Optical fiber synchronous UWB positioning micro-fluidic biological detection equipment traceability method

Abstract

The invention discloses an optical fiber synchronous UWB (Ultra Wideband) positioning microfluidic biological detection equipment traceability method, which comprises the following steps: deploying an optical fiber synchronous UWB positioning anchor point array, and uniformly accessing local clock signals of UWB positioning anchor points into a master control clock module through a single-mode optical fiber to realize nanosecond time synchronization; a UWB tag module, a Beidou / GNSS receiving module and an MEMS inertial measurement unit are integrated on a micro-fluidic PCR equipment shell, and a multi-scale positioning terminal is constructed; based on an adaptive weighted fusion algorithm, performing real-time fusion on the UWB ranging data, the Beidou positioning coordinates and the angular velocity and acceleration output by the MEMS inertial measurement unit to generate current space coordinates of the equipment; the invention aims to solve the problems of insufficient positioning precision, discontinuous multi-source positioning switching and weak space-time coupling of biological detection and position information of microfluidic biological detection equipment in a complex environment or a mobile scene in the prior art.

Description

Technical Field

[0001] This invention relates to the field of biosensing and precision positioning fusion technology, specifically to a traceability method for microfluidic biosensing devices with fiber optic synchronous UWB positioning. Background Technology

[0002] In the field of biodetection and traceability, microfluidic technology has been widely applied in pathogen detection, gene analysis, and other scenarios due to its advantages such as low sample consumption, fast reaction speed, and high integration. Among them, microfluidic biodetection devices based on polymerase chain reaction (PCR) can achieve rapid amplification and quantitative analysis of trace amounts of nucleic acid samples, which has important value in epidemic monitoring, food safety, and clinical diagnosis. However, to ensure the traceability of test results, the spatial location information of the detection device needs to be accurately recorded. Especially in multi-point sampling, mobile detection, or complex environments, the positioning accuracy directly affects the reliability of traceability.

[0003] Currently, ultra-wideband (UWB) positioning technology, with its centimeter-level ranging capability and strong resistance to multipath interference, has been applied in indoor positioning scenarios. However, traditional UWB systems are susceptible to wireless signal synchronization errors when deployed at multiple anchor points, leading to decreased positioning stability. Some solutions attempt to introduce fiber optic links to improve synchronization accuracy, but they still lack specific designs for collaborative work with microfluidic detection equipment, making it difficult to meet the requirements for spatiotemporal information consistency in biological detection processes. Furthermore, existing positioning terminals mostly rely on single technologies, resulting in insufficient positioning continuity in outdoor or signal-blocked environments. While multi-source positioning methods integrating BeiDou navigation, inertial sensors, and UWB have been explored, there is still room for optimization in terms of portability, adaptive switching, and dynamic correction mechanisms.

[0004] Meanwhile, although microfluidic PCR devices have made progress in integration and automation, research on the organic combination of quantitative fluorescence detection and high-precision positioning is still insufficient, limiting their application efficiency in end-to-end traceability systems. Therefore, there is an urgent need for a technical solution that integrates high-precision synchronous positioning and efficient biological detection capabilities to support the reliable traceability requirements of microfluidic biological detection devices in complex scenarios. Summary of the Invention

[0005] This invention provides a method for tracing the source of microfluidic biological detection devices using fiber optic synchronous UWB positioning. The purpose is to solve the problems of insufficient positioning accuracy, discontinuous switching of multi-source positioning, and weak spatiotemporal coupling between biological detection and location information in existing technologies under complex environments or mobile scenarios.

[0006] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows:

[0007] A method for tracing microfluidic biological detection equipment using fiber-optic synchronized UWB positioning includes: deploying a fiber-optic synchronized UWB positioning anchor array; unifying the local clock signals of each UWB positioning anchor point into a main control clock module via single-mode fiber to achieve nanosecond-level time synchronization; integrating a UWB tag module, a BeiDou / GNSS receiver module, and a MEMS inertial measurement unit onto the shell of the microfluidic PCR equipment to construct a multi-scale positioning terminal; based on an adaptive weighted fusion algorithm, fusing UWB ranging data, BeiDou positioning coordinates, and the angular velocity and acceleration output by the MEMS inertial measurement unit in real time to generate the current spatial coordinates of the equipment; and embedding a fluorescence excitation and acquisition optical path within the microfluidic chip to synchronously record PC data. The timestamp sequence of the R amplification curve and positioning coordinates; based on the timestamp alignment mechanism, the three-dimensional coordinates corresponding to the fluorescence signal acquisition time of each round are written into the detection log; when the UWB signal is lost or the Beidou signal is blocked, the inertial calculation mode is activated, and the position drift is dynamically corrected according to the preset motion model; after the detection is completed, the complete spatiotemporal trajectory and biological amplification data are extracted from the log to construct a sample-position-time triplet traceability record; for trajectory anomalies, the sliding window covariance analysis method is used to identify positioning jumps. If the covariance exceeds the threshold, historical trajectory backtracking and inertial data re-integration are triggered to generate a corrected trajectory sequence; the corrected trajectory is bound to the original biological data to form a verifiable traceability certificate.

[0008] In one aspect of the invention, the UWB positioning anchor array with fiber optic synchronization connects the local clock signals of each UWB positioning anchor point to the main control clock module via single-mode fiber to achieve nanosecond-level time synchronization, including:

[0009] Five UWB positioning anchor points are fixedly installed at the four corners and the center of the target area. Each UWB positioning anchor point has a built-in temperature-compensated crystal oscillator and photoelectric conversion module.

[0010] Each UWB positioning anchor point is connected to the central master clock module via single-mode fiber in a star topology. The master clock module outputs a 10MHz reference clock and PPS signal, which are distributed to each UWB positioning anchor point via fiber optic splitter.

[0011] After receiving the optical signal, each UWB positioning anchor point converts it into an electrical signal through a photodetector, which drives the local phase-locked loop circuit to lock to the main control clock frequency, so as to achieve a network-wide clock phase error of less than ±2ns.

[0012] A timestamp calibration register is set inside each UWB positioning anchor point. A synchronization verification frame sent by the main control clock module is received every 500ms. If the time difference between the local counter and the verification frame exceeds 3ns, the local clock fine-tuning is triggered.

