184 results about "Accelography" patented technology

An ultrasound imaging system configured to generate a three-dimensional (3D) ultrasound image of a target area. The ultrasound imaging system includes a console including one or more processors and non-transitory computer readable medium having stored thereon one or more logic modules, and an ultrasound probe configured to acquire a plurality of ultrasound images of a target area. The ultrasound probe can be coupled to the console by an ultrasound probe connector having optical fiber including one or more core fibers. The console is configured to generate the 3D ultrasound image by stitching together the plurality of ultrasound images, starting from a point of reference. The point of reference can be the ultrasound probe, one or more anatomical targets, an elongate medical device, a reference magnet, or one or more accelerometers.

The invention relates to the technical field of artificial intelligence and biomedical sensing, and discloses a cognitive disorder risk identification device and method integrating multi-modal physiological data, and the device comprises an EEG module, an eye movement module, an fNIRS module, an edge calculation module and an acceleration sensor; the EEG module collects EEG data, the eye movement module collects eye movement eye-tracing data, and the fNIRS module collects near infrared spectrum fNIRS data and inputs the data to the edge calculation module; the edge calculation module runs the multi-modal space-time attention fusion model to output a cognitive impairment risk assessment result by using the multi-modal space-time attention fusion model; the acceleration sensor operates based on an operation dynamic filtering algorithm of a motion accelerometer to inhibit signal drift caused by head motion. According to the invention, through the modularized head-mounted multi-mode edge device, the physiological data is collected and edge end processing and cognitive disorder recognition and screening are carried out in combination with the edge calculation module, so that early recognition and screening of neurodegenerative diseases can be conveniently and effectively carried out at low cost.

A medical monitoring system comprises a wearable garment incorporating multiple physiological sensors for real-time patient monitoring. The garment integrates an embedded processing unit that receives sensor data and transmits it wirelessly to a base station or remote server. A multi-modal physiological signal processing unit analyses the data to generate composite physiological indices, including metabolic rate, work of breathing, and fall risk assessments. The garment includes optional monitoring features such as transcutaneous carbon dioxide measurement, electrocardiography, pulse oximetry, blood pressure monitoring, and accelerometer - gyroscope-based motion tracking. The system provides early-warning alerts for clinical deterioration, enabling proactive therapeutic interventions. A wireless communication module ensures real-time data transmission, supporting remote monitoring and integration with hospital networks. The garment's modular design allows for non-invasive physiological assessment while maintaining patient mobility, making it suitable for critical care, ambulatory monitoring, and telemedicine applications.

The invention is a system for continuous monitoring of respiratory and gastric functions using wearable devices. Each device includes a three-axis accelerometer and optionally a gyroscopic sensor. They feature wireless communication for data transmission and means for attachment to the skin. A computation device analyzes the data, using a machine learning model to detect coughing, swallowing and respiration. The method involves placing sensors on the skin of the cricoid region and epigastric region, filtering and transmitting data, training the model, and plotting coughing frequency. This system enhances detection accuracy and facilitates early medical interventions, benefiting chronic condition management and postoperative care.

The invention discloses a non-invasive wearable vascular arteriosclerosis assessment system and method based on multi-mode pulse wave signal fusion, and belongs to the field of vascular function assessment. The system comprises a distributed acquisition front end, a butterfly-shaped flexible substrate, an integrated double-accelerometer, a four-wavelength LED (530nm / 660nm superficial blood vessel measurement), a 810nm / 940nm deep artery measurement device, a double-photodiode, a double-impedance electrode and a pressure sensor. The central integrated control end processes a multi-mode signal and realizes pressure-LED current closed-loop control; the upper computer terminal extracts the multi-modal pulse wave time difference of the limbs and the neck, the local and regional pulse wave conduction velocity and the blood oxygen hemoglobin change parameters induced by the standardized posture, the dimension is reduced to 30 through principal component analysis, then the parameters are input into the random forest regression model, and the vascular elasticity index is output. Signal stability is improved through flexible fitting, single-source limitation is solved through multi-modal fusion, signal quality is guaranteed through closed-loop control, sensitivity is enhanced through dynamic physiological excitation, and accuracy and universality of arteriosclerosis assessment are improved.

