33 results about "Biosensor array" patented technology

The invention relates to the technical field of metabolite monitoring, and discloses a continuous multi-metabolite monitoring method based on multi-modal cross calibration. The method comprises the following steps: acquiring a multi-source metabolite signal sequence containing an electrochemical signal, an optical signal and a thermodynamic signal through an implantable biosensor array; performing time sequence segmentation on the multi-source metabolite signal sequence to generate metabolite concentration time sequence fragments; and synchronously inputting the metabolite concentration time sequence fragment into a metabolite dynamic response model and a metabolite interaction characteristic model, and respectively generating a first metabolite concentration track and a second metabolite concentration track. According to the method, by means of multi-modal signal fusion and cross calibration, in combination with time sequence segmentation and multi-model analysis, dynamic changes and interaction of metabolites can be comprehensively captured, the integrity and accuracy of metabolite monitoring are improved, and the method is suitable for continuous multi-metabolite monitoring scenes.

The invention discloses a hearing aid health analysis method based on a physiological signal monitoring function. The method comprises the following steps: collecting physiological signal data of a user in real time through a multi-mode biosensor array integrated on a hearing aid body; the hearing aid body comprises a digital signal processor and a wireless communication module; the physiological signal data at least comprises a brain wave signal, a skin electric response signal and a temporal artery pulse signal; performing motion artifact elimination processing on the physiological signal data through an adaptive filtering algorithm; performing feature extraction on the preprocessed physiological signal by using an embedded health analysis engine to generate a composite health feature vector containing a sympathetic nerve activity index, cognitive load measurement and a cardiovascular function index; and dynamically generating a health risk assessment report based on an association relationship between the composite health feature vector and a preset hearing scene, the bone conduction vibration unit and the audio synthesis module of the hearing aid body output graded health alarm signals.

The invention provides an underground coal mine ventilation control method and device, electronic equipment and a storage medium, and belongs to the technical field of mine ventilation. The method comprises the steps that the type and concentration characteristics of harmful gas in a target area are determined according to data collected by a biosensor array; determining time sequence data of the harmful gas according to the concentration of the harmful gas, and determining a target concentration change rate of the harmful gas according to the time sequence data; according to the concentration of the harmful gas, the target concentration change rate and the current underground acoustic wave characteristics of the coal mine, the target air volume of the target area is determined; according to the target air volume of the target area, the ventilation resistance of the target area and the current opening degree of the ventilation valve, the opening degree of the ventilation valve is controlled, and the ventilation air volume is determined. According to the coal mine underground ventilation control method and device, the electronic equipment and the storage medium, the ventilation quantity can be accurately and timely adjusted.

The invention relates to the technical field of veterinary epidemic disease detection, and discloses a veterinary epidemic disease remote monitoring and intelligent diagnosis system, which comprises a multi-mode biosensor array including an implantable miniature biochip, a wearable flexible physiological monitoring patch and an environment sensing sensor cluster, the implantable miniature biochip is used for being implanted into a key tissue organ area in an animal body and collecting microscopic physiological data such as cellular metabolism signals and local immune reaction marker concentration in real time, and the wearable flexible physiological monitoring patch is used for being attached to the body surface of the animal. By means of the multi-mode biosensor array and the edge intelligent preprocessing unit, animal physiology and environment data are accurately monitored in real time. The multi-modal biosensor array covers the implantable miniature biochip, the wearable flexible physiological monitoring patch and the environment sensing sensor cluster, and can comprehensively collect in-vivo microscopic physiological data, body surface macroscopic physiological parameters and feeding environment information of animals.

The invention provides methods for associating volatile compounds or mixtures of volatile compounds with combinatorial response patterns of Olfactory Receptors (OlfRs), a biosensor array comprising a plurality of biosensors, the use of said biosensor and of the method of the invention to screen for diseases, a molecule identified by a method of the invention as well as the use se of said molecule to modify the behavior of an insect.

