CN119014883B - A voice monitoring and analysis training device and method based on myoelectric current sensor - Google Patents
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Abstract
本发明公开了一种基于肌电流传感器的嗓音监控分析训练装置和方法，包括：肌电流传感器阵列及至少一个参考用肌电流传感器，肌电流传感器阵列安装在人体咽喉口腔及胸腔部，参考用肌电流传感器安装在不限于肩、臂或腿部的人体发声时肌肉不发生收缩位置；控制及数据处理单元，该单元与各肌电流传感器连接进行数据交换；设备终端，与控制及数据处理单元连接并实现命令、信息传输。该装置对嗓音监控分析训练是通过肌电流传感器获得肌肉震动数据，经滤波、降噪处理获得不同肌肉位置信号功率谱密度，判断肌肉收缩位置，确定男性或女性发声，并对发声部位训练。本技术方案将肌电流传感器用于医学声音分析和训练，为该技术领域发展提出一个创新性路径。
The present invention discloses a voice monitoring and analysis training device and method based on myoelectric current sensors, comprising: an myoelectric current sensor array and at least one reference myoelectric current sensor, the myoelectric current sensor array being installed in the throat, oral cavity and chest of the human body, the reference myoelectric current 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 myoelectric current 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 myoelectric current 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 myoelectric current sensors for medical voice analysis and training, proposing an innovative path for the development of this technical field.
Description
Technical Field
The application belongs to the technical field of intelligent medical equipment, in particular to a device for monitoring, analyzing and training human body occurrence by means of a myocurrent sensor and a data control processing module which are conventionally used for heart monitoring in combination with a signal processing and analyzing method in the field of medical equipment.
Background
The surface electromyographic signals are superposition of bioelectric signals generated by exciting a plurality of motion units in time and space when human muscles contract. The human body controls muscle strength by adjusting the excitement of muscles and the number of exercise units involved in contraction, and both of them cause changes in the surface electromyographic signals. The most widely used application of surface electromyographic signals in the diagnosis and treatment of human biological features is the measurement of the electrocardiogram, which is performed by measuring the tiny electrical signals generated by the contraction of the heart muscle during the beating of the heart to obtain the heart dynamic information. The measurement of myoelectric current typically uses skin surface electrodes that are placed on the skin surface to record the electrical activity of the entire muscle, thereby obtaining nerve conduction velocity, spinal cord reflex, involuntary movement of the muscle, and the like. The myoelectric current measuring instrument can distinguish neurogenic damage and myogenic damage by measuring the time limit and amplitude of motor unit potential, spontaneous electric activity under quiet condition and waveform and amplitude of muscle strong contraction, and diagnose acute and chronic damage of anterior horn of spinal cord (such as poliomyelitis and motor neuron disease), nerve root and peripheral neuropathy (for example, electromyography examination can help to determine the position, degree, range and prognosis of nerve damage). In addition, the kit has diagnostic value for neuromuscular diseases, neuritis, genetic metabolic disorder neuropathy and various muscle diseases.
Careful breakdown of the human body during the process can be found to require the cooperative operation of three systems, namely, the power system, the vibration system and the resonance system. The specific correspondence of each system on human organs is that respiratory organs (including lung, diaphragm and abdominal muscle) belong to a power system, throats and vocal cords belong to a vibration system, oral cavities, pharyngeal cavities, thoracic cavities, nasal cavities and head cavities belong to a resonance system, and in addition, the biting sound and word parts are matched to generate lips, tongues, cheeks, teeth and the like of speech. The operation of these systems is performed by muscle activation. Therefore, the characteristic parameters of sound production, such as audio, tone quality, volume and the like are all determined by the states of the three systems. In a physiological disease state, the human body changes the sound just due to the pathological changes of certain parts in the system. In the existing treatment process, doctors obtain disease information through voice analysis and examination of related organs, and along with the application of big data technology, voice symptoms are also determined by adopting an audio analysis method. In addition, for some professionals who are engaged in industries such as vocal music and broadcasting, the sound production of each organ is guaranteed to be perfectly presented, and in order to achieve professional effects of guaranteeing voice, the professionals need to perform professional training on each sound production organ, and in training, the working states of each organ are adjusted through hearing to obtain effects so as to achieve the training purpose. The sounding process is the process that the muscles of each organ participate in contraction, so that the quantitative calibration of the sounding effect is achieved by actively controlling the muscles of the organs. The application provides technical innovation aiming at the blank technical field of upper sound detection, analysis and training, which quantifies the existing monitoring, measurement and training of human sound production by means of other equipment measurement (non-sound detection) without related instruments and devices.