Systems and methods for providing assessments of a disease using sensor data for a subject captured during day-to-day living are provided. The sensor data includes accelerometer data and is acquired by a sensor disposed on the subject's wrist while the subject performs both active and sedentary activities. The sensor data is analyzed for one or more bouts of activity; the sensor data is filtered, optionally rotated, and Fourier transformed. Spectral analysis parameters are then calculated from the transformed data to detect disease-relevant movement patterns. Movement distribution parameters for the accelerometer data associated with the disease-relevant movement patterns are calculated and compared to one or more disease scores to evaluate a progression of the disease or an efficacy of a treatment

The invention discloses a real-time multi-mode physiological signal analysis method for myocardial ischemia, and belongs to the technical field of data analys.The technical scheme includes that electrocardiogram, photoelectric volume pulse waves and thoracic impedance signals are synchronously acquired, and phase difference caused by motion displacement is compensated in real time by the aid of a triaxial accelerometer; constructing a multi-dimensional quality evaluation matrix containing an electrocardiogram signal-to-noise ratio, a photoelectric volume pulse wave perfusion index and a chest impedance variance, and jointly judging whether signal reconstruction is triggered or not based on a dynamic threshold value and accelerometer data; a multi-channel signal block which is judged to be low in quality through the quality evaluation matrix and comprises the electrocardiogram and photoelectric volume pulse waves and chest impedance synchronized with the electrocardiogram is input into a generative adversarial network with electrophysiological constraints to be reconstructed, and a reconstructed high-quality electrocardiogram signal is output; and myocardial ischemia key indexes are extracted from the reconstructed signals, and multi-level risk early warning is carried out. The real-time multi-modal physiological signal analysis method for myocardial ischemia has the beneficial effect that the real-time multi-modal physiological signal analysis method for myocardial ischemia is provided.

The invention discloses a gastrointestinal decompression nursing device and a gastrointestinal tract pressure supervision system, and belongs to the technical field of medical nursing. A gastrointestinal decompression nursing device comprises a suction tank, a regulation and control box, a stomach tube and a flexible arm band, and the regulation and control box comprises a data preprocessing module and a control module; a plurality of flexible resistance type sensors are distributed in the flexible arm band at equal intervals, an in-vivo capsule is arranged at the front end of the stomach tube, and a pressure sensor and a three-axis accelerometer are arranged in the in-vivo capsule. According to the gastrointestinal nursing pressure reducer, the problem that an existing gastrointestinal nursing pressure reducer cannot achieve pressure nursing and supervision work according to different patients is solved, the in-vivo capsule is integrated with the pressure sensor, the triaxial accelerometer and the impedance sensor, and the pressure in an intestinal tract cavity, the peristalsis frequency and the content impedance can be synchronously collected; in combination with body surface pressure gradient data of the flexible arm band, improper treatment caused by misjudgment is avoided, and serious complications such as intestinal perforation and bleeding caused by delayed treatment are avoided.

A system and method for optimizing a patient's Kegel exercises is provided. The system includes a user interface device and a vaginal device. The vaginal device includes an intra-vaginal probe having an accelerometer that is configured to generate a signal in response to movement of the probe. The user interface device is connected to the vaginal device and analyzes signals from the accelerometer to provide physiological feedback information to the patient. The vaginal device may be connected to the user interface device via wireless communications such as Bluetooth or by wire. The user interface device may be a smart device or a computer that transmits information to central web-based data server accessible by the patient or authorized healthcare providers or third-party payers.

