135 results about "Muscle activity" patented technology

The invention relates to the technical field of pelvic floor muscle repair, in particular to a pelvic floor muscle repair method and related equipment, and the method comprises the following steps: acquiring a surface electromyogram signal collected by a surface electrode; based on bispectrum analysis, effective feature extraction is carried out on the abdominal electromyographic signals and the pelvic floor electromyographic signals, the extracted features are input into a deep learning model, and the muscle activity state is analyzed; the muscle activity state is fed back to the patient, and the patient is prompted to adjust contraction and relaxation of pelvic floor muscles through voice; through contraction and relaxation of pelvic floor muscles, the pelvic floor function condition is evaluated based on a Glazer evaluation method; and according to the pelvic floor function condition, selecting a corresponding treatment mode for pelvic floor muscle repair. The pelvic floor muscle repairing effect can be improved.

The invention discloses a multi-link collaborative evaluation and feedback system for upper limb rehabilitation training, and belongs to the technical field of medical rehabilitation, and the system comprises a data collection module which is used for obtaining the related data of the upper limb of a patient in the rehabilitation training process, and the related data comprises the motion posture, the muscle activity condition and the joint activity degree; the data processing module responds to the data acquisition module and is used for preprocessing the acquired related data, including filtering and denoising the related data, acquiring feature information in the preprocessed related data and sending the feature information to the data acquisition module; the feature information comprises movement tracks of joints, contraction intensity and time of muscles and coordination of upper limb movement. Multi-dimensional data such as action postures, muscle movement conditions and joint movement ranges in upper limb rehabilitation training are collected, preprocessing and feature extraction are carried out through the data processing module, the upper limb rehabilitation condition of a patient can be comprehensively and accurately evaluated, and a basis is provided for formulating a personalized rehabilitation scheme.

The invention discloses an exoskeleton attitude prediction system for building construction, particularly relates to the field of attitude prediction, and comprises a multi-dimensional sensing module, a data preprocessing module, an attitude prediction model module and a control decision module. A multi-dimensional sensing module collects joint movement, muscle movement and human-computer interaction force data through a nine-axis IMU, a surface myoelectricity sensor and a miniature strain type force sensor; the preprocessing module obtains standardized feature data through filtering, standardization and exception elimination; the attitude prediction model uses a CNN-LSTM hybrid architecture, and outputs a target attitude of 0.5-2 seconds; and the control decision module compares a prediction result with a safety threshold value, generates control instructions in three levels to drive exoskeleton correction, synchronous feedback and recording, solves the problem of response delay of a traditional exoskeleton, and improves the construction safety and efficiency.

The invention provides a system for controlling a manipulator in real time through hand electromyographic signals, which comprises a data acquisition unit, a terminal equipment unit and a tail end execution unit which are in communication connection through serial ports. The data acquisition unit comprises a data acquisition device and a signal acquisition module, and is configured to acquire a multi-channel electromyographic signal of a hand of a user in real time and perform signal conditioning and digitization so as to obtain a digital signal sequence representing a muscle activity intention of the user; the terminal equipment unit comprises a data preprocessing module, a model training module, a gesture recognition module and an instruction generation module; the tail end execution unit comprises a manipulator control unit which is in communication connection with the control output module and is configured to be used for receiving the manipulator control instruction and driving a manipulator to execute corresponding actions; in combination with a control method, the problems of insufficient real-time performance, poor hand action recognition precision and robustness, unstable control instruction, poor user adaptability and the like in the prior art are solved, and the man-machine interaction performance is improved.

The invention relates to the technical field of nursing monitoring, in particular to a nursing monitoring system for collecting postoperative data of a patient based on myoelectricity sensing. The system comprises a frequency calculation unit, a power quality unit and a monitoring scheme unit. The active degree of the muscle signals around the postoperative wound of the patient is monitored through the broken line and the horizontal reference line in the postoperative wound electromyogram of the patient, when the root mean square point of the corresponding electromyographic signal in the broken line is higher than the horizontal reference line, it is monitored that the active degree of the muscles around the postoperative wound of the patient is increased, and the postoperative wound recovery state of the patient is good; the postoperative wound recovery condition of the patient is monitored in real time through the electromyogram, unnecessary examination and intervention can be reduced, a nurse can accurately judge the muscle activity condition of the patient according to the result of the electromyogram, and pain and burden brought to the patient by excessive examination are avoided. Meanwhile, unnecessary measures can be avoided, the medical cost is reduced, and the nursing efficiency is improved.

The invention discloses a multi-modal fusion muscular tension dynamic assessment method and system, relates to the technical field of biological dynamic assessment, and is used for solving the problem that muscle activity grade classification errors are increased due to dependence on single surface myoelectricity or joint angle sensor data. Joint angle variation, resistance variation and force feedback intensity are extracted, an evaluation mechanism is constructed in combination with region division and historical threshold values, and muscle activity evaluation levels are calculated; and comparing a preset threshold value to identify a flexibility level, entering a resistance evaluation mechanism when a condition is met, analyzing a muscular tension change trend in resistance data, completing dynamic refined judgment of a flexible state, realizing staged, regionalized and trended fusion evaluation, and improving muscular tension state identification and flexibility level judgment precision.

An apparatus (1) comprising a garment (2), the garment comprising: at least one muscle activity sensor (4, 34) for detecting activity of a muscle at least partially covered by the garment; at least one electrical visual indicator device (14); and a controller (11) configured to: receive an activity signal indicative of detected activity of the muscle from the at least one muscle activity sensor; and cause the at least one electrical visual indicator device to output a visual indication of the detected activity of the muscle in dependence on the received activity signal.

