497 results about "Test subject" patented technology

A method and system for determining one or more sources of a cell free deoxyribonucleic acid (cfDNA) test sample from a test subject. The cfDNA test sample contains a plurality of deoxyribonucleic acid (DNA) molecules with numerous CpG sites that may be methylated or unmethylated. A trained deconvolution model comprises a plurality of methylation parameters, including a methylation level at each CpG site for each source, and a function relating a sample vector as input and a source of origin prediction as output. The method generates a test sample vector comprising a site methylation metric relating to DNA molecules from the test sample that are methylated at that CpG site. The method inputs the test sample vector into the trained deconvolution model to generate a source of origin prediction indicating a predicted DNA molecule contribution of each source.

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.

In various examples, circadian rhythm-based data augmentation for drowsiness detection systems and applications are provided. Embodiments described herein may produce an estimated circadian rhythm for a test subject and / or vehicle driver or other machine operator or occupant, and use the pattern of that circadian rhythm to correct, confirm, calibrate, or otherwise augment drowsiness assessments derived from video image data. The position of a person in the context of their process C circadian cycle may be used as indication of their level of drowsiness. An estimated process C circadian cycle may be used to generate more accurate ground truth training data for training machine learning models, and may be used by real-time, in-vehicle drowsiness detection systems that infer driver drowsiness levels based on captured images. In various embodiments, a circadian rhythm drowsiness estimate may be used to correct, calibrate, augment, and / or replace a drowsiness score predicted by a machine learning model.

In various examples, circadian rhythm-based data augmentation for drowsiness detection systems and applications are provided. Embodiments described herein may produce an estimated circadian rhythm for a test subject and / or vehicle driver or other machine operator or occupant, and use the pattern of that circadian rhythm to correct, confirm, calibrate, or otherwise augment drowsiness assessments derived from video image data. The position of a person in the context of their process C circadian cycle may be used as indication of their level of drowsiness. An estimated process C circadian cycle may be used to generate more accurate ground truth training data for training machine learning models, and may be used by real-time, in-vehicle drowsiness detection systems that infer driver drowsiness levels based on captured images. In various embodiments, a circadian rhythm drowsiness estimate may be used to correct, calibrate, augment, and / or replace a drowsiness score predicted by a machine learning model.

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 fragrance preference degree detection system and method based on facial micro-expressions. The system comprises a data acquisition module and a detection module, the data acquisition module is used for creating a test scene and acquiring facial micro-expressions of a subject in a test process to obtain micro-expression data; the detection module is used for constructing feature vectors according to the micro expression data; when a plurality of evaluation steps exist in the test process, respectively constructing the feature vectors according to the evaluation steps; predicting the feature vector through a trained neural network model to obtain a detection result; the method can recognize the facial micro-expression based on the evaluation video, and achieves the detection of the preference degree according to the micro-expression data in the whole evaluation process.

A method performed by at least one processor includes obtaining an image of a subject; preprocessing the image of the subject; inputting the preprocessed image into a machine learning model trained in accordance with a first frequency distribution corresponding to a first ground truth obtained from one or more sensors performing a vital measurement on one or more test subjects; and obtaining, from the machine learning model, an estimate of a signal corresponding to the vital measurement of the subject.

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.

The invention provides a method and device for evaluating real emotion and a video consultation system, and the method comprises the steps: obtaining audio and video data of a testee, and separating the audio and video data into an audio stream and a video stream; respectively carrying out framing processing on the audio stream and the video stream to obtain a plurality of voice frames and a plurality of video frames; performing face detection preprocessing on the video frame to obtain a face image, inputting the face image into an expression recognition model to obtain expression confidence, processing through an expression analysis method to obtain expression comprehensive confidence, inputting an audio frame into an emotion recognition model to obtain emotion confidence, and processing through an emotion analysis method to obtain expression comprehensive confidence; the emotion comprehensive confidence is obtained; according to the emotion analysis method, based on emotion abrupt change, an audio and video frame rate FPS and the emotion confidence coefficient, similarity calculation is carried out on the expression comprehensive confidence coefficient and a first standard confidence coefficient, and similarity calculation is carried out on the emotion comprehensive confidence coefficient and a second standard confidence coefficient. Through the expression recognition model and the emotion analysis method, the accuracy of evaluating the real emotion of the testee is improved.