The invention discloses a wearable tactile biological gait feedback system and method for a Parkinson's patient, and belongs to the field of human gait rehabilitation, and the system comprises the following modules: a posture sensing module which obtains the information of an accelerometer, a magnetometer and a gyroscope at the positions of two feet by using an inertial sensor IMU bound to the surfaces of the two feet; the data processing module is used for receiving the data information of the posture sensing module, estimating the posture of the two feet, estimating the gait phase of the two feet by using the posture of the two feet, and finally outputting a signal according to a gait feedback stimulation strategy; and the tactile feedback module is used for receiving the stimulation signals of the data processing module and providing vibration stimulation signals at the back and thigh gastrocnemius muscles. According to the wearable tactile biological gait feedback system and method for the Parkinson's patient, related posture data provided by an IMU can be utilized, double-foot posture estimation can be completed through multi-rate multiple-correlation-entropy Kalman filtering, double-foot phases are estimated through a self-adaptive oscillator algorithm, and the wearable tactile biological gait feedback system and method for the Parkinson's patient are obtained. And implementing vibration stimulation based on a set gait feedback strategy.

The invention belongs to the technical field of medical treatment, and discloses an osteoarthritis rehabilitation auxiliary device and system, and the device comprises an intelligent vibration treatment module, a pressure sensor and biological feedback module, an intelligent control and APP remote management module, a pressure sensor, an accelerometer, and a myoelectricity sensor. The joint pain is relieved, vibration can stimulate sensory nerves, pain signal transmission is reduced, and the pain degree is reduced. Vibration promotes secretion of joint fluid, friction is reduced, and the range of motion is improved. Low-frequency vibration stimulates the activity of cartilage cells, and cartilage degeneration is slowed down. And a biological feedback system is intelligently regulated and controlled, so that the treatment accuracy is improved. Non-invasive treatment is achieved, and no side effect exists; gastrointestinal discomfort caused by drug treatment or high cost of long-term physical treatment is avoided. Remote monitoring is achieved, compliance is improved, a patient can be treated at home and does not need to see a doctor frequently, and medical cost is reduced.

The invention relates to the technical field of disease monitoring, in particular to a multi-device collaborative disease risk prediction system. The system comprises a non-contact type signal receiving and transmitting device, a gait collecting device, an intelligent bracelet and a central processing unit, the non-contact type signal receiving and transmitting device captures macroscopic movement data of a user through a millimeter wave signal transmitting and receiving module, and the macroscopic movement data comprises periodic characteristics of gaits, movement tracks of four limbs and posture changes; the gait acquisition device acquires plantar pressure distribution data of a user through a pressure sensor array; the smart bracelet collects motion data of a user through an accelerometer and a gyroscope; and the central processing unit carries out space-time alignment on data of the non-contact signal transceiving device, the gait acquisition device and the intelligent bracelet through a timestamp synchronization algorithm, so that the disease risk is predicted according to the analysis data. The system supports all-weather and multi-scene monitoring, is suitable for disease risk assessment, and can early warn cardiovascular events and other health problems.

The invention relates to a safety monitoring method for rehabilitation training of an elderly weak patient. The safety monitoring method is used for automatically optimizing the rehabilitation training process of the elderly weak patient. According to the method, physical strength level, disease history and medicine use condition information of a patient are collected, physiological data of a rehabilitation person are monitored in real time in combination with various sensors, heart rate, blood oxygen, body temperature, myoelectric activity, fall detection, an accelerometer and a gyroscope, and a corresponding training scheme or adjustment suggestion is generated; the system outputs the physical health state of the rehabilitation person through the attention neural network; the body health state and the real-time data of the sensor serve as rule engine algorithm input, and then decision suggestions in rehabilitation training are made in real time; the method can reduce the health risk in training, and is especially suitable for personalized rehabilitation training of weak elderly patients.