Disclosure of Invention
The technical scheme of the application aims at the current medical field and focuses on the detection limitation of the emitted sound performance parameters in the sound analysis measurement, and the application develops a new way of applying the myoelectric current measurement technology to three systems (a power system, a vibration system and a resonance system) for sounding a human body. The application aims at achieving the purpose, and adopts the technical scheme that the voice monitoring analysis training device based on the myoelectric current sensor comprises a myoelectric current sensor array for measurement and at least one myoelectric current sensor for reference, wherein the myoelectric current sensor array for measurement is arranged at the oral cavity part and the chest part of a human body, the myoelectric current sensor array for measurement is arranged at the position which is not limited by the shoulder, the arm or the leg and is not contracted when the muscle of the human body sounds, a control and data processing unit, a device terminal and a command and information transmission unit are connected, the myoelectric current sensor for measurement is attached to the skin surface of the throat oral cavity part and the chest part of the human body, and the myoelectric signal (sEMG) of the surface in muscle contraction is measured and acquired. The device creatively lays out the myoelectric current sensors at the positions of muscles of organs of human body sounding for the first time, thereby directly acquiring electric signals of contraction of each muscle in the sounding process, acquiring muscle working parameters of each position through data analysis, and displaying acquired information to medical staff or users in real time by utilizing a terminal. In order to avoid the influence of noise signals of other movements on data in the sounding process, a myocurrent sensor for reference is specially arranged on the configuration of the myocurrent sensor, and the measurement data of the myocurrent sensor is used for removing noise information of sounding data.
The key of the signal processing of the control and data processing unit comprises a surface electromyographic signal (sEMG) signal processing module, wherein the surface electromyographic signal processing module firstly synchronizes the data of the surface electromyographic signals transmitted by the current sensors at different positions, and then filters the synchronized signals to reserve the signals only related to voice sound production, and carries out frequency spectrum processing and power density calculation on the signals. The filtered myoelectric current signals include, but are not limited to, electrical muscle contraction signals generated by heart beating, throat swallowing, and non-sounding, reference being made to the signals of the myoelectric current sensors for reference of the filtering. The data processing unit is used for processing surface electromyographic signals (sEMG), so that the information is more accurate, the data processing and subsequent calculation are more accurate in obtaining the sound spectrum power, and the determination of subsequent disease positions and the training of sounding positions are ensured.
The data communication between the myoelectric current sensor and the control and data processing unit adopts a wired or wireless mode, and the equipment terminal is connected with the control and data processing unit through the wired or wireless mode to display the data result and receive external instructions. The adoption of the wireless connection modes is more beneficial to the real-time transmission and analysis of data, and provides convenience for diagnosis and training.
The application also provides a method for monitoring, analyzing and training voice by using the device, which comprises the following steps:
S1, attaching myoelectric current sensors to the throat and chest of a human body to form an array, wherein the myoelectric current sensors are used for measuring point signals generated by muscle contraction of the throat and chest when sounding, and attaching myoelectric current sensors for reference to positions of the human body, such as shoulders, arms or legs, where the muscles do not contract when sounding, so as to provide reference signals in the measurement process;
S2, acquiring signal data in real time by the myoelectric current sensor, transmitting the signal data to a control and data processing unit, synchronizing the signal data, carrying out noise processing according to a reference signal, and calculating frequency spectrums and power spectrums of sensor signals at different positions after filtering processing, wherein the signal processing comprises carrying out signal synchronization on a time domain according to different positions of each myoelectric current sensor by considering time delay, and carrying out noise reduction and low-frequency noise filtering on a measurement signal mainly according to the characteristics of the reference signal;
S3, judging the constitution of muscles contracted by the voice signal according to the data of the myoelectric current sensors at different positions obtained in the step S2, realizing voice analysis, judging that the voice is generated for men if the voice is generated in a mode that the vibration of the chest cavity in the generation ratio of the voice is larger than that of the throat cavity part, and otherwise, generating for women;
And S4, presenting the data processing results in the steps S2 and S3 through the equipment terminal.
In the above process, the trainer can intentionally train the muscle actions in the occurrence process of himself according to the result presented in the step S4, namely, when the sound effect is required to be more masculinized, the muscle contraction of the chest part is used for sounding, and when the sound effect is required to be more masculinized, the muscle contraction of the throat and the oral part is used for sounding.
In the method, through the data processing and analysis of the steps S1 and S2, the muscle movement information at the positions of the muscle current sensors can be clearly known, and medical staff can obtain diagnosis and treatment results of whether the diseases exist at the positions through the data analysis of the muscle movement information.