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 hydrothermal coupling model test system and a hydrothermal coupling model test method for simulating a liquid nitrogen frozen stratum in different seepage environments. The system and the method are used for experimental research of a multi-physical field coupling effect of a test object in a large-seepage liquid nitrogen frozen stratum. The model test system comprises a liquid nitrogen freezing system, a flowing water seepage circulation system and a monitoring system, the liquid nitrogen freezing system is used for controlling the temperature of a liquid nitrogen freezing pipe embedded in a sand layer by changing the liquid nitrogen flow, so that the test sand layer is quickly frozen; the flowing water seepage circulation system simulates different underground water seepage speeds through a pressure pump, and the temperature of test water is kept constant through a heating rod. The monitoring system is used for recording the change trend of the temperature field and the seepage field in the liquid nitrogen stratum freezing process. According to the device, the ultra-low temperature effect of the liquid nitrogen is utilized to perform top-speed freezing on the sand layer under the high-flow-speed seepage environment, so that the freezing curtain can be effectively closed, and the evolution law of a large-seepage-flow stratum liquid nitrogen artificial freezing temperature field and a seepage field is obtained by simulating the liquid nitrogen stratum freezing process under different seepage environments; and a basis is provided for manual liquid nitrogen freezing construction of the large-seepage stratum.

Provided herein are methods of generating a homologous recombination repair deficiency (HRD) score, determining a reference HRD score, determining a HRD status of a test subject having one or more cancer types, and / or treating a disease based on HRD status. Additional methods as well as related systems, apparatuses, and computer readable media are also provided.

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.

A mask-based diagnostic apparatus for detecting a biomarker contained in exhaled breath of a test subject. An exhaled breath condensate (EBC) collector converts breath vapor from the lungs and airways into a fluid biosample. The EBC collector includes a condensate-forming surface and a thermal mass in thermal connection with the condensate-forming surface. A fluid transfer system transfers the EBC to at least one of a testing unit and an EBC containment vessel. Prior to testing, a semipermeable membrane concentrates a target biomarker portion in the fluid biosample to form a concentrated fluid biosample for testing. A target biomarker releasing material, such as a lysing agent, and / or mechanical lysing, can be used to obtained a target biomarker for testing that is within a viral envelope. The testing unit can be a universal g-FET biosensor constructed as a packaged semiconductor device that receives and tests the EBC as a fluid biosample.

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.

An exhaled breath condensate (EBC) collector for converting breath vapor received from the lungs and airways of a test subject into an EBC fluid biosample. The EBC collector including a cooling system for cooling a condensing surface wherein the breath vapor is coalesced into liquid droplets forming the EBC fluid sample. A biomarker concentrator concentrates a target biomarker portion in the fluid biosample to form a concentrated fluid biosample. The biomarker concentrator comprises a selectively permeable barrier for allowing excess water in the fluid biosample to pass through the selectively permeable barrier and block the target biomarker in the fluid biosample from passing through the selectively permeable barrier. A biomarker testing unit receives the concentrated fluid biosample and tests the concentrated fluid biosample for the target biomarker.

Methods, systems, and software are provided for estimating a circulating tumor fraction (ctFE) for a test subject. Sequence reads are obtained from a panel-enriched sequencing reaction, including sequences for cfDNA fragments corresponding to probe sequences and sequences for cfDNA fragments not corresponding to probe sequences. Bin coverage values are determined from the sequences. Segments are formed by grouping adjacent bins based on similar coverage value and segment coverage values are determined based on bin coverage values for bins mapping to each segment. For each simulated ctFE in a plurality of ctFEs, segments are fitted to an integer copy state by identifying the integer copy state that best matches the segment coverage value. The circulating tumor fraction for the test subject is determined using error optimization between segment coverage values and integer copy states across the simulated ctFEs.

