340 results about "Test subject" patented technology

The invention relates to the technical field of blood pressure measurement, in particular to a cuff-free blood pressure continuous monitoring method based on ICG, PPG and ECG multi-mode physiological signals. According to the method, deep mining and fusion are carried out based on multi-modal physiological signals such as a chest impedance signal ICG, a photoelectric volume pulse wave signal PPG and an electrocardiosignal ECG of a tested object synchronously collected by multi-modal hemodynamics monitoring equipment, and a richer multi-modal feature matrix related to blood pressure changes is constructed; after deep learning fusion training is carried out on the constructed cuff-free blood pressure prediction model, prediction output of a cuff-free blood pressure prediction result can be directly carried out according to ICG, PPG and ECG multi-mode physiological signals of a to-be-detected tested object by means of the cuff-free blood pressure prediction model, the generalization ability and monitoring precision of continuous monitoring of the cuff-free blood pressure can be effectively improved, and the accuracy of continuous monitoring of the cuff-free blood pressure can be improved. The continuous, non-invasive and high-precision blood pressure monitoring requirements are met, and the clinical application value is more remarkable.

A mask-based diagnostic apparatus is provided for detecting a biomarker contained in exhaled breath of a test subject. An exhaled breath condensate (EBC) collector converts breath vapor received from the lungs and airways of the test subject into a fluid biosample. The EBC collector including a thermal mass, a condensate-forming surface and a fluid conductor disposed on the condensate-forming surface. A fluid transfer system receives the fluid biosample from the EBC collector. A biomarker testing unit receives the fluid biosample from the fluid transfer system and tests the fluid biosample for a target biomarker. A testing system support is provided for supporting the EBC collector, the fluid transfer system and the biomarker testing unit. The testing system support is configured and dimensioned to fit inside a face mask. A face mask is provided forming an exhaled breath vapor containment volume to hold the exhaled breath vapor in proximity to the EBC collector to enable the condensate-forming surface cooled by the thermal mass to coalesce the exhaled breath vapor into the fluid biosample.

The invention discloses a neural disease diagnosis system based on space-time attention and dynamic field self-adaption. The method belongs to the technical field of cross-modal medical data adaptive analysis. The technical problem that a brand new system capable of simultaneously fusing multi-modal information and modeling multi-scale spatial-temporal features and having dynamic field adaptive ability is urgently needed to improve the accuracy and generalization ability of intelligent diagnosis of multi-site nerve diseases is solved. The system comprises a data preprocessing module for extracting a standardized time sequence of a brain region from fMRI time sequence data; the two-channel feature coding network module obtains global features through an attention mechanism; according to the feature fusion and classification module, a main task classifier executes a main task and predicts whether a to-be-tested person suffers from nerve diseases or not, and a domain task classifier executes a domain task and predicts a site to which the to-be-tested person belongs; and the dynamic balance training module adjusts the dynamic balance of the main task and the domain task through a dynamic balance control strategy.

The invention discloses a psychological health education auxiliary system based on big data, and relates to the technical field of psychological health education, the psychological health education auxiliary system uses a camera to collect eye movement data, combines CNN to extract static features and LSTM to capture time sequence changes, improves anxiety detection objectivity, combines embedded online learning, short video watching or classroom scenes, and improves anxiety detection accuracy. Daily data collection is carried out, the anxiety trend is continuously tracked by adopting a dynamic analysis method, and the change of the psychological state is monitored and evaluated in real time; the psychological intervention content can be dynamically adjusted based on anxiety scores and personalized feedback strategies, for example, relaxation training, psychological adjustment videos or emotion evaluation questionnaires are pushed, so that psychological health education is more personalized, and invalid or generalized psychological education information is reduced; in addition, a reinforcement learning algorithm is introduced, recommendation content is continuously optimized through interaction data of a tested object, the intervention effect is improved, and psychological education resources can adapt to dynamic changes of individual psychological states.

A mask-based diagnostic apparatus is provided for detecting a biomarker contained in exhaled breath of a test subject. An exhaled breath condensate (EBC) collector converts breath vapor received from the lungs and airways of the test subject into a fluid biosample. The EBC collector including a thermal mass, a condensate-forming surface and a fluid conductor disposed on the condensate-forming surface. A fluid transfer system receives the fluid biosample from the EBC collector. A biomarker testing unit receives the fluid biosample from the fluid transfer system and tests the fluid biosample for a target biomarker. A testing system support is provided for supporting the EBC collector, the fluid transfer system and the biomarker testing unit. The testing system support is configured and dimensioned to fit inside a face mask. A face mask is provided forming an exhaled breath vapor containment volume to hold the exhaled breath vapor in proximity to the EBC collector to enable the condensate-forming surface cooled by the thermal mass to coalesce the exhaled breath vapor into the fluid biosample.