[0013] After calibration, each UWB positioning anchor point transmits UWB ranging pulses based on the synchronization clock, receives response signals from the UWB tag module, and calculates the two-way flight time.

[0014] Multiply the flight time by the speed of light and divide by 2 to obtain the distance values ​​from the device to each UWB positioning anchor point, and then upload them to the edge computing node;

[0015] Edge computing nodes calculate the device's 3D coordinates using the least squares method, with an output frequency of 20Hz and a coordinate update delay of no more than 50ms.

[0016] In one aspect of the invention, the integration of a UWB tag module, a BeiDou / GNSS receiver module, and a MEMS inertial measurement unit onto the casing of a microfluidic PCR device to construct a multi-scale positioning terminal includes:

[0017] A PCB mounting slot is reserved on the top of the microfluidic PCR device housing to weld the UWB tag module, Beidou / GNSS receiver module and MEMS inertial measurement unit onto the same flexible circuit board.

[0018] The UWB tag module connects to the main control MCU via the SPI interface, the Beidou / GNSS receiver module outputs NMEA-0183 format data via UART, and the MEMS inertial measurement unit transmits raw acceleration and angular velocity data via the I²C bus.

[0019] The flexible circuit board is bonded to the inside of the top cover of the microfluidic PCR device using conductive adhesive and then encapsulated with epoxy resin for fixation.

[0020] The UWB antenna adopts a planar inverted-F structure, which is printed on the outer surface of the microfluidic PCR device housing and connected to the UWB tag module via a 50Ω microstrip line.

[0021] The Beidou antenna is a ceramic patch type, installed at the top center of the microfluidic PCR device housing, with no metal obstruction above it. The power supply point is led to the Beidou / GNSS receiving module via a coaxial cable.

[0022] The MEMS inertial measurement unit is installed in the same direction as the equipment coordinate system, with the X-axis pointing in the direction of equipment movement and the Z-axis pointing vertically upward. The installation error angle is controlled within ±1°.

[0023] All modules share the same power management unit, which is powered by a lithium battery with a stable voltage of 3.3V±0.1V.

[0024] In one aspect of the invention, the method of real-time fusion of UWB ranging data, BeiDou positioning coordinates, and angular velocity and acceleration output by the MEMS inertial measurement unit based on an adaptive weighted fusion algorithm to generate the current spatial coordinates of the device includes:

[0025] A Kalman filter is run in the main control MCU, and the state vector includes position, velocity, attitude angle and sensor bias terms;

[0026] When the number of effective UWB anchor points is ≥4 and BeiDou HDOP is ≤2.0, the ENU coordinates after UWB calculation and BeiDou latitude and longitude conversion are used as the observation input, with weights set to 0.6 and 0.4 respectively.

[0027] When the effective UWB anchor points are less than 4 but the BeiDou signal is normal, only the BeiDou coordinates are used as the observation, with a weight of 1.0. At the same time, the output of the MEMS inertial measurement unit is used for the prediction model.

[0028] When the BeiDou signal is lost and UWB is unavailable, switch to pure inertial calculation mode, use acceleration quadratic integration to calculate displacement, angular velocity integration to update attitude, and perform state prediction every 100ms.

[0029] At the mode switching boundary, a smooth transition factor is introduced, and the process noise covariance matrix is ​​dynamically adjusted according to the signal availability index.

[0030] After each filter update, the fused position coordinates are output along with a confidence score. Points with a score below 0.7 are marked as low reliability points.

[0031] Low-reliability points will not participate in subsequent biological data binding and will continue to be recorded after the next high-confidence coordinate is updated.

[0032] In one aspect of the invention, the embedding of a fluorescence excitation and acquisition optical path within a microfluidic chip to simultaneously record the timestamp sequence of PCR amplification curves and positioning coordinates includes:

[0033] A 470nm blue LED array is integrated below the microfluidic chip substrate as an excitation source, and a bandpass filter and a CMOS image sensor are set above it.

[0034] The CMOS image sensor acquires fluorescence intensity images at a frequency of one frame every 30 seconds, and a timestamp T_img is generated for each frame.

[0035] The main control MCU sends a synchronization request to the positioning module 10ms before each image acquisition is triggered to obtain the current fused coordinates and its timestamp T_loc;

[0036] If |T_img-T_loc|≤15ms, then bind the coordinate to the image; otherwise, discard the frame or interpolate the nearest valid coordinate.

[0037] After background subtraction and region integration, the fluorescence image generates a sequence of Ct values, with each Ct value associated with a three-dimensional coordinate.

[0038] All data is packaged in JSON format, including device ID, sample number, timestamp, coordinates, Ct value, and location confidence.

[0039] Data packets are uploaded to the cloud-based traceability platform in real time via Wi-Fi or 4G module, while the most recent 100 records are cached locally in Flash.

[0040] In one aspect of the invention, the step of activating the inertial calculation mode and dynamically correcting the position drift based on a preset motion model when the UWB signal is lost or the BeiDou signal is blocked includes:

[0041] In the stationary detection module, the triaxial acceleration amplitude output by the MEMS inertial measurement unit is continuously monitored. If the standard deviation of the triaxial acceleration is less than 0.05 m / s² for one consecutive second, it is determined to be in a stationary state.

[0042] Once stationary, the velocity is forcibly reduced to zero, and the current position is used as the zero-velocity correction point to reset the initial conditions for inertial calculation.

[0043] If the equipment is in uniform linear motion, the rate of change of heading is determined by the integral of angular velocity. If it is less than 0.5° / s, the uniform model is used to constrain the integral of acceleration.

[0044] During the turning or acceleration phase, a combined strategy of zero angular rate update and zero speed update is adopted, and the error state is reset every 2 seconds.

[0045] Position drift error is compensated by the curvature of the historical trajectory within the sliding window; the greater the curvature, the lower the inertial weight.

[0046] The corrected location sequence is aligned with the biological sampling time;

[0047] After the interruption is recovered, the inertial calculation endpoint will be smoothly stitched together with the new UWB or BeiDou coordinates.

