85 results about "Wearable sensing" patented technology

The invention provides an artificial intelligence spinal nerve regulation and control system and method based on a multi-modal physiology-nerve-experience closed loop, and relates to the technical field of medical instruments, the system comprises an implantable stimulation and sensing subsystem, a body surface and wearable sensing subsystem, a communication and time synchronization subsystem and a control processing unit, the implantable stimulation and sensing subsystem, the body surface / wearable sensing subsystem and the control processing unit are in communication connection in pairs through the communication and time synchronization subsystem. According to the method, the fundamental limitation that in the prior art, only dosage is maintained, and brain and subjective experience is ignored is broken through, and more stable, more efficient and more personalized accurate pain management is realized through multi-modal fusion and hierarchical cooperative control.

The invention belongs to the technical field of physical ability analysis and diagnosis, and particularly relates to a latent variable fusion modeling method and system for old people weakness trajectory prediction based on biomechanics. According to the method, the plantar pressure, the joint angle and the electromyographic signal in the gait process of the elderly are collected through wearable sensing equipment, multi-dimensional structured feature parameters are extracted, and a key index group reflecting the weakness degree is generated based on preset weight fusion. And in combination with time sequence fitting and variation trend analysis, dynamic evaluation and risk level judgment of the weakness state of the old people are realized. The system comprises a data acquisition module, a feature extraction module, an index fusion module, a trend analysis module and a result output module, has the characteristics of high accuracy, strong real-time performance, good interpretability and the like, and is suitable for weakness risk screening and rehabilitation intervention guidance.

The invention discloses a badminton player action posture analysis system and method based on multi-sensor fusion, and relates to the technical field of athletic training auxiliary systems.The system comprises a wearable sensing subsystem, an environment sensing subsystem and a central processing and feedback subsystem; the wearable sensing subsystem is arranged on an inertia measurement unit and a pressure sensing insole of a body to collect movement inertia and plantar pressure data; the environment perception subsystem collects global videos through multiple cameras. The central processing and feedback subsystem performs synchronous processing on multi-source data, adopts a hierarchical fusion algorithm, restrains inertia integral drift by utilizing a plantar contact state, reconstructs a three-dimensional skeleton posture and a motion trail in combination with visual key points and skeleton restraint, drives a digital twin model, compares with a standard motion model, and performs three-dimensional motion control on the three-dimensional skeleton posture and the motion trail. Quantitative evaluation results such as joint angle deviation, time sequence difference and pressure center track are generated, and visual feedback is performed through a display device and an augmented reality terminal for badminton training evaluation and technical deviation correction.

The invention discloses a dynamic risk early warning method and system based on student exercise data. The method comprises the steps that S1, original exercise data of student exercise is collected through wearable sensing equipment; s2, obtaining mapping motion data through an improved near-end depth Q network based on the original motion data and the normal motion data; s3, according to the mapping relation data, obtaining an action risk point through threshold comparison and considering duration time; and S4, performing matching detection on the obtained action risk points through an abnormal action chain type detection mechanism based on motion time-space association to obtain a risk prediction result, thereby avoiding misjudgment of a single tiny deviation as a risk, capturing a damage trend of a continuous abnormal action, scientifically fitting a motion damage occurrence rule, and accurately adapting to various campus motion scenes.

The invention discloses an intelligent monitoring system for tumor nursing. The intelligent monitoring system comprises a wearable sensing terminal group, a patient terminal, a cloud platform intelligent analysis center and a medical care terminal. The wearable terminal is used for collecting multi-modal physiological and behavior data such as electroencephalogram, near-infrared brain blood oxygen, heart rate variability, body movement, electrodermal response and gaits; the patient terminal is used for recording subjective symptoms and completing cognition and exercise task evaluation. The cloud platform intelligent analysis center constructs a multi-parameter individualized baseline through data fusion, noise suppression and time alignment, comprehensively analyzes real-time deviation, electroencephalogram abnormality, cognitive deviation and gait change by using a short-term acute early warning model and a long-term trend early warning model, and generates a risk level. The digital twinborn visualization module is used for dynamically displaying the state of the patient, and the medical care terminal performs clinical response based on the graded alarm board. According to the invention, extra-hospital multi-mode continuous monitoring, individualized trend identification and intelligent early warning can be realized, and the real-time performance of follow-up management of brain tumor patients is improved.

Disclosed are systems and techniques for proximity detection using a wearable sensing device. An example method can include obtaining sensing data based on one or more wireless signals, the sensing data comprising at least one of a proximity measurement and a distance measurement; determining, based on the sensing data, a spatial relationship between a device associated with a user and a source of the one or more wireless signals; determining whether the spatial relationship satisfies a proximity condition associated with a distance threshold; and based on a determination that the spatial relationship satisfies the proximity condition associated with the distance threshold, triggering a sensory alert via one or more output components.

Disclosed are systems and techniques for proximity detection using a wearable sensing device. An example method can include obtaining sensing data based on one or more wireless signals, the sensing data comprising at least one of a proximity measurement and a distance measurement; determining, based on the sensing data, a spatial relationship between a device associated with a user and a source of the one or more wireless signals; determining whether the spatial relationship satisfies a proximity condition associated with a distance threshold; and based on a determination that the spatial relationship satisfies the proximity condition associated with the distance threshold, triggering a sensory alert via one or more output components.

The invention discloses a wearable sensing system and a respiratory wave generation and respiratory rate estimation method thereof, relates to the field of respiratory processing, solves the problem that respiratory waves and respiratory rates cannot be accurately analyzed based on electrocardiograms, and comprises a data processing module, a stacking convolution module, a respiratory discrimination module, a signal demodulation module and a data calculation module. The data processing module is used for performing initial processing on an electrocardiogram of a person to be detected; the stack convolution module is used for performing stack convolution on the voltage intensity sequence of the heart of the to-be-detected person and the convolution kernels in different convolution layers to obtain a respiratory wave sequence of the to-be-detected person; the respiration discrimination module is used for discriminating a respiration wave sequence of a person to be detected; the signal demodulation module is used for carrying out signal demodulation on the respiratory wave of the person to be detected to obtain a final respiratory wave; and the data calculation module is used for calculating the respiratory rate of the to-be-detected person. According to the invention, accurate analysis of the respiratory wave and the respiratory rate based on the electrocardiogram is realized.

The invention provides a personalized training subject adaptive generation and recommendation method for an unmanned aerial vehicle driver, and the method comprises the steps: collecting environment dimensions and physiological and psychological state data through a flight simulator and wearable sensing equipment, carrying out the time-space alignment and normalization processing, discretizing situation parameters through the combination of the statistical features of a sliding time window and a clustering algorithm, and carrying out the adaptive generation and recommendation of a personalized training subject. Forming a standardized situation mode label set; performing off-line modeling on a situation compensation function library by utilizing historical behavior data and situation characteristics to realize accurate evaluation on various situation influence coefficients; in the real-time evaluation, the skill score and the situation adjustment amount are dynamically fused through the gating proportion parameter, personalized correction is carried out based on the personal historical offset characteristics, the stable and adaptive calibrated skill score is output, and the fairness, accuracy and individualization level of training evaluation are effectively improved.

This invention relates to a wearable, integrated, self-powered pressure sensing device based on a flexible zinc-sodium hybrid battery and its fabrication method. The device includes an integrated sensor and a signal processing unit. The integrated sensor comprises a sensing layer, a shared positive electrode layer, and a battery layer arranged sequentially from top to bottom. The signal processing unit is connected to the sensing layer, the shared positive electrode layer, and the battery layer. This invention effectively overcomes the challenges of baseline instability and mechanical failure of flexible devices in complex environments by leveraging the sensitivity enhancement effect of MXene nanosheets, the zero-drift control technology of nylon mesh, and the low-temperature antifreeze mechanism of ethylene glycol (EG). This invention opens up a key path from "modification of basic electrochemical materials" to "portable terminal system applications," truly realizing portable, wide-temperature-range, and long-life in-situ online monitoring of human physiological signals, providing a new design paradigm for the engineering implementation of next-generation high-performance, low-power wearable sensing systems.

