23 results about "EMG - Electromyography" patented technology

A user interface system enables communication through inaudible speech by detecting physiological signals associated with inner voice communication. The system includes a wearable device positioned in, on, or around a user's ear, housing one or more sensor modalities such as electromyography (EMG) sensors for detecting muscle movements, functional near-infrared spectroscopy (fNIR) sensors for brain activity, and / or detection-and-ranging systems using sonar or radar for micro-deformations. Pre-processing modules condition the sensor data, which is then analyzed by one or more machine learning models to reconstruct the content of the user's inaudible communication and produce output representations. The system enables high-bandwidth natural language interaction without audible vocalization, maintaining privacy while supporting applications including AI assistant interaction, real-time translation, secure authentication, and inter-party communication.

A system and method for visualizing a position of a needle inside a patient's body for use in providing regional anesthesia and a system and method for providing electro anesthesia during surgery, post surgery and during rehabilitation. The method and system use EMG / AMG information regarding activity of a muscle associated with a target nerve to provide a visualization of a position of a needle or other device relative to the target nerve and to determine efficacy of the electro anesthesia. EMG / AMG information and feedback information such as EEG information may be used to provide automatic adjustment of a waveform provided for electro anesthesia to maintain a suitable pain level.

A system includes at least one wearable device having a housing, at least one sensor disposed within the housing, at least one output device disposed within the housing, and at least one processor operatively connected to the sensors and output devices, wherein one or more sensors are configured to detect electrical activity from a user's facial muscles and to transmit a data signal concerning the electrical activity of the user's facial muscles to one of more of the processors. A method of controlling a wearable device includes determining facial muscular electrical data of a facial gesture made by a user, interpreting the facial muscular electrical data to determine a user response, and performing an action based on the user response.

This invention discloses a muscle stimulation modulation system and method based on real-time dynamic optimization, comprising: a real-time signal acquisition module for continuously acquiring multimodal physiological signals of the target limb, including at least electromyography (EMG) signals, joint kinematic angle signals, and neural electrical signals; a state assessment and prediction module for calculating real-time human state indicators based on the multimodal physiological signals, fusing historical state data, and generating future state trend prediction information through a time series prediction model; and a dynamic parameter optimization module for solving the optimal combination of stimulation parameters for the neuromuscular stimulator in real-time using an embedded optimization algorithm, based on the real-time human state indicators and state trend prediction information, with minimizing the objective function as the core. The stimulation parameter combination includes stimulation pulse intensity, frequency sequence, and waveform duty cycle. This invention enables better muscle stimulation modulation.

A method, human interface device, and computer program product that provide improved multilevel switching from each bioelectrical sensor with inclusion of switch filtering based on extraneous events (e.g., spasms). A biosignal is received from a sensor device by an electronic processor of a first electrode switch device. In response to determining that the amplitude of the signal has changed from less than a first switch range to greater than the first switch range and less than the second switch range, the electrode switch device communicates a first switch signal to control the human interface system. In response to determining that the amplitude of the biosignal has changed from less than the second switch range to greater than the second switch range, the electronic switch device performs one of: (i) ignoring the instance and (ii) transmitting a second switch signal to control the human interface system.

The present invention provides improved methods for positioning of an implantable lead in a patient with an integrated EMG and stimulation clinician programmer. The integrated clinician programmer is coupled to the implantable lead, wherein the implantable lead comprises at least four electrodes, and to at least one EMG sensing electrode minimally invasively positioned on a skin surface or within the patient. The method comprises delivering a test stimulation at a stimulation amplitude level from the integrated clinician programmer to a nerve tissue of the patient with a principal electrode of the implantable lead. Test stimulations are delivered at a same stimulation amplitude level for a same period of time sequentially to each of the four electrodes of the implantable lead. A stimulation-induced EMG motor response is recorded with the integrated clinician programmer for each test stimulation on each electrode of the implantable lead via the at least one pair of EMG sensing electrodes so as to facilitate initial positioning of the implantable lead at a target stimulation region.

A glove-mountable system for pelvic floor muscle (PFM) examination includes a first flexible member including a force sensor configured to detect a force applied to a PFM of a patient by a user. A second flexible member includes an electromyography (EMG) electrode, a stimulation electrode, and a 3-D digitization probe. The second flexible member is stacked on the first flexible member and each flexible member is secured to an examination glove. An actuation button is actuated by the user when at least one point of interest is detected in at least on PFM. A computer including a processor and a memory is in communication with the first flexible member, the second flexible member and the actuation button. The computer generates a 3-D map of a plurality of PFMs of the patient based on data received from the first flexible member, the second flexible member and the actuation button.

