measurement data is used to remove the noise information of the vocalization data.

[0005] The key to the signal processing of the above-mentioned control and data processing unit includes: a surface electromyographic signal (sEMG) signal processing module, which first synchronizes the surface electromyographic signals transmitted by current sensors at different positions, and then filters the synchronized signals to retain only the signals related to the voice production and performs spectrum processing on the signals and calculates the power density. The muscle current signals filtered by the filter here include but are not limited to the muscle contraction electrical signals generated by the heart beating, throat swallowing and other non-vocalization, and the signal of the reference muscle current sensor is used as a reference for filtering. Through the processing of the surface electromyographic signal (sEMG) by the data processing unit, its information is more accurate, and the data processing and subsequent calculation to obtain the sound spectrum power will be more accurate, which provides a guarantee for the subsequent determination of the site of the disease and the training of the vocalization site.

[0006] The data communication between the myoelectric sensor and the control and data processing unit is wired or wireless; and the equipment terminal is connected to the control and data processing unit through wired or wireless means to display data results and receive external instructions. The use of these wireless connection methods is more conducive to real-time data transmission and analysis, providing convenience for diagnosis and training.

[0007] Using the aforementioned device, the present application also proposes a method for monitoring and analyzing voice training, which comprises the following steps:

[0008] S1: An array of myoelectric current sensors is attached to the throat and chest of the human body to measure the point signal generated by the muscle contraction of the throat and chest when the human body is speaking. A reference myoelectric current sensor is attached to the position of the shoulder, arm or leg of the human body where the muscle does not contract when the human body is speaking to provide a reference signal during the measurement process;

[0009] S2: The myoelectric current sensor acquires signal data in real time and transmits it to the control and data processing unit. This module synchronizes the signal data, performs noise processing according to the reference signal, and calculates the frequency spectrum and power spectrum of the sensor signals at different positions after filtering. The signal processing here includes signal synchronization in the time domain considering the delay of each myoelectric current sensor according to its different positions. The signal filtering processing mainly reduces the noise of the measurement signal and filters the low-frequency noise according to the characteristics of the reference signal.

[0010] S3: judging the composition of the contracted muscles that produce the voice signal based on the data of the myoelectric sensors at different positions obtained in step S2, and realizing voice analysis. If the analysis finds that the vibration of the chest cavity is greater than that of the throat and oral cavity in the production proportion of the voice, then the voice is judged to be produced by a male, otherwise it is produced by a female;

[0011] S4: The data processing results of the above steps S2 and S3 are presented through the device terminal.

[0012] In the above process, the trainee can consciously train his / her muscle movements according to the result presented in step S4: when a more masculine sound effect is required, the chest muscles can be contracted to produce sound; when a more feminine sound effect is required, the throat and oral muscles can be contracted to produce sound.

[0013] In the above method, after the data processing and analysis of steps S1 and S2, the muscle movement information at each electromyographic sensor position can be clearly obtained, and medical personnel can also obtain the diagnosis and treatment results of whether there is a disease in the part by analyzing the data.

[0014] The voice monitoring, analysis and training device of the present application introduces electromyographic sensors into the field of sound analysis and treatment for the first time, thereby combining them with data analysis and control to produce a new device that can be used for sound pathology diagnosis and professional voice training. At the same time, in the processing and analysis of electromyographic signal data, the measurement data of the reference sensor is used to purify the signal data to ensure the correctness of the analysis results. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 A structural schematic diagram of a voice monitoring and analysis training device based on an electromyographic sensor is proposed for this application. DETAILED DESCRIPTION

[0016] The present invention is further described below in conjunction with the embodiments, but is not limited to the contents of the specification. It should be noted that the terms "upper", "lower", "front", "back", "left", "right", "top", "bottom", "inner", "outer", "center", "vertical", "horizontal" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the accompanying drawings, and are only simplified descriptions for the convenience of describing the present invention, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention.

[0017] In the field of medical devices, the surface electromyographic signal can be used as the most direct form of expression to show the occurrence and resting state of myoelectric activity. The strength of the surface electromyographic signal can be used to analyze the patient's Max (μV) muscle activity's maximum discharge capacity to determine the patient's muscle contraction state; if the electromyographic signal of the voice-related part is monitored, the mode of voice production can be obtained. For example, when the chest muscles are active, the density and height of the original electromyographic signal directly reflect the amplitude and strength of the muscle contraction. The higher the density and height, the stronger the surface electromyographic signal, and the stronger the contraction, thus providing a reference for judging the chest vibration during voice production.

[0018] According to the above measurement principle, the present application proposes a voice monitoring and analysis training device based on myoelectric current sensor, as shown in the attached Figure 1The device includes: an array of measuring myoelectric current sensors and at least one reference myoelectric current sensor. The array of measuring myoelectric current sensors is installed in the throat, oral cavity and chest of the human body. The reference myoelectric current sensor is usually installed in the arm or a position where the muscles do not contract when the human body speaks. When the muscles in these parts contract, the above sensors obtain surface electromyographic signals (sEMG), thereby obtaining the muscle contraction state of each organ involved in the voice. At the same time, in order to facilitate the correction and processing of signal noise, the reference myoelectric current sensor obtains the myoelectric current information of the organs not involved in the voice. The above-mentioned measured electrical signals are transmitted to the control and data processing unit in the present application via wired or wireless data transmission. The surface electromyography (sEMG) signal processing module of the unit first synchronizes the surface electromyography signals transmitted by current sensors at different positions, and then filters the synchronized signals to retain only the signals related to the voice production and performs spectrum processing and calculates the power density of the signals. The muscle contraction state of different human organs during voice production is obtained through the installation position relationship of the corresponding sensors; the results are then transmitted to the terminal via wired or wireless means through the control module, and hospital medical staff or customers can judge whether there are any diseases in the vocal part or understand their own muscle state during the vocalization process based on the results.