Methods, systems, and software for estimating circulating tumor fraction are provided. A first plurality of nucleic acid sequences for a plurality of loci in genomic DNA from a solid tumor sample is obtained. A second plurality of nucleic acid sequences for a plurality of cell-free DNA fragments obtained from a liquid biopsy sample from the same subject is obtained. One or more somatic mutations is identified in the first plurality of nucleic acid sequences. A variant allele frequency (VAF) is determined for each somatic mutation based on a frequency of the respective somatic mutation in the liquid biopsy sample and a frequency of the corresponding wild type allele in the liquid biopsy sample, thereby determining a set of VAFs. An estimate of the circulating tumor fraction for the test subject is determined based on the set of VAFs for the one or more somatic mutations.

Systems and methods for determining a blood tumor mutational burden (bTMB) for a test subject are provided in which there is obtained, from a panel-enriched sequencing reaction, a plurality of nucleic acid sequences. The plurality of nucleic acid sequences comprises a corresponding sequence for each cell-free DNA fragment in a plurality of cell-free DNA fragments obtained from a liquid biopsy sample from the test subject. Each respective cell-free DNA fragment in the plurality of cell-free DNA fragments corresponds to a respective probe sequence in a plurality of probe sequences used to enrich cell-free DNA fragments in the liquid biopsy sample in the panel-enriched sequencing reaction. There is determined, using the panel-enriched sequencing reaction, that a circulating tumor fraction (ctFE) is above a threshold ctFE value. Responsive to this determination, the bTMB is calculated for the test subject from the panel-enriched sequencing reaction and reported.

A mask-based testing system for detecting a biomarker received from lungs and airways of a test subject includes an exhaled breath condensate (EBC) collector integrated into an inside of a face mask worn by the test subject. The EBC collector converts breath vapor received from the lungs and airways of the test subject into a fluid biosample. A biosensor is fixed to the inside of the face mask for receiving a fluid biosample from the EBC collector and testing the fluid biosample for a target analyte. The biosensor generates a test signal dependent on at least the presence and absence of the target analyte in the fluid biosample. An electronic circuit is fixed to an outside of the mask for receiving the test signal, determining from the test signal a test result signal depending on detecting or not detecting the target analyte, and transmitting the test result signal to a remote receiver.

Methods, systems, and software are provided for predicting care pathway options for a medical condition in a test subject. In one implementation, a method includes retrieving a set of characteristics of the test subject from an electronic medical record for the test subject, retrieving data from a system modeling human tissue, and providing information comprising the set of characteristics from the electronic medical record and the data from the system modeling human tissue to an artificial intelligence (AI) component to receive as output from the AI component one or more care pathways for the medical condition.

The invention relates to a multi-mode-based micro-expression recognition method, which comprises the steps of acquiring data to obtain a face image and a depth image, preprocessing the data to remove redundant information and obtain an optical flow graph and depth difference information, training a model, deploying the model and the like. The data acquisition module is also used for acquiring data of a to-be-recognized object and inputting the data into the trained micro-expression recognition model; and finally, the identification model outputs a prediction result of the to-be-identified data. According to the multi-modal-based micro-expression recognition system method, analysis can be carried out according to image data of the test object, the micro-expression state of the test object can be automatically classified and recognized, and compared with a single-modal recognition system and method, the performance is better.

The invention provides an artificial cochlea objective debugging method and system based on wide-spectrum natural sound evoked electroencephalography, and the method comprises the steps: collecting an auditory electroencephalogram of a tested person under the stimulation of wide-spectrum natural scale sound synthesized by a plurality of vocoders, and carrying out the preprocessing of the auditory electroencephalogram, and obtaining an auditory electroencephalogram data set; training the deep learning network model by using data in the auditory electroencephalogram data set to obtain a trained deep learning network model; the deep learning network model is provided with two convolution layers for extracting features including time frequency and channel information of an auditory electroencephalogram, and is provided with a full connection layer for classification to obtain scale sound sensing electroencephalogram decoding and prediction accuracy; and quantizing different vocoder algorithm performances according to the obtained scale sound sensing electroencephalogram decoding and prediction accuracy, and objectively debugging the artificial cochlea based on the quantized different vocoder algorithm performances.

