2000results about "Pressure sensors" patented technology

Various systems, devices, and methods are disclosed herein for treating acute myocardial infarction (AMI) patients using a heart pump controlled in a manner that maximizes mechanical unloading of the left ventricle in the presence of cardiovascular instability and minimizes myocardial oxygen consumption (MVO2) and consequentially infarct size to prevent the development of subsequent heart failure. In a closed feedback system, the system can include a sensor configured to generate an output used to measure or calculate a left ventricular systolic pressure (LSVP) within the left ventricle of a heart and a controller coupled to a heart pump. The controller can be configured to measure or calculate the LVSP based on the output of the sensor and to control an operation of the heart pump to maximize mechanical unloading of the left ventricle based on the measured or calculated LVSP.

A fluid management system for use in a tissue resection procedure includes a controller. An inflow pump is operated by the controller and configured to provide fluid inflow through a flow path to a site in patient's body. An outflow pump is operated by the controller and configured to provide fluid outflow through a flow path from the site in patient's body. A motor driven resecting device may be provided for resecting tissue at the site. The controller is configured to actuate an inflow pump and an outflow pump in response to various signals and various algorithms are provided to provide malfunction warnings and assure safe operation.

A wearable device consists of a smart band and a display unit. The smart band comprises a microbial biosensor, a particulate matter sensor, an enviro sensor, a physiological sensor, a biofluid sensor, a biokinetics sensor, a lifestyle sensor, and a single board computer. The microbial biosensor detects, measures, and monitors microorganisms, and a sterilizer kills pathogens. The particulate matter sensor detects, measures, and monitors a set of suspended particles in the surrounding air. The enviro sensor monitors environmental conditions surrounding the user. The biofluid sensor detects, measures, and monitors biological fluid parameters of the user. The physiological sensor detects, measures, and monitors physiological parameters of the user. The biokinetics sensor detects, measures, and monitors physical activities of the user. The lifestyle sensor detects, measures, and monitors healthy lifestyle activities of the user. The wearable device allows for continuous monitoring of user health for accurate clinical outcomes and wellness programs.

The invention relates to a sensor head device for a heart support system, wherein the sensor head device has at least one sensor carrying element, wherein the sensor carrying element has at least one sensor cavity for accommodating at least one sensor and / or at least one signal transmitter cavity for accommodating at least one signal transmitter.

The invention provides a muscle stimulation adjusting method and system based on gait detection. The method comprises the following steps: acquiring lower limb biomechanical data; performing phase recognition according to a dynamic programming algorithm, and constructing a pressure center track to perform feature extraction to obtain gait features; carrying out feature analysis on the gait features through a reverse dynamics model and a machine learning model, and carrying out output judgment according to a double-model collaborative decision-making mechanism to obtain a stimulation parameter decision-making result; generating an electrical stimulation waveform according to the decision result, and applying differential electrical stimulation to the target muscle in the gait cycle to obtain a stimulation scheme; and monitoring stimulated myoelectricity feedback signals and gait changes, and carrying out parameter updating by calculating a signal change rate and analyzing a motion track error to obtain an updating scheme. According to the method, through a double decision-making mechanism of the reverse dynamics model and the machine learning model and a real-time feedback regulation mechanism, the gait phase recognition precision is improved, and precise regulation and control of stimulation parameters are realized.

The invention provides a stroke patient gait walking analysis method and device. The stroke patient gait walking analysis method comprises the steps that pressure data and inertial data generated in the gait walking process of a patient are collected based on a plantar pressure sensing module and an inertial measurement module; performing data preprocessing on the pressure data and the inertial data; constructing a double-flow neural network to respectively extract pressure features and inertial features of the pressure data and the inertial data, performing feature fusion, and calculating step length, stride frequency, gait asymmetry index and gait stability index key indexes based on the fused features so as to realize gait evaluation; an evaluation result is transmitted to the flexible OLED touch screen, and gait parameters, rehabilitation progress, abnormal early warning and training guidance information are displayed in real time through the flexible OLED touch screen. According to the method, the end-to-end process from original sensor data to clinical application is realized, manual monitoring is avoided, the accuracy and clinical practicability of evaluation are improved, and the method is particularly suitable for family rehabilitation monitoring of stroke patients and precise rehabilitation evaluation of medical institutions.