The invention discloses an underground water pollution rapid detection device based on a biosensor array, and relates to the technical field of detection devices.The underground water pollution rapid detection device comprises a crawling pipeline, a biosensing detection module, a sampling module and a liquid feeding module, the sampling module, the liquid feeding module and the biosensing detection module are independently assembled and are in butt joint through standard interfaces, and maintenance and cleaning are convenient; meanwhile, the problems of independent work and connection fault of a traditional split device module are solved, the liquid conveying module can automatically convey sample liquid to the detection module, seamless connection is achieved in the whole process, time loss caused by independent work of the traditional split device module is avoided, redundant structures are reduced, a crawling pipeline serves as a common carrier, and the detection efficiency is improved. The modules are distributed along the axis instead of being stacked, the overall size is reduced, and the device is more suitable for being deployed in a narrow space.

The invention discloses a differential low-noise integrated biosensor array for cell culture detection and a preparation method thereof, and the differential low-noise integrated biosensor array integrates an ISHFET device, an REHFET device and an EXHFET device, so that extracellular action potential signals and local field potential signals can be detected during in-vitro cell culture; therefore, interference of factors such as tissue trauma and immune response on cell activity signal detection is avoided, and good reliability is realized; the ISHFET device and the REHFET device can form a differential sensing unit, so that the effect of reducing the detection error is realized; the EXHFET device not only can detect extracellular action potential signals, but also can independently detect local field potential signals, so that more diversified cell activity signals can be detected, and more data support is provided for in-vitro cell culture research. The method is widely applied to the technical field of semiconductors.

The invention relates to the technical field of active ingredient extraction, and particularly provides an extraction method for classifying and screening active ingredients, raw materials are subjected to low-temperature freeze-drying pretreatment by adopting supercritical CO2, and treatment is performed for 4-6 hours under the conditions of minus 40-minus 20 DEG C and 8-12 MPa, so that the active ingredients are reserved to the greatest extent; through gradient ultrasonic-assisted extraction of ultrapure water, a 50% ethanol solution and a 95% ethanol solution, step-by-step separation of water-soluble, alcohol-soluble and fat-soluble components is realized; carrying out multi-dimensional purification by using a composite chromatographic column containing a 0.2 mu m ceramic membrane layer, a macroporous adsorption resin layer and a sephadex layer; a two-channel biosensor array is adopted to synchronously detect a cell response signal and a molecule binding signal, and components with the activity intensity reaching 80% or above are screened; and finally, carrying out vacuum rotary evaporation concentration and spray drying to obtain a finished product, and completing system purity verification through a high performance liquid chromatography-mass spectrometry technology to form a complete quality control system.

A semiconductor device includes a first gate electrode, an insulating part, a source electrode, a drain electrode, and a contact part. The insulating part is on one surface of the first gate electrode. The source electrode is connected to the insulating part. The drain electrode is connected to the insulating part. The contact part is between the source electrode and the drain electrode and on the insulating part. The contact part contains an atomic layered material. The contact part has a second part contactable with a sample. The second surface is opposite to a first surface facing the insulating part. A surface of the insulating part, the surface facing the contact part, has an uneven structure with respect to the first gate electrode.

This invention relates to the fields of medical device technology, biosignal processing, and artificial intelligence-assisted diagnostic technology. Specifically, it relates to a non-invasive dynamic monitoring system and method for gastric function based on quantum sensing and multimodal artificial intelligence. The system includes a quantum dot biosensor array, a multimodal signal fusion processor, an artificial intelligence dynamic evaluation algorithm, and a cloud-based collaborative diagnostic platform. The quantum sensor uses graphene quantum dot material and achieves 128-channel parallel acquisition through capacitive coupling. In this invention, by setting up the quantum dot biosensor, the sensitivity reaches the single-photon level, the resolution is 0.1μV, the frequency response range is 0.01-100Hz, and the anti-interference capability is 90dB common-mode rejection ratio, thus improving signal acquisition accuracy and anti-interference capability.