The present application relates to the technical field of health monitoring, in particular to a kind of infant asphyxia risk autonomous monitoring method and system based on laryngeal respiratory sound, comprising: utilize high sensitivity MEMS microphone to collect the airflow and respiratory sound signal of infant larynx, and utilize micro accelerometer to monitor the thoracic movement data of infant synchronously;The airflow and respiratory sound signal are denoising, and the denoising respiratory sound signal is obtained;The denoising respiratory sound signal is separated according to respiratory event Signal, and is enhanced and combined into respiratory sound data set;Respiratory sound feature is extracted in respiratory sound data set, and asphyxia anomaly classification model is constructed based on respiratory sound feature by machine learning model, and dynamic baseline model that adapts individual respiratory difference is established according to respiratory sound feature.The present application utilizes the hardware device of high sensitivity MEMS microphone and micro accelerometer and artificial intelligence model to combine, realizes the use of laryngeal respiratory sound signal in home environment and autonomously completes infant asphyxia risk identification and early warning.

To make it possible to identify causes that may lead to damage to a medical device by monitoring corresponding usage conditions, and to record appropriate data for predictive diagnosis.SOLUTION: A monitoring system (20) comprises: an accelerometer (22) adapted to detect acceleration of a medical device (10) during handling of the medical device (10); a sensor unit (24) adapted to detect a further condition of the medical device (10) during handling of the medical device (10); and a control unit (26) with a dedicated storage unit (26a), wherein the control unit (26) is operatively connected to the accelerometer (22) and the sensor unit (24) and adapted to derive use data of the medical device (10) from the output data of the accelerometer (22) and the sensor unit (24) and to differentiate based on the respective output data of the accelerometer (22) and the sensor unit (24) between a regular use state and an unintended use state of the medical device (10).SELECTED DRAWING: Figure 1

The disclosure provides systems and methods for treating obstructive sleep apnea using an inertial measurement unit (IMU) comprising an accelerometer and a gyroscope, wherein the IMU is configured to detect chest and / or abdominal movement by a patient during the inspiration and expiration stages of a respiratory cycle and to generate positional data based on the detected movement. Positional data generated by the IMU is used by an implanted stimulation system to determine when to deliver electrical stimulation to a nerve which innervates an upper airway muscle, such as the hypoglossal nerve, to treat sleep apnea.

A system for monitoring medical conditions including pressure ulcers, pressure-induced ischemia and related medical conditions comprises at least one sensor adapted to detect one or more patient characteristic including at least position, orientation, temperature, acceleration, moisture, resistance, stress, heart rate, respiration rate, and blood oxygenation, a host for processing the data received from the sensors together with historical patient data to develop an assessment of patient condition and suggested course of treatment, including either suspending or adjusting turn schedule based on various types of patient movement. The sensor can include bi-axial or tri-axial accelerometers, as well as resistive, inductive, capacitive, magnetic and other sensing devices, depending on whether the sensor is located on the patient or the support surface, and for what purpose.

The invention discloses a uterine contraction detection method based on multi-modal signal fusion reconstruction, which comprises the following steps of: 1, synchronously acquiring an abdominal surface uterine electromyographic signal in real time through a high-density electrode array, acquiring a uterine contraction pressure signal in cooperation with a fundus pressure sensor, synchronizing a triaxial accelerometer signal to acquire a maternal motion signal, and preprocessing; 2, performing time sequence alignment and resampling on the data, and constructing a quality mask to form a multi-mode uterine contraction signal data set; 3, constructing a reconstruction network based on multi-modal feature fusion; 4, constructing a total loss function of the multi-modal feature fusion reconstruction network; and 5, training a reconstruction network of multi-modal feature fusion, wherein the reconstruction network is used for fusion reconstruction of the multi-modal uterine contraction data. According to the invention, through multi-modal signal fusion and deep feature correlation analysis, accurate monitoring and prediction of uterine contraction and premature delivery risks in the pregnant and birth period can be realized.

Neurostimulation therapy can be efficiently controlled based on information from an acceleration signal, such as can be obtained from an accelerometer. In an example, the accelerometer can be implanted in a cervical region or submandibular region of a patient. Circuitry can be configured to identify a first series of respiration phase transition events in the acceleration signal and, in response, provide the neurostimulation therapy synchronously with an inspiration phase of a patient's respirator cycle. In an example, m absence of identifying the first series of respiration phase transition events in the acceleration signal, the neurostimulation therapy can be provided asynchronously with the patient's respiratory cycle.