The invention discloses an epilepsy detection method, system and equipment based on electroencephalogram signals and a medium, and relates to the technical field of electroencephalogram signal processing. The method comprises the following steps: preprocessing multichannel original electroencephalogram signals of a detector, and constructing a graphic structure for describing spatial features of the electroencephalogram signals; the graphic structure comprises nodes and connecting lines, the nodes represent channels, and the connecting lines represent correlation coefficients between the channels; determining a final epilepsy detection result according to the graphic structure and an epilepsy detection model; the epilepsy detection model comprises a graph attention network, a Transform network and a Softmax classifier which are connected in sequence; wherein the graph attention network is used for aggregating spatial features between channels, the Transform network is used for extracting time features, and the Softmax classifier is used for carrying out binary epilepsy classification. The detection accuracy can be improved.

The invention discloses a signal identification method and system, electronic equipment and a storage medium. The method comprises the following steps: acquiring an original electroencephalogram signal of a test object; performing feature extraction on the original electroencephalogram signals, and constructing an initial feature matrix of the original electroencephalogram signals; reconstructing the initial feature matrix based on module parameters of a plurality of target hardware modules in the signal recognition device to obtain a target feature matrix, the target feature matrix satisfying processing conditions of the plurality of target hardware modules, and the data dimension of the target feature matrix being greater than the data dimension of the initial feature matrix; the target feature matrix is input into a signal recognition device, the original electroencephalogram signals are recognized through the signal recognition device, a signal recognition result is obtained, and the signal recognition result is used for representing the behavior intention of the test object. The technical problem that the operation speed of electroencephalogram signal recognition is low in the prior art is solved.

A method for generating speech includes uploading a reference set of features that were extracted from sensed movements of one or more target regions of skin on faces of one or more reference human subjects in response to words articulated by the subjects and without contacting the one or more target regions. A test set of features is extracted a from the sensed movements of at least one of the target regions of skin on a face of a test subject in response to words articulated silently by the test subject and without contacting the one or more target regions. The extracted test set of features is compared to the reference set of features, and, based on the comparison, a speech output is generated, that includes the articulated words of the test subject.

The present invention relates to a multi-luminance visual navigation test field for performing a vision test on a test subject. The multi-luminance visual navigation test field comprises: a test map, which can be operated to form a plurality of test scenes, each of which is provided with a preset walking route; a plurality of static obstacles, which are arranged on the test map and are used to form obstacles on the test map to hinder the test subject's progress; and a light source assembly, which is used to provide a plurality of light intensities. The multi-luminance visual navigation test field solves the problem in the prior art that the route design of the MLMT scheme is a full white background and arrows are used to indicate the direction of travel, but since most RP patients have extremely low vision and show decreased panretinal light sensitivity mainly due to rod cell damage, the problem that patients have difficulty distinguishing route markings and thus have difficulty in detection is solved. The multi-luminance visual navigation test field has a wide range of applications, low cost and higher detection accuracy.

The invention belongs to the technical field of computers, and particularly discloses a programming knowledge tracking method based on code prediction enhancement, and the method comprises the steps: extracting embedded representations based on historical programming questions and corresponding historical programming answers, and obtaining historical question embedded representations and historical answer embedded representations; based on the embedded representation of the historical question, the embedded representation of the historical answer and the embedded representation of the target programming question, the embedded representation of a source code input by the tested object for the target programming question is predicted through a multi-head attention mechanism model, and the predicted embedded representation of the source code serves as a programming answer prediction result; on the basis of the embedded representation of the target programming question, the programming answer prediction result and the current knowledge state of the tested object, the correct answer probability of the tested object for the target programming question is predicted, and the current knowledge state is obtained by analyzing time sequence evolution of the knowledge state on the basis of historical programming answers of the tested object. Through the method, the programming performance of the learner can be accurately predicted.

A device, system and methodology for horizontal gaze nystagmus (HGN) testing. Prior to a test subject taking an action that is verboten in an impaired state, such as driving a vehicle or operating complex or dangerous machinery, the test subject is positioned within a face recognition box of a screen and a HGN simulation test performed, capturing HGN eye movements of the test subject from which the present HGN physiological state of the test subject is determined. The present HGN physiological state of the test subject is compared to a reference HGN state to determine whether the test subject is impaired. Impairment causes temporary restriction of the functionality of the machinery or vehicle.

