CN109925587A - A kind of deep sleep improvement detection system and method based on biological low noise - Google Patents

Abstract

The invention belongs to the technical field of integration of integrated circuit design and biomedicine, and discloses a deep sleep improvement detection system and method based on biological low noise amplifier; EEG signals are amplified and processed by analog front-ends such as biological low-noise amplifiers to form EEG spectrograms; the spectral characteristics of EEG are analyzed with the help of the computer technology of the equipment. When delta waves (long pulse waves released by the brain during deep sleep) are detected, The device automatically plays some sound in the corresponding band, diffracting more delta bands, which in turn induces deep sleep. The invention uses biological low-noise amplifier to amplify and process the extracted EEG signals, analyzes the sleep state and provides certain improvement, prolongs the deep sleep time and improves the physiological state. Compared with the traditional EEG spectrum application, the present invention no longer just observes the human brain activity through manual and computer analysis of the spectrum, but directly applies it to the improvement of sleep and puts it into action.

Description

A deep sleep improvement detection system and method based on biological low noise amplifier

technical field

The invention belongs to the technical field of integrated circuit design and biomedicine, and in particular relates to a deep sleep improvement detection system and method based on biological low noise amplifiers.

Background technique

At present, the closest existing technology: At present, based on wireless body area network, most of the technology is to observe and monitor people's current physical state, and then feed back to people for easy analysis and propose solutions, such as high blood sugar prompting taking insulin; When observing emergencies, for example, through the analysis of ECG signals, a heart attack of the subject is detected, and the smart device will call an ambulance, etc. In terms of human sleep, the focus of the existing technology is mainly to detect and evaluate people's sleep, and then archive feedback to people, so that people can better understand their sleep and how to do better in the next sleep. The disadvantage caused by this is that the device can only provide observation sleep, but cannot directly improve the subject's sleep during the observation process. And this program is to detect people's sleep state at the same time, to give a certain improvement.

Secondly, most human body signal detection and analysis devices are connected to the device through sensor nodes to detect the physiological signals of the human body, such as ECG and EEG signals. The state of the object at this time is then analyzed on the instrument and archived for feedback to people. Most of these devices are tested on people in specific locations, and their large size and wired connection make them very limited for home use and portability. In this solution, the detection and analysis links are incorporated into a portable head-mounted device, which not only solves the limitations of home use and portability, but also maximizes the comfort of sleep.

With the continuous development of the economy and the continuous improvement of living standards, people's demand for health and medical care has gradually increased. Sleep plays a vital role in maintaining people's health. Long-term lack of sleep can easily lead to diseases such as Alzheimer's, cardiovascular disease, stroke and diabetes. The length of deep sleep time determines the quality of sleep.

Detecting the state of people's sleep and being able to analyze the sleep stage is the premise of improving sleep. However, most medical equipments (electrocardiographs, electroencephalographs) are not portable due to their size, so it is difficult to meet the requirements of home use and sleep comfort. Therefore, there is an urgent need for a portable and intelligent electronic monitoring and processing equipment to complete the extraction, processing and analysis of EEG signals.

To sum up, the existing problems in the prior art are: the existing medical equipment for detecting people's sleep has poor portability, and it is difficult to meet the requirements of household and sleep comfort. If it is difficult to meet the requirements of home use and sleep comfort, the application and promotion of the wireless body area network will be further limited; and it will directly interfere with the working state of the intelligent analysis module and reduce the efficiency of the entire solution.

Difficulty in solving the above-mentioned technical problems: In order to solve the above-mentioned problems, the main difficulty lies in the integration of equipment in the links of detection, processing and analysis, and the wireless driving of audio peripherals by the equipment.

The significance of solving the above technical problems: the limitations of portability and household use have always been obstacles to people's full use of wireless body area networks. If the integration of equipment for detection, processing and analysis can be solved, the site of biological detection equipment can be directly solved. The use of restrictions makes people more fully benefit from technology, and can broaden the application field of the wireless body area network and improve the efficiency of use.

SUMMARY OF THE INVENTION

In view of the problems existing in the prior art, the present invention provides a deep sleep improvement detection system and method based on biological low noise amplifier.