Disclosed is an anti-snoring pillow, including a pillow bottom plate, a sleeping posture sensor is fixedly connected to a lower surface of the pillow bottom plate, and a sleeping posture airbag and a main control box are fixedly connected to an upper surface of the pillow bottom plate, wherein a head position sensor is fixedly connected to an upper surface of the sleeping posture airbag, an anti-snoring airbag is fixedly connected to an upper surface of the head position sensor, and the main control box is in communication connection with an air pump box, the air pump box is connected to the sleeping posture airbag and the anti-snoring airbag through pipelines, and wherein the sleeping posture sensor and the head position sensor are in communication connection with the main control box, and a pillow supporting cotton is provided on the upper surface of the pillow bottom plate.

The invention discloses an intelligent ring with a physiological feature detection function and a physiological feature detection method. The smart ring comprises a pressure detector and an arithmetic processor. The pressure detector is used for detecting the value of pressure applied to the smart ring by the target object. The arithmetic processor is electrically connected with the pressure detector and used for comparing the pressure value with a preset condition and judging the behavior of the target object according to the comparison result of the pressure value and the preset condition so as to generate a corresponding operation instruction. The smart ring not only can utilize the pressure detector to correct the detection result of the light volume change tracing detector, but also can utilize the pressure detector to detect the degree of tightness, gestures or finger actions when a user wears the smart ring, and has diversified application changes.

Medical systems, devices, and methods for determining whether a blood vessel is a vein or an artery. The system includes an optical fiber configured for insertion into a blood vessel coupled with a console having a light source, an optical receiver, processors, and logic stored in memory. The optical fiber includes sensors disposed along its length configured to determine a state or condition of the optical fiber. The state or condition can include a strain, movement, pressure, and / or temperature. The logic is configured to analyze reflected signals from the sensors to determine whether the optical fiber is inserted within an artery or within a vein. The logic may also determine a red-blue shift of a projected light to determine a blood flow direction with respect to the optical fiber.

A device for providing a passage between a first and second heart chamber is provided. The device includes a middle region having first and second ends, a lumen extending therethrough having a longitudinal axis, a first end region coupled to the first end, and a second end region coupled to the second end. The first end region may be delivered in the first heart chamber in a compressed state and transitioned to a deployed state, the first end region being deformable such that portions of the first end region are expandable to different angles relative to the longitudinal axis. The second end region may be delivered in the second heart chamber in a compressed state and transitioned to a deployed state therein, the second end region being deformable such that portions of the second end region are expandable to different angles relative to the longitudinal axis.

The invention provides an intelligent pillow control method and system, and belongs to the technical field of intelligent control. The method comprises the steps that an FPGA obtains a user sleeping posture data set collected by a pressure sensor array; and determining a current sleep stage based on the user sleep posture data set and a pre-trained sleep stage recognition model. According to the user sleeping posture data set, the historical sleeping posture data set and a preset cervical vertebra supporting curve, a first correction target parameter matrix corresponding to the current cervical vertebra curvature deviation value of the user is determined; wherein the first correction target parameter matrix comprises first correction target parameters corresponding to air bags in different areas of the intelligent pillow; the first correction target parameter is the airbag pressure adjustment amount dynamically constrained by the receptor dynamic frequency; and based on the current sleep stage and the first correction target parameter matrix, determining a corresponding airbag adjustment parameter group, operating an airbag driving module according to the airbag adjustment parameter group, performing airbag pressure adjustment, and updating the first correction target parameter matrix according to the real-time body movement frequency.

The invention provides a health monitoring module and electronic equipment. The health monitoring module comprises a shell, an optical heart rate module, a circuit board and a light transmitting part, the shell is fixed to one side of the circuit board, and the shell and the circuit board jointly define a containing space. The shell comprises a conductive part made of conductive materials, one part of the conductive part is exposed out of the top face of the shell, and the other part of the conductive part is electrically connected with the circuit board. The optical heart rate module is located in the containing space, the optical heart rate module is fixed to the circuit board and electrically connected with the circuit board, the optical heart rate module and the light hole are oppositely arranged, and the optical heart rate module emits and receives light through the light hole and the light transmitting piece. The optical heart rate module can be used for acquiring PPG signals of a user. The conductive part can be used for collecting electric signals of a user. And the ECG signal of the user can be obtained after the electric signal is processed. Devices for measuring ECG signals and PPG signals are integrated in one module, so that the module can realize multiple functions in a small size.