The invention discloses a flight safety warning method based on pilot operation intention recognition, which comprises the following steps: S1, collecting EEG data of a subject in each stage of simulated flight through an electroencephalogram signal data collection device; s2, carrying out preprocessing operation on the collected EEG data; s3, extracting and fusing the electroencephalogram signals by constructing a convolutional gradient attention network, and mapping fused features to an operation intention of a pilot; s4, calculating safety risk factors according to the deviation between the flight state and the preset flight envelope, the pilot operation intention and the external environment factors; s5, comparing the risk factor with a preset risk threshold, and dividing the risk into a high level, a middle level and a low level; and S6, the cockpit touch alarm system triggers multi-mode alarm in the cockpit according to the risk level, and adjusts the flight state in real time. The flight accident risk caused by human factors can be reduced, and the aviation safety is improved.

The invention discloses a state evaluation early warning device and method based on multiple modes, and relates to the technical field of psychological evaluation. According to the invention, the physiological signal acquisition sensor is used for acquiring physiological signal data and processing the data; based on the incidence relation among the sensors, the wearing states are recognized by combining a deep convolutional neural network and an autocorrelation algorithm, and the wearing states are divided into correct wearing, incorrect wearing and non-wearing; collecting answers of the tested person based on the test question bank, and converting the answers into text contents through a voice recognition algorithm; analyzing an anti-test behavior in combination with the action signal, and judging that the anti-test behavior exists when the answer is abnormal or the action exceeds the limit; carrying out band-pass filtering and feature extraction on the physiological signals in the effective time period, and carrying out weighted calculation on a scoring result; a decision tree algorithm is combined with historical data for optimization, and dynamic adjustment is achieved.

The utility model relates to the field of brain electrodes, in particular to an electroneurographic signal acquisition and stimulation unit capable of shortening implantation duration, which comprises an electrode wire, an electroneurographic signal acquisition and stimulation unit and an electroneurographic signal acquisition and stimulation unit, the curing assembly is used for wrapping and restraining the roots of the electrode wires, so that the adjacent electrode wires are kept parallel to each other; the shaping part is made of a material which can be dissolved in the process of implanting the electrode wire into the brain area and is used for being solidified at the connecting part of the solidifying assembly and the electrode wire so as to wrap and restrain the electrode wire; wherein the part, exposed on the outer side of the shaping piece, of the electrode wire is straight, the part, restrained on the inner side of the shaping piece, of the electrode wire is bent, and the electrode wire has the elastic force for restoring to be straight after being released from the inner side of the shaping piece. According to the embodiment of the utility model, on the premise that the length of the electrode wire is not shortened, the length of the shaping piece is shortened, so that the speed of completely dissolving the shaping piece is accelerated, and the total time of implanting the electrode wire is further reduced.

The invention discloses a primary hypertension risk assessment method based on infrared thermal imaging. The method comprises the following steps: (1) respectively taking two-hand infrared thermograms of a healthy subject, a hypertension patient and a hypertension patient before and after cold stimulation by adopting a medical infrared thermal imager; (2) analyzing hand infrared thermograms before and after cold stimulation of a healthy subject, a hypertensive patient and a hypertensive patient so as to reflect vascular reactivity and blood perfusion states of hands of the healthy subject, the hypertensive patient and the hypertensive patient; and (3) taking hand infrared thermograms of the to-be-tested subject before and after cold stimulation by adopting a medical infrared thermal imager, and obtaining a judgment result according to the vascular reactivity and blood perfusion state of the hand. According to the invention, a medical infrared thermal imager is utilized to shoot infrared thermograms of hands of a subject before and after cold stimulation, so that vascular reactivity and blood perfusion states are visually reflected in a non-contact, real-time and visualized manner, and finally, the purpose of evaluating the risk of primary hypertension is achieved.

A hand portable screen includes three portions connected in series relation, each portion having a camera for capturing image data from a field of view in front of a front surface of the respective portion of the screen. The screen is free standing when configured in an upright use position on a horizontal surface, e.g. a tabletop, so that the three front surfaces form three sides of a forwardly open recess. The side portions may be adjustable to converge the fields of view on a user sitting in front of the screen, for example, during an edible product test. Microphones may be provided, optionally in-ear, to capture sound data simultaneously with the image data from the cameras. The screen may be deployed to provide an individual test environment, for example, for testing snack food in an informal location.

The present application is to solve the problem that the optical characteristics of a plurality of LEDs cannot be inspected at the same time by a method of causing one of a pair of LEDs to emit light and causing the other to receive light, and using the current value of the current output by the photoelectric effect to inspect the optical characteristics of the LEDs. To solve the above problem, the present application proposes a test device provided with: an electrical connection portion electrically connected to the terminals of each of a plurality of LEDs that are test subjects; a light source portion that irradiates light to the plurality of LEDs at the same time; a measurement portion that measures a photoelectric signal that is photoelectrically converted by each of the plurality of LEDs with respect to the light irradiated by the light source portion and output via the electrical connection portion; and a determination portion that determines the good or bad of each of the plurality of LEDs based on the measurement result of the measurement portion.