This invention relates to the field of metabolite monitoring technology and discloses a multimodal cross-calibrated method for continuous multi-metabolite monitoring. The method acquires multi-source metabolite signal sequences containing electrochemical, optical, and thermodynamic signals through an implanted biosensor array; it performs time-series segmentation of the multi-source metabolite signal sequences to generate metabolite concentration time-series segments; and it synchronously inputs these metabolite concentration time-series segments into a metabolite dynamic response model and a metabolite interaction feature model to generate a first metabolite concentration trajectory and a second metabolite concentration trajectory, respectively. This method, by leveraging multimodal signal fusion and cross-calibration, combined with time-series segmentation and multi-model analysis, can comprehensively capture the dynamic changes and interactions of metabolites, improving the completeness and accuracy of metabolite monitoring, and is suitable for continuous multi-metabolite monitoring scenarios.

The invention discloses an intelligent nursing behavior monitoring system, and relates to the field of intelligent nursing. Comprising a multi-mode sensing terminal which collects multi-dimensional data of nursing operation through a three-view synchronous collection module and a biosensor array; the edge intelligent analysis node is used for carrying out behavior identification and risk assessment on the collected data by adopting a containerized processing architecture; the block chain evidence storage platform is used for constructing an operation evidence chain which cannot be tampered through a Hyperledger Fabric alliance chain architecture; and the feedback optimization engine adopts a double-model operation framework to be matched with a federated learning framework to realize self-optimization and scene self-adaption of the system. According to the method, the technical problem of space and time information processing separation is effectively solved by adopting a space-time diagram convolutional network technical means, so that deeper and more global understanding and modeling of nursing actions are realized, the recognition precision and robustness of complex and fine actions are greatly improved, and the false alarm rate and the missing report rate are reduced.

This invention relates to the fields of digital therapy, intelligent medical devices, and applied artificial intelligence technologies, and more specifically to a closed-loop pain management method and system integrating diagnostic assistance and interference-resistant sensing. It includes: a wearable device comprising: a neuromodulation signal generator configured to generate neuromodulation stimulation pulses; a biosensor array physically integrated with the neuromodulation signal generator configured to sense physiological data indicating the user's autonomic nervous system activity; a controller configured to execute a time-division multiplexing protocol; a processor; and a non-transitory computer-readable storage medium associated with the processor for generating a diagnostic support report. This invention enables simultaneous effective neural stimulation and high-fidelity ANS signal acquisition on a single wearable device.

The invention relates to the technical field of pain state prediction, and discloses a method for constructing a patient pain state prediction model based on brain electric signals. The method comprises the following steps: acquiring an original data stream of brain electric signals of a patient through a multi-channel biosensor array, synchronously recording pain event labeling information, and generating a standardized signal sequence after preprocessing; extracting multi-modal features of time domain stability, frequency domain resonance and space domain connectivity, and constructing a feature-label mapping table; training the graph convolutional neural network model, and obtaining an initial prediction model in combination with a node embedding technology; dynamically adjusting parameters through an adaptive filtering algorithm to generate an optimization model; and in combination with the real-time electric signal flow and the physiological context information, outputting a pain level evaluation report, and automatically matching a clinical intervention protocol library to form a personalized scheme. According to the method, multi-modal features and a dynamic optimization mechanism are integrated, and prediction accuracy and real-time performance are improved.

The invention provides an emotion monitoring system based on a hybrid architecture, and the system comprises a multi-mode biosensor array which is used for collecting a physiological monitoring signal of a target person; the edge calculation unit is used for determining preliminary emotion classification information according to the physiological monitoring signals and a lightweight model; the cloud server is used for determining an emotion monitoring result according to the preliminary emotion classification information and a GNN-Transform mixed architecture model; wherein the GNN-Transform hybrid architecture model comprises a plurality of layers of GNN-Transform co-processing modules, and the GNN-Transform hybrid architecture model comprises a plurality of layers of GNN-Transform co-processing modules; each layer of GNN-Transform coprocessing module is used for completing feature optimization and determining an attention sampling focus of the next layer according to a feature optimization result of the current layer; and the lightweight model is obtained by the lightweight of the GNN-Transform hybrid architecture model. According to the method, a GNN-Transform hybrid architecture is provided, time-space association among all modals is modeled through a neural network, and meanwhile, multi-modal time sequence data is processed by utilizing a self-attention mechanism of Transform, so that deep fusion of cross-modal features is realized, and the emotion monitoring precision is improved.