The invention relates to the technical field of electronic equipment, and provides a pressure detection device and electronic equipment. The pressure detection device comprises a plurality of pressure sensors; the flexible supporting layer comprises a first surface and a second surface which are oppositely arranged in the first direction; the plurality of pressure sensors are attached to the first surface of the flexible supporting layer at intervals, and the plurality of pressure sensors are mechanically connected at least through the flexible supporting layer; the one or more rigid sheets are attached to the second surface of the flexible supporting layer; wherein each rigid sheet in the one or more rigid sheets corresponds to part of the pressure sensors, and the projection of each rigid sheet in the first direction covers the projection of the pressure sensor corresponding to the rigid sheet in the first direction. Through the arrangement of the flexible supporting layer, the flexible packaging layer and the reinforcing layer, the pressure detection precision can be improved.

The invention discloses midstream urine collection equipment with high sealing performance, belongs to the technical field of midstream urine collection, and aims to solve the problems that a patient cannot accurately control the urination rhythm, so that the boundary between forepart urine and midstream urine is fuzzy, the collected midstream urine contains part of forepart urine, and the midstream urine collection accuracy is influenced. A fixing frame is fixed to the inner side wall of the collecting hopper, a contact plate is arranged on one side of the fixing frame, four evenly-distributed positioning columns are fixed to the side, close to the fixing frame, of the contact plate, and the positioning columns are movably connected to one side face of the fixing frame; after the contact plate is impacted by urine, impact force can be transmitted to the pressure sensor, the impact force of the urine can be detected through the arranged pressure sensor, and then the pressure sensor is matched with the PLC to distinguish anterior urine, midstream urine and posterior urine, so that the boundary distinguishing between the midstream urine and the anterior urine is obvious, and the accuracy of urine detection is improved. The problem that the accuracy of midstream urine collection is affected due to the fact that the collected midstream urine contains part of anterior urine due to autonomous judgment of a patient is avoided.

The invention is suitable for the technical field of medical equipment, and provides a gait analysis system which comprises a first pressure sensor module, a second pressure sensor module, an FPGA processor module and an upper computer module.The first pressure sensor module is used for collecting first pressure data generated when a user walks on a first sensor array, and the second pressure sensor module is used for collecting second pressure data generated when the user walks on a second sensor array; the second pressure sensor module is used for collecting second pressure data generated when the user walks by wearing a second sensor array, and the FPGA processor module is used for receiving the first pressure data and the second pressure data at the same time. The first pressure module is used for receiving first pressure data and second pressure data, converting the first pressure data and the second pressure data into target data according to a target protocol and transmitting the target data to the upper computer module, and the upper computer module is used for processing the target data to obtain gait analysis data. The use conditions of gait analysis can be reduced, and the accuracy of gait analysis is improved.

The embodiment of the invention discloses an ovarian health assessment method and related equipment, the method is applied to first electronic equipment, the first electronic equipment can display a first interface, and the first interface comprises a first control; receiving a first operation acting on the first control; acquiring first data, wherein the first data comprises heart rate variability data of the user in a preset time period; according to the physical sign data of the user, determining an ovary health assessment result; the user sign data comprises first data; the ovarian health assessment result is used for indicating the ovarian health condition of the user in a preset time period; after the preset time period, a second interface is displayed, and the display content of the second interface comprises the ovarian health assessment result. By adopting the method, the ovarian function abnormity of the user can be found in time.

The invention relates to a multifunctional fabric-based flexible pressure sensor for fetal movement monitoring, a preparation method and a system, and belongs to the technical field of vital sign monitoring. The fetal movement monitoring system comprises a waist-surrounding fixing belt, a sensing device, a control circuit and an upper computer subsystem. Wherein the sensing device is sewn on the side, close to the skin, of the waist surrounding fixing belt, and the sensing device is fixed to the abdomen position through the waist surrounding fixing belt; the sensing device is used for monitoring fetal movement signals, and the monitored fetal movement signals are transmitted to the upper computer subsystem through the control circuit to graphically display fetal movement information. The sensing device comprises a plurality of fabric-based flexible pressure sensors arranged in an array, two ends of each sensor are respectively connected with a first wire and a second wire, the first wire and the second wire are respectively connected with the control circuit through a multichannel analog switch, the multichannel analog switch is controlled by the control circuit to sequentially gate all the sensors, and the fabric-based flexible pressure sensors are connected with the control circuit. Therefore, electric signals generated by the sensors can be read out.

