7 results about "Fetal movement" patented technology

The application provides a wearing device based on promoting fetal movement and inducing fetal movement track, which comprises a wearable flexible base, an array of sound pickups, a sound collection detection module, a sound fetal education storage and playing module, an illumination fetal education LED lamp array, a system control module and a system power module are arranged on the wearable flexible base; the array of sound pickups is used for collecting fetal sound and fetal movement signals, converting the fetal sound and fetal movement signals into voltage signals that can be processed by a later unit, and sending the signals to the sound collection detection module.

The application provides a dynamic modeling method and system for multi-field skill AI automatic semantic labeling, and relates to information retrieval, medical health and cross-field skill fusion scene. Through nonlinear dynamic modeling and biomedical stability control, the semantic label automatic generation and real-time matching of talent skill and health intervention effectiveness are realized. The application innovatively integrates the sound wave frequency of fetal brain promoting music method, maternal action instruction and blood type nutrition scheme into the "skill-time" frequency domain space, combines the Gevrey smoothing operator and fractional derivative evolution equation, accurately separates the temporary fetal movement fluctuation and low-frequency core characteristics, and breaks through the characterization limitation of traditional models on nonlinear biological coupling effect. By introducing the "intervention effect-time" frequency domain component and local dependency constraint, the short-term effectiveness and long-term value of music intervention on fetal neurodevelopment are quantified, and the model distortion problem caused by extreme data or cross-field parameter resonance in traditional methods is solved.

This invention relates to the field of medical monitoring equipment technology, and discloses a wearable device for dynamic electrocardiogram (ECG) monitoring of pregnant women. The device includes a wearable base and an ECG acquisition component, a signal processing unit, and a power supply module mounted on the wearable base. The ECG acquisition component and the signal processing unit are electrically connected. The wearable base includes an upper fixing strap, a lower fixing strap, and a flexible mesh support base fixedly connected between the upper and lower fixing straps. The ECG acquisition component includes at least one ECG electrode and a fixing base. A temperature-sensing control component is disposed inside the ECG electrode. The ECG electrode is attached to one side of the pregnant woman's abdominal skin, and the side of the ECG electrode closest to the pregnant woman's skin has a concave arc-shaped portion adapted to the contour of the pregnant woman's abdomen. The fixing base is located on the side of the flexible mesh support base opposite to the skin. This device improves the accuracy and stability of acquiring weak fetal ECG signals through the temperature-controlled arc-shaped electrode adapted to the pregnant woman's abdomen and the detachable mesh base, simultaneously realizing fetal movement sensing.

This invention discloses a method and related equipment for predicting and intervening in the risk of stillbirth related to umbilical cord torsion. The method acquires multimodal clinical data, including the pregnant woman's complaints and prenatal ultrasound examination information, and standardizes the data to extract core predictive factors such as changes in fetal movement, signs of umbilical cord root torsion, and fetal growth restriction, as well as auxiliary predictive factors such as abnormal amniotic fluid volume and abnormal placental-umbilical cord insertion, constructing a feature vector that the model can process. Based on a pre-trained risk prediction model, the risk of stillbirth related to umbilical cord torsion is quantitatively assessed, a comprehensive risk score is output, and risk levels are classified. Based on the risk level, a pre-set clinical intervention strategy is automatically matched to form standardized treatment recommendations, which are then output to the clinical terminal. This method overcomes the limitations of traditional methods that rely on low sensitivity of single ultrasound diagnosis, achieving early risk identification and tiered management.

Disclosed is a method of determining fetal movement during pregnancy or labour. The method comprises receiving patient data from measurements from a first sensor and a second sensor attached to a patient, each of the first and second sensors being selected from a set of sensor types consisting of an EMG (Electromyography) sensor, a flex sensor and an accelerometer, the patient data from the second sensor allowing detection of fetal movement when physiological signals impede detection of the fetal movement in the patient data from the first sensor, wherein the first sensor is a different sensor type from the second sensor. The method also comprises determining that fetal movement has occurred by processing the received patient data from the first and second sensors in order to indicate the determined fetal movement.

The application relates to the technical field of sensors, and provides a preparation method of a strain-pressure sensor, a monitoring device and a monitoring method. The monitoring device based on the strain-pressure sensor comprises at least one strain-pressure sensor and a signal acquisition circuit module and a signal processing module which are uniformly distributed, the strain-pressure sensor generates a first resistance signal and a second resistance signal according to different physiological states, the signal acquisition circuit module outputs corresponding first digital signals and second digital signals based on the first resistance signal and the second resistance signal, the signals are transmitted to the signal processing module in a wireless transmission mode, and the signal processing module calculates and outputs continuous physiological information and analysis results of a user through a "double band-pass-peak value detection" algorithm and a "fetal movement monitoring" algorithm. Through the monitoring device, the problems of single function, insufficient sensitivity, difficulty in adapting to the slight deformation or jumping of human skin, lack of continuous monitoring capacity and the like of the existing health monitoring devices can be solved.

This application provides an intelligent analysis method and system for fetal movement monitoring, relating to the field of smart medical system technology. The method includes: receiving time-series data of the pregnant woman's abdomen from a fetal movement sensor array; filtering the time-series data of the pregnant woman's abdomen using a least mean square adaptive filter to determine the pregnant woman's fetal movement data; extracting fetal movement feature data corresponding to the pregnant woman's fetal movement data; selecting a predetermined number of memory units with the highest corresponding affinity from each memory unit to form an associated antibody cluster; determining the fetal movement abnormality risk value based on the fetal movement risk label and corresponding affinity of each antibody in the associated antibody cluster; if the fetal movement abnormality risk value does not exceed a preset risk threshold, it is determined that there is no fetal movement abnormality risk; and if the fetal movement abnormality risk value exceeds the risk threshold, it is determined that there is a fetal movement abnormality risk. Thus, continuous, real-time, and accurate intelligent monitoring and early warning of the pregnant woman's fetal movement status is achieved.