[0048] In one aspect of the invention, after detection is completed, extracting complete spatiotemporal trajectories and biological amplification data from the log to construct a sample-location-time triplet source tracing record includes:

[0049] Download the complete detection log file from local storage or the cloud, and parse the timestamp, coordinates, Ct value and device status code of each record;

[0050] Reconstruct the equipment's motion trajectory in chronological order and remove coordinate points with a confidence level below 0.5;

[0051] Each valid Ct value is paired with its nearest high-confidence coordinates to form a quintuple of <sample ID, latitude and longitude, elevation, time, Ct value>.

[0052] Clustering of multiple test results at the same sampling point, if the spatial distance is less than 1 meter and the time interval is less than 5 minutes, they are merged into the same source tracing event;

[0053] Generate a standardized traceability report, including trajectory map, amplification curve, sampling point heat map and equipment operation log;

[0054] The report is encrypted with a digital signature, and the hash value is written to the blockchain's evidence storage node.

[0055] Authorized users can query the complete traceability chain using the sample ID.

[0056] In one aspect of the invention, for trajectory anomalies, a sliding window covariance analysis method is used to identify positioning jumps. If the covariance exceeds a threshold, historical trajectory backtracking and inertial data re-integration are triggered to generate a corrected trajectory sequence, including:

[0057] Set the sliding window length to 10 consecutive coordinate points, and calculate the covariance matrix of each dimension of the coordinates within the window;

[0058] If the covariance of any dimension is greater than 0.25m², or if the Euclidean distance between two adjacent points changes abruptly by more than 2 meters, it is marked as an outlier segment.

[0059] The starting point of the anomaly segment is traced back to the most recent stationary point or high-confidence UWB location point, which serves as the starting point of the reintegration.

[0060] Read the raw MEMS acceleration and angular velocity data from the starting point to the end of the abnormal segment, and re-execute the high-precision numerical integration;

[0061] Zero-velocity correction and terrain constraints are introduced during the integration process;

[0062] The original abnormal segment is replaced by the result of the multiple integration to generate a smooth and continuous corrected trajectory;

[0063] The corrected trajectory was realigned with the biological data, and the source tracing record was updated.

[0064] Compared with the prior art, the present invention has the following beneficial effects:

[0065] The fiber-optic synchronous UWB positioning-based traceability method for microfluidic biological detection equipment provided by this invention has significant and multiple beneficial effects: First, by employing a single-mode fiber star topology to achieve nanosecond-level time synchronization of each UWB anchor point, it effectively overcomes the clock drift and multipath interference problems in traditional wireless synchronization, ensuring that positioning accuracy remains stable at the centimeter level even in complex indoor environments, providing a reliable high-precision benchmark for spatial traceability of biological samples. Second, the multi-source positioning terminal design integrating UWB, BeiDou / GNSS, and MEMS inertial measurement achieves seamless switching and continuous positioning between indoor and outdoor environments. Even in the event of signal obstruction or loss, relying on inertial calculation and dynamic correction of the motion model, it can still maintain the physical rationality and temporal continuity of the trajectory, greatly enhancing the system's environmental adaptability and robustness in mobile detection scenarios. Third, through a strict timestamp alignment mechanism, it achieves microsecond-level synchronous binding of fluorescence signal acquisition and spatial coordinates, ensuring that each round of PCR amplification curve can be accurately associated with its three-dimensional position at the time of occurrence, solving the key problem of the disconnect between biological detection data and spatial information, and providing a spatiotemporally consistent data foundation for end-to-end traceability. Furthermore, the system possesses intelligent anomaly detection and trajectory correction capabilities. Based on sliding window covariance analysis, it identifies location jumps and triggers inertial data re-integration and historical trajectory backtracking, effectively suppressing trajectory abrupt changes caused by factors such as occlusion and interference, thus improving the reliability and consistency of traceability data. Finally, the entire method supports closed-loop management across the entire chain, from data acquisition, fusion processing, anomaly correction to voucher generation. Traceability records are digitally signed and stored on the blockchain, ensuring the immutability and verifiability of the data. This provides an efficient and reliable spatiotemporal traceability solution for scenarios such as public health monitoring and food safety tracking, demonstrating significant practical application value and promising prospects for wider adoption. Attached Figure Description

[0066] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained from these drawings without creative effort.

[0067] Figure 1 This is one of the flowcharts for a traceability method of a microfluidic biological detection device with fiber optic synchronous UWB positioning according to the present invention.

[0068] Figure 2 This is the second flowchart of a traceability method for a microfluidic biological detection device based on fiber optic synchronous UWB positioning according to the present invention.

[0069] Figure 3 This is the third flowchart of a traceability method for a microfluidic biological detection device based on fiber optic synchronous UWB positioning according to the present invention. Detailed Implementation

[0070] The present invention will be further described below with reference to embodiments. These embodiments are merely some, not all, of the embodiments of the present invention. Other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are all within the protection scope of the present invention.

[0071] Example 1

[0072] Please see Figures 1-3 As shown, this embodiment discloses a method for tracing microfluidic biological detection equipment using fiber-optic synchronized UWB positioning, including: deploying a fiber-optic synchronized UWB positioning anchor array; connecting the local clock signals of each UWB positioning anchor point to the main control clock module via single-mode fiber to achieve nanosecond-level time synchronization; integrating a UWB tag module, a BeiDou / GNSS receiver module, and a MEMS inertial measurement unit on the shell of the microfluidic PCR equipment to construct a multi-scale positioning terminal; based on an adaptive weighted fusion algorithm, fusing UWB ranging data, BeiDou positioning coordinates, and the angular velocity and acceleration output by the MEMS inertial measurement unit in real time to generate the current spatial coordinates of the equipment; embedding a fluorescence excitation and acquisition optical path within the microfluidic chip, and simultaneously... The system records the timestamp sequence of PCR amplification curves and positioning coordinates. Based on the timestamp alignment mechanism, the three-dimensional coordinates corresponding to each round of fluorescence signal acquisition are written into the detection log. When the UWB signal is lost or the BeiDou signal is blocked, the inertial calculation mode is activated, and the position drift is dynamically corrected according to the preset motion model. After the detection is completed, the complete spatiotemporal trajectory and biological amplification data are extracted from the log to construct a sample-location-time triplet traceability record. For trajectory anomalies, the sliding window covariance analysis method is used to identify positioning jumps. If the covariance exceeds the threshold, historical trajectory backtracking and inertial data re-integration are triggered to generate a corrected trajectory sequence. The corrected trajectory is bound to the original biological data to form a verifiable traceability certificate.