The invention relates to the technical field of cervical vertebra rehabilitation systems, and discloses an intelligent self-adaptive cervical vertebra rehabilitation system. The system comprises a multi-mode sensing unit which synchronously collects form data and soft tissue data of the cervical vertebra of a user through an optical mark point array and an ultrasonic probe array to generate a multi-source sensing data set; the intelligent analysis unit constructs a cervical vertebra dynamic mechanical model by using a graph convolutional neural network based on the multi-source sensing data set, analyzes a cervical vertebra joint coupling relation and stress distribution, and generates an analysis parameter set; the strategy generation unit generates a personalized rehabilitation strategy according to the analysis parameter set, the personalized rehabilitation strategy comprises an action sequence and an impedance adjustment parameter, and a strategy instruction set is formed; the dynamic control unit responds to the strategy instruction set and combines muscle activity data fed back by the electromyographic signal sensor in real time to adjust an execution strategy and generate a control command set; and the flexible driving unit drives the soft robot outer skeleton to perform multi-axis linkage rehabilitation training based on the control command set.

The invention belongs to the technical field of shoulder joint detection, and discloses a shoulder joint stability evaluation system based on surface electromyogram signals, which comprises a data acquisition module, a data processing module and an evaluation analysis module. According to the invention, by synchronously acquiring the angle signal and the surface electromyogram signal, the muscle activity dynamic change of the shoulder joint in the whole movement process can be accurately captured in real time, the evaluation accuracy is remarkably improved, and a foundation is built for accurate diagnosis; in a signal processing link, a plurality of filtering methods are comprehensively applied to carry out deep purification on original surface electromyogram signals, various interference factors such as 50Hz power frequency interference, low-frequency motion artifacts and high-frequency noise are effectively eliminated, the purity and reliability of the signals are guaranteed, and high-quality data are provided for subsequent analysis; and meanwhile, a characterization index of an amplitude absolute value mean value is introduced, so that the muscle activity intensity is reflected more visually and accurately, and the internal correlation between the shoulder joint stability and the muscle activity is deeply excavated.

An electromyography (EMG) measurement device includes a garment configured to be worn on an anatomical region of an associated wearer, a plurality of electrodes arranged on the garment to contact skin of the anatomical region when the garment is worn on the anatomical region of the associated wearer, electronics operatively connected with the plurality of electrodes and configured to measure EMG data emanating from the anatomical region, and an electronic processor programmed to derive a contribution of spatial muscle activity of a target muscle or muscle group to the measured EMG data.

The invention discloses a doctor-patient speech communication model training method and system based on multi-modal corpus analysis, and belongs to the crossing field of artificial intelligence and medical treatment, and the method comprises the steps: carrying out the extraction according to an OpenPose algorithm to obtain motion features, carrying out the muscle activity intensity detection to obtain expression features, carrying out the speech recognition to obtain text features, and carrying out the recognition of the text features; speech segmentation is carried out based on the time domain energy parameters, and a segmentation result is subjected to modal analysis to obtain acoustic features; performing feature fusion based on an attention mechanism to obtain fusion features, and inputting an obstacle recognition model to obtain an obstacle type; the method comprises the steps of obtaining an obstacle type, obtaining an intervention strategy and an intervention identity according to a solution mapping relation, taking the obstacle type, the intervention strategy and the intervention identity as multi-dimensional labels, carrying out time domain alignment and structured packaging to obtain target data, and training according to the target data to obtain a communication model used for providing dialogue prompt information. Obstacle recognition accuracy can be improved, and the intelligent agent application effect can be improved.

The invention belongs to the technical field of medical rehabilitation instruments and biological signals, and particularly relates to a multi-mode fusion intelligent rehabilitation evaluation system based on EMG and PPG. The system comprises a flexible multi-mode sensor array module used for collecting surface electromyogram signals EMG and photoelectric volume pulse wave signals PPG and capturing muscle activation intensity and blood perfusion dynamics in real time; the self-adaptive contact enhancing module is used for driving the airbag assembly to dynamically adjust the contact pressure between the embedded pressure sensor and the skin through the micro air pump; the edge calculation unit module is used for carrying out localization processing on the collected original signals, quantitatively evaluating the collaboration of muscle activity and blood flow fluctuation and judging whether muscle contraction drives local blood flow change or not or whether vessel limitation reversely inhibits neuromuscular activation or not; and the lightweight classification model module is used for processing the time-frequency characteristics of the EMG and the waveform fragments of the PPG, and outputting rehabilitation state labels after screening key collaborative characteristics through an attention mechanism.

Methods and systems for determining changes in muscle activity patterns based on the optical response of subcutaneous human body structures are presented, along with methods and systems for controlling assistive robotic systems based on the measured muscle activity patterns. Elements of a muscle activity measurement system are mechanically coupled to a wearable structure that fits closely to a portion of the body of a human user. The muscle activity measurement system includes multiple emitters and detectors at different spacing along the skin surface. In some embodiments, the illumination intensity of each measurement channel, the programmable gain of each measurement channel, or both, are calibrated to maximize measurement sensitivity. In some embodiments, optical measurement data is employed to more accurately locate the muscle activity measurement system with respect to the human body. In some embodiments, a muscle activity measurement system tracks changes in muscle structure over time.

The invention belongs to the technical field of medical electronic equipment, and particularly relates to a wireless surface electromyogram nerve conduction testing system which comprises a flexible wearable sensor module. A multi-mode signal processing module and a wireless transmission and edge calculation module; an intelligent analysis terminal; according to the wireless surface electromyogram nerve conduction test system, a wireless transmission mode is adopted, limitation of a cable to motