239 results about "Biological signaling" patented technology

In a training control method using biofeedback, and an apparatus using the method, the method includes setting a target exercise zone for a user based on a bio-signal from the user, the target exercise zone including a range of indices and comparing a current index obtained from the bio-signal with the target exercise zone in time units in an exercise training mode and providing at least one of positive biofeedback information, negative biofeedback information, and a warning message to the user according to a result of the comparison.

A flexible membrane of piezoelectric material sized to be supported by and to conform to the eardrum. Electrodes on the membrane allow the membrane to function as an audio transducer stimulating the eardrum with an audio signal or detecting audio signals at the eardrum. Applications may include detecting a variety of pathophysiological and biomechanical features of the tissues of the tympanic membrane and regional integrated anatomy, detecting audio, physical and biological signals, and/or delivery a variety of therapeutic modalities.

A method and apparatus for measuring the biological condition of an animal by acquiring and analyzing its biological signals are provided. The biological signals from skin temperature, a photoplenthysmogram (PPG), an electrocardiogram (ECG), electrodermal activity (EDA), an electromyogram (EMG), and an electrogastrogram (EGG) are detected using a biological signal detection unit which is attached to the animal's skin. Feature vectors, including the mean heart rate of the photoplenthysmogram and its standard deviation, the very low frequency, low frequency, and high frequency components of heart rate variability, the frequency and mean amplitude of skin conductance responses, and the mean and maximum skin temperatures, are extracted from the detected biological signals. The biological condition, including needs and emotions, of the animal as to whether or not the animal feels hunger or fear, how much the animal is stressed, or whether or not the animal needs to have a bowel movement, is determined using a pattern classifier which has learned reference vectors, which reflect the behaviors, needs, and emotions of different kinds of animals for various biological conditions and are stored in a predetermined database. Therefore, the biological condition of the animal can be determined through instrumental communication, not through human languages, and the breeding of pets can be efficiently managed.

A method and system for customizing agriculture management using biological signals and making decisions according to pre-programmed algorithms, including decisions related to irrigation, prediction of future yield, characterization of plant varieties, and administration of topical applications.

A biological signal measurement device includes: a circular or hyperbolic fitting section (101) to be worn on a part of a human body; a sensing section (103) which is provided to the fitting section (101), and senses a biological signal by being closely attached to a specific part of the human body; a measurement environment judging section for judging an environment for measuring the biological signal by using the sensing section (103); a measurement environment notifying section (104) for notifying a user of a judgment result, according to the result of judgment performed by the measurement environment judging section; and a measurement environment adjusting section (102) for adjusting the measurement environment of the sensing section (103). Thus, it is possible to provide a human-wearable biological signal measurement device that allows easier maintenance of suitable measurement conditions.

The invention discloses an upper limb rehabilitation system based on biological signals. The upper limb rehabilitation system based on the biological signals is characterized in that a brain electric cap is attached to the surface of a brain, brain electric signals can be sensed through the brain electric cap, features of the brain electric signals are extracted and classified sequentially through a CSP feature extraction algorithm and a classifier with an adaptive LDA classification algorithm after amplification, filtering and noise reduction are performed on the brain electric signals, and then the brain electric signals are translated into drive instructions used to control drive motor equipment and pneumatic tendon auxiliary equipment, a system central processing unit fuses and sorts the drive instructions and motion state data collected by a motion state collector, and then feeds the drive instructions and the motion state data, which are fused and sorted, back to the drive motor equipment, the pneumatic tendon auxiliary equipment and a mobile terminal, and therefore a mechanical arm is driven to perform rehabilitation exercise. Work personnel remotely monitor motion and rehabilitation states of patients through the mobile terminal, and the patients also can invoke rehabilitation games in a display platform through a voice input and output device so as to perform auxiliary rehabilitation training. Accordingly, the upper limb rehabilitation system based on the biological signals improves training effectiveness of the patients, and simultaneously guarantees safety and stability in the training.

Disclosed is a method and apparatus for detecting a state of a vehicle occupant, wherein a bio-signal of an occupant riding in a vehicle may be acquired by executing an artificial intelligence (AI) algorithm or a machine learning algorithm, and a physical change of the occupant may be measured by a movement signal, a respiratory signal, and a heart rate signal from the acquired bio-signal of the vehicle occupant, such that it is possible to control an operation of an internal vehicle device or to control operation of the vehicle so as to correspond to the physical change of the occupant estimated by communicating with the internal vehicle device in a 5G communication environment. According to the present disclosure, the movement signal, respiratory signal, and heart rate signal of the occupant in the vehicle may be extracted via an RF sensor mounted in the vehicle, and the physical state of the occupant may be estimated based on the extracted bio-signal of the occupant, and when the physical state is estimated to be abnormal, the occupant may be informed of the abnormal physical state.

The invention relates to a chip of a surface plasmon resonance instrument which is based on polyethylene glycol and a preparation method. The chip comprises a glass film base and a gold plating film on the glass film base; wherein the gold plating film is provided with an initiator layer which is introduced in the way of self-assembly and a functionalized polyethylene glycol layer which is combined with the initiator layer. The invention uses a quartz crystal microbalance to monitor the growth of the film at the surface of the chip at real time and the chip of the invention effectively solves the problem of non-specific absorption of protein. As the surface ornament of the chip is not limited to traditional carboxylic dextran, the density and types of the functional groups at the chip surface are no longer strictly restricted. Furthermore, the chip of the invention also has good performance in terms of the specificity maintenance and quality control of biological signaling molecule and so on. The preparation method of the chip of the invention has few steps and the low manufacturing cost and is more suitable for industrial production. The chip has more potential of deep development and more superior generality.

The invention relates to an intelligent biological signal anomaly detection method and a system capable of carrying out efficient, accurate and low-cost automatic analysis on biological signals. The system comprises a model training stage and a model application stage, wherein the model training stage comprises the following steps: acquiring a biological signal; preprocessing the acquired signal;sending the preprocessed data to a CNN-BilSTM-Attention combination model to extract features, wherein the signal firstly enters a CNN convolution neural network to extract the spatial features, thenenters a two-way long-short time memory network to extract time features, then passes through each network connection layer and finally passes through a SoftMax layer to calculate the final result, each link of the network is established, and the emphasis degree of different sequence points of signals are optimized by setting an Attention mechanism; calculating loss of the network module until themodule loss is less than the threshold, then the model training is completed, and otherwise Adam is used to optimize model parameters. The invention effectively improves the analysis effect of biomedical signals.

The invention relates to a preparation method and application of an electrochemical sensor for heavy metal lead ion detection and belongs to the technical field of electrochemical detection. The biosensor is characterized in that firstly, an NG-PTCA nanomaterial is synthesized, then, HAuCl4 is reduced to gold nanoparticles (AuNPs) through Thi and modified on the NG-PTCA nanomaterial to obtain an NG-PTCA-Thi-Au nanocomposite, and a hairpin-like DNA signal probe is mixed with the composite to prepare a biological signal probe; before construction of the sensor, 8-17 DNAzyme is cut in vitro in the presence of Pb<2+>; then, the hairpin-like capture probe is fixed by a gold deposition electrode; after introduction of a cut fragment S1, a catalytic hairpin assembly process is started and the biological signal probe is fixed, so that double-signal detection of heavy metal lead ions is realized. The sensor is successfully applied to detection of lead ions in the environment. The biosensor hasthe advantages of high sensitivity, high specificity and convenience in detection. The biosensor provides experiment basis for research and development of the lead ion detection technology and provides a new thought and a new technical platform for monitoring of lead ions in the environment.

The invention relates to a preparation method and application of an electrochemical sensor for detecting a blood concentration level of an insulin sensitivity reduction early diagnosis biomarker, namely galectin-3 (Gal-3), causing type II diabetes, and belongs to the technical field of electrochemical detection. The preparation method is characterized by comprising the following steps: respectively synthesizing an N-GNRs-Fe-MOFs@AuPNs sensor substrate modified nano composite material and an AuPt-MB nano composite signal material, enabling a detection antibody capable of being in specific binding to the Gal-3 to be mixed with the AuPt-MB composite material so as to prepare a biological signal probe; conjugating a Gal-3 specific capture antibody on a substrate platform modified by the N-GNRs-Fe-MOFs@AuPNs composite material so as to conveniently and specifically capture a target Gal-3; finally, performing specific binding on the Gal-3 as well as the detection antibody and the capture antibody, thereby obtaining the electrochemical sensor for detecting the blood concentration level of the Gal-3. The sensor is successfully used for detecting the Gal-3 in serum. The electrochemical sensor disclosed by the invention has the advantages of being high in sensitivity, high in specificity, rapid in detection and convenient. An early diagnostic basis is provided for insulin resistance causing the type II diabetes.

