15 results about "Behavioral state" patented technology

This invention discloses a remote discrimination method for giant panda behavior based on collar sensors, specifically relating to the field of animal behavior monitoring using collar sensors. The method includes collecting behavior monitoring data output by the collar during continuous monitoring, arranging the data chronologically according to sampling times, and calculating the corresponding activity and displacement values ​​at each sampling time to obtain a monitoring sequence. Based on the direction of activity and displacement changes at adjacent sampling times in the monitoring sequence, the connection point where the direction of activity change changes and the displacement change state simultaneously change is determined as the behavior transition point. This invention solves the problems in existing technologies where the correlation between behavior transitions is difficult to retain, and the correspondence and stability between remote discrimination results and actual behavior states are insufficient. It extracts continuous segments around the behavior transition point before and after the transition and determines the behavior state based on the corresponding changes in these segments.

This invention provides an intelligent delivery room care system integrating multimodal environmental control based on sound, light, and temperature, belonging to the field of medical care equipment technology. By integrating multimodal environmental sensing and control capabilities based on sound, light, and temperature, combined with real-time analysis of the mother's physiological and behavioral states, this invention achieves intelligent, personalized, and contextualized management of the delivery room environment. Its main advantages include: significantly reducing the mother's anxiety and pain perception during childbirth, increasing the success rate of natural childbirth; reducing the burden of environmental control operations on medical staff, improving nursing efficiency; supporting adaptive environmental switching across multiple stages and scenarios, meeting the needs of the entire cycle from labor to postpartum recovery; ensuring the dignity of the mother and data security through non-invasive monitoring and privacy protection design; and a modular system design that facilitates integration with existing hospital information systems (HIS) and intelligent ward platforms.

This invention discloses an antenna reverse compensation method and system using digital twin virtual commissioning. The method acquires continuous behavioral data streams of the antenna system, reconstructs the state using a pre-associated physical characteristic computational model of the digital twin, and performs temporal evolution prediction using a data-driven fitting model to generate a behavioral state stream. Within the digital twin, a multi-dimensional deviation evolution analysis is performed between the behavioral state stream and a healthy baseline behavioral template to extract early covert mode feature sets. Based on this, a strategy self-exploration domain is defined in the virtual commissioning space. A perturbation action generator generates a perturbation action self-combination sequence and injects it into the digital twin, monitoring the repair state stream to construct a repair state mapping table. Finally, based on the repair state mapping table and the healthy baseline behavioral template, effective trial strategy clusters are selected, and the optimal reverse compensation strategy is selected based on the strategy stability metric, generating physical antenna reverse compensation commands.

This application discloses a music recommendation method, device, and vehicle. The music recommendation method includes: acquiring passenger images, with the number of passengers being no less than two; identifying the behavioral state characteristics of each passenger based on the acquired images, including the passenger's facial expression, whether the passenger is asleep, and the passenger's body posture; and analyzing the human body state data of each passenger based on the behavioral state characteristics, whereby the human body state data can characterize the user's cognitive and physiological state; recommending music that matches the human body state data of the same category when the number of passengers corresponding to the same category of human body state data reaches a first threshold; and recommending music that matches the human body state data of the category with the highest priority based on the priority of each category of human body state data when the number of passengers corresponding to the same category of human body state data does not reach the first threshold, thereby improving the user experience.

This invention discloses an energy-saving control method and device for a bird tracker based on sensor fusion. The method uses an accelerometer to collect triaxial acceleration data to identify the bird's behavioral state, activating the heart rate and blood oxygenation sensors only when the bird is stationary and deactivating them during movement. It combines illumination data, location information, and the device's real-time time to determine signal obstruction environments and dynamically adjusts the operating strategies of the positioning and communication modules. Before positioning calculation, it detects the number of satellites in a low-power mode, performing full positioning only when the target is met. Power management independently controls the on / off operation of the positioning, communication, and storage modules, with standby power supplied only to the real-time clock module. The corresponding device includes a main control unit, a sensor data acquisition and tracking unit, and an energy-saving control unit, integrating multiple types of sensors and a power management module. This invention significantly reduces the tracker's ineffective power consumption and extends its battery life in the field through multi-sensor fusion and dynamic energy-saving scheduling, adapting to the long-term monitoring needs of birds.

The invention relates to a method for operating at least one comfort system (16) of a motor vehicle (10), wherein an interior configuration device (22): receives an occupant observation signal (S1) that describes at least one behavior parameter relating to a current behavior of at least one user (12), and determines a current behavioral state of the user (12) (S2), receives a situation description signal (S3) that describes at least one situation parameter influencing the current journey, and categorizes the current journey based on a situation parameter (S4);Based on the combination of the determined behavior pattern and the specified driving category, a comfort fulfillment criterion is determined (S5) which describes the suitability of one or more settings of the at least one comfort system (16) for providing behavior-specific and situation-specific support to the user (12) during the journey, a configuration model is provided (S6) which describes a course of at least one configuration parameter for the at least one comfort system (16) over a specified driving period in order to fulfill the specified comfort fulfillment criterion, at least one configuration signal is generated (S8), and the at least one generated configuration signal is transmitted to a specified receiving device (16, 20) (S9).