A dynamic testing system includes a test station and at least one controller. The test station includes a hydraulic actuator configured to drive an actuation of a test subject using a hydraulic fluid flow, and a control valve that includes a housing, a valve body contained within the housing having a position that controls a flow rate and direction of the hydraulic fluid flow, a valve body driver configured to adjust the position of the valve body based on a reference signal, and a valve position sensor configured to output a position signal that is indicative of the position of the valve body. The at least one controller is configured to obtain a current position of the valve body using the position signal, obtain a diagnostic reference, detect a diagnostic condition based on a difference between the current position and the diagnostic reference, and generate a diagnostic signal.

The invention provides a vehicle seat comfort optimization method and optimization system, and relates to the technical field of vehicle seat adjustment. The vehicle seat comfort optimization method comprises the steps that sitting posture test data of a test object are acquired, the sitting posture test data at least comprise static state data and driving state data, and the driving state data are seat stress data generated when the test object drives a vehicle in a simulated driving scene; the static state data is seat stress data generated when the test object is in a static state; determining a seat stress model based on the sitting posture test data; based on the seat stress model, a seat comfort optimization strategy is generated, and the seat comfort optimization strategy at least comprises one of a material optimization strategy, a softness optimization strategy and a seat contour optimization strategy. By means of the technical scheme, the angle and the supporting degree of the seat can be accurately adjusted so as to ensure that the comfort level of the seat can be improved, driving fatigue can be reduced, driving safety can be improved, and user experience can be improved.

Examples may provide an electronic neural network that has been trained on a set of training data that comprises a plurality of reference subject medical data sets that are each labeled with a medical determination and are each assigned a ground truth concordance score generated by a plurality of experts in which a value of a given ground truth concordance score comprises a fraction of the plurality of experts, if any, that are in accord with the medical determination label of a given reference subject medical data set in the plurality of reference subject medical data sets. The electronic neural network is configured to provide an output concordance score of the medical determination being indicated by a test subject medical data set.

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.

A system may include a headset device comprising a display screen positioned proximate to, or within a viewable distance from a user's eyes. The headset device may be communicatively coupled to one or more processors. The system may cause the one or more processors to display a stimulus to a test subject (e.g., a patient), store in computer memory a response of the test subject to the displayed stimulus, analyze the response based on a location of the displayed stimulus, and provide feedback to the test subject based on the response and analysis.

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.

Methods, systems, and software are provided for estimating a circulating tumor fraction (ctFE) for a test subject. Sequence reads are obtained from a panel-enriched sequencing reaction, including sequences for cfDNA fragments corresponding to probe sequences and sequences for cfDNA fragments not corresponding to probe sequences. Bin coverage values are determined from the sequences. Segments are formed by grouping adjacent bins based on similar coverage value and segment coverage values are determined based on bin coverage values for bins mapping to each segment. For each simulated ctFE in a plurality of ctFEs, segments are fitted to an integer copy state by identifying the integer copy state that best matches the segment coverage value. The circulating tumor fraction for the test subject is determined using error optimization between segment coverage values and integer copy states across the simulated ctFEs.

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.

The invention relates to a kit for diagnosing non-small cell lung cancer as well as a use method and application thereof, and belongs to the field of biological medicines. The kit comprises reagents required by RNA extraction and reverse transcription, and a PCR amplification system containing primers and probes for respectively and specifically targeting SFTPA1 and SFTPA2 genes, wherein the PCR amplification system comprises primers and probes for respectively and specifically targeting SFTPA1 and SFTPA2 genes; the 5'end of the probe is provided with a fluorophore, and the 3 'end of the probe is provided with a quenching agent; the probe and the primer are designed based on specific regions of SFTPA1 and SFTPA2 genes, so that high specificity and high sensitivity of the probe and the primer in gene expression detection are ensured. The use method of the kit comprises the following steps: extracting RNA (Ribonucleic Acid) in a detection sample, reversely transcribing the RNA into cDNA (Complementary Deoxyribose Nucleic Acid), detecting the expression levels of the SFTPA1 and SFTPA2 genes by utilizing a qPCR (Quantitative Polymerase Chain Reaction) technology or a dPCR technology, and finally, preliminarily diagnosing whether a detection object suffers from the non-small cell lung cancer or not by comparing the expression differences of the SFTPA1 and SFTPA2 genes of the detection object and healthy people and non-small cell lung cancer patients. The invention provides a reliable tool for early diagnosis and individualized treatment of the non-small cell lung cancer.