The invention is applied to the field of sleep management, and discloses a sleep state recognition regulation and control method and system.The method comprises the steps that piezoelectric signal data captured by piezoelectric sensing equipment and optical pulse signal data captured by wearable sensing equipment in the sleep process of a target user are obtained; body movement artifact removal processing is conducted on the piezoelectric signal data and the optical pulse signal data, and first piezoelectric signal data and first optical pulse signal data are obtained; performing fusion processing on the first piezoelectric signal data and the first optical pulse signal data to obtain a target fusion feature; determining a sleep type of the target user based on the target fusion feature, performing sleep state recognition on the target fusion feature based on the sleep type, and generating a sleep core index corresponding to a recognition result; and according to the sleep type and the sleep core index, generating and executing a sleep regulation strategy of the target user. According to the method, the sleep quality of the user is improved.

The invention relates to an organic heterojunction-based light-temperature dual-response sensor element, which is prepared from a substrate, a source electrode, a drain electrode, a grid electrode, an organic active layer, a dielectric layer and a device encapsulation layer, and is characterized in that the organic active layer is composed of a Rho group and an imide group in a Rho diimide system organic small molecular structure; the compound has a long conjugated molecular structure, and charge transfer and energy level matching can be effectively promoted. The organic heterojunction structure has the advantages that the organic heterojunction structure has an interpenetrating network form, the donor-acceptor interface area is remarkably increased, so that the charge separation efficiency is enhanced, the carrier mobility is improved, the transconductance, the on-off ratio and the stability of a sensor element are improved, and the organic heterojunction structure has good solution processability and can be applied to the field of sensor devices. The method is suitable for large-area and low-cost flexible electronic manufacturing. The invention provides a new material system for light and temperature dual-response sensor elements, and has wide application prospects in the fields of wearable sensing, Internet of Things, environment monitoring and the like.

The invention discloses a rehabilitation treatment evaluation method and system based on wearable equipment, and relates to the technical field of medical rehabilitation. The system comprises a wearable sensing module, a wireless communication module, a cloud data processing module, a man-machine interaction module and an auxiliary stimulation module. The wearable sensing module collects joint movement, muscle movement and stress parameters in a non-invasive mode. According to the method, through closed-loop processes of equipment preprocessing and personalized configuration, adaptive model training, real-time data acquisition, cloud quantitative evaluation and multi-dimensional feedback adjustment, full-chain coverage of'perception-analysis-evaluation-feedback 'of rehabilitation treatment is realized. According to the method, the defect that a cognitive movement therapy lacks quantitative indexes is overcome, the problems that traditional rehabilitation evaluation is subjective and a sensor can only detect and cannot assist in treatment are solved, rehabilitation treatment standardization, individuation and high efficiency are achieved, the labor cost is reduced, the rehabilitation quality is improved, and the method is suitable for rehabilitation scenes such as cerebral apoplexy and movement injury.

Various components, methods, and systems are provided herein for monitoring physiological responses associated with force-impact events using a mouth-wearable sensing device positioned within an oral cavity of a subject. In some embodiments, the device integrates inertial sensing, force sensing, temperature sensing, and optical physiological sensing on a compact intraoral substrate and transmits physiological data wirelessly to an external computing device for analysis and reporting. In some embodiments, the mouth-wearable sensing device is customized using intraoral scan data to generate a three-dimensional oral cavity model and to position one or more sensors to align with anatomical landmarks when worn.

A personal electronic device and wearable sensing system includes one or more dermal-contact electrochemical sensors integrated into one or more skin-contact surfaces of the electronic device, wearable, accessory, or interactive electronic system. The electrochemical sensors obtain measurements indicative of one or more analyte classes associated with a user. One or more additional sensors obtain non-electrochemical measurements associated with the user. A sensor-fusion module derives electrochemical and non-electrochemical features and generates a unified state estimate. One or more inference modules determine a user-state output based on the unified state estimate and a comparison of electrochemical-derived information, or features derived therefrom, to an individualized baseline reference profile associated with the user. In some embodiments, the analyte classes include endogenous physiological markers including glucose-related markers, exogenous exposure analytes, or both. In some embodiments, a credential derived from the individualized baseline reference profile is portable across multiple authorized devices within a trusted ecosystem.

The application provides a blind person discrimination device, system and method based on a distributed optical fiber sensing device.The device comprises an optical time domain reflectometer module, a signal preprocessing module, a signal cutting module, a signal feature extraction module and a signal classification module.The method provides a high recognition rate without video monitoring equipment and wearable sensing equipment, more comprehensively and effectively provides application support for the field of security and blind person travel, enhances the adaptability for different human body recognition, and identifies the source of the human body walking signal accepted by the current device, whether it is a visually impaired user or a normal user, so as to provide related services for the visually impaired user in the future.The long-time and short-time feature joint recognition mode is adopted in the feature extraction algorithm, and the accuracy is further improved.

According to the plug-in type interface between the flexible sensor and the mobile detector provided by the invention, the trapezoidal bulge structure with specific three-dimensional geometric parameters is constructed at the tail end of the polyimide substrate, and mechanical self-locking in the plug-in process is realized through the matching of the self-locking plate at the tail part of the patch and the limiting groove of the connector; therefore, the connection stability and the anti-seismic property are effectively improved. The structure does not need an additional clamping or fixing device, is suitable for a high-density and ultra-thin wearable sensing system, has the advantages of being small in size, high in self-locking force, capable of being repeatedly plugged and unplugged, simplified in manufacturing process and the like, can remarkably reduce the contact failure risk caused by mechanical vibration, and meets the development requirements of high-reliability flexible electronic products in the future. The pluggable interface between the flexible sensor and the mobile detector is arranged between the flexible sensor and the wearable mobile detector, and is suitable for a non-invasive continuous blood glucose monitoring and wearable medical electronic system.

The application provides a silk fabric sensor and application thereof in gesture recognition, and belongs to the technical field of flexible electronics and wearable sensing. X MXene nanosheets are functional fillers, and Ti X MXene nanosheets are loaded on the surface of silk fibers through an immersion coating process to form a core-shell structure conductive fabric, and Ti X MXene and silk fibroin are stably combined through a hydrogen bond network and electrostatic interaction, the water vapor transmission rate of the sensor is more than 2000 g / m²・day, the sensitivity coefficient GF in the low strain region of 0-18% is 149.31, and the sensitivity coefficient GF in the high strain region of 18-32% is 24.57. X MXene nanosheets are functional fillers, and stable combination of MXene and silk fibers is realized through optimization of a preparation process, so that the application has high sensitivity, good air permeability and excellent fatigue resistance, and a high-precision and low-delay gesture recognition and human-computer interaction system is constructed.

The invention discloses a holographic sensing high-voltage live-line anti-mistaken-entry locking method, and relates to a high-voltage live-line anti-mistaken-entry method, which is characterized in that a group of cable temperature information, current information, insulation aging information and partial discharge information which are monitored and acquired by a fusion monitoring device are respectively arranged in various power equipment and are uploaded to a monitoring department after being collected; a detection sampling module of an upper computer main control system of a monitoring department compares collected information with a multi-parameter model module, and after comparison, a parameter comparison module of the upper computer main control system sends information exceeding a preset value to portable sensing equipment of inspection personnel. The inspection personnel read the fault prompt problem of the corresponding cable through the OLED display screen of the inspection personnel carry-on sensing equipment, and the inspection personnel carry-on sensing equipment can carry out a specific maintenance task after receiving an operation notification; according to the invention, the fault information of the cable is obtained by fusing holographic sensing monitored by the monitoring device, and the inspection personnel carry-on sensing equipment ensures the electrified anti-mistaken-entry locking of the inspection personnel.

The invention relates to the technical field of artificial intelligence and self-powered wearable sensing, in particular to an intelligent insole based on a self-powered sensor array and a sole pressure behavior recognition method thereof. The system comprises a self-energized sensor array, a signal acquisition and processing module and a data analysis module which are arranged in an insole, the self-energized sensor array is composed of a plurality of friction nanometer power generation units which are arranged in an array mode, and the friction nanometer power generation units are arranged in the forefoot area, the arch area and the heel area of the insole respectively. Electric signals can be generated under the action of plantar pressure or impact without external power supply. The system performs synchronous acquisition, analog-to-digital conversion and normalization processing on the electric signals output by the friction nanometer power generation units to form multi-channel plantar pressure characteristic signals, and realizes reconstruction of plantar pressure distribution and identification analysis of behavior states based on the characteristic signals. The system can effectively reflect stress differences of different areas of the sole, can be used for distinguishing various motion behaviors such as walking and running, realizes self-energy-supply acquisition, visual perception and behavior recognition of sole pressure information, and has good application prospects in the fields of motion monitoring, gait analysis, health assessment and the like.