A mount (3) comprising a clamp (11) and a suction pad (13) for attaching a reconstitution device (1) containing the constituent parts of a reconstitution drug to a touch screen (15) of a smart phone (5). A control program (27) provided in a memory (21) of the smart phone (5) causes a processor (17) to compare motion of the smart phone (5) as detected by an accelerometer (19) to a required motion for mixing the constituent parts of a reconstitution drug contained a reconstitution device (1) and provide a user with feedback to a user indicating when the smart phone (5) to which a reconstitution device (1) containing the constituent parts of a reconstitution drug is attached by the mount (3) has been sufficiently shaken to reconstitute the drug contained within the reconstitution device (1).

Implantable medical devices and methods that utilize a sensing circuit to sense cardiac activity (CA) signals and an accelerometer to obtain accelerometer data. Memory stores program instructions and device parameters associated with a collection of ventricular arrhythmia (VA) therapies. A processor analyzes the CA signals over one or more cardiac beats, determines a VA episode based on the analysis of the CA signals, determines the VA episode to be hemodynamically stable or unstable based on at least one of the accelerometer data or the CA signals, selects a first VA therapy from the collection of VA therapies based on whether the VA episode is hemodynamically stable or unstable, and apply the first VA therapy using at least one of the at least two coils.

A patient support apparatus includes a support surface, a control panel, a network transceiver, and a controller. The controller is adapted to send one or more messages to a server that indicates at least one of the following: an incorrect passcode was entered into the control panel; a correct passcode was entered into the control panel; a post-passcode-entry window of time expired; a microphone detected a sound level exceeding a threshold; the microphone detected a keyword; a block control was activated on the patient support apparatus; an agitation level of the patient; a patient activation of a nurse call control; a status of a patient restraint; a status of a restraint attachment cover; or movement of the patient support apparatus as detected by an accelerometer. A software application executed by a server may be configured to instruct a display to display an indicator relating to any of these messages.

An apparatus includes a photoplethysmography (PPG) sensor configured to measure a PPG signal associated with a user, an accelerometer configured to measure an acceleration signal associated with the user, and a processor operatively coupled to the PPG sensor and the accelerometer. The processor is configured to determine whether the user is engaging in movement based on the acceleration signal, in response to determining that the user is engaging in movement, determine a type of movement of the user based on the acceleration signal, generate a probability distribution associated with a pulse rate of the user based on the type of movement, and determine the pulse rate of the user based on the PPG signal, the acceleration signal, and the probability distribution.

A circulatory support system includes an implantable blood pump including a housing, a rotor operable to pump blood from an inlet to an outlet, a stator, and at least two of the following: a current sensor, a rotor position sensor, an accelerometer, and a pressure sensor. The controller is connected to the sensors and includes a signal-processing module configured to receive, from each of the sensors, a data stream. The signal-processing module is also configured to filter the data streams received from the plurality of sensors, determine at least one of a pump operating parameter, a cardiac characteristic, and a pump control parameter based on at least two of the filtered data streams, and output the at least one of the pump operating parameter, the cardiac characteristic, and the pump control parameter to at least one of the operator interface module and the pump control module.

The invention particularly relates to an internal arteriovenous fistula power loss early warning system based on fusion of miniature ultrasound and biological impedance, and relates to the technical field of medical instruments. A data processing module; and an intelligent early warning module. According to the invention, through the integrated design of the miniature ultrasonic probe module and the biological impedance electrode module, the synchronous measurement of the blood flow velocity and the blood vessel volume change is realized; wherein the PMUT array is combined with a three-axis accelerometer to correct the angle of a probe in real time, angle errors caused by operation are avoided, meanwhile, the biological impedance electrode measures the blood vessel volume through alternating current, an impedance diameter model is dynamically updated through AI, the cross sectional area of the blood vessel is calculated, and traditional static calibration is replaced; the problem of insufficient precision of a single mode is solved, more reliable hemodynamic data is provided for clinic, and the abnormal state of the blood vessel is recognized in an early stage.