The present invention is implemented in this way, a deep sleep improvement detection method based on biological low noise amplifier, the deep sleep improvement detection method based on biological low noise amplifier includes:

The first step is to wear a detection device on the head before the human body sleeps;

In the second step, the biological electrode in the detection device samples the EEG signal, and after being amplified by the biological low-noise amplifier analog front-end, an EEG spectrogram is formed;

The weak low-frequency electrophysiological signal is collected by the electrode in contact with the head. The front-stage low-noise amplifier amplifies the signal multiple times, and the latter-stage amplifies the power of the output signal to drive the mechanical movement of the recording pen. That is, the EEG signal is digitally sampled point by point, and then passes through the analog-to-digital converter in the front-end module to form an analog EEG graph (EEG map).

The third step is to analyze the spectral characteristics of the EEG with the help of the computer technology of the equipment. When the delta wave is detected, the sound of the corresponding band is automatically played, and the delta band is diffracted.

Wavelet analysis is used for overview observation, and then the spectral characteristics of EEG are obtained. The detection of a specific waveband is mainly based on the comparison of frequency, amplitude, time phase and phase relationship, etc. The above characteristics of the delta waveform of the normal human brain are pre-stored in the intelligent terminal module in the form of digital signals. Triggers a level when the bands are relatively matched. Excite the infrared module in the device to work, that is, apply the PPM encoding method, first modulate it on a specific carrier frequency, and then transmit it through the infrared light-emitting diode, and the receiving module of the audio peripheral on the human head will filter out other clutter Only receive the signal of the specific frequency and restore it to binary pulse code, and drive the player to play the sound after demodulation.

Further, the detection equipment in the first step disperses the biomedical nodes on the inside according to the sampling requirements, and is close to the head of the human body when worn; the analog front-end module for processing the sampling signal is embedded in the head-mounted equipment.

Further, the biological low-noise amplifier analog front-end amplification processing in the second step adopts the combination of chopper technology and capacitive coupling; and then current multiplexing technology is added.

Further, in the third step, the standard human body delta waveband is preset as a reference template in the form of a signal.

Further, in the third step, when the intelligent terminal module recognizes the delta waveband generated by the human computer, the terminal module drives the external audio module, plays the pre-stored sound clip, and derives the delta waveband in the deep water period.

Another object of the present invention is to provide a biological low-noise amplifier-based deep sleep improvement detection system that implements the biological low-noise amplifier-based deep sleep improvement detection method, and the biological low-noise amplifier-based deep sleep improvement detection system include:

The head-mounted signal acquisition device is connected with the analog front-end module, and is used to realize the conversion of the ion signal of human tissue to the electronic signal;

The analog front-end module is used to realize human physiological signal processing;

The intelligent terminal module processes the EEG signals extracted by the biological electrodes through the analog front-end module, obtains the EEG spectrum after processing in the intelligent terminal, and performs spectrum analysis in the terminal module to identify the target band delta wave;

Audio module, when the intelligent terminal module recognizes the target band, it plays the pre-stored repeated audio, and automatically turns off after the preset time is reached.

Another object of the present invention is to provide an electrocardiograph applying the biological low noise amplifier-based deep sleep improvement detection method.

Another object of the present invention is to provide an electroencephalography machine using the biological low noise amplifier-based deep sleep improvement detection method.

To sum up, the advantages and positive effects of the present invention are: compared with the traditional EEG spectrum application, the present invention no longer merely observes human brain activity through manual and computer analysis of the spectrum, but directly applies it to the improvement of sleep , put it into action.

The contrast between the prior art and this scheme: as shown in Table 1:

Table 1. Comparison of prior art and the present invention

The invention realizes that people can detect and prolong the deep sleep time in daily sleep at home. Deep sleep accounts for one-fourth of the total sleep of the human body. Measuring the quality of sleep directly affects people's physical condition and state. So far, prolonging deep sleep is mainly through maintaining the regularity of work and rest, relaxing before going to bed, and improving the sleep environment. These methods are susceptible to certain external or internal interference during the implementation process, and it is difficult to fundamentally prolong the deep sleep time. EEG maps can observe people's brain activity and, of course, determine their immediate physical state. The delta band in the EEG map can reflect that the test subject maintains a deep sleep state for a certain period of time, and most of the current technologies also stay in monitoring sleep. A medical study was done in Germany, which was later promoted by Harvard Medical School: if a person plays the sound of the corresponding band during deep sleep, the deep sleep can be prolonged, and unexpected results have been achieved. The instruments needed to monitor brain activity are difficult to meet the requirements of home use and portability. The invention proposes to complete it through the wireless body area network, the low-noise and low-power amplifier of the analog front end ensures the filtering of noise inside the circuit, the post-stage amplifier can realize power amplification, and the analog-to-digital converter can help to complete the formation of the EEG map; This integrated device completely solves the limitations of common equipment and ensures the quality of sleep. By swapping the roles of people and devices, people can no longer do the aforementioned bedtime preparations and be affected during sleep. This is a problem that has always been wanted to be solved but has not been solved, which fills the current domestic strategy gap for the achievability of extending deep sleep, and makes it possible to easily improve sleep in daily life.