The voice monitoring analysis training device of the application introduces the myoelectric current sensor into the field of voice analysis and treatment for the first time, thereby combining with data analysis and control to generate a new device which can be used for voice pathological diagnosis and professional voice training, and simultaneously purifying the signal data by utilizing the measurement data of the reference sensor in the processing and analysis of the myoelectric signal data to ensure the accuracy of analysis results.
Drawings
Fig. 1 is a schematic diagram of a voice monitoring analysis training device based on a myoelectric current sensor.
Detailed Description
The invention is further illustrated, but is not limited to, the following examples. It should be noted that, the terms "upper," "lower," "front," "rear," "left," "right," "top," "bottom," "inner," "outer," "center," "vertical," "horizontal," and the like indicate orientations or positional relationships based on the orientations or positional relationships illustrated in the drawings, and are merely for convenience in describing the present invention, and do not indicate or imply that the apparatus or element being referred to must have a specific orientation, be configured and operated in a specific orientation, and therefore should not be construed as limiting the present invention.
In the field of medical devices, myosurface electrical signals can be used as the most direct manifestation of myoelectric activity occurrence and rest conditions. The maximum discharge capacity of Max (mu V) muscle activity of a patient can be analyzed through the intensity of the electromyographic signals to judge the state of muscle contraction and movement of the patient, and if the electromyographic signals of relevant positions of sounding are monitored, the sounding mode can be obtained. For example, when the chest muscle is active, the intensity and the height of the original myoelectric signals intuitively reflect the amplitude and the strength of muscle contraction, and the higher the intensity and the height, the stronger the surface myoelectric signals are, the stronger the contraction is, so that a reference is provided for judging chest vibration during sounding.
According to the measurement principle, the application provides a voice monitoring analysis training device based on a myoelectric current sensor, as shown in figure 1. The device comprises a measuring myoelectric current sensor array and at least one reference myoelectric current sensor, wherein the measuring myoelectric current sensor array is arranged at the throat and chest parts of a human body, the reference myoelectric current sensor is usually arranged at the positions where muscles do not shrink when arms or the human body sounds, and when the muscles at the positions shrink, the sensor obtains surface myoelectric signals (sEMG) so as to obtain the muscle contraction state of each sounding participating organ when the sounding is performed, and meanwhile, the reference myoelectric current sensor obtains myoelectric current information of non-participating sounding organs in order to be convenient for correcting and processing signal noise. The measured electric signals are transmitted to a control and data processing unit in the application through a wired or wireless data transmission mode, a surface electromyographic signal (sEMG) signal processing module of the unit firstly synchronizes the data of the surface electromyographic signals transmitted by current sensors at different positions, then filters the synchronized signals to retain signals only related to voice sounding, carries out frequency spectrum processing and power density calculation on the signals, obtains muscle contraction states of different human organs during sounding through the installation position relation of the corresponding sensors, and then transmits the result to a terminal through a control module in a wired or wireless mode, and medical staff or clients in a hospital can judge whether the sounding part has symptoms or know the muscle states during self sounding according to the result.
The voice state analysis and training can be realized by using the device, and the specific process is as follows:
S1, attaching myoelectric current sensors to the throat and chest of a human body to form an array, wherein the myoelectric current sensors are used for measuring point signals generated by muscle contraction of the throat and chest when sounding, and attaching myoelectric current sensors for reference to positions of the human body, such as shoulders, arms or legs, where the muscles do not contract when sounding, so as to provide reference signals in the measurement process;
S2, acquiring signal data in real time by the myoelectric current sensor, transmitting the signal data to a control and data processing unit, synchronizing the signal data, carrying out noise processing according to a reference signal, and calculating frequency spectrums and power spectrums of sensor signals at different positions after filtering processing, wherein the signal processing comprises carrying out signal synchronization on a time domain according to different positions of each myoelectric current sensor by considering time delay, and carrying out noise reduction and low-frequency noise filtering on a measurement signal mainly according to the characteristics of the reference signal;
S3, judging the constitution of muscles contracted by the voice signal according to the data of the myoelectric current sensors at different positions obtained in the step S2, realizing voice analysis, judging that the voice is generated for men if the voice is generated in a mode that the vibration of the chest cavity in the generation ratio of the voice is larger than that of the throat cavity part, and otherwise, generating for women;
And S4, presenting the data processing results in the steps S2 and S3 through the equipment terminal.
In the above process, the trainer can intentionally train the muscle actions in the occurrence process of himself according to the result presented in the step S4, namely, when the sound effect is required to be more masculinized, the muscle contraction of the chest part is used for sounding, and when the sound effect is required to be more masculinized, the muscle contraction of the throat and the oral part is used for sounding.