Disclosed herein a neurosurgical simulator for training of various tasks involved in Endoscopic Endonasal Transsphenoidal Surgery, composed of a human head model comprising an anterior portion including a nose part, and a posterior portion detachably mounted on an inclined base part; a plurality of apertures on the nose part for insertion of an endoscope and an instrument for manipulation; said inclined base part placed at an inclination to mimic a patient position during endo-nasal surgery; wherein said base part comprises a protruded platform having slots to create male-female connection with corresponding a plurality of protrusions provided under one or more activity plates; wherein said activity plates are so designed to train various tasks including pick-place, drilling, incising, punching / grasping and precision movements around the anatomical structures. The simulator further comprises sensors including touch sensors, force sensors and accelerometers configured to track the performance of the user and provide feedback. The simulator further comprises a pair of articulated arms with encoders at each joint of said arm connected to the endoscope and the instrument for tracking the kinematic data of the user.

Implantable medical devices include a first sensor for detecting a magnetic field that indicates an exposure mode of operation is appropriate. The implantable medical devices include a second sensor for detecting whether an MRI characteristic is present that indicates whether MRI or non-MRI post exposure diagnostics and other actions should be implemented and may also indicate whether the exposure mode should be MRI or non-MRI specific. An MRI post exposure diagnostic may perform pacing capture threshold tests and the post exposure pacing amplitude output may be kept at a higher than normal level. The second sensor may be an overvoltage clamp circuit of a telemetry coil that indicates whether an overvoltage condition on the telemetry coil is occurring to indicate whether an MRI characteristic is present. The second sensor may be a second threshold magnetic sensor, an accelerometer, or a microphone to indicate whether an MRI characteristic is present.

An impaction device that may include a force transducer and optional accelerometer to measure an impact force between an impactor device and broach / implant or broach / implant handle. The impaction device may include a microcontroller electrically coupled to memory and the force transducer and optional accelerometer, wherein the microcontroller is configured to execute operations stored in the memory, the operations comprising: receiving resistive force data and acceleration data to calculate resistance for each impaction and generate a resistance curve for output to a display.

This invention provides a motion monitoring method, system, and wearable device. It collects acceleration and angular velocity data during a patient's movement using an inertial measurement unit (IMU). The collected data is filtered and subjected to variational mode processing to extract gait information. Utilizing the waveform stability characteristics of the accelerometer and gyroscope at rest, the zero-velocity angular velocity point is identified. Based on the zero-velocity angular velocity point in the gyroscope data, the zero-velocity acceleration segment is also identified. Subsequently, the gyroscope's attitude is corrected using the acceleration data. The corrected gyroscope data generates a rotation matrix to transform the IMU coordinate system to the navigation coordinate system, and finally, trajectory reconstruction is performed. During trajectory reconstruction, data such as gait variability, step count, step frequency, stride length, movement distance, and movement trajectory are displayed on the wearable device or transmitted to a remote device for reference by doctors and patients.

This utility model discloses an exoskeleton robot control system that facilitates control, improves control effectiveness, and simplifies control methods. The exoskeleton robot control system includes an exoskeleton robot frame, an online acquisition system, a data processor, and an exoskeleton robot controller. The online acquisition system includes a smart bracelet, multiple patch-type IMU signal acquisition devices, and multiple patch-type electromyography (EMG) sensors. The smart bracelet is capable of detecting heart rate and blood pressure and can connect via WiFi or Bluetooth. The patch-type IMU signal acquisition devices integrate accelerometers and gyroscopes. The online acquisition system and the exoskeleton robot controller are electrically connected to the data processor. This exoskeleton robot control system improves user comfort and is suitable for controlling medical rehabilitation assistive exoskeleton robots, thus improving rehabilitation outcomes.