[0073] The fiber-optic synchronous UWB positioning-based traceability method for microfluidic biological detection equipment provided by this invention has significant and multiple beneficial effects: First, by employing a single-mode fiber star topology to achieve nanosecond-level time synchronization of each UWB anchor point, it effectively overcomes the clock drift and multipath interference problems in traditional wireless synchronization, ensuring that positioning accuracy remains stable at the centimeter level even in complex indoor environments, providing a reliable high-precision benchmark for spatial traceability of biological samples. Second, the multi-source positioning terminal design integrating UWB, BeiDou / GNSS, and MEMS inertial measurement achieves seamless switching and continuous positioning between indoor and outdoor environments. Even in the event of signal obstruction or loss, relying on inertial calculation and dynamic correction of the motion model, it can still maintain the physical rationality and temporal continuity of the trajectory, greatly enhancing the system's environmental adaptability and robustness in mobile detection scenarios. Third, through a strict timestamp alignment mechanism, it achieves microsecond-level synchronous binding of fluorescence signal acquisition and spatial coordinates, ensuring that each round of PCR amplification curve can be accurately associated with its three-dimensional position at the time of occurrence, solving the key problem of the disconnect between biological detection data and spatial information, and providing a spatiotemporally consistent data foundation for end-to-end traceability. Furthermore, the system possesses intelligent anomaly detection and trajectory correction capabilities. Based on sliding window covariance analysis, it identifies location jumps and triggers inertial data re-integration and historical trajectory backtracking, effectively suppressing trajectory abrupt changes caused by factors such as occlusion and interference, thus improving the reliability and consistency of traceability data. Finally, the entire method supports closed-loop management across the entire chain, from data acquisition, fusion processing, anomaly correction to voucher generation. Traceability records are digitally signed and stored on the blockchain, ensuring the immutability and verifiability of the data. This provides an efficient and reliable spatiotemporal traceability solution for scenarios such as public health monitoring and food safety tracking, demonstrating significant practical application value and promising prospects for wider adoption.

[0074] Example 2

[0075] This embodiment is a further optimization based on Embodiment 1. In this embodiment, a microfluidic biodetection device traceability system with fiber-optic synchronous UWB positioning is constructed. Its core lies in using a high-precision spatiotemporal synchronization mechanism to strictly align the biological signals during microfluidic PCR amplification with the three-dimensional spatial location of the device, thereby achieving verifiable and tamper-proof sample traceability capabilities. The following details the system from five aspects: hardware deployment, module integration, data fusion, trajectory correction, and traceability generation.

[0076] The microfluidic PCR device's outer shell serves as a monolithic support structure, injection molded from polycarbonate, with a pre-drilled PCB mounting slot on the top. Within this slot, the UWB tag module, BeiDou / GNSS receiver module, and MEMS inertial measurement unit are soldered onto the same flexible circuit board. The flexible circuit board, made of polyimide substrate with a thickness of 0.1mm, possesses excellent bending resistance to accommodate deformation during movement or vibration. The UWB tag module utilizes a Decawave DW3000 chip, communicating with the main control MCU via an SPI interface; the BeiDou / GNSS receiver module employs a Hexin Xingtong UM982 dual-frequency positioning chip, outputting NMEA-0183 format data via a UART interface; and the MEMS inertial measurement unit is an STMicroelectronics LSM6DSOX six-axis sensor, transmitting raw three-axis acceleration and three-axis angular velocity data to the main control MCU via an I²C bus. The flexible circuit board is bonded to the inside of the top cover of the microfluidic PCR device housing with conductive adhesive, and its surface is covered with a layer of epoxy resin for potting to prevent solder joints from breaking or components from falling off due to mechanical vibration during transportation or operation.

[0077] The UWB antenna adopts a planar inverted-F antenna (PIFA) structure, directly printed on the outer surface of the microfluidic PCR device housing, located directly above the flexible circuit board. It is connected to the UWB tag module via a microstrip line with a 50Ω characteristic impedance. The microstrip line width is calculated to be 1.8mm based on the dielectric constant of the FR-4 dielectric substrate to ensure impedance matching. The BeiDou antenna is a ceramic patch GNSS antenna, measuring 18mm × 18mm × 4mm, installed at the center of the top of the microfluidic PCR device housing, with no metal structure obstructing it. The feed point is led to the RF input port of the BeiDou / GNSS receiver module via an RG178 coaxial cable no longer than 30mm to reduce signal loss. The MEMS inertial measurement unit is installed in a direction strictly aligned with the device's coordinate system: the X-axis points in the direction of device movement (i.e., the direction of propulsion when held by the user), the Y-axis is horizontal, and the Z-axis is vertical. During installation, a laser calibrator is used to ensure that the axial error angle is controlled within ±1° to avoid introducing systematic deviations in attitude calculation. All electronic modules share a single power management unit, powered by a built-in 3.7V lithium polymer battery. The LDO regulator outputs a DC voltage of 3.3V±0.1V to provide a stable power supply for each sensor and ensure consistent sampling timing.

[0078] Five UWB positioning anchors are deployed within the target area, fixed at the four corners and geometric center of the area. Each anchor integrates a temperature-compensated crystal oscillator (TCXO), a photoelectric conversion module, and a UWB transceiver chip. Each UWB positioning anchor is connected to the central master clock module via a star topology using single-mode fiber. The master clock module outputs a 10MHz sine wave reference clock signal and a PPS (pulse per second) square wave signal, which are split into five optical signals by a fiber optic splitter and transmitted to each UWB positioning anchor via single-mode fiber. Inside each UWB positioning anchor, the optical signal is first converted into an electrical signal by a PIN photodetector, then shaped by a limiting amplifier before being input to a local phase-locked loop (PLL) circuit. This locks the local crystal oscillator frequency to the 10MHz reference source of the master clock module, achieving a network-wide clock phase error of less than ±2ns. In addition, each UWB positioning anchor point has a 32-bit timestamp calibration register. The main control clock module sends a synchronization verification frame containing absolute UTC time every 500ms. If the time difference between the local counter reading and the verification frame exceeds 3ns, the local crystal oscillator frequency is fine-tuned via digital control words to complete closed-loop calibration. After calibration, each UWB positioning anchor point periodically transmits UWB ranging pulses (center frequency 6.5GHz, bandwidth 500MHz) based on the synchronization clock, receives response signals from the UWB tag module on the microfluidic device, calculates the round-trip time of the signal based on the Two-Way Range (TWR) protocol, multiplies it by the speed of light, and divides by 2 to obtain the distance value from the device to each anchor point. This distance data is uploaded to the edge computing node via Gigabit Ethernet. The latter uses the least squares method to solve the device's three-dimensional coordinates, with an output frequency of 20Hz. The end-to-end delay from ranging completion to coordinate output does not exceed 50ms.

[0079] During operation, the main control MCU receives distance data from the UWB tag module, latitude and longitude and HDOP values ​​from the BeiDou / GNSS receiver module, and raw acceleration and angular velocity data from the MEMS inertial measurement unit in real time. The main control MCU internally runs an extended Kalman filter (EKF), whose state vector includes 15 dimensions: three-dimensional position, three-dimensional velocity, Euler angles (pitch, roll, yaw), accelerometer zero bias, and gyroscope zero bias. When the number of effective UWB positioning anchor points is ≥4 and the BeiDou HDOP is ≤2.0, the system uses the coordinates in the local coordinate system calculated by UWB and the results of the WGS-84 latitude and longitude output by BeiDou after ENU (East-North-Sky) coordinate transformation as observation inputs, assigning a weight of 0.6 to UWB observations and 0.4 to BeiDou observations. When there are fewer than 4 effective UWB anchor points but the BeiDou signal is normal, only BeiDou coordinates are used as observations, with a weight of 1.0, and MEMS data is used for the state prediction model. When neither is available, the system switches to a pure inertial calculation mode, using the second integral of acceleration to calculate the displacement increment and the integral of angular velocity to update the attitude angle, performing a state prediction every 100ms. At the mode switching boundary, the system calculates the signal availability index based on the UWB signal strength (RSSI) and BeiDou signal-to-noise ratio (SNR), and dynamically adjusts the process noise covariance matrix Q accordingly, introducing a smooth transition factor to avoid state jumps. After each filter update, the fused coordinates are output and a confidence score is calculated. If the score is below 0.7, the coordinates are marked as low reliability points and will not be included in subsequent biological data binding.

[0080] The microfluidic chip integrates a fluorescence excitation and acquisition optical path: a 470nm blue LED array is arranged below the substrate as the excitation source, and a bandpass filter with a center wavelength of 520nm and a bandwidth of 40nm and a 1 / 4-inch CMOS image sensor are arranged above it. The CMOS image sensor triggers the acquisition of a fluorescence image frame every 30 seconds, generating a timestamp T_img accurate to the microsecond level for each frame. 10ms before each image acquisition trigger, the main control MCU sends a synchronization request to the positioning module to obtain the current fused positioning coordinates and their corresponding timestamp T_loc. The timestamp alignment module determines whether |T_img-T_loc| is ≤15ms. If so, the coordinate is bound to the image; otherwise, the frame is discarded or the intermediate position is estimated from the two valid coordinates using linear interpolation. After background subtraction, region integration, and threshold segmentation, the fluorescence image generates a sequence of Ct values, with each Ct value associated with a three-dimensional coordinate. All data is packaged in JSON format, with fields including device ID, sample number, timestamp, coordinates (x, y, z), Ct value and location confidence. It is uploaded to the cloud traceability platform in real time via Wi-Fi or 4G module, while the most recent 100 records are cached in local Flash.

[0081] When the UWB signal is lost or the BeiDou signal is blocked by buildings, the system automatically activates the inertial estimation mode. At this time, the stationary detection module continuously monitors the three-axis acceleration data output by the MEMS inertial measurement unit. If the standard deviation of acceleration for each axis is less than 0.05 m / s² for one consecutive second, the device is determined to be stationary, its velocity is forcibly zeroed, and the current position is set as the Zero Velocity Correction Point (ZUPT), resetting the initial conditions for inertial estimation. If the device is in uniform linear motion, the system calculates the rate of change of heading through angular velocity integration. If it is less than 0.5° / s, the uniform motion model constrains the acceleration integration process. During turning or acceleration phases, the system executes a combined strategy of Zero Angular Rate Update (ZARU) and Zero Velocity Update (ZUPT) every 2 seconds to reset the error state. Furthermore, position drift errors are dynamically compensated for using the curvature of the historical trajectory within a sliding window: the radius of curvature of the trajectory over the last 5 seconds is calculated; if the radius of curvature is less than 2 meters, the weight of inertial estimation is reduced, increasing the reliance on historical trajectory trends. The corrected location sequence is strictly aligned with the biological sampling time, ensuring traceability of sample locations even during signal interruptions lasting up to 30 seconds. Upon resumption of the interruption, the system performs cubic spline interpolation to stitch the inertial calculation endpoint with the newly acquired UWB or BeiDou coordinates, generating a continuous and smooth trajectory and avoiding abrupt changes.

[0082] After detection, the system downloads the complete detection log from local storage or the cloud, parsing the timestamp, coordinates, Ct value, and device status code of each record. The system reconstructs the device's movement trajectory in chronological order, removing coordinate points with a confidence level below 0.5. The timestamp alignment module pairs each valid Ct value with its nearest high-confidence coordinate in time, forming a quintuple of <sample ID, longitude, latitude, elevation, time, Ct value>. For multiple detections of the same sampling point, if the spatial distance is less than 1 meter and the time interval is less than 5 minutes, they are considered the same traceability event and the data is clustered and merged. Finally, a standardized traceability report is generated, including a trajectory map, amplification curve, sampling point heatmap, and device operation log. The report is digitally signed using the SM2 national cryptographic algorithm, and its SHA-256 hash value is written to the Hyperledger Fabric blockchain storage node to ensure data immutability. Authorized users can query the complete traceability chain on the traceability platform using the sample ID.