[0019] The above device can also be used to analyze and train the voice state, and the specific process is as follows:

[0020] S1: An array of myoelectric current sensors is attached to the throat and chest of the human body to measure the point signal generated by the muscle contraction of the throat and chest when the human body is speaking. A reference myoelectric current sensor is attached to the position of the shoulder, arm or leg of the human body where the muscle does not contract when the human body is speaking to provide a reference signal during the measurement process;

[0021] S2: The myoelectric current sensor acquires signal data in real time and transmits it to the control and data processing unit. This module synchronizes the signal data, performs noise processing according to the reference signal, and calculates the frequency spectrum and power spectrum of the sensor signals at different positions after filtering. The signal processing here includes signal synchronization in the time domain considering the delay of each myoelectric current sensor according to its different positions. The signal filtering processing mainly reduces the noise of the measurement signal and filters the low-frequency noise according to the characteristics of the reference signal.

[0022] S3: judging the composition of the contracted muscles that produce the voice signal based on the data of the myoelectric sensors at different positions obtained in step S2, and realizing voice analysis. If the analysis finds that the vibration of the chest cavity is greater than that of the throat and oral cavity in the production proportion of the voice, then the voice is judged to be produced by a male, otherwise it is produced by a female;

[0023] S4: The data processing results of the above steps S2 and S3 are presented through the device terminal.

[0024] In the above process, the trainee can consciously train his / her muscle movements according to the result presented in step S4: when a more masculine sound effect is required, the chest muscles can be contracted to produce sound; when a more feminine sound effect is required, the throat and oral muscles can be contracted to produce sound.

[0025] In the above method, after the data processing and analysis of steps S1 and S2, the muscle movement information at each electromyographic sensor position can be clearly obtained, and medical personnel can also obtain the diagnosis and treatment results of whether there is a disease in the part by analyzing the data.

[0026] Obviously, the above-mentioned embodiments of the present invention are merely examples for clearly explaining the present invention, and are not intended to limit the embodiments of the present invention. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is impossible to list all the embodiments here. Any obvious changes or modifications derived from the technical solution of the present invention are still within the scope of protection of the present invention.

Claims

1. A method for voice monitoring and analysis training based on a voice monitoring and analysis training device using an electromyographic sensor, characterized in that: The voice monitoring and analysis training device based on myoelectric current sensor comprises: an array of myoelectric current sensors for measurement and at least one myoelectric current sensor for reference, wherein the array of myoelectric current sensors for measurement is installed on the skin surface of the throat, oral cavity and chest of the human body to measure and obtain the surface electromyographic signal (sEMG) in muscle contraction, and the reference myoelectric current sensor is installed at a position where the muscle does not contract when the human body makes a sound; a control and data processing unit, which realizes data exchange with each myoelectric current sensor in a wired or wireless manner, and comprises: a surface electromyographic signal (sEMG) signal processing module, which first synchronizes the surface electromyographic signals transmitted by myoelectric current sensors at different positions, and then filters the synchronized signals to retain only the signals related to the voice production and performs spectrum processing and calculates the power density of the signals, wherein the myoelectric current signals filtered by the filtering include the muscle contraction electrical signals generated by non-voice production, and the signals of the reference myoelectric current sensor are used as references for filtering; a device terminal, which is connected to the control and data processing unit in a wired or wireless manner to realize command and information transmission; a method for voice monitoring and analysis training using the device comprises the following steps: S1: An array of myoelectric sensors is attached to the throat and chest of the human body to measure the electrical signals generated by the contraction of the muscles in the throat and chest when the human body is speaking. A reference myoelectric sensor is attached to the position where the muscles do not contract when the human body is speaking to provide a reference signal during the measurement process. S2: The myoelectric current sensor acquires signal data in real time and transmits it to the control and data processing unit, which synchronizes the signal data, performs noise processing based on the reference signal, and calculates the frequency spectrum and power spectrum of the sensor signals at different positions after filtering; S3: judging the composition of the contracted muscles that produce the voice signal based on the data of the myoelectric sensors at different positions obtained in step S2, and realizing voice analysis. If the analysis finds that the vibration of the chest cavity is greater than that of the throat and oral cavity in the production proportion of the voice, then the voice is judged to be produced by a male, otherwise it is produced by a female; S4: The data processing results of the above steps S2 and S3 are presented through the device terminal.

2. The method for voice monitoring and analysis training according to claim 1, characterized in that: According to the result presented in step S4, the trainee consciously trains his muscle movements during vocalization: when the sound effect needs to be more masculine, the chest muscles contract to produce sound; when the sound effect needs to be more feminine, the throat and oral muscles contract to produce sound.

3. The method for voice monitoring and analysis training according to claim 1, characterized in that: The signal processing in step S2 includes signal synchronization in the time domain by considering the delay of each myoelectric current sensor according to its different position, and the signal filtering processing mainly reduces the noise of the measurement signal and filters the low-frequency noise according to the characteristics of the reference signal.

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