The present invention relates to sampling kits for the collection, storage and transport of a tissue sample of a test subject. The kit comprises a sampling tool having a tip section configured to collect the tissue sample. The collected tissue sample may be directly retained and stored in the tip section or may be transferred onto a tape element and stored thereon.

The present application relates to the field of intelligent medical care, and specifically to a method, device, and program product for evaluating pulmonary circulation time based on contrast agent-enhanced EIT. The method comprises S1, obtaining contrast agent-enhanced pulmonary EIT data of a test subject; S2, determining the pulmonary circulation start time and pulmonary perfusion end time based on the contrast agent-enhanced pulmonary EIT data; the pulmonary circulation start time is the moment when the electrical impedance signal of the contrast agent injected changes while the test subject holds his breath, and the pulmonary perfusion end time is the moment when the electrical impedance signal does not change after the contrast agent is injected while the test subject holds his breath; S3, subtracting the pulmonary circulation start time from the pulmonary perfusion end time to obtain the pulmonary circulation time. The pulmonary circulation time evaluation method of the present application can realize bedside detection, is easy to operate, and has great clinical application value.

The invention relates to a method for creating an audiogram of a test person by means of a hearing instrument (1), in which a sound signal (22) is received by a first electro-acoustic input transducer (10) of the hearing instrument (1) in an ear canal (4) of the test person, which ear canal is at least partially closed by the hearing instrument (1), and a first input signal (24) is generated therefrom, a test sound (32) is generated by an electro-acoustic output transducer (18) of the hearing instrument (1) and is output into an ear canal (4) of the test person, which ear canal is at least partially closed by the hearing instrument (1), and wherein the hearing threshold of the test person at the at least one test frequency is determined on the basis of a reaction of the test person to the test sound (32) and by means of the first input signal (24).

Self-administered tests for a broad range of visual functions use angular indications on a peripheral structure selected by the test subject to indicate the position of a visible feature of a stimulus. The tests are performed on a computer and use artificial intelligence to adapt and personalize the range of difficulty and type of test to the subject's vision issues. The tests can be used for diagnosis in the fields of optometry, ophthalmology, neurology, psychology, and psychiatry. The technology also can be used to determine a subject's optical prescription in combination with the use of ophthalmic lenses that are provided to the test subject.

This application relates to the field of cardiopulmonary testing technology, and in particular to a cardiopulmonary endurance testing system and method based on a power bicycle. The method includes: acquiring basic information about the test subject; analyzing the basic information to determine the test subject's testing mode; acquiring real-time cycling video; analyzing the real-time cycling video to determine cycling operations; and determining a cycling adjustment plan based on the real-time cycling video and the cycling operations. By acquiring and analyzing the test subject's basic information, a testing mode suitable for the individual's physical fitness level and exercise intensity can be customized, improving the relevance and effectiveness of the test. The analysis of the real-time cycling video can provide immediate feedback on the test subject's exercise status, helping the test subject to adjust their posture in a timely manner and avoid incorrect movements and excessive fatigue.

Computerized systems, methods, media, and computer program products are provided for improving the computational efficiency of evaluating and selecting a tendency scoring model. In an example method, a computer system accesses first data representing a plurality of characteristics of a test subject and second data representing a plurality of candidate tendency score models that may be used to estimate effectiveness of a treatment. The system selects a set of tendency score models by sequentially evaluating at least some of the candidate tendency score models until one or more stop criteria are met. The effectiveness of the treatment may be estimated by utilizing the selected set of tendency score models. Further, the system stores a data structure representing the set of tendency score models, and outputs the data structure.

An object of the present invention is to provide a cover film in which chips during cutting are unlikely to be generated, voids during bonding to a substrate using an enclosing solution are unlikely to be generated, and adhesiveness with the substrate is excellent. The cover film of the present invention is used for covering a test subject on a substrate, the cover film including a support and a polymer layer containing a polymer, in which a fracture toughness value of the polymer layer is 0.2 MPa·m0.5 or more, an in-plane retardation of the support at a wavelength of 590 nm is 1,000 nm or less, and a requirement regarding a dissolution rate of the polymer layer in xylene and a requirement regarding a viscosity of a xylene solution of the polymer layer are satisfied.