This invention is a model that simulates the complexity of biological signaling in a cell in response to radiation therapy. Using gene expression profiles and radiation survival assays in an algorithm, a systems model was generated of the radiosensitivity network. The network consists of ten highly interconnected genetic hubs with significant signal redundancy. The model was validated with in vitro tests perturbing network components, correctly predicting radiation sensitivity 2/3 times. The model's clinical relevance was shown by linking clinical radiosensitivity targets to the model network. Clinical applications were confirmed by testing model predictions against clinical response to preoperative radiochemotherapy in patients with rectal or esophageal cancer.

The invention relates to a preparation method and application of an electrochemical sensor for achondroplasia prenatal diagnosis gene-fibroblast growth factor receptor 3 (FGFR3) gene polymorphism detection, belonging to the technical field of electrochemical detection. The preparation method is characterized by comprising the following steps: synthesizing a Hemin-MOFs composite material, reducing platinum nanoparticles onto the Hemin-MOFs composite material, and mixing a single-strand DNA signal probe with the composite material to obtain a biological signal probe; and carrying out layer-by-layer self-assembly by using reducible graphene oxide tetraethylenepentamine, nano gold and avidin to fix the biotinylated DNA capture probe, thereby preparing the electrochemical sensor for FGFR3-1138G>A gene polymorphism detection. The sensor is successfully used for detecting FGFR3-gene single base mutation. The sensor has the advantages of high sensitivity and high specificity, and is quick and convenient for detection. The invention provides a new detection method for prenatal noninvasive diagnosis of achondroplasia.

The invention discloses a personal safety protection mode which comprises the steps of logging into an information platform to input information of a safety equipment carrier, collecting fingerprint and/or sound information of a guardian, periodically obtaining the location information of the safety equipment carrier, sending the location information to the information platform, and monitoring the location information of the safety equipment carrier and alarm information through an intelligent terminal. The invention further provides a personal safety protection system. The personal safety protection mode and system have the advantages that a locating module periodically receives location information sent by a navigational satellite, and the guardian logs in to the information platform through the intelligent terminal and observes location information of safety equipment every time received by the information platform to judge the movement locus of the safety equipment carrier; it is guaranteed that only the guardian can control the normal starting and closing of the safety equipment through collection of biological signals of the guardian; the safety equipment can give an alarm when a closed loop structure is destroyed, important information and precious rescuing time are provided for the guardian and police.

The present invention provides a light-weight wearable sensor that can capture electroencephalogram (EEG or brain signals), electromyography (EMG or muscle signal), and electrooculography (EOG or eye movement signal) using a pair of modified off-the-shelf earplugs. The present invention further provides a supervised non-negative matrix factorization learning algorithm to analyze and extract these signals from the mixed signal collected by the sensor. The present invention further provides an autonomous and whole-night sleep staging system utilizing the sensor's outputs.

An electronic device is disclosed. The electronic device identifies a user on the basis of: a biological signal input unit for receiving the input of a user's biological signal detected through an electrode; a voice input unit for receiving the input of a voice signal; a biological signal inputted through the biological signal input unit; and a voice signal inputted through a microphone.

The invention discloses a signal amplification immunodetection method. According to the method, signal amplification immunity quantitative detection is conducted through a filter, and the method comprises the step of adopting the filter for sequentially filtering a to-be-detected sample solution A containing objects to be detected, a detected object solution B labeled through avidin and an indicator solution C labeled through biotin, wherein a filter element of a filter layer of the filter is a solid phase material coupled to a specific binder of the objects to be detected, detected objects labeled through the avidin can be specifically bound to the objects to be detected, and thereby the quantity of the objects to be detected in the solution A is calculated according to the color or light quantity variation of an indicator. It is proved through experiments that compared with a conventional biotin-avidin amplification reaction sequence, the avidin-biotin amplification reaction sequence has a greater biological signal amplification effect. The method can be used for detecting samples which are from human bodies and animal bodies and can be subjected to disease diagnosis and health detection and applied to development of products for sample quantitative immunodetection in the fields of environment, pharmaceutical analysis, food and industrial analysis.

An apparatus, system, and method of a brain computer interface in a headset including an augmented reality display, one or more sensors, a processing module, at least one biofeedback device, and a battery. The interface may include a printed circuit board that has the sensors to read bio-signals, provides biofeedback, and performs the processing, analyzing, and mapping of bio-signals into output. The output provides feedback via stimulation of multiple sensory brain systems of a user, including audio and visual on the augmented reality display, or audio and haptic in terms of vibration patterns that a human user may feel. All together this forms a closed-loop system, by detecting the bio-signal, then providing sensory-feedback, which in turn enhances the bio-signal.

The invention relates to the field of biological signal monitoring, and provides an alarm management method, an alarm management device and a supervision device. The alarm management method comprises the following steps of: 1, establishing an alarm pool comprising a plurality of nodes, wherein each node comprises a storage part for storing alarm information and a pointer part for storing an address; 2, setting an alarm chain for mounting the nodes storing the alarm information, wherein the alarm chain comprises a first pointer for storing the address of a first mounted node; and 3, when alarm information is received, selecting a node from the alarm pool by using the processor, storing the alarm information into the storage part of the node, and mounting the node in the alarm chain. According to the alarm management method, the limitation of subdivision is avoided, and the alarm chain can be randomly allocated to the nodes in the alarm pool according to needs, so that alarm failure risks when the alarm information is generated in a centralized way are greatly reduced.

The present disclosure provides a delirium risk predicting method which includes receiving at least one of blood data, severity evaluation data, mental state evaluation data, and bio signal data, medication data, and medical treatment data, for an subject, predicting a delirium risk for the subject, using a delirium risk prediction model configured to predict a delirium risk, based on at least one data, the medication data, and the medical treatment data, and providing the delirium risk predicted for the subject. The at least one data, the medication data, and the medical treatment data are defined as initial data which is evaluated or measured only once for the subject and a delirium risk predicting device using the same.

A patient health management platform accesses a metabolic profile for a patient and biosignals recorded for the patient during a current time period comprising sensor data and/or lab test data collected for the patient. The platform encodes the biosignals into a vector representation and inputs the vector representation into a patient-specific metabolic model to determine a metabolic state of the patient at a conclusion of the current time period. The patient-specific metabolic model comprises a set of parameter values determined based on labels assigned to the previous metabolic states and a function representing one or more effects of the plurality of biosignals of the personalized metabolic profile. The platform compares the determined metabolic state of the patient to a threshold metabolic state representing a target metabolism. The platform generates a patient-specific treatment recommendation outlining instructions for the patient to improve the determined metabolic state to the functional metabolic state.

The present invention relates to bone substitute compositions and methods of their preparation, and their use in a wide variety of clinical applications. The compositions include calcium phosphate, acidic calcium salt, basic calcium salt, sodium hydrogen phosphate and porogen. The compositions further include a mixing liquid. The compositions can optionally include biological signaling molecules and/or a growth compound. Further, the compositions can optionally include a plasticizer.

The invention belongs to the field of biological signals and intelligent processing, and particularly relates to a wearable electrocardio health interactive platform based on social network and an implementation method thereof. Electrocardio data of a patient is collected through a wearable electrocardio collecting system, an electrocardio data transmission system transmits the electrocardio data collected through the wearable electrocardio collecting system to a mobile phone client side, the electrocardio data is saved, and an electrocardio oscillogram is displayed; the mobile phone client side sends the electrocardio data to a group through social software, an administrator of the group uses an electrocardio data preprocessing system for preprocessing and analyzing the electrocardio data through an electrocardio data preprocessing system, and a doctor receives the pre-analyzed and processed electrocardio data, checks the electrocardio waveform through a doctor mobile phone client side to analyze the electrocardio waveform and feeds a diagnosis and suggests back to the patient in a short message or calling form. The wearable electrocardio health interactive platform has the advantages that the communication mode between the user in electrocardio monitoring and the doctor is changed, the information transmission speed is increased, the electrocardio data is collected in real time, the diagnostic feedback of the doctor is obtained in time, the risks of diseases are reduced, and an alarm can be given in time.

The invention discloses an upper limb exoskeleton mechanical arm and a control method of rehabilitation training, and the rehabilitation training is guided by medical staff and self-adaptive to patient limbs. According to the invention, the movement trajectory of rehabilitation training is recorded by a teaching mode, patient exercise intensity is identified by a deep learning framework, the identified results are embedded into an overall rehabilitation training control strategy based on deep reinforcement learning, and the adjusted joint movement rate signals are output to the mechanical arm to complete the rehabilitation training. On the premise of preventing secondary injuries of patients from the rehabilitation training, the method can eliminate the influence of hysteretic nature of movement signals and individual differences of bioelectric signals, improve the identification accuracy of exercise intensity and broaden the application area of rehabilitation movement trajectory by the vector fusion of movement signals and biological signals, so as to achieve advantages of reducing the burden of medical staff and optimizing the rehabilitation cycle of patients, thus improving the safety and applicability of the rehabilitation training.