Electronic system (1) designed to analyse and validate of emergency interventions of a vehicle according to a behavioural state of a subject driving the vehicle and comprising: a sensory system (2) configured to output signals indicative of physiological and image data related to the subject; and an electronic processing unit (3) in communication with the sensory system and being configured to receive the signals and process them to output corresponding statistical data related to the subject. The electronic system (1) is designed to process the data outputted by electronic processing unit (3) to determine a behavioural state and / or transitions thereof to determine the sleepiness level, the motion sickness level and the emotional state of the subject and generate a feedback to provide to an end user and provide emergency intervention to the subject based on the sleepiness level, the motion sickness level and the emotional state of the subject.

This invention provides a risk assessment-based fall prevention and management system for hospitalized patients, relating to the fields of smart healthcare and patient safety technology. It includes a multi-source data fusion module, which collects and processes diverse patient data to form a comprehensive dataset; the multi-source data fusion module includes an IoT sensor array; and a behavioral intent recognition module, which performs collaborative fusion processing on the IoT sensor array to form behavioral intent tags. This risk assessment-based fall prevention and management system for hospitalized patients, through multi-source data fusion and behavioral intent recognition modules, captures real-time changes in the patient's physiological and behavioral states, dynamically assesses fall risk, and forms an accurate dynamic risk profile of the patient. The fall prevention and management system for hospitalized patients overcomes the limitations of traditional static assessment methods, implements precise intervention for high-risk patients, and significantly reduces the probability of falls.

The present application provides a behavior analysis system and a behavior analysis method, which can analyze the behavior state of each person through the cooperation of each edge device and a server device even if the number of edge devices increases. An AI edge processor (10) of a behavior analysis system (100) has: an edge-side analysis section (12) that performs preprocessing in analysis processing of analyzing the behavior of an elderly person (40) from data obtained by photographing the elderly person (40); an analysis result extraction section (13) that extracts data containing information for determining the elderly person (40); and an analysis result transmission section (14) that transmits the data extracted by the analysis result extraction section (13) to a cloud server (20). The cloud server (20) has a server-side analysis section (23) that performs post-processing in the analysis processing from the data transmitted from the analysis result transmission section (14) and displays the analysis result on an analysis result display section (24).

This invention relates to the field of fire safety and emergency management, and discloses a method for planning evacuation routes during the fire growth phase. The method includes real-time collection of fire physical quantities, personnel distribution, individual characteristics, and behavioral states, while simultaneously digitizing building floor plans, evacuation routes, and obstacles. Based on multi-dimensional environmental and personnel data, it predicts fire spread, temperature, and smoke diffusion, generating a dynamic risk map. It assesses individual escape windows and threat levels, establishes behavioral models to analyze herd mentality and potential congestion, and generates multi-dimensional behavioral risk parameters. Using these multi-dimensional behavioral risk parameters as the core, it employs an ant colony algorithm to generate preliminary routes and combines VR, lighting, and sound to guide the crowd in real time. It executes a safe behavior flow plan, dynamically diverting traffic, providing backup routes, and intervening in abnormal behaviors. Simultaneously, it feeds back personnel behavior and environmental feedback data to generate a continuously updated risk model and adaptive guidance strategy. This invention has the advantage of improving evacuation safety.

Systems and methods for decision-making with multi-channel data inputs are provided. The system includes a plurality of devices, and a server in data communication with the plurality of devices. The server includes a decision engine, a sentiment analysis machine learning model, and a behavior analysis machine learning model. The server is configured to: receive the at least one data input from each of the plurality of device; perform, using the sentiment analysis machine learning model, a sentiment analysis on the at least one data input to generate sentiment information indicative of an emotional state of a user; perform, using the behavior analysis machine learning model, a behavior analysis on the at least one data input to generate behavior information indicative of a behavioral state of the user; determine, using the decision engine, a responsive action based on the sentiment information and the behavior information; and perform the responsive action.

An orchestration system for research utilizing a Sentiment Sensor, a Synthesis Engine, and an Autonomous Conversational Agent. The system captures behavioral State-Series Data, transforms it into synthesized qualitative prompts, and manages a voice-based moderation session following a Microphone Consent Gate. The entire process is programmatically bookended by a Third-Party Survey Platform via a Silent Handover mechanism.

This invention discloses a real-time emotion monitoring method and system based on a smart bracelet, relating to the field of bracelet monitoring technology. It collects behavioral perception data generated during the user's wearing of the smart bracelet, constructs a behavioral state feature set Mov representing the user's physical activity state, and generates a motion determination result Sta based on this. This clearly distinguishes whether the user is in a moving state before the emotion analysis process is initiated. Based on the motion determination result Sta, an emotion triggering result Trg is generated, ensuring that the emotion analysis process is only triggered when the user is not in a moving state. Physiological perception data is collected only within the time period indicated by the emotion triggering result Trg, allowing the execution of the emotion analysis process, and an emotion analysis dataset Emo is generated. This ensures that the data in the emotion analysis dataset Emo originates from physiological state intervals that better meet the preconditions of emotion analysis, improving the effectiveness and reliability of the emotion analysis.

This application provides a risk data analysis method and apparatus for a resource interaction risk control system, applied in the field of information security technology. It constructs a sequence of interactive behaviors with temporal characteristics; extracts multi-dimensional feature data from the sequence; performs state transition analysis within a preset behavioral state model based on operational logic and feature changes; calculates the degree of variation in input data and output results to identify potential data theft behaviors and side-channel anomalies; and finally integrates the analysis results to generate a real-time risk score and dynamically adjusts alarm thresholds according to preset scenario parameters to determine the existence of compliance vulnerability risks. Therefore, this application has the beneficial effect of identifying combined patterns of multiple independent behaviors with specific attack intentions.