The present application relates to the technical field of intelligent monitoring, in particular to an old people fall monitoring and early warning method and system based on multi-source information fusion, the system comprising a visual perception module, a wearable sensing module, a central processing unit and an early warning module. The method is as follows: collecting human posture video stream, human waist three-axis acceleration and three-axis angular velocity, foot pressure, heart rate and blood oxygen physiological data in the monitoring area; respectively analyzing visual posture information, inertial sensing and foot pressure data, and extracting key motion features; comprehensively analyzing the features of the three types of information sources, especially using the MediaPipe framework to efficiently analyze human posture, combining with wearable sensor data, adopting a multi-modal feature fusion strategy based on attention mechanism, improving the accuracy of multi-source information fusion, so as to accurately judge the stability of the current posture of the old people and the fall risk level, and timely trigger the early warning, improving the accuracy and safety of the monitoring.

The invention discloses an antelope migration trajectory tracking and emergency risk avoiding system in a Qinling Mountain high-altitude environment. The system is composed of a wearable sensing unit, an edge calculation and self-adaptive sampling module, a non-uniform space-time gridding trajectory modeling unit, a risk field calculation and risk avoiding decision engine, a multi-channel low-duty-ratio communication and disaster recovery link, an emergency risk avoiding execution and linkage module and an operation and maintenance and safety audit module. By introducing a non-uniform space-time grid, risk field-velocity field coupling, a self-adaptive sampling frequency function, multi-channel link self-adaptive switching and an emergency risk avoiding instruction sequence, high-precision reconstruction of an antelope migration trajectory and dynamic generation of a risk avoiding path under a high-altitude complex terrain are realized; and the availability and the security of the system are kept in a communication limited scene.

This wearable sensing device (1) comprises: a base material (10) composed of a flexible material to be worn on the body of a measurement subject; a plurality of electrodes (11) disposed on the surface of the base material in contact with the skin of the measurement subject; a sensor terminal (12) that detects, via the plurality of electrodes (11), a current flowing through the body of the measurement subject and measures the impedance in the measurement subject; and a plurality of wires (13) that connect the plurality of electrodes (11) and the sensor terminal (12).

The invention discloses a feedback data management method for wearable sensing equipment after a cardiac valve operation, and relates to the technical field of data processing. The management method comprises the following steps: acquiring postoperative continuous dynamic original ECG data of a target patient, configuring an edge computing node, executing P-wave feature extraction and structured processing on the original ECG data, calculating to obtain a key feature parameter set, and executing a structured packaging processing action; combining an acquired clinical feature data set according to the key feature parameter set; the technical key points are as follows: when a Pmean trend correction mechanism and a Pmin fluctuation suppression mechanism are synchronously activated, a secondary collaborative correction strategy based on clinical credibility score is introduced, so that not only can a dominant mechanism be determined by quantitatively comparing pathological directivity of two types of signals, but also decision conflicts can be avoided through weighted fusion, and the accuracy of decision making is improved. The problem of logic confusion caused by parallel multi-source feedback signals is solved, and robustness decision-making in a complex scene is realized.

A wearable sensing device for detecting at least one analyte, comprising a device body comprising a first surface extending in a first plane and a second surface, wherein the first surface surrounds the second surface and the first surface is offset by an offset distance from the second surface along a longitudinal axis, the first surface being configured to receive adhesive means for affixing the device body to an application surface of a user, the device body further comprising a tapered surface extending between a taper first end and a taper second end, wherein the tapered surface adjoins the first surface and the second surface such that the taper first end is adjacent to the second surface and the taper second end is adjacent to the first surface, and an array of microneedles each extending along a microneedle axis that is parallel to the longitudinal axis, each microneedle extending through apertures in the second surface and comprising at least one electrode that is capable of generating an electrochemical response in the presence of at least one analyte. A taper first axis extends from the taper first end and is parallel to the longitudinal axis, and a first distance for each microneedle is defined as extending between the respective microneedle axis and the taper first axis in a direction perpendicular to the longitudinal axis, and wherein the first distance is 3.0 mm or less.