A foot covering comprising an elongated fabric body. The foot covering includes a biosensor system that includes a biosensor array integrated into the elongated fabric body, and a microprocessor that is configured to removably electronically couple to the biosensor array and removably physically couple to the elongated fabric body.

The invention relates to the field of whole-cell biosensors, and provides a whole-cell biosensor array and an early warning model for monitoring the mildewing degree and aflatoxin content of corn peanuts. The Escherichia coli cell comprises a promoter related to the response of a volatile organic compound released by Aspergillus flavus pollution, the promoter is operably connected with a reporter gene, and an expression product of the reporter gene is used for generating a bioluminescence signal which can be detected. Through the whole-cell biosensor and the array thereof, related volatile organic compounds after corn peanuts are infected by aspergillus flavus can be accurately responded, so that rapid and high-sensitivity monitoring on aspergillus flavus mildew and toxin pollution is realized. Besides, the whole-cell biosensor array is combined with a machine learning regression model, so that the aspergillus flavus infection degree can be quantified, and the aflatoxin content can be predicted.

The application discloses a groundwater pollution rapid detection device based on a biosensor array, and relates to the technical field of detection devices.The device comprises a crawling pipeline, a biosensing detection module, a sampling module and a liquid feeding module.The sampling module, the liquid feeding module and the biosensing detection module are independently assembled and are connected through standardized interfaces, which facilitates maintenance and cleaning, and simultaneously solves the problem of independent work and connection faults of traditional split-type equipment modules.The liquid feeding module of the application can automatically feed sample liquid to the detection module, and the whole process is seamlessly connected, thereby avoiding time loss caused by independent work of modules in traditional split-type devices, reducing redundant structures, and reducing the overall volume by arranging the modules along an axis instead of stacking them, which is more suitable for deployment in narrow spaces.

The invention relates to the technical field of vegetable heavy metal detection, and discloses a continuous detection method based on organic fertilizer heavy metals in vegetables. The method comprises the following steps: collecting a heavy metal ion concentration signal of a mixed solution of a vegetable sample and an organic fertilizer through a biosensor array, and generating original electrochemical response data; performing baseline correction and noise filtering on the original data, and extracting a characteristic response peak value of each heavy metal ion; calculating initial concentration values of the various heavy metal ions according to a mapping relation between the characteristic response peak values and a preset standard curve; and inputting the initial concentration value into a dynamic weighted fusion model, and generating a corrected heavy metal concentration distribution table in combination with vegetable growth cycle data and an organic fertilizer application record. The method can be used for synchronously detecting various heavy metals, simplifying the process, improving the data accuracy, reflecting the concentration change under different growth and fertilization conditions, and is suitable for detecting heavy metals in agricultural vegetables and assisting quality safety management and control.

