Brain blood oxygen detection sensing system

Abstract

The invention relates to a brain blood oxygen detection sensing system which comprises sensor nodes arranged in a matrix. The sensor node comprises a wireless MCU, a PPG chip and an optical detection unit; the wireless MCU can be configured with a corresponding PPG chip; any PPG chip is configured to generate driving current so as to drive the corresponding optical detection unit to emit modulated light to a position to be detected; the PPG chips can be connected with the hardware synchronous bus, respond to global trigger signals of the hardware synchronous bus, synchronously drive the corresponding optical detection units to collect reflected light signals of modulated light and generate blood oxygen detection signals based on the reflected light signals. Wherein a blood oxygen detection signal is transmitted to the corresponding wireless MCU through the PPG chip. The problem that high-precision and low-noise multi-node synchronous signal acquisition is difficult to realize due to high framework complexity of a traditional discrete system is effectively solved.

Description

Technical Field

[0001] This invention relates to the field of optical sensing technology, and more particularly to a brain blood oxygen detection sensing system. Background Technology

[0002] Cerebral oxygenation detection generally refers to the non-invasive monitoring of changes in the concentrations of oxyhemoglobin and deoxyhemoglobin in brain tissue to reflect the oxygen metabolism status and neural activity of the brain. Functional near-infrared spectroscopy (fNIRS) is currently the primary method for cerebral oxygenation detection. It utilizes near-infrared light of a specified wavelength to penetrate biological tissue, and calculates oxygenation parameters by detecting changes in the intensity of the emitted light. Because different brain regions exhibit different temporal dynamics in their oxygenation changes, simultaneous multi-point signal acquisition is crucial for accurately acquiring oxygenation signals from different brain regions.

[0003] Existing fNIRS systems typically rely on discrete optical components and circuits to construct sensing units for detecting blood oxygen signals. However, the complex discrete system architecture makes it difficult to achieve high-precision synchronous acquisition when performing multi-point detection, and it is also prone to introducing noise, resulting in poor accuracy and consistency of synchronous acquisition. Summary of the Invention

[0004] Based on the foregoing analysis, the main objective of this invention is to provide a brain blood oxygen detection sensing system that solves the problem that the high complexity of traditional discrete system architecture makes it difficult to achieve high-precision, low-noise multi-node synchronous signal acquisition.

[0005] To address this, a brain oxygenation detection sensing system of the present invention includes: sensor nodes arranged in a matrix; each sensor node includes a wireless MCU, a PPG chip, and an optical detection unit; the wireless MCU is configured to configure a corresponding PPG chip; each PPG chip is configured to generate a drive current to drive the corresponding optical detection unit to emit modulated light toward the detection location; and each PPG chip is connected to a hardware synchronization bus, responding to a global trigger signal in the hardware synchronization bus to synchronously drive the corresponding optical detection unit to collect the reflected light signal of the modulated light, and generate an oxygenation detection signal based on the reflected light signal; wherein the oxygenation detection signal is transmitted to the corresponding wireless MCU via the PPG chip.

[0006] Preferably, a Hub is also included; the Hub is used to issue node configuration instructions and process the blood oxygen detection signal; the wireless MCU can configure the corresponding PPG chip based on the node configuration instructions, and designate the corresponding sensor node as a master sensor node or a slave sensor node; the PPG chip corresponding to the master sensor node is configured to generate the drive current, and is also configured to output the global trigger signal to the hardware synchronization bus, so that all PPG chips respond to the global trigger signal to synchronously drive the corresponding optical detection unit to collect the reflected light signal of the modulated light; wherein, the reflected light signal collected by the optical detection unit corresponding to the master sensor node is a shallow reflected light signal; the reflected light signal collected by the optical detection unit corresponding to the slave sensor node is a deep reflected light signal.

[0007] As a further preferred embodiment, the Hub further includes a signal processing unit; the signal processing unit is used to generate blood oxygen detection data based on the blood oxygen detection signal generated by the correspondence between the shallow reflected light signal and the deep reflected light signal.

[0008] As a further preferred embodiment, the sensor node further includes a six-axis sensor; the six-axis sensor is used to collect spatial position information of the corresponding sensor node; the wireless MCU can also generate a positioning signal based on the spatial position information; the hub is used to issue no fewer than the number of the sensor nodes in each time window based on the positioning signal, so that each sensor node is designated as the master sensor node at least once in each time window; wherein, the node configuration instruction includes specifying the master sensor node number and the coding frequency.

[0009] Preferably, the wireless MCU uses Bluetooth or WAN as its communication protocol.

[0010] Preferably, the antenna of the wireless MCU is a button battery.

[0011] Preferably, the PPG chip includes a DAC module and a constant current driving circuit; the DAC module is used to generate the driving voltage signal; the constant current driving circuit is used to convert the driving voltage signal into the driving current to drive the corresponding optical detection unit to emit the modulated light to the position to be detected.

[0012] Preferably, the PPG chip further includes a low-noise amplifier and an ADC circuit; the low-noise amplifier is used to perform gain amplification on the reflected light signal; the ADC circuit is used to perform digital signal conversion on the amplified reflected light signal to generate the blood oxygen detection signal.

[0013] Preferably, the optical detection unit includes an LED light source and a photodiode; the LED light source is used to emit modulated light to the position to be detected based on the driving current; the photodiode is used to collect the reflected light signal of the modulated light.

[0014] As a further preferred embodiment, the LED light source includes a first LED light source with a wavelength of 735nm to 750nm and a second LED light source with a wavelength of 850nm.

[0015] The brain blood oxygen detection sensing system of the present invention has the following beneficial effects: First, unlike traditional solutions that use discrete optical components and circuits to build sensing units, resulting in complex system architecture and easy introduction of noise, this system uses PPG chips and improves the system architecture of their external interaction. It adopts a modulation mechanism based on MCU configuration of PPG chips to drive the photoelectric detection unit to perform modulated light emission of a single sensor node and synchronous acquisition of reflected light signals by all sensor nodes, effectively reducing the introduced circuit noise and preventing weak cerebral blood oxygenation signals from being overwhelmed by noise.

[0016] Secondly, unlike traditional discrete architectures which struggle to achieve high-precision synchronous acquisition when detecting multiple points, this system directly connects each PPG chip to the hardware synchronization bus and makes them respond to the same global trigger signal, synchronously driving all optical detection units to acquire reflected light signals. This ensures that all sensor nodes work in strict synchronization, achieving high-precision, multi-point synchronous signal acquisition.

[0017] Furthermore, unlike traditional discrete solutions that suffer from high power consumption, high cost, and difficulty in expansion due to component redundancy and complex debugging, this system leverages the high integration characteristics of the PPG chip to significantly reduce single-node power consumption and hardware cost, enabling core analog front-end functions such as drive current generation and reflected light signal acquisition. This significantly simplifies the system architecture and makes it easier to implement and expand. At the same time, the matrix-arranged sensor nodes and the configuration management of the wireless MCU support flexible expansion and convenient deployment of the brain detection area, and can also solve the problem of high-precision synchronous acquisition of multiple nodes in traditional solutions. Attached Figure Description

[0018] Figure 1 This is an overview architecture diagram of a brain blood oxygen detection sensing system according to an embodiment of the present invention; Figure 2 This is an interactive timing diagram of a brain blood oxygen detection sensing system according to an embodiment of the present invention; Figure 3 This is an architectural diagram of a brain blood oxygen detection sensing system according to an embodiment of the present invention. Detailed Implementation

[0019] The present invention will now be described in more detail with reference to the accompanying drawings. It should be noted that the following description of the present invention with reference to the accompanying drawings is merely illustrative and not restrictive.

[0020] Where possible, the various embodiments described below can be rearranged to form other embodiments not shown in the following description; the various technical features described below can also be rearranged to form other embodiments not shown in the following description.

[0021] Example: To address the challenge of achieving high-precision, low-noise multi-node synchronous signal acquisition due to the high complexity of traditional discrete system architectures, this embodiment provides a brain blood oxygenation detection sensing system. This system primarily comprises sensor nodes arranged in a matrix. This arrangement facilitates distributed acquisition of blood oxygenation signals from different brain regions, improving spatial resolution and data coverage. Each sensor node includes a wireless MCU, a PPG chip, and an optical detection unit. This modular design enhances the system's scalability and deployment flexibility. The wireless MCU can be configured with corresponding PPG chips, enabling any PPG chip to generate a drive current to drive the corresponding optical detection unit to emit modulated light towards the detection location. Since all PPG chips are connected to a hardware synchronization bus, they can respond to the global trigger signal on the hardware synchronization bus, thus synchronously driving the corresponding optical detection unit to acquire the reflected light signal of the modulated light. By introducing a hardware synchronization bus and a global trigger mechanism, the time synchronization problem between multiple sensor nodes is effectively solved, significantly improving the consistency and accuracy of multi-point data acquisition. Furthermore, this system employs a single optical detection unit emitting light, with all optical detection units simultaneously acquiring data. This ensures low noise interference in the reflected light signals collected by sensor nodes far from the light-emitting location, and the reflected light signals collected by sensor nodes entering and exiting the light-emitting location can serve as shallow reflection reference signals. The PPG chip can generate a blood oxygen detection signal based on the reflected light signal and transmit it to the corresponding wireless MCU. This makes the system architecture more lightweight, significantly reducing the computational burden on the main control unit, while improving the system's real-time performance and communication efficiency, thus achieving high-precision, low-noise synchronous acquisition of blood oxygen detection signals.

[0022] This embodiment employs PPG technology. By optimizing the peripheral system architecture of the PPG chip and reusing its front-end simulation functions, it is applied to brain tissue blood oxygenation detection. While its optical detection path depth differs from the fNIRS system, it significantly reduces system complexity while achieving multi-point synchronous acquisition based on a synchronous drive mechanism. Simultaneously, based on the modulation light emission and acquisition mechanism of the wireless MCU, PPG chip, and optical detection units, it ensures that optical detection units closer to the modulation light emission source can acquire reflected light signals for noise reference, while optical detection units farther from the modulation light emission source can acquire accurate reflected light signals. This results in a final blood oxygenation detection signal that combines low noise and accuracy.

[0023] As attached Figure 1 The diagram illustrates the overall signal interaction process of this system, where the wireless MCU, PPG chip, and optical detection unit work together to achieve efficient management and precise control of multiple sensor nodes. The wireless MCU sends configuration signals to the PPG chip and receives blood oxygen detection signals via the I2C bus. The PPG chip generates a drive current based on the configuration signal and processes the reflected light signal. INT is an interrupt signal generated by the PPG chip, used to indicate the completion of a complete data acquisition cycle or an abnormal status indication. RST is a reset signal from the wireless MCU to the PPG chip, used to restore the PPG chip to its default operating state during system initialization or communication failures, both ensuring the stability and reliability of system operation. LED indicates that the PPG chip drives the optical detection unit to emit modulated light with the drive current, and PD indicates the reflected light signal returned by the optical detection unit to the PPG chip. Sensor nodes maintain time synchronization through a global trigger signal sync, ensuring consistency of multi-channel data acquisition. Furthermore, the wireless MCU communicates wirelessly with other nodes or the central control unit via an antenna, making it suitable for applications requiring high precision and multi-point monitoring.

[0024] To improve the accuracy of blood oxygenation detection signals for different brain regions, in some embodiments, sensor nodes can be flexibly configured according to the actual wearing shape and brain region monitoring needs. When the flexible blood oxygenation detection cap-shaped device is worn on the head and fits snugly against the head, multiple sensor nodes can be distributed in different areas of the head, such as near key brain functional areas like the forehead, top of the head, temporal region, or occipital region. The optical detection unit of each node is adapted to the wearing surface via a flexible circuit board, allowing it to fit snugly against the skin and adapt to changes in the curvature of the head. Specifically, sensor nodes can be arranged in several matrix configurations: Regular matrix array: nodes are evenly distributed in rows and columns, suitable for universal detection cap designs for standard head shapes; Circular matrix distribution: arranged in a ring around the forehead or top of the head, enhancing coverage density for specific brain regions (such as the prefrontal cortex); Non-uniform adaptive arrangement: based on the importance of brain regions and the characteristics of light propagation, node density is increased in key areas and the number of nodes is reduced in non-key areas, achieving focused monitoring and resource optimization; Differentiated tilt angle arrangement: the optical detection units in each node have different emission and reception angles to adapt to the curvature of the head and improve the consistency of near-infrared light penetration depth and signal quality. These diverse matrix arrangements not only improve the system's adaptability and comfort but also enhance the comprehensiveness and accuracy of blood oxygenation signal acquisition from different brain regions, providing a solid hardware foundation for multi-channel brain function research.

[0025] To achieve centralized control and data processing of the multi-node system and improve system configuration flexibility and synchronous acquisition accuracy, a Hub is included in the preferred embodiment. By introducing the Hub as the system control and data processing center, unified management and efficient scheduling of multiple sensor nodes are achieved, enhancing the system's integration and intelligence. The Hub is used to issue node configuration commands and process blood oxygen detection signals. Its command issuance and signal processing capabilities help improve system response speed and data processing efficiency, providing support for real-time monitoring and analysis. The wireless MCU can configure the corresponding PPG chip based on the node configuration commands and designate the corresponding sensor node as a master or slave sensor node. The flexible configuration of PPG chips and the assignment of master and slave roles through the wireless MCU give the system stronger programmability and task allocation capabilities, adapting to different monitoring needs. The PPG chip corresponding to the master sensor node is configured to generate drive current and output a global trigger signal to the hardware synchronization bus. This ensures that all PPG chips respond to the global trigger signal, synchronously driving the corresponding optical detection unit to collect the reflected light signal of the modulated light. The master sensor node uniformly outputs the global trigger signal, ensuring strict synchronization of all slave sensor nodes in time, effectively improving the consistency and signal-to-noise ratio of multi-channel data acquisition. The reflected light signal collected by the optical detection unit corresponding to the master sensor node is a shallow reflected light signal. This is because, according to the banana path theory of light reflection, the distance between the photodiode and the LED light source of the master sensor node is relatively short. Therefore, the signal collected by the master sensor node mainly comes from the reflected light from the superficial layer of the scalp, rather than the ideal deep brain tissue signal. Although the signal collected by the master sensor node is not suitable as a direct basis for blood oxygen calculation, it can be used as a reference signal for noise cancellation and environmental interference correction. Similarly, the reflected light signal collected by the optical detection unit corresponding to the slave sensor node is a deep reflected light signal. Because it is adjacent to or further from the modulation light emission position, the collected signal is a reflected light signal after absorption, scattering, or transmission by brain tissue, resulting in lower noise interference. Therefore, combining the reflected light signals collected by the main sensor node and the slave sensor node enables differential blood oxygenation analysis in the subsequent process, which significantly improves the accuracy of cerebral blood oxygenation detection.

[0026] As attached Figure 2The system's operational sequence is demonstrated. The Hub is responsible for issuing node configuration commands to the master and slave sensor nodes. After node configuration is complete, the optical detection subsystem emits modulated light and outputs a global trigger signal (SYNC). Based on the SYNC signal, the master sensor node collects shallow reflected light signals, while the slave sensor nodes collect deep reflected light signals, and upload the corresponding blood oxygen detection signals to the Hub. The Hub aligns these signals and processes them into blood oxygen detection data. Within a time window, the Hub polls all sensor nodes to act as the master sensor node and repeats the above process, ensuring that each node completes data acquisition within the time window. The time window can be set according to actual working needs, such as 1 second, to improve the system's signal acquisition and analysis efficiency or adapt to other application scenarios. Throughout the process, the nodes communicate wirelessly via Bluetooth and are powered by button batteries, minimizing size and achieving efficient data acquisition and transmission.

[0027] To improve the accuracy and depth of brain oxygenation detection, in a further preferred embodiment, the Hub also includes a signal processing unit to enhance the system's ability to fuse and process multi-channel oxygenation signals, thereby improving the overall system's data intelligence level. The signal processing unit generates oxygenation detection data based on the corresponding shallow and deep reflected light signals. Joint analysis of the shallow and deep signals effectively eliminates surface interference factors, improving the measurement accuracy and reliability of changes in brain tissue oxygenation concentration.

[0028] To expand practical application scenarios, in some embodiments, the Hub can be selected from various smart terminal devices with data processing and communication capabilities, such as wearable computing devices, edge computing gateways, cloud servers, or medical-specific control consoles. In other embodiments, depending on the needs of different application scenarios, the Hub can flexibly choose between local processing mode or cloud collaborative processing mode to achieve real-time analysis, long-term trend tracking, and remote health monitoring of blood oxygen detection data.

[0029] To achieve dynamic role allocation and spatial perception optimization of sensor nodes, in a further preferred embodiment, the sensor nodes also include a six-axis sensor. Introducing the six-axis sensor allows for real-time acquisition of spatial attitude information for each node, providing fundamental support for device wear status monitoring and node positioning. The six-axis sensor collects the spatial position information of the corresponding sensor node. This spatial position information helps construct a three-dimensional distribution model of the nodes on the head, improving the spatial resolution and interpretability of the data acquisition. The wireless MCU can also generate positioning signals based on the spatial position information. By processing the six-axis data to generate positioning signals, the wireless MCU achieves automatic identification and mapping of node positions, improving the system's intelligence and user interaction experience. The Hub is used to issue node configuration instructions for no fewer than the number of sensor nodes within each time window based on the positioning signals. This ensures that each sensor node is designated as the primary sensor node at least once within each time window. By rotating the primary sensor node, all nodes have the opportunity to participate in global synchronization triggering as primary sensor nodes, avoiding performance bottlenecks and signal deviations caused by a single primary sensor node. Furthermore, polling the primary sensor node allows for more comprehensive and accurate blood oxygenation detection signals to be collected for different brain regions. The node configuration instructions include specifying the master sensor node number and coding frequency. After receiving the master sensor node number, each sensor node matches it with itself. If the match is successful, it is designated as the master sensor node; if the match fails, the instruction is discarded. This gives the system a flexible time coding and synchronization control mechanism, further enhancing the stability and accuracy of multi-node collaborative work.

[0030] To enhance the system's communication stability and applicability, in another preferred embodiment, the wireless MCU employs Bluetooth or WAN as the communication protocol. This facilitates low-power, long-distance, or high-bandwidth data transmission between sensor nodes and the hub, adapting to communication needs across various application scenarios. In other embodiments, the wireless MCU may also employ communication protocols such as ZigBee, Wi-Fi, LoRa, or 5G to further expand the system's applicability and performance. For example, ZigBee is suitable for low-power, self-organizing network scenarios and provides stable communication under large-scale node deployments; Wi-Fi offers higher data transmission rates to meet the real-time uploading requirements of high-precision blood oxygen signals; LoRa has long-distance transmission capabilities, making it suitable for outdoor or mobile monitoring scenarios; and 5G offers significant advantages in high speed and low latency, making it suitable for clinical or research applications with high real-time requirements. By supporting multiple communication protocols, the system can flexibly switch according to the actual usage environment, improving overall communication stability, coverage, and adaptability.

[0031] To facilitate the miniaturization and ease of wearing of the device, in another preferred embodiment, the button battery is used as the antenna of the wireless MCU by utilizing the structural characteristics of the button battery. This not only saves space and improves system integration, but also enhances the overall portability and wearing comfort of the device, making it suitable for flexible wearable brain monitoring systems.

[0032] To improve the stability and controllability of the light source driving, in another preferred embodiment, the PPG chip includes a DAC module and a constant current driving circuit. By incorporating the DAC module and constant current driving circuit, precise control of the LED light source is achieved, ensuring the consistency and repeatability of the emitted light intensity, thereby improving detection accuracy. The DAC module generates a driving voltage signal, converting digital control commands into analog voltage signals, providing a basis for subsequent constant current driving and enhancing the flexibility and resolution of light source control. The constant current driving circuit converts the driving voltage signal into a driving current to drive the corresponding optical detection unit to emit modulated light towards the detection position. The constant current driving circuit ensures that the light source operates in a constant current state, avoiding light intensity changes caused by power supply fluctuations.

[0033] To improve the sensitivity and accuracy of signal acquisition, in another preferred embodiment, the PPG chip also includes a low-noise amplifier and an ADC circuit. Integrating the low-noise amplifier and ADC circuit gives the PPG chip complete analog front-end processing capabilities, effectively improving the acquisition quality of weak physiological signals. The low-noise amplifier is used to amplify the reflected light signal, amplifying the weak reflected light signal with minimal noise introduction, significantly improving the signal-to-noise ratio and laying a good foundation for subsequent analog-to-digital conversion. The ADC circuit is used to perform digital signal conversion on the amplified reflected light signal to generate a blood oxygen detection signal. The ADC circuit converts the analog signal into a digital signal, facilitating subsequent data processing and analysis by the wireless MCU, while also improving anti-interference capability and data transmission stability.

[0034] To achieve effective detection of blood oxygen-related spectral parameters, in another preferred embodiment, the optical detection unit includes an LED light source and a photodiode. This combination of LEDs and photodiodes offers advantages such as fast response, long lifespan, and low cost, making it suitable for large-scale deployment and long-term continuous monitoring applications. The LED light source emits modulated light to the detection location based on the driving current. The modulation light emission method helps distinguish ambient light interference, improving the detection system's anti-interference capability and measurement accuracy. The photodiode collects the reflected light signal from the modulated light. With high sensitivity and fast response characteristics, the photodiode is suitable for efficient acquisition of reflected light signals and is a key component for achieving high-quality blood oxygen detection. In other embodiments, to further improve the accuracy and adaptability of blood oxygen detection, the number of LEDs and photodiodes in the optical detection unit can be expanded according to actual needs. For example, each node can be configured with multiple LEDs, emitting light of different wavelengths to achieve differentiated measurement of oxyhemoglobin and deoxyhemoglobin; simultaneously, multiple photodiodes are equipped to receive reflected light signals from different angles or distances, enhancing adaptability to changes in the light path. In addition, some embodiments may employ an array-type photodiode structure to improve the stability and signal-to-noise ratio of signal acquisition, thereby enabling more accurate blood oxygen saturation calculation and tissue state analysis under complex physiological conditions.

[0035] As attached Figure 3 The diagram illustrates the system architecture in several other embodiments. The Bluetooth MCU communicates bidirectionally with the PPG chip via an I2C bus, sending configuration signals and receiving blood oxygen detection signals. The I2C bus includes SCL (clock line) and SDA (data line) for transmitting control commands and data. Furthermore, the Bluetooth MCU receives an interrupt signal INT from the PPG chip via an interrupt interface and sends configuration information and a reset signal RST to the PPG chip via a reset interface to reinitialize the device. The PPG chip generates a drive current to control the LED light source to emit modulated light through the LED interface; each node uses six LEDs (LED x 6). Simultaneously, photodiodes (PDs) convert the received reflected light into electrical signals and transmit them to the PPG chip for processing via the PD interface; each node is equipped with four photodiodes (PD x 4). Nodes A and B, as well as Nodes C and D, maintain time synchronization via a global trigger signal sync, ensuring that each node performs the same operation within the same time window, improving the consistency and accuracy of data acquisition.

[0036] To match the absorption peaks of hemoglobin and deoxyhemoglobin and improve detection accuracy, in a further preferred embodiment, the LED light source includes a first LED light source with a wavelength of 735nm to 750nm and a second LED light source with a wavelength of 850nm. These two wavelength ranges precisely correspond to the main absorption peaks of oxyhemoglobin and deoxyhemoglobin in the near-infrared region, respectively, enabling highly sensitive differential spectroscopy detection. Other wavelengths, due to strong tissue absorption and scattering interference or the indistinct absorption characteristics of hemoglobin, are difficult to accurately reflect changes in blood oxygen saturation. Therefore, selecting the aforementioned two wavelengths of LED light sources enables differential blood oxygen concentration calculation, improving the scientific rigor and accuracy of the detection results.