This invention relates to an instrument for treating neurological or psychiatric disorders using i-wave periodicity-dependent four-pulse theta burst stimulation (iQPS). The system includes a transcranial magnetic stimulation (TMS) stimulator configured to deliver test pulses to a target motor cortex region and therapeutic theta bursts to a treatment region, wherein the pulse frequency is customized according to the patient's individual i-wave periodicity. An electromyography (EMG) device records motor evoked potentials (MEPs) from the target muscles and analyzes the intervals between MEPs to determine the i-wave periodicity. Personalized stimulation enhances cortical plasticity by synchronizing stimulation with the brain's intrinsic neural timing. This invention is applicable to neurological and psychiatric conditions including depression, schizophrenia, stroke recovery, and neuropathic pain. Advantages include improved therapeutic efficacy, reduced patient response variability, and a non-invasive adaptive therapy model aligned with the patient's unique neurophysiological characteristics, thus providing a precise and scalable approach to brain stimulation.

A spinal cord stimulator (SCS) system and method for placing SCS electrodes in a patient for spinal cord stimulation therapy. The SCS system comprises a stimulator and an amplifier unit. The amplifier unit comprises an algorithm module to store and process algorithms for processing data received from recording electrodes placed in a patient's body. The recording electrodes send real-time electromyography (EMG) data related to the patient to the algorithm module. The algorithm module processes the real-time EMG data, including filtering the EMG data to remove artifacts generated by the SCS electrodes. The SCS system compares the filtered EMG data in real-time with the pre-clinical EMG data and displays the comparison data on the display device. The displayed data is used, by the surgeon, for lateralization of the SCS electrode.

A spinal cord stimulator (SCS) system and method for placing SCS electrodes in a patient for spinal cord stimulation therapy. The SCS system includes a stimulator and a base unit. In conjunction with a machine learning (ML) block, the base unit includes an algorithm module to store and process algorithms for processing data received from recording electrodes placed in a patient's body. The recording electrodes send electromyography (EMG) data to the algorithm module. The algorithm module processes and sends the EMG data to a display device. The displayed data is used, by a surgeon, for lateralization of the SCS electrode. The SCS system further includes algorithms to adjust stimulation parameters related to SCS electrodes based upon the surgeon's workflow. Further, the SCS system allows manual modification of stimulation parameters based upon muscle responses and the EMG data from the recording electrodes.

An electromyography measurement sensing pad according to an embodiment of the present invention comprises: an electrode pad including a plurality of electrodes spaced apart from each other; and a wire pad including a wire connected to the plurality of electrodes, wherein a small angle among the angles between the electrode pad and the wire pad satisfies 45 to 90 degrees. The sensing pad for electromyography measurement of the present invention can improve the feeling of irritation of a patient, minimize damage to the esophagus or airways that may occur when inserted into the trachea, have dramatically reduced thickness, and improve signal noise.

An example a wrist-wearable device, comprises a capsule that includes an electromyography (EMG) sensor configured to provide biopotential information of a user for determining a movement of the user. The capsule includes a photoplethysmogram (PPG) sensor configured to provide information for determining a heart rate of the user. The biopotential information and information for determining the heart rate of the user is received simultaneously, and sensing of the biopotential information does not alter the information for determining heart rate of the user, and sensing of the information for determining the heart rate of the user does not alter the biopotential information.

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

The present invention relates to a wrist-wearable device with integrated electromyography sensors and heart rate monitor. An example wrist-wearable device includes a capsule that includes electromyography (EMG) sensors configured to provide biopotential information of a user for determining motion of the user. The capsule includes photoplethysmogram (PPG) sensors configured to provide information for determining a heart rate of the user. The biopotential information and the information for determining a heart rate of the user are received simultaneously, and sensing of the biopotential information does not alter the information for determining a heart rate of the user, and sensing of the information for determining a heart rate of the user does not alter the biopotential information.

This invention relates to the fields of artificial intelligence and biomedical technology, specifically to a robotic automated patching method and system for peripheral nerve conduction detection, as follows: After the doctor selects the examination items on the electromyography instrument, the robot receives instructions and executes the operation; it extracts the patient's limb contour image through a binocular industrial camera system, and calls the nerve-electrode position mapping database to determine the relative positions of standard anatomical feature points; it uses probabilistic Hough transform to filter the lines corresponding to the joints, calculates the intersection points to obtain the feature point image coordinates, combines the relative positions to calculate the target patch position, and then solves the transformation matrix to obtain the three-dimensional coordinates of the robotic arm end; after determining that the electrode inventory is sufficient, it plans a path to grasp the electrodes, aligns and applies them with pressure, verifies the adhesion and contact resistance, and makes fine adjustments if they are unqualified or the impedance drifts; after completing the patching at multiple positioning points, it records the status to form a log, ensuring electrode stability before testing, achieving precise, stable and intelligent patching, reducing medical care intensity and improving diagnostic efficiency.