[0083] For trajectory anomalies, the system initiates a sliding window covariance analysis unit. The window length is set to 10 consecutive coordinate points (corresponding to 500ms of data), and the covariance matrix of the x, y, and z coordinates within the window is calculated. If the covariance of any dimension is greater than 0.25m², or if the abrupt change in Euclidean distance between two adjacent points exceeds 2 meters, the segment is marked as an anomalous trajectory. Subsequently, the system traces back from the starting point of the anomalous segment to find the nearest stationary point (marked by ZUPT) or a high-confidence UWB positioning point (confidence ≥ 0.9), as the starting point for re-integration. The inertial data re-integration module reads the original MEMS acceleration and angular velocity data stored from this starting point to the end of the anomalous segment and re-executes high-precision numerical integration using the fourth-order Runge-Kutta method. During integration, if the device is in an indoor environment, a constant height constraint (z-coordinate remains unchanged); if it is outdoors, terrain correction is performed using a digital elevation model (DEM). Simultaneously, ZUPT correction points are inserted when a stationary segment is detected to suppress accumulated errors. After the reintegration is completed, the result replaces the original abnormal segment, generates the corrected trajectory, and is re-aligned with the original biological amplification data in time to update the source tracing record and ensure that the location information conforms to the laws of physical motion.

[0084] All the above steps constitute a complete closed-loop traceability process. From hardware deployment, multi-source positioning fusion, biological-location synchronous acquisition, trajectory anomaly correction to final certificate generation, each link has a clear technical implementation path and parameter configuration. Those skilled in the art can reproduce the technical solution of this invention based on this implementation method.

[0085] To enable those skilled in the art to fully understand and implement this invention, the specific implementation principles of this invention are further supplemented below with a specific application scenario.

[0086] When conducting mobile pathogen screening at the scene of a public health emergency, testing personnel carry the microfluidic biodetection device described in this invention into a multi-story office building to perform sample collection and real-time PCR amplification. In this scenario, indoor UWB signals are easily blocked by walls, outdoor BeiDou signals are frequently interrupted in corridors and elevators, and sampling points are distributed across different floors and rooms, placing stringent requirements on positioning continuity and spatial accuracy. Against this backdrop, the system operates and achieves highly reliable traceability according to the following steps:

[0087] First, during the deployment phase, staff installed five UWB positioning anchor points in the target area—specifically, the key passageway intersections and stairwells on the first to third floors of the office building. These anchor points were fixed to the four corner pillars and the ceiling at the center of each floor, and connected to the main control clock module located in the rooftop equipment room via single-mode fiber in a star topology. The main control clock module then distributed a 10MHz reference clock and PPS signal synchronously to each UWB positioning anchor point via a fiber optic splitter, ensuring that the local crystal oscillator phase error was controlled within ±2ns. This synchronization mechanism effectively eliminated the nanosecond-level delay jitter caused by multipath propagation in traditional wireless synchronization, resulting in stable distance measurement accuracy within ±5cm based on two-way time-of-flight (TWR), laying the foundation for centimeter-level indoor positioning.

[0088] Subsequently, the testing personnel activated the multi-source positioning terminal integrated within the microfluidic PCR device's casing. At this time, the UWB tag module periodically interacted with each UWB positioning anchor point for distance measurement, the BeiDou / GNSS receiver module continuously received satellite signals, and the MEMS inertial measurement unit output raw triaxial acceleration and angular velocity data at a frequency of 100Hz. When personnel entered the building's first-floor lobby from outdoors, the HDOP value of the BeiDou / GNSS receiver module rose to 3.5 due to attenuation caused by the glass curtain wall, and the system automatically reduced its observation weight. Simultaneously, all four UWB positioning anchor points were within line-of-sight. The main control MCU, according to preset rules, used the UWB calculated coordinates as the primary observation input, fused with the MEMS predicted state, and output the three-dimensional position in the ENU coordinate system, updating at a frequency of 20Hz. This process dynamically adjusted the process noise covariance matrix Q using an extended Kalman filter to avoid state jumps caused by sudden changes in BeiDou signal quality, thus ensuring a smooth trajectory transition.

[0089] As the inspectors ascended the elevator to the second floor, the UWB signal was completely lost due to shielding by the metal car, and the BeiDou signal was also blocked by the building structure. The system immediately switched to a pure inertial calculation mode. At this time, the MEMS inertial measurement unit continuously collected motion data. The stationary detection module detected an instantaneous peak in the three-axis acceleration during the elevator's start-up phase, determining it to be in a non-stationary state. During the elevator's uniform speed operation, the angular velocity integral showed a heading change rate below 0.3° / s. The system then used a uniform linear motion model to constrain the acceleration quadratic integration process and maintained a high inertial weight by combining the curvature of the historical trajectory within the sliding window (calculated to have a radius of curvature of approximately 15 meters). Upon reaching the second floor and opening the door, the acceleration standard deviation dropped to 0.03 m / s² within one second. The stationary detection module triggered a zero-velocity correction point (ZUPT), forcing the velocity to zero and locking the current position as the new initial point, effectively suppressing the height drift introduced by the elevator's vertical motion.

[0090] During sample testing in an office on the second floor, the microfluidic chip initiated the PCR amplification program. The CMOS image sensor generates a timestamp T_img at the moment of fluorescence image acquisition. The main control MCU calls the timestamp alignment module 10ms in advance to obtain the current fusion positioning coordinates and their timestamp T_loc. Since the UWB signal has recovered and HDOP=1.8 at this time, the confidence score of the fusion coordinates is 0.85, satisfying the binding condition |T_img-T_loc|≤15ms. Therefore, the coordinates are successfully associated with the corresponding Ct value. This strict time alignment mechanism relies on all sensors sharing the same regulated power supply (3.3V±0.1V) and the high-precision timer inside the main control MCU to ensure that biosignal acquisition and spatial positioning are synchronized on a microsecond-level timescale, solving the spatiotemporal misalignment problem caused by asynchronous sampling in traditional solutions.