The invention relates to the technical field of fall prevention, in particular to a fall prediction method and system based on action analysis, an early warning device and a medium. The prediction method comprises the following steps of collecting multi-dimensional action data of an individual in real time through a plurality of sensors distributed in an environment and / or wearable equipment worn by the individual; and preprocessing the multi-dimensional action data to generate standardized action data, and inputting the standardized action data into a feature extraction model. Through a multi-sensor fusion technology, various data sources such as a video camera, an inertial measurement unit (IMU), a pressure sensor and a heart rate sensor are effectively integrated. The limitation of a single sensor on data comprehensiveness and accuracy is overcome, and richer individual state information can be provided.

The invention discloses wearable equipment, a blood pressure measuring method and a related device, and belongs to the field of data processing. The method comprises the following steps: acquiring a pressure data set acquired by at least one sensor array, and determining an effective pressure sensing unit from absolute pressure sensing units included in the at least one sensor array based on the pressure data set acquired by the at least one sensor array, determining arterial pressure data corresponding to at least one arterial blood vessel on the basis of pressure data collected by the effective pressure sensing units in the at least one sensor array, and determining the blood pressure of the user on the basis of the arterial pressure data corresponding to the at least one arterial blood vessel. As the arterial pressure data can represent the pressure actually borne by the corresponding arterial blood vessel in the blood pressure measurement process, the accuracy of the blood pressure result determined based on the arterial pressure data corresponding to the arterial blood vessel is high.

The invention relates to the technical field of intelligent nursing, in particular to an electrical impedance tomography-based pressure sore risk perception and prevention control system, which comprises an EIT signal acquisition module, an impedance trend grading module, a risk area judgment module, a bed body intervention control module and an intervention feedback regulation module. According to the invention, through an electrical impedance imaging principle, fine distinguishing of body surface and superficial tissue physiological states of a patient is realized, multi-region impedance signals are continuously collected and dynamically integrated, local tissue perfusion changes and abnormal stress trends are accurately mapped, high-risk regions are automatically identified and classified, bed body action intervention is triggered in real time, and an intervention effect is dynamically tracked; according to the method, intervention parameters are cooperatively adjusted, the response logic and the intervention rhythm of each region are gradually improved, intelligent risk judgment and closed-loop adaptive intervention are completed, individuation, initialization and process data traceability in a nursing scene are promoted, and adaptive response aiming at complex illness conditions and variable nursing requirements is supported.

The invention relates to the technical field of gait recognition, in particular to a gait recognition method based on a PFTgait model, and the method comprises the steps: collecting plantar pressure data; the multi-layer convolution feature extractor, the frequency domain feature fusion module and the time sequence correlation feature encoder are cascaded; gait feature extraction is carried out by using a multi-layer convolution feature extractor; performing frequency domain feature extraction and frequency-time feature conversion on the gait features by using a frequency domain feature fusion module; capturing a global dependency relationship of gaits by using a time sequence correlation feature encoder; and outputting a gait category by using the classifier. The method solves the problems that existing manual feature engineering depends on prior knowledge, a complex mode of gait data is difficult to comprehensively mine, and the representation capacity of a model is limited; an existing frequency domain analysis method is prone to noise interference, and the stability and generalization ability of features are affected. A traditional RNN structure is difficult to effectively model a global dependency relationship when processing a long-time gait sequence, resulting in the problems of attenuation or loss of key information and the like.

Some embodiments of the present disclosure include, for example, a method for automatically entering content into a periodontal chart. Such methods include, for example, providing an Intra Oral Scanner (IOS) with an elongate probe extending therefrom, contacting a first point inside an oral cavity with the probe while scanning the cavity with the IOS, determining a position of the first point based on the scanning to determine a position in space of the elongate probe, calculating content to be entered into a periodontal chart, and entering the content into the periodontal chart. Related apparatus and methods are also described.

A bed apparatus includes: a mattress mounted on a bed body; and, first cells arranged on both left and right sides in a longitudinal direction of the bed body and is configured to change the body position of a patient on the mattress by inflating the first cells alternately. When the first cells on the left and right sides are inflated, and when a difference in pressure between the first cells on the left and right sides has continuously fallen within a decision pressure value range for a decision pressure value continuation time, the body position of the patient is changed, whereas when the difference has not continuously fallen within the pressure value range for the continuation time or when the difference has continuously fallen out of the pressure value range for the continuation time, change of the body position of the patient will not be performed.