A device for the manufacture and administration of a smart therapeutic composition for the treatment of diabetes and Alzheimer's disease, the device comprising the following: an extraction chamber configured to isolate phytochemicals derived from turmeric, including curcuminoids and turmerones, from turmeric rhizome powder or pre-purified extracts, the extraction chamber further comprising a solvent-assisted ultrasonic unit and a temperature-controlled housing to maintain bioactive stability during extraction; a microfluidic encapsulation chamber which is operatively connected to the extraction chamber and is configured to embed the extracted phytochemicals in lipid-polymer hybrid nanoparticles, wherein the encapsulation chamber comprises a polydimethylsiloxane (PDMS) microchannel network, flow-controlled carrier inlets and a photonic scattering sensor to monitor the size distribution of the nanoparticles; a stabilization unit located downstream of the encapsulation chamber and configured to convert the encapsulated nanoparticles into stable formulations by means of freeze-drying or spray-drying, wherein the stabilization unit includes a humidity-controlled environment to maintain long-term storage stability; a delivery interface configured to deliver the stabilized formulations via oral capsules or transdermal patches, the delivery interface also including a microprocessor-operated dosage controller for programmable delivery schedules; a biosensor array integrated into the device, configured to detect biomarkers from the group consisting of glucose, indicators of oxidative stress, and β-amyloid fragments; and a feedback control system that is operationally connected to the biosensor array and the microfluidic encapsulation chamber, wherein the feedback control system includes an embedded microcontroller with adaptive techniques to dynamically adjust encapsulation ratios, nanoparticle size and dosing intervals based on patient-specific biomarker data.

This invention discloses an intelligent monitoring contact lens system and its control method based on the integration of radio frequency wireless power supply and self-oxygen supply, belonging to the technical field of intelligent contact lenses and flexible wearable devices. The system includes a self-oxygenating contact lens, a radio frequency energy harvester, a microcontroller, a biosensor array, and an antenna; the accompanying control software is deployed on a smart terminal to realize device management, energy scheduling, and data interaction. The radio frequency energy harvester is used to capture ambient radio frequency energy and power the intelligent contact lens; the antenna is used for bidirectional data transmission with the terminal; and the biosensor array collects biological information from the cornea and tears in real time. This invention significantly simplifies the contact lens structure by offloading complex control logic to the smart terminal software, which is beneficial for the integrated design of multifunctional modules, while improving the system's wearing safety and ease of use.

The invention relates to the technical field of biosensors and wireless health monitoring, and particularly discloses a renal rejection monitoring system based on a wireless implantable biosensor. The system comprises a wireless implantable biosensor array, an in-vivo signal preprocessing unit, an in-vitro data receiving and synchronizing device, a multi-modal heterogeneous data fusion engine and a space-time diagram neural network prediction model, immune and metabolism multi-dimensional biomarkers are collected around a transplanted kidney in real time, a dynamic'immunity-metabolism 'knowledge graph is constructed, and accurate prediction and graded early warning of rejection risks are achieved by means of space cascading and time evolution laws of time-space diagram neural network modeling signals. By the adoption of the technical scheme, sub-clinical rejection signals can be recognized before conventional indexes such as creatinine are abnormal, a window is intervened in advance, meanwhile, long-term non-invasive monitoring is achieved through wireless low-power-consumption design, and the accuracy and the intelligent level of postoperative management are improved.

The present disclosure provides methods and devices for simultaneous identification of a plurality of target nucleic acid sequences in a single sample chamber that includes an addressable array of nucleic acid probes attached to a solid surface. Addressable signals can be generated and measured, in real-time, upon hybridization of target sequences at the individual probe locations within the array while the temperature of the system is varied. Such generated signals, as a function temperature, can then be used to compute the properties of nucleic acid hybridization at each addressable location which is ultimately utilized to estimate the sequence of the target nucleic acids. In particular, an integrated semiconductor biosensor array device can be used to measure the addressable signals.

This invention relates to a quality testing method for low-odor wire harness materials, belonging to the field of quality testing technology. The method includes: placing a wire harness sample in an intelligent sealed chamber; dynamically adjusting temperature, humidity, and ventilation rate using the Internet of Things (IoT) to simulate the entire lifecycle of VOCs slow-release processes, generating a test gas that closely resembles real-world operating conditions; capturing ppb-level trace VOCs molecular signals using a chip equipped with specific biological olfactory receptor proteins, forming a high signal-to-noise ratio dataset; performing toxicity verification by matching a sensitive bacterial strain library with an AI-based microbial sensor array, outputting component-toxicity correlation assessment results; and outputting quantitative detection results after multi-channel filtering calibration and operating condition deviation correction. Based on the results, an N-BEATS model is constructed to achieve risk warning, matching remediation solutions, and forming a closed loop of detection-warning-control-verification. This invention clearly defines the concentration and toxicity contribution of trace components, captures synergistic / antagonistic toxicity effects between components, and significantly improves detection accuracy and data reliability.

