262 results about "Accelography" patented technology

The invention relates to a cervical vertebra rehabilitation system based on virtual reality. The cervical vertebra rehabilitation system comprises a virtual reality display module, a cervical vertebra action detection module, a central processing module, a rehabilitation training control module and a data recording and analyzing module. The virtual reality display module provides an immersive rehabilitation environment for a patient through a head-mounted display device, and the cervical vertebra motion detection module captures cervical vertebra motion data of the patient in real time through an accelerometer, a gyroscope and a magnetometer. And the central processing module fuses the multi-dimensional data through a Kalman filtering algorithm, accurately estimates the cervical vertebra posture of the patient, and synchronizes the action of the patient to a virtual environment. The rehabilitation training control module dynamically adjusts the training content according to the actual rehabilitation progress of the patient, provides a personalized rehabilitation scheme, and enhances interactivity and interestingness. The data recording and analyzing module records training data of the patient in real time and generates a rehabilitation report to help doctors to perform scientific evaluation.

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.

Aspects of the disclosure describe an implantable system for monitoring intracranial pressure (ICP) in a subject, the system comprising: a conduit for the flow of cerebrospinal fluid (CSF); a hermetically sealed compartment; a first pressure sensor configured to measure an absolute ICP and output a measurement, wherein the first pressure sensor is hermetically sealed in the compartment, and wherein the first pressure sensor comprises a surface exposed to the CSF in the conduit; a microcontroller disposed in the hermetically sealed compartment that receives multiple inputs including at least the output of the first pressure sensor; and an accelerometer disposed in the hermetically sealed compartment for monitoring a subject's positional status, and wherein the accelerometer communicates an output to the microcontroller.

A system for closed-loop control of sub-perception spinal cord stimulation therapy is provided. The system includes an implantable pulse generator (IPG) with an evoked compound action potential (ECAP) recording module and accelerometer. A regression model maps accelerometer data to optimal stimulation parameters for consistent nerve activation. This enables closed-loop therapy in the sub-perception domain where ECAP features are not visually detectable. A clinician programmer applies the model and sub-perception dose to therapy programs deployed to the IPG. The model can be customized to each patient by collecting ECAP and accelerometer data. The mapping reconciles ECAP -based control between perception and sub-perception domains by supplementing unavailable ECAP data with accelerometer data. This improves stimulation therapies for patients receiving sub-perception and multi-sensor paresthesia treatments.

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 provides an epilepsy detection device, and relates to a medical equipment technology. The epilepsy detection device comprises a wearable device, the wearable device comprises a data acquisition module, a data processing unit, a communication module, a software algorithm and a system platform, and the data acquisition module comprises an electromyogram sensor, a heart rate monitoring sensor, an accelerometer, a gyroscope and a skin electrical activity sensor. The data processing unit comprises a microprocessor and a memory, the communication module comprises a Bluetooth / Wi-Fi module and a mobile application / cloud platform, and the software algorithm comprises a signal processing algorithm and an optimization algorithm. By combining medical history data of a patient, including epileptic seizure history, seizure type, frequency, duration time, preamble before seizure, symptoms after seizure and the like of the patient, genetic history and medical history of epilepsy or other related diseases in a family, a more personalized model is trained, and more accurate monitoring and early warning are provided for the patient.

A system for closed-loop control of sub-perception spinal cord stimulation therapy is provided. The system includes an implantable pulse generator (IPG) with an evoked compound action potential (ECAP) recording module and accelerometer. A regression model maps accelerometer data to optimal stimulation parameters for consistent nerve activation. This enables closed-loop therapy in the sub-perception domain where ECAP features are not visually detectable. A clinician programmer applies the model and sub-perception dose to therapy programs deployed to the IPG. The model can be customized to each patient by collecting ECAP and accelerometer data. The mapping reconciles ECAP-based control between perception and sub-perception domains by supplementing unavailable ECAP data with accelerometer data. This improves stimulation therapies for patients receiving sub-perception and multi-sensor paresthesia treatments.

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.

An implantable cardiovascular pressure sensing system can be used to measure blood pressure accurately and safely without any patient intervention. It can include a pressure sensor that makes blood pressure measurements, circuitry for processing and storing the blood pressure measurements, and an antenna for transmitting the processed measurements to an external device (i.e., a device not implanted in the patient). The circuitry can average blood pressure measurements and / or remove artefacts caused by patient motion that is sensed with an accelerometer integrated into implantable cardiovascular pressure sensing system. A multilayer ceramic / polymer coating forms a hermetic seal around the components, preventing leakage or contamination. The implantable cardiovascular pressure sensing system is very versatile: it can be implanted in a blood vessel, next to a blood vessel, in an aneurysm sac, or integrated with another medical implant, such as an Amplatzer septal occluder, and implanted into or next to another vascular structure.