[0037] It should be understood that the embodiments are for illustrative purposes only and are not intended to limit the scope of the invention. Furthermore, it should be understood that after reading the teachings of this invention, those skilled in the art can make various alterations or modifications to the invention, and these equivalent forms also fall within the scope defined by the appended claims.

Claims

1. A brain blood oxygen detection sensing system, characterized in that, This includes sensor nodes arranged in a matrix; The sensor node includes a wireless MCU, a PPG chip, and an optical detection unit; The wireless MCU can be configured with a corresponding PPG chip; Any of the PPG chips is configured to generate a drive current to drive the corresponding optical detection unit to emit modulated light toward the position to be detected; and The PPG chips can all be connected to the hardware synchronization bus and respond to the global trigger signal in the hardware synchronization bus to synchronously drive the corresponding optical detection unit to collect the reflected light signal of the modulated light and generate a blood oxygen detection signal based on the reflected light signal. The blood oxygen detection signal is transmitted to the corresponding wireless MCU via the PPG chip.

2. The brain blood oxygenation detection and sensing system according to claim 1, characterized in that, Also includes Hub; The Hub is used to issue node configuration commands and process the blood oxygen detection signal. The wireless MCU can configure the corresponding PPG chip based on the node configuration instructions, and designate the corresponding sensor node as a master sensor node or a slave sensor node. The PPG chip corresponding to the main sensor node is configured to generate the driving current and is also configured to output the global trigger signal to the hardware synchronization bus, so that all PPG chips respond to the global trigger signal to synchronously drive the corresponding optical detection unit to collect the reflected light signal of the modulated light. The reflected light signal collected by the optical detection unit corresponding to the main sensor node is a shallow reflected light signal; the reflected light signal collected by the optical detection unit corresponding to the slave sensor node is a deep reflected light signal.

3. The brain blood oxygenation detection and sensing system according to claim 2, characterized in that, The Hub also includes a signal processing unit; The signal processing unit is used to generate blood oxygen detection data based on the blood oxygen detection signal generated by the correspondence between the shallow reflected light signal and the deep reflected light signal.

4. The brain blood oxygenation detection sensing system according to claim 2, characterized in that, The sensor node also includes a six-axis sensor; The six-axis sensor is used to collect spatial position information of the corresponding sensor nodes; The wireless MCU can also generate a positioning signal based on the spatial location information; The Hub is used to issue no less than the number of sensor nodes in each time window based on the positioning signal, so that each sensor node is designated as the master sensor node at least once in each time window; The node configuration instructions include specifying the main sensor node number and the coding frequency.

5. The brain blood oxygenation detection and sensing system according to claim 1, characterized in that, The wireless MCU uses Bluetooth or WAN as its communication protocol.

6. The brain blood oxygenation detection sensing system according to claim 1, characterized in that, The antenna of the wireless MCU is a button battery.

7. The brain blood oxygenation detection sensing system according to claim 1, characterized in that, The PPG chip includes a DAC module and a constant current drive circuit. The DAC module is used to generate drive voltage signals; The constant current driving circuit is used to convert the driving voltage signal into the driving current, so as to drive the corresponding optical detection unit to emit the modulated light to the position to be detected.

8. The brain oxygenation detection sensing system according to claim 1, characterized in that, The PPG chip also includes a low-noise amplifier and an ADC circuit. The low-noise amplifier is used to amplify the gain of the reflected light signal; The ADC circuit is used to perform digital signal conversion on the amplified reflected light signal to generate the blood oxygen detection signal.

9. The brain blood oxygenation detection sensing system according to claims 1 to 8, characterized in that, The optical detection unit includes an LED light source and a photodiode; The LED light source is used to emit modulated light toward the position to be detected based on the driving current; The photodiode is used to collect the reflected light signal of the modulated light.

10. The brain oxygenation detection sensing system according to claim 9, characterized in that, The LED light source includes a first LED light source with a wavelength of 735nm to 750nm and a second LED light source with a wavelength of 850nm.

Images