In the method, through the data processing and analysis of the steps S1 and S2, the muscle movement information at the positions of the muscle current sensors can be clearly known, and medical staff can obtain diagnosis and treatment results of whether the diseases exist at the positions through the data analysis of the muscle movement information.
It should be understood that the above-described embodiments of the present invention are provided by way of example only and are not intended to limit the scope of the invention. Other variations or modifications of the above teachings will be apparent to those of ordinary skill in the art. Not all embodiments are exhaustive. All obvious changes or modifications which come within the spirit of the invention are desired to be protected.
Claims (3)
1. A voice monitoring analysis training device based on a myocurrent sensor is characterized by comprising a myocurrent sensor array for measurement and at least one myocurrent sensor for reference, wherein the myocurrent sensor array for measurement is arranged on the surface of skin of the oral cavity part and the chest part of a human body, surface myoelectric signals (sEMG) in muscle contraction are measured and acquired, the myocurrent sensor for reference is arranged at a position where muscle does not shrink when the human body sounds, a control and data processing unit which is used for realizing data exchange with each myocurrent sensor in a wired or wireless mode, the unit comprises a surface myoelectric signal (sEMG) signal processing module, the module firstly synchronizes data of the surface myoelectric signals transmitted by the myocurrent sensors at different positions, then filters the synchronized signals to reserve signals only related to the voice sounds and processes frequency spectrum and calculates power density of the signals, the filtered myoelectric signals comprise muscle electric signals generated by non-sound production, a control and data processing unit which is used for realizing data exchange with each myoelectric signal sensor in a wired or wireless mode, a terminal for the control and data processing unit which is connected with a control and data processing device for realizing the wireless mode, and a method for realizing the data analysis training by using the control and data processing unit, wherein the voice monitoring and the voice monitoring analysis training device is used for realizing the voice monitoring analysis training and the voice monitoring device based on the voice monitoring analysis training voice on the voice monitoring:
s1, attaching myoelectric current sensors to the throat and chest of a human body to form an array, wherein the myoelectric current sensors are used for measuring electric signals generated by muscle contraction of the throat and chest when sounding, and attaching myoelectric current sensors for reference to positions where the muscles do not contract when sounding are used for providing reference signals in the measurement process;
s2, the myoelectric current sensor acquires signal data in real time and transmits the signal data to the control and data processing unit, and the module synchronizes the signal data, carries out noise processing according to a reference signal, and calculates frequency spectrums and power spectrums of sensor signals at different positions after filtering processing;
S3, judging the constitution of muscles contracted by the voice signal according to the data of the myoelectric current sensors at different positions obtained in the step S2, realizing voice analysis, judging that the voice is generated for men if the voice is generated in a mode that the vibration of the chest cavity in the generation ratio of the voice is larger than that of the throat cavity part, and otherwise, generating for women;
And S4, presenting the data processing results in the steps S2 and S3 through the equipment terminal.
2. The method for voice monitoring, analyzing and training according to claim 1, wherein the training person intentionally trains the muscle action in the process of self-sounding according to the result presented in the step S4, namely, sounds by chest muscle contraction when the sound effect is more masculine, and sounds by throat and oral muscle contraction when the sound effect is more masculine.
3. The voice-monitoring analysis training method according to claim 1, wherein the signal processing in step S2 includes signal synchronization in a time domain considering a delay according to a position of each of the myoelectric current sensors, and the signal filtering process mainly performs noise reduction on the measurement signal and filters low-frequency noise according to characteristics of the reference signal.
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| JP5030150B2 (en) * | 2007-03-20 | 2012-09-19 | 独立行政法人産業技術総合研究所 | Voice recognition device using myoelectric signal |
| JP2011237676A (en) * | 2010-05-12 | 2011-11-24 | Prefectural Univ Of Hiroshima | Utterance training device |
| WO2012040027A1 (en) * | 2010-09-21 | 2012-03-29 | Kennesaw State University Research And Services Foundation, Inc. | Vocalization training method |
| CN113571151A (en) * | 2017-09-05 | 2021-10-29 | 无锡时代天使医疗器械科技有限公司 | Apparatus and method for monitoring orofacial muscle training |
| CN109875515B (en) * | 2019-03-25 | 2020-05-26 | 中国科学院深圳先进技术研究院 | Pronunciation function evaluation system based on array surface myoelectricity |
| WO2020243299A1 (en) * | 2019-05-29 | 2020-12-03 | Cornell University | Devices, systems, and methods for personal speech recognition and replacement |
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