Compared with the traditional detection equipment, the present invention is more convenient, intelligent and home-use. The analog front-end module that processes the signal reduces the power consumption again on the basis of the low-noise amplifier, reduces the power consumption of the entire analog module, and reduces the volume occupied by the power supply equipment.

Description of drawings

1 is a schematic structural diagram of a deep sleep improvement detection system based on biological low noise amplifier provided by an embodiment of the present invention;

In the figure: 1. Head-loaded signal acquisition device; 2. Analog front-end module; 3. Intelligent terminal module; 4. Intelligent terminal-driven audio module.

FIG. 2 is a flowchart of a method for detecting deep sleep improvement based on biological low noise amplifier provided by an embodiment of the present invention.

FIG. 3 is a schematic diagram of a head-mounted device carrying a biomedical collection node provided by an embodiment of the present invention.

FIG. 4 is a schematic diagram of placing an analog front-end module and an intelligent terminal module according to an embodiment of the present invention.

FIG. 5 is a schematic diagram of delta-band matching in an intelligent terminal module according to an embodiment of the present invention.

FIG. 6 is a schematic diagram of an audio module driven by an intelligent terminal module according to an embodiment of the present invention.

Detailed ways

In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention, but not to limit the present invention.

The invention aims to provide a deep sleep improvement method based on biological low-noise amplifier, which can prolong people's deep sleep time and improve sleep quality without affecting normal rest and home use.

The application principle of the present invention will be described in detail below with reference to the accompanying drawings.

As shown in FIG. 1 , the biological low-noise amplifier-based deep sleep improvement detection system provided by the embodiment of the present invention includes: a head-mounted signal acquisition device 1 , an analog front-end module 2 , an intelligent terminal module 3 , and an intelligent terminal-driven audio module 4 .

The head-mounted signal acquisition device 1 adopts a small head-mounted wireless acquisition and transmission, and on the premise of ensuring sleep comfort, the head-attached sensor is used to realize the transformation of the ion signal of the human tissue into the electronic electrical signal. Connection with analog front-end module 2.

Analog front-end module 2 introduces a low-noise and low-power amplifier. Compared with other common signals, human bioelectrical signals have lower frequency and amplitude, and are easily affected by various system internal noise and external interference. The frequency range of the human brain electrical signal required by the present invention is about 0.5 Hz to 50 Hz, and the amplitude thereof is 1 μV to 100 μV. Therefore, the human body signals represented by ECG signals and EEG signals are greatly interfered by low-frequency noise. Therefore, a high-performance low-noise and low-power amplifier suitable for human physiological signal processing becomes the premise of completing the analog front-end module 2 .

The intelligent terminal module 3 processes the EEG signals extracted by the biological electrodes through the analog front-end module 2, and obtains the EEG spectrum after processing in the intelligent terminal, and then performs spectrum analysis in the terminal module to identify the target band - delta wave. In the module, the analysis of EEG spectrogram is usually done manually. At present, it is mostly done by computer. The main methods are automatic frequency analysis, power spectrum analysis, and quantitative analysis. After the spectrum analysis is completed, a comparison band template is pre-implanted in the module to facilitate the identification of the delta band (0.5 to 3 Hz) in the corresponding frequency region.

When the audio module 4 and the intelligent terminal module 3 identify the target band, it indicates that people have gradually entered a state of deep sleep. The terminal drives the audio module, plays the pre-stored repetitive audio (with an appropriate volume), and automatically turns off when the preset time is reached.

As shown in FIG. 2 , the deep sleep improvement detection method based on biological low noise amplifier provided by the embodiment of the present invention includes the following steps:

S201: Before the human body sleeps, wear the detection device on the head;

S202: The EEG signal is sampled by the biological electrode in the detection device, and the EEG spectrum is formed after being amplified by an analog front-end such as a biological low-noise amplifier;

S203: Analyze the spectral characteristics of EEG with the help of the computer technology of the device. When delta waves (long pulsed radio waves released by the brain during deep sleep) are detected, the device will automatically play some sounds in the corresponding bands, diffracting more delta bands, promoting depth sleep.

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

As shown in FIG. 3-FIG. 6, the deep sleep improvement detection method based on biological low noise amplifier provided by the embodiment of the present invention includes the following steps:

Step 1, configure the header signal acquisition device;

The effective acquisition of human brain signals is the premise for the normal implementation of the entire program. Most of the traditional EEG acquisitions attach medical nodes to the head of the human body, and then lead out signal lines from the nodes to connect to processing equipment, and then come out and observe the state of brain activity. . Wired devices are complicated and have limited use occasions, and it is very difficult to acquire and process signals without affecting people's sleep.

The head-mounted signal acquisition device, as shown in Figure 3, disperses the biomedical nodes on the inside according to the sampling requirements, and can be closely attached to the head of the human body when worn to ensure the realization of the transmission of ion electrical signals generated by human muscles and nerves to electronic electrical signals. Transformation and extraction. As an analog front-end module that processes the sampled signal, it is embedded in the head-mounted device, eliminating the inconvenience of connecting external devices from the node leads, greatly improving the comfort of sleep, and providing a guarantee for the subsequent identification of human brain wave bands.

Step 2, introduce a low-noise and low-power amplifier;

Since the amplitude of the human bioelectrical signal is very small, it is very easy to be interfered by the external environment and the internal noise of the circuit (the analog front-end circuit samples the CMOS process, and there is internal noise in the circuit), and the collected signal will produce certain errors after processing. The wireless body area network technology has a very obvious feature, that is, it can detect the human bioelectrical signal uninterrupted for an unlimited time, which has certain requirements on the power consumption of the whole solution. Regardless of whether the solution uses self-powered devices or batteries, it is undoubtedly beneficial to reduce the power consumption of the amplifier as much as possible.

Combining the industry's popular chopping technology with capacitive coupling, it can effectively isolate the DC offset of the biological electrode, the influence of the high impedance of the electrode in the low frequency band, and eliminate the flicker noise in the low frequency band (main bioelectric signal frequency band) of the CMOS circuit. Finally, the current multiplexing technology is used to reduce thermal noise. To ensure the correctness of the subsequent digital processing of the amplified signal.

Step 3, deploy the intelligent terminal module;

The signal processed in the analog front-end module is characterized as an EEG spectrogram after the burned-in program in this module. Before realizing automatic spectrum analysis, it is necessary to preset the standard human body delta band as a reference template in this module in the form of a signal to ensure the validity of the analysis, as shown in Figure 5. Then the analog front-end module is incorporated into the head-mounted device together with this module to ensure space saving and home-use, as shown in Figure 4.

Step 4, the intelligent terminal drives the audio module;

When the intelligent terminal module recognizes the delta-band generated by the human computer, it indicates that the human body has entered a deep sleep period. At this time, the characteristics of the wireless body area network are more manifested. The terminal module drives the (wireless) external audio module to play (preset time, preset volume) pre-stored sound clips (the repeated clips have the same delta wave) The same burst frequency), and then more delta bands are derived in the deep water period to achieve the purpose of improving deep sleep, as shown in Figure 6.

The technical principle of the deep sleep improvement detection system based on biological low noise amplifier provided by the embodiment of the present invention;

1. Wireless Body Area Network (WBAN)

Wireless Body Area Networks (WBAN) is a radio frequency-based wireless network technology that can interconnect tiny nodes with sensors in or around the human body. Main components: biomedical sensor nodes, analog front-end modules and intelligent terminals and other modules.

Biomedical sensor nodes: Their main function is to obtain a variety of human physiological signals, such as pulse, heartbeat and brain activity, blood pressure, blood sugar, etc., and convert these human physiological signals into electrical signals. The invention adopts an adhesive sensor to collect brain activity to ensure sleep comfort.

Analog front-end module: The analog front-end completes the functions of human body electrical signal amplification, digital processing and transmission, including low noise amplifier (Low Noise Amplifier, LNA), analog to digital converter (Analog to Digital Converter, ADC), digital signal processing Circuit modules such as digital signal processor (DSP), radio frequency transceiver (RadioFrequencytransceiver, RF-transceiver).

Intelligent terminal module: Through the analysis and processing of these human body signals, the physiological state of the human body can be obtained, and further responses can be made according to the obtained results. The main result obtained by the present invention is the EEG spectrogram.