Abstract A wearable apparatus and method for monitoring physiological parameters of an individual during sleep, the apparatus comprising: (a) a head-applied sensor assembly configured to be worn on the head of an individual, the sensor assembly comprising: (i) at least one electroencephalography (EEG) sensor; (ii) at least one electrooculography (EOG) sensor; (iii) at least one electromyography (EMG) sensor; and (iv) at least one photoplethysmography (PPG) oximetry sensor; and (b) an electronics module operatively coupled to the head-applied sensor assembly and configured to acquire signals from the EEG, EOG, EMG, and PPG oximetry sensors during a common monitoring period. Abstract

This invention provides a method and system for generating intelligent diagnostic reports based on electromyography (EMG) and evoked potential (EVP) data, belonging to the field of medical diagnostic technology. First, it acquires the subject's EMG and EVP data sets, performs difference compensation and association mapping on the two types of data, establishes dynamic association relationships, and obtains a cross-data type association feature set. Then, it calls a multi-round iterative intelligent diagnostic reasoning model to perform symptom association analysis and generate a preliminary diagnostic conclusion. Next, it integrates the preliminary diagnostic conclusion with clinical reference information to obtain an optimized diagnostic conclusion. Finally, it generates a structured intelligent diagnostic report based on the optimized diagnostic conclusion, including an electrophysiological evidence chain, association analysis details, clinical matching results, and phased suggestions. Each part can be viewed through an associated index, improving diagnostic accuracy and efficiency.

Finger angle information is estimated from electromyographic data with less computation. [Solution] The finger angle estimation system 1 comprises an electromyographic signal acquisition unit 11 attached to the surface of the skin to acquire electromyographic signals, a finger angle information acquisition unit 12 that acquires finger joint angle information, and an estimation unit 13 that performs machine learning using the electromyographic signals acquired by the electromyographic signal acquisition unit 11 and the finger joint angle information acquired by the finger angle information acquisition unit 12 as training data to generate a model that estimates the finger joint angle when new electromyographic information is provided. The estimation unit 13 performs machine learning using RC (reservoir computing).

A user interface system enables communication through inaudible speech by detecting physiological signals associated with inner voice communication. The system includes a wearable device positioned in, on, or around a user's ear, housing one or more sensor modalities such as electromyography (EMG) sensors for detecting muscle movements, functional near-infrared spectroscopy (fNIR) sensors for brain activity, and / or detection-and-ranging systems using sonar or radar for micro-deformations. Pre-processing modules condition the sensor data, which is then analyzed by one or more machine learning models to reconstruct the content of the user's inaudible communication and produce output representations. The system enables high-bandwidth natural language interaction without audible vocalization, maintaining privacy while supporting applications including AI assistant interaction, real-time translation, secure authentication, and inter-party communication.

The present invention relates to a movement recovery system, and a method of improving the functional motor recovery of a subject with a movement disorder. The present invention provides for a system and method, which in some embodiments can accurately quantify therapy parameters including compliance, task time spent, muscle coordination and functional improvement by utilizing kinetic, gyroscopic or other movement related information, and / or electromyography (EMG) data. In other embodiments, the system and method provide for functional electrical stimulation (FES) to help control the exercise therapy. The present invention further includes the methods of controlling or utilizing the movement related information, EMG and / or FES to detect, monitor, and control the exercise therapy.

Methods and systems are disclosed for measuring and quantifying inner speech production. The methods and systems present an instruction to a user to produce inner speech and collect electromyograph (EMG) data corresponding to the inner speech. The methods and systems process the EMG data by a machine learning model to generate a prediction comprising a word or phrase corresponding to the inner speech and concurrently generate an evaluation of inner speech production and detection.

An electromyogram (EMG) electrode formed from two different length tubes that each enclose one of the two EMG wires and are sized and oriented with respect to each other so that the ends of the two tubes are spaced apart and offset from each other. The ends of the wires are exposed at the ends of the tubes so that positioning of the electrode in the muscle of an animal will allow for long-term EMG recording while reducing tissue damage at the recording site.