A biosensor system includes an array of biosensors with a plurality of electrodes situated proximate the biosensor. A controller is configured to selectively energize the plurality of electrodes to generate a DEP force to selectively position a test sample relative to the array of biosensors.

This invention discloses an integrated light source biological cell culture sensing device. The device comprises a Micro-LED array and a biosensor array, which are bonded together. A DGHFET device and the Micro-LED device form a field-effect biosensor, with the DGHFET device located within the light spot coverage area of ​​the Micro-LED device within the same field-effect biosensor. This integrated light source biological cell culture sensing device successfully integrates efficient photostimulation, high-sensitivity biosensing, and high-reliability anti-interference capabilities onto a single platform, providing a powerful, reliable, and flexible integrated solution for optogenetic research. This invention has wide applications in the semiconductor technology field.

This invention relates to a biosensor array monitoring system and method for imaging the distribution of small organic molecules in plants. The system includes a biosensor array and a control module. The control module includes a signal output and input conditioning unit and a control and data processing unit. The biosensor array is used to couple with a live plant sample and acquire current signals caused by corresponding small organic molecules based on an applied linear scanning voltage signal. The signal output and input conditioning unit is used to apply the linear scanning voltage signal to the biosensor array and condition the current signals acquired by the biosensor array to obtain voltage signals. The control and data processing unit is used to calibrate the biosensor array and the signal output and input conditioning unit, generate linear scanning voltage signals, and analyze and process the obtained voltage signals to obtain in-situ distribution images of small organic molecules in the plant. This invention can be widely applied in the field of sensor technology in agriculture.

The invention discloses an apple planting greenhouse environment tracking management method and system based on the Internet of Things. The method comprises the steps of collecting multi-source data of apples in a greenhouse through a multispectral imaging sensor, a biosensor array and a wearable apple physiological sensor; the multi-source data is preliminarily integrated, verified and cached through a local gateway and then uploaded to a data processing system through a 4G / 5G network; the data processing system extracts spatial features of the multi-source data based on a neural network fusing CNN and RNN features, and compares and matches the spatial features of the multi-source data with pest and disease damage feature modes and apple pathophysiological knowledge in a knowledge base to obtain a matching result; and outputting an apple planting optimization scheme or a disease and pest diagnosis result based on a matching result. The method is used for solving the problems of how to accurately know the growth condition of apples and how to immediately optimize a cultivation scheme.

The structure of a semiconductor device with an array of bioFET sensors, a biometric fingerprint sensor, and a temperature sensor and a method of fabricating the semiconductor device are disclosed. A method for fabricating the semiconductor device includes forming a gate electrode on a first side of a semiconductor substrate, forming a channel region between source and drain regions within the semiconductor substrate, and forming a piezoelectric sensor region on a second side of the semiconductor substrate. The second side is substantially parallel and opposite to the first side. The method further includes forming a temperature sensing electrode on the second side during the forming of the piezoelectric sensor region, forming a sensing well on the channel region, and binding capture reagents on the sensing well.

A semiconductor device includes a first gate electrode, a first insulating unit, a source electrode, a drain electrode, and a contact part. The first insulating unit is provided on a second gate electrode configured to control a reference voltage in a transport characteristic. The source electrode is connected to the first insulating unit. The drain electrode is connected to the first insulating unit. The contact part is provided between the source electrode and the drain electrode on the first insulating unit, and being able to be in contact with a sample. The sample is able to be in contact with the first gate electrode. A surface opposite to the first insulating unit, of the contact part is configured to be in contact with the sample.