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.

Examples provide a system and method for continuous respiratory rate monitoring with greater accuracy and reliability. Sensor data is obtained from a wearable sensor device simultaneously generating both multi-wavelength photoplethysmography (PPG) sensor data as well as inertial measurement unit (IMU) sensor data, such as respiratory body movement data generated by an accelerometer and / or a gyroscope. The system performs signal processing and filtering on the sensor data using a set of rules and threshold(s) to remove Mayer-wave in-band noise, transients, and motion artifacts. PPG-based respiratory rate estimates are generated and combined into a single PPG-based respiratory rate estimate based on the PPG sensor data. IMU-based respiratory rate estimates are generated and combined in parallel using the IMU sensor data to generate a single IMU-based respiratory rate estimate. A final respiratory rate estimate is selected from the final PPG-based respiratory rate estimate and the final IMU-based respiratory rate estimate.

Embodiments include an ingestible capsule comprising a housing including a therapeutic payload carrying compartment; a power supply; a release mechanism; and a sensing mechanism, the sensing mechanism being sensitive to an environment external to the housing; the ingestible capsule being configured for passage through a GI tract of a subject mammal, during which passage: the sensing mechanism is configured to output a signal varying according to a GI tract environment, wherein the sensing mechanism comprises one or more sensors from among: a VOC gas sensor; a TCD gas sensor; a reflectometer formed by a transmission antenna of the ingestible capsule connected in series with a directional coupler configured to measure a reflected signal from the transmission antenna; and an accelerometer; the release mechanism is configured to cause a therapeutic payload to be released into the GI tract from the therapeutic payload carrying compartment at a release timing determined according to the output signal.

The invention provides an acupuncture level quantification standard and device based on the acupuncture process of a nurse, and aims to establish an objective and scientific evaluation system by performing quantitative analysis on key data of the acupuncture process so as to improve the nursing quality. The method comprises three main steps of data collection and preprocessing, evaluation standard establishment and acupuncture process scoring. Acceleration data in the acupuncture process are collected in real time through a three-axis accelerometer, a speed and displacement sequence is obtained through filtering and integral calculation, the operation process is divided into three stages of skin contact, subcutaneous insertion and target depth approaching, and statistical characteristics of all the stages are extracted to serve as quantitative indexes. The evaluation standard covers key indexes such as speed stability, sudden stop times and insertion time, and quantitative evaluation of the needle insertion level of the nurse is achieved in combination with the segmentation scoring weight and the comprehensive scoring rule. The device consists of a hardware module (a sensor, a microprocessor, a wireless communication module and the like) and a software module (a data processing and analysis algorithm), supports real-time data transmission and feedback, and has the characteristics of portability, automation and high precision. Scientific basis is provided for continuous improvement of the nursing level, and more comfortable and safer medical experience is created for a patient.

Systems and methods of neurofeedback intervention reduce the negative effects of neurological disorders, including Parkinson's disease, essential tremor, dystonia, epilepsy, dysfunction following stroke, obsessive-compulsive disorder, Tourette syndrome, dementia, complex regional pain syndrome, and the like. Haptic devices, including eccentric-mass actuators and computer-controlled tightening haptic straps provide haptic sensation to a body. The haptic sensations are controlled by a haptic control signal determined by a control program. The control program may determine the haptic control signal from a neurological signal from an EEG, an electrode detecting a signal in a nerve fiber, or an accelerometer. Haptic therapy un-trains and desynchronizes abnormal neuron synchrony, to reduce the negative effects of neurological disorders.

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.

A system for monitoring a user that includes a sensor unit configured and arranged to be disposed on the user, the sensor unit including an accelerometer and a communication arrangement; and at least one processor configured and arranged for performing actions including: receiving signals from the accelerometer of the sensor unit; determining a step count from the signals; determining a gait velocity from the signals; determining a step distance from the signals; determining a posture of the user from the signals; and determining a gait posture index as a function of the step count, gait velocity, step distance, and posture. In other embodiments, the system can be used to determine metrics other than the gait posture index, such as a fall prediction score based on gait velocity and posture deviation.

Blood circulation assist systems include a ventricular assist device (VAD), a remote accelerometer, and a controller that controls operation of the VAD based on output of the remote accelerometer. A blood circulation assist system includes a VAD, a controller, and a remote accelerometer. The VAD includes an impeller. The remote accelerometer is configured to generate a remote accelerometer output indicative of accelerations measured by the remote accelerometer. The implanted controller controls a rotation speed of the impeller based on the remote accelerometer output.