This invention, which offers the advantage of an automatic repetitive blood pressure measurement that minimizes discomfort for the subject while continuously measuring blood pressure regardless of the subject's movement, thereby enhancing the reliability of the measurement results, which leads to the development of an automatic repetitive blood pressure measurement device and method for a smart blood pressure monitor, relates to blood pressure measurement technology, involving periodically repeating the inflation and deflation of a cuff a set number of times upon receiving a single operation signal input. The method includes the steps of detecting arterial wall vibrations when the cuff pressure is between the systolic and diastolic pressures of the artery during cuff inflation and deflation, recognizing the point where maximum vibration is detected as the systolic blood pressure based on the detection results, recognizing the diastolic blood pressure if the vibration decrease exceeds a threshold, and providing measurement results sequentially, including the recognized systolic and diastolic blood pressure values during the repeated inflation and deflation of the cuff a set number of times.

The invention relates to the field of pressure sensors, in particular to a triboelectric pressure sensor and a sleep monitoring method and system. The triboelectric pressure sensor comprises a positive friction layer, a negative friction layer, a deformation electrode connected to the negative friction layer and a flexible electrode connected to the positive friction layer. The contact ends of the tips of the multiple micro-cone structures of the positive friction layer all face the negative friction layer, and gaps are formed between the contact ends and the negative friction layer. The Young modulus of the negative friction layer is smaller than that of the micro-cone structure, so that when the negative friction layer approaches the deformed electrode, the negative friction layer sinks and makes contact with the side face of the micro-cone structure. The change amplitude of the contact surface along with the pressure is large, so that the sensitivity of the sensor is improved. Respiration and pulse frequencies are respectively detected by a triboelectric pressure sensor to obtain electric signals, the electric signals are segmented and enhanced into waves, then the waves are classified by a big data method, a learning model for identifying sleep state categories corresponding to the waves is obtained, the categories are further rapidly and accurately identified, and an alarm is given according to the number of abnormal times. The method and the system have high reliability.

A medical system is disclosed that includes a medical device having an optical fiber, and an interchangeable connection component configured to provide a fiber optic connection between the medical device and capital equipment. The connection component is configured to facilitate cleaning and / or polishing of fiber optic interfaces include therewith. The connection component is also configured for replacement by a medical technician while the capital equipment is operational. The capital equipment may include one or more of an optical interrogator, a patch cable, a medical probe, an ultrasound machine, a display, a magnet sensor, or an electro-cardiogram (ECG) machine. The medical device may include an elongate member configured for insertion within the patient body, where the optical fiber core extends along a length of the elongate member.

The present disclosure provides an electronic device. The electronic device includes a flexible element, and a sensing element adjacent to the flexible element and configured to detect a biosignal. The electronic device also includes an active component in the flexible element and electrically connected with the sensing element. A method of manufacturing an electronic device is also disclosed.

A system obtains high-resolution data of actual over-ground gait rehabilitation interactions through a custom-made wearable system for identifying abnormal gait patterns and the therapists' assistance strategies. The system implements an impedance learning algorithm with feature selection and a goal-directed attractor definition reproduces therapist assistance in a way that integrates clinical insights into the control of lower-limb exoskeletons.

The present invention relates to a walking mat and a walking state determination method using the same, and more particularly, to a walking mat capable of determining a user's walking state and a walking state determination method using the same. A walking state determination device according to an embodiment of the present invention includes a modem that receives and outputs sensing information from a connected walking mat, a memory that stores one or more of predetermined correct walking information and correct standing information, and a processor. The memory may store program instructions executable by the processor that update the correct walking information or the correct standing information when sensing information is received and determine whether an emergency situation exists when sensing information is not received. In this case, the walking mat may generate sensing information through a pressure sensor formed therein and transmit it to the walking state determination device.

The invention discloses an intelligent anti-falling risk management system based on artificial intelligence, and relates to the technical field of artificial intelligence, the intelligent anti-falling risk management system comprises a management center, and the management center is connected with a monitoring acquisition module, a transmission processing module, a body position analysis module and a multi-dimensional supervision module; constructing a resting virtual space for the bedridden old person, and performing position marking on the collected bedridden state data through the resting virtual space based on the intelligent anti-falling bed to obtain a continuous track of the bedridden old person; boundary distance statistics is carried out according to the continuous track of the bedridden patient, the boundary distance is converted into a real-time track fluctuation map, range division is carried out on the real-time track fluctuation map, the range proportion is counted, and a curve judgment range is obtained; carrying out simulation diagnosis through the static lying virtual space to obtain an abnormal identification state, and carrying out dynamic feedback adjustment on the bedridden old people according to the abnormal identification state based on the static lying virtual space to obtain an anti-falling intervention measure; the occurrence of falling-off accidents of old people is effectively reduced, the nursing efficiency is improved, and the burden of nursing personnel is relieved.