2. EEG spectrum analysis corresponds to sound excitation

As shown in Figure 5, when the smart terminal analyzes the delta wave band (indicating that the person has entered deep sleep), the audio module releases the stored sound clip, and the released sound also has the same burst frequency as the delta wave, which can make The human brain diffracts more delta bands to achieve the purpose of prolonging deep sleep.

After countless experiments and efforts by engineers, the release of the wireless body area network standard IEEE802.15.6 affirms the scientific nature of the wireless body area network's role in human medical care. First of all, the German medical laboratory found for the first time that playing delta-band audio after the human body enters deep sleep can prolong deep sleep, but there is no solution based on wireless body area network applications. Secondly, the sleep-related applications of the wireless body area network currently only stop at observation and archiving, and have not been extended to actively affect sleep through devices. Finally, the concept of extracting, processing, and detecting EEG signals remains on the larger analysis equipment. At present, there is no plan to integrate it into the wireless body area network to solve household and portable problems.

The above descriptions are only preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements and improvements made within the spirit and principles of the present invention shall be included in the protection of the present invention. within the range.

Claims (8)

1. a kind of deep sleep based on biological low noise improves detection method, which is characterized in that described based on biological low noise Deep sleep improve detection method include:

The first step wears detection device in head before sleep quality；

Second step, the bioelectrode in detection device sample EEG signals, after biological low noise AFE(analog front end) enhanced processing, shape At EEG spectrogram；

Faint low frequency electricity physiological signal is collected by the electrode contacted with head, prime low-noise amplifier is to the multiple of signal Amplification, rear class carry out the power amplification of output signal again, drive the mechanical movement of recording pen.Namely to EEG signals point by point into Digitized sampling, by the analog-digital converter in front-end module, forms simulated electroencephalogram figure；

Third step plays corresponding wave when detecting δ wave by the spectrum signature of the computer technology analysis EEG of equipment automatically The sound of section, diffraction go out δ wave band；

General picture observation is done using wavelet analysis, obtains the spectrum signature of EEG；Comparison frequency is essentially consisted in the detection of specific band The These characteristics of the δ waveform of normal human's brain are prestored by rate, wave amplitude, phase and phase relation in a manner of digital signal In intelligent terminal module, when the general picture that wavelet analysis detects is opposite with wave band is prestored coincide, a level is triggered；Excitation Infrared module work in equipment, will first be modulated in specific carrier frequency, then launch again through infrared light-emitting diode It goes, the receiving module of the audio peripheral hardware of human body head can filter out other clutters and only receive the signal of the specific frequency and be restored At binary pulse code, player plays sound is driven after demodulation.

2. deep sleep based on biological low noise improves detection method as described in claim 1, which is characterized in that described the Biologic medical node is placed in inside according to sampling request dispersion by the detection device of one step, and when wearing is close to human body head；To adopting The analog front-end module that sample signal is handled is embedded in head and carries equipment.

3. deep sleep based on biological low noise improves detection method as described in claim 1, which is characterized in that described the The biological low noise AFE(analog front end) enhanced processing of two steps is combined using wave chopping technology with capacitive coupling；Again plus current multiplexing skill Art.

4. deep sleep based on biological low noise improves detection method as described in claim 1, which is characterized in that described the Three steps are placed in advance in the form of a signal using the human body δ wave band of standard as referring to template.

5. deep sleep based on biological low noise improves detection method as described in claim 1, which is characterized in that described the Three steps recognize the δ wave band of human body computer generation when intelligent terminal module, and terminal module drives external audio module, play preparatory The sound clip of deposit derives δ wave band in the deep water phase.

6. it is a kind of realize the deep sleep described in claim 1 based on biological low noise improve detection method based on biological low noise The deep sleep put improves detection system, which is characterized in that the deep sleep based on biological low noise improves detection system Include:

Head carries signal collecting device, connect with analog front-end module, for realizing tissue ion signal to electronic telecommunication Number transformation；

Analog front-end module, for realizing human physiological signal treatment；

Intelligent terminal module is handled by the EEG signals that analog front-end module extracts bioelectrode, in intelligent terminal EEG spectrogram is obtained by processing, spectrum analysis is carried out in terminal module, identifies target wave band δ wave；

Audio-frequency module when intelligent terminal module identifies target wave band, plays the repetition audio being prestored into, reaches the preset time After be automatically closed.

7. a kind of deep sleep using described in Claims 1 to 5 any one based on biological low noise improves detection method Electrocardiograph.

8. a kind of deep sleep using described in Claims 1 to 5 any one based on biological low noise improves detection method Electroence phalograph.