The invention discloses a low-power-consumption inductive patch inspired by organisms, and belongs to the field of flexible wearable devices. The bionic octopus island bridge structure comprises a bionic octopus island bridge structure configuration, an active communication module, a battery module, a passive communication module and a hybrid energy collection module, the bionic octopus island bridge structure configuration adopts the island bridge structure configuration, the bionic octopus island bridge structure configuration can better adapt to the human body curved surface, the communication mode is adaptively switched based on the battery electric quantity, the functions are diversified, and the application scene is wider. According to the invention, an effective reference is provided for the application of a low-power-consumption technology in the wearable sensing system and the novel configuration of the wearable sensing system, and the problems of single system function, high power and unstable radio frequency circuit when the patch is stretched in the flexible wearable field are solved.

The present invention relates to the field of diagnostics. In particular, it relates to a computer-implemented method for assessing a medical condition in a subject comprising the steps of determining the amount of at least one biomarker of interest for said medical condition in a sample of the subject, comparing the determined amount of the at least one biomarker to a reference, and assessing the medical condition in the subject based on the comparison and improving the reliability of the said assessment by integrating at least one clinical parameter value of the medical condition obtained from a dataset of continuously determined clinical parameter values comprising the said at least one clinical parameter value into the biomarker-based assessment, wherein the sample and the at least one clinical parameter value have been obtained from the subject within a short time window, wherein said at least one biomarker is determined continuously by using a point-of-care analytical device and / or wherein the dataset comprising the at least one clinical parameter is determined by a wearable sensing device. Moreover, the invention provides a system and a device for assessing a medical condition in a subject as well as the use of the amount of at least one biomarker of interest for said medical condition in a sample of the subject or a detection agent therefor for assessing a medical condition in said subject.

The application relates to the field of intelligent construction and man-machine interaction technology, in particular to an intelligent construction site auxiliary decision system based on augmented reality; the system comprises the following: a data acquisition module: through a wearable sensing device and augmented reality glasses, real-time acquisition of physiological and behavioral data of operators; a first processing module: generation of a cooperation trust index of a quantitative man-machine cooperation state based on the acquired data; a second processing module: combination of the cooperation trust index and a preset basic risk, evaluation and output of a current overall failure risk through a nonlinear evolution model; an adaptive decision module: determination and output of a final decision scheme according to the overall failure risk, combination of efficiency priority and resilience priority two utility functions; the application converts the physiological and behavioral data of the operators into quantitative state indexes by introducing the cooperation trust index, solves the problems that the man-machine cooperation state is fuzzy and difficult to accurately measure in the prior art, and provides a data basis for risk assessment and adaptive decision.

The application provides a kind of based on swallowable and wearable sensing detection mutton sheep vitality level evaluation method and system, it is related to wisdom breeding and agricultural internet of things technical field.The method of the application comprises: obtaining mutton sheep rumen habitat physiological data and body surface kinematic data;The two types of data are preprocessed and multi-source time series are registered, and a multi-dimensional heterogeneous feature fusion input matrix is constructed;Based on the preset intelligent evaluation model of double-domain feature fusion network, the evaluation model is obtained by supervised training and dynamic optimization;Real-time feature tensor is input into the evaluation model to output vitality level evaluation results by non-gradient forward reasoning.The method fuses rumen physiological parameters and motion behavior parameters, and realizes objective, continuous and automatic evaluation.

The application discloses a kind of intelligent wearable sensing system and method based on flexible metasurface.The one end of the one-dimensional periodic structure of the metasurface of the intelligent wearable sensing system is attached to the C-shaped ring, and the C-shaped ring, signal transmitter and signal receiving processor are electrically connected.The method comprises the following steps: attaching the one-dimensional periodic structure of the metasurface to the human body;transmitting radio frequency signals as standard signals by radio frequency signal transmitting circuit without action;transmitting radio frequency signals as to-be-detected signals when performing action, outputting reflection coefficient after analysis and comparison;obtaining the corresponding preset gesture action according to the reflection coefficient, transmitting it to the external intelligent device as the judgment result, and realizing the judgment of human body gesture action.The application of the system and method to metasurface material can confine electromagnetic waves on the surface of propagation, better confine energy, reduce loss, thereby increase the sensitivity of electromagnetic detection, and can be used for disabled people assistance, sports health monitoring and other aspects, and has good application value.