[0091] During the detection process, if a person rapidly traverses the corridor, causing an anomaly in UWB ranging within a frame (e.g., a distance jump due to human occlusion), the coordinates output by the edge computing node may abruptly change. At this point, the sliding window covariance analysis unit calculates the covariance matrix of the most recent 10 coordinate points (500ms window) in real time. It finds that the covariance along the y-axis reaches 0.31m², exceeding the 0.25m² threshold, and thus marks this segment as an abnormal trajectory. The system immediately backtracks to the previous stationary point (marked by ZUPT), retrieves the original MEMS data stored in the inertial data re-integration module, re-integrates using the fourth-order Runge-Kutta method, and applies a constant indoor height constraint (z-coordinate remains unchanged). After replacing the original abnormal segment with the re-integration result, a corrected trajectory is generated and re-aligned with the original bio-amplification data to ensure that the spatial location of the sampling point conforms to the physical continuity of human walking.

[0092] After the testing task is completed, the system automatically uploads a 5-tuple containing <sample ID, longitude, latitude, elevation, time, Ct value> to the cloud. Simultaneously, the local cached logs are signed using the SM2 algorithm, and their SHA-256 hash values ​​are written to the Hyperledger Fabric blockchain. Authorized personnel from the CDC can retrieve the complete traceability chain using the sample ID to verify that the positive sample was indeed collected in the conference room on the east side of the second floor, and not in other floors or areas, thus supporting accurate epidemiological investigation decisions. The entire process relies on the high-precision spatiotemporal reference provided by the fiber-optic synchronous UWB anchor array, the multi-source sensor adaptive fusion mechanism, and the microsecond-level alignment strategy for bio-location data, achieving a strong consistency traceability capability of "where the sample was amplified and where it was amplified" in complex mobile scenarios.

[0093] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for tracing the origin of a microfluidic biological detection device using fiber-optic synchronous UWB positioning, characterized in that, include: A fiber-optic synchronized UWB positioning anchor array is deployed, and the local clock signals of each UWB positioning anchor are uniformly connected to the main control clock module through single-mode fiber to achieve nanosecond-level time synchronization. A multi-scale positioning terminal was constructed by integrating a UWB tag module, a BeiDou / GNSS receiver module, and a MEMS inertial measurement unit onto the shell of a microfluidic PCR device. Based on an adaptive weighted fusion algorithm, UWB ranging data, BeiDou positioning coordinates, and angular velocity and acceleration output by MEMS inertial measurement unit are fused in real time to generate the current spatial coordinates of the device. A fluorescence excitation and acquisition optical path is embedded in a microfluidic chip to simultaneously record the timestamp sequence of PCR amplification curve and positioning coordinates. Based on the timestamp alignment mechanism, the three-dimensional coordinates corresponding to the time of each round of fluorescence signal acquisition are written into the detection log; When the UWB signal is lost or the BeiDou signal is blocked, the inertial calculation mode is activated, and the position drift is dynamically corrected according to the preset motion model. After the detection is completed, the complete spatiotemporal trajectory and biological amplification data are extracted from the log to construct a sample-location-time triplet traceability record; For trajectory anomalies, a sliding window covariance analysis method is used to identify positioning jumps. If the covariance exceeds the threshold, historical trajectory backtracking and inertial data re-integration are triggered to generate a corrected trajectory sequence. The corrected trajectory is then linked to the original biological data to create a verifiable traceability credential.

2. The method for tracing the source of a microfluidic biological detection device using fiber optic synchronous UWB positioning according to claim 1, characterized in that: The UWB positioning anchor array with fiber optic synchronization uses single-mode fiber to connect the local clock signals of each UWB positioning anchor to the main control clock module, achieving nanosecond-level time synchronization, including: Five UWB positioning anchor points are fixedly installed at the four corners and the center of the target area. Each UWB positioning anchor point has a built-in temperature-compensated crystal oscillator and photoelectric conversion module. Each UWB positioning anchor point is connected to the central master clock module via single-mode fiber in a star topology. The master clock module outputs a 10MHz reference clock and PPS signal, which are distributed to each UWB positioning anchor point via fiber optic splitter. After receiving the optical signal, each UWB positioning anchor point converts it into an electrical signal through a photodetector, which drives the local phase-locked loop circuit to lock to the main control clock frequency, so as to achieve a network-wide clock phase error of less than ±2ns. A timestamp calibration register is set inside each UWB positioning anchor point. A synchronization verification frame sent by the main control clock module is received every 500ms. If the time difference between the local counter and the verification frame exceeds 3ns, the local clock fine-tuning is triggered. After calibration, each UWB positioning anchor point transmits UWB ranging pulses based on the synchronization clock, receives response signals from the UWB tag module, and calculates the two-way flight time. Multiply the flight time by the speed of light and divide by 2 to obtain the distance values ​​from the device to each UWB positioning anchor point, and then upload them to the edge computing node; Edge computing nodes calculate the device's 3D coordinates using the least squares method, with an output frequency of 20Hz and a coordinate update delay of no more than 50ms.

3. The method for tracing the source of a microfluidic biological detection device with fiber optic synchronous UWB positioning according to claim 1, characterized in that: The method of integrating a UWB tag module, a BeiDou / GNSS receiver module, and a MEMS inertial measurement unit onto the shell of a microfluidic PCR device to construct a multi-scale positioning terminal includes: A PCB mounting slot is reserved on the top of the microfluidic PCR device housing to weld the UWB tag module, Beidou / GNSS receiver module and MEMS inertial measurement unit onto the same flexible circuit board. The UWB tag module connects to the main control MCU via the SPI interface, the Beidou / GNSS receiver module outputs NMEA-0183 format data via UART, and the MEMS inertial measurement unit transmits raw acceleration and angular velocity data via the I²C bus. The flexible circuit board is bonded to the inside of the top cover of the microfluidic PCR device using conductive adhesive and then encapsulated with epoxy resin for fixation. The UWB antenna adopts a planar inverted-F structure, which is printed on the outer surface of the microfluidic PCR device housing and connected to the UWB tag module via a 50Ω microstrip line. The Beidou antenna is a ceramic patch type, installed at the top center of the microfluidic PCR device housing, with no metal obstruction above it. The power supply point is led to the Beidou / GNSS receiving module via a coaxial cable. The MEMS inertial measurement unit is installed in the same direction as the equipment coordinate system, with the X-axis pointing in the direction of equipment movement and the Z-axis pointing vertically upward. The installation error angle is controlled within ±1°. All modules share the same power management unit, which is powered by a lithium battery with a stable voltage of 3.3V±0.1V.

4. The method for tracing the origin of a microfluidic biological detection device using fiber-optic synchronous UWB positioning as described in claim 1, characterized in that: The adaptive weighted fusion algorithm is used to fuse UWB ranging data, BeiDou positioning coordinates, and angular velocity and acceleration output from the MEMS inertial measurement unit in real time to generate the device's current spatial coordinates, including: A Kalman filter is run in the main control MCU, and the state vector includes position, velocity, attitude angle and sensor bias terms; When the number of effective UWB anchor points is ≥4 and BeiDou HDOP is ≤2.0, the ENU coordinates after UWB calculation and BeiDou latitude and longitude conversion are used as the observation input, with weights set to 0.6 and 0.4 respectively. When the effective UWB anchor points are less than 4 but the BeiDou signal is normal, only the BeiDou coordinates are used as the observation, with a weight of 1.

0. At the same time, the output of the MEMS inertial measurement unit is used for the prediction model. When the BeiDou signal is lost and UWB is unavailable, switch to pure inertial calculation mode, use acceleration quadratic integration to calculate displacement, angular velocity integration to update attitude, and perform state prediction every 100ms. At the mode switching boundary, a smooth transition factor is introduced, and the process noise covariance matrix is ​​dynamically adjusted according to the signal availability index. After each filter update, the fused position coordinates are output along with a confidence score. Points with a score below 0.7 are marked as low reliability points. Low-reliability points will not participate in subsequent biological data binding and will continue to be recorded after the next high-confidence coordinate is updated.

5. The method for tracing the origin of a microfluidic biological detection device using fiber-optic synchronous UWB positioning as described in claim 1, characterized in that: The method of embedding a fluorescence excitation and acquisition optical path within a microfluidic chip to simultaneously record the timestamp sequence of PCR amplification curves and positioning coordinates includes: A 470nm blue LED array is integrated below the microfluidic chip substrate as an excitation source, and a bandpass filter and a CMOS image sensor are set above it. The CMOS image sensor acquires fluorescence intensity images at a frequency of one frame every 30 seconds, and a timestamp T_img is generated for each frame. The main control MCU sends a synchronization request to the positioning module 10ms before each image acquisition is triggered to obtain the current fused coordinates and its timestamp T_loc; If |T_img-T_loc|≤15ms, then bind the coordinate to the image; otherwise, discard the frame or interpolate the nearest valid coordinate. After background subtraction and region integration, the fluorescence image generates a sequence of Ct values, with each Ct value associated with a three-dimensional coordinate. All data is packaged in JSON format, including device ID, sample number, timestamp, coordinates, Ct value, and location confidence. Data packets are uploaded to the cloud-based traceability platform in real time via Wi-Fi or 4G module, while the most recent 100 records are cached locally in Flash.

6. The method for tracing the origin of a microfluidic biological detection device with fiber optic synchronous UWB positioning according to claim 1, characterized in that: When the UWB signal is lost or the BeiDou signal is blocked, the inertial calculation mode is activated, and the position drift is dynamically corrected according to the preset motion model, including: In the stationary detection module, the triaxial acceleration amplitude output by the MEMS inertial measurement unit is continuously monitored. If the standard deviation of the triaxial acceleration is less than 0.05 m / s² for one consecutive second, it is determined to be in a stationary state. Once stationary, the velocity is forcibly reduced to zero, and the current position is used as the zero-velocity correction point to reset the initial conditions for inertial calculation. If the equipment is in uniform linear motion, the rate of change of heading is determined by the integral of angular velocity. If it is less than 0.5° / s, the uniform model is used to constrain the integral of acceleration. During the turning or acceleration phase, a combined strategy of zero angular rate update and zero speed update is adopted, and the error state is reset every 2 seconds. Position drift error is compensated by the curvature of the historical trajectory within the sliding window; the greater the curvature, the lower the inertial weight. The corrected location sequence is aligned with the biological sampling time; After the interruption is recovered, the inertial calculation endpoint will be smoothly stitched together with the new UWB or BeiDou coordinates.

7. The method for tracing the origin of a microfluidic biological detection device using fiber-optic synchronous UWB positioning according to claim 1, characterized in that: After the detection is completed, the complete spatiotemporal trajectory and biological amplification data are extracted from the log to construct a sample-location-time triplet source tracing record, including: Download the complete detection log file from local storage or the cloud, and parse the timestamp, coordinates, Ct value and device status code of each record; Reconstruct the equipment's motion trajectory in chronological order and remove coordinate points with a confidence level below 0.5; Each valid Ct value is paired with its nearest high-confidence coordinates to form a quintuple of <sample ID, latitude and longitude, elevation, time, Ct value>. Clustering of multiple test results at the same sampling point, if the spatial distance is less than 1 meter and the time interval is less than 5 minutes, they are merged into the same source tracing event; Generate a standardized traceability report, including trajectory map, amplification curve, sampling point heat map and equipment operation log; The report is encrypted with a digital signature, and the hash value is written to the blockchain's evidence storage node. Authorized users can query the complete traceability chain using the sample ID.

8. The method for tracing the origin of a microfluidic biological detection device with fiber optic synchronous UWB positioning according to claim 1, characterized in that: For trajectory anomalies, a sliding window covariance analysis method is used to identify positioning jumps. If the covariance exceeds a threshold, historical trajectory backtracking and inertial data re-integration are triggered to generate a corrected trajectory sequence, including: Set the sliding window length to 10 consecutive coordinate points, and calculate the covariance matrix of each dimension of the coordinates within the window; If the covariance of any dimension is greater than 0.25m², or if the Euclidean distance between two adjacent points changes abruptly by more than 2 meters, it is marked as an outlier segment. The starting point of the anomaly segment is traced back to the most recent stationary point or high-confidence UWB location point, which serves as the starting point of the reintegration. Read the raw MEMS acceleration and angular velocity data from the starting point to the end of the abnormal segment, and re-execute the high-precision numerical integration; Zero-velocity correction and terrain constraints are introduced during the integration process; The original abnormal segment is replaced by the result of the multiple integration to generate a smooth and continuous corrected trajectory; The corrected trajectory was realigned with the biological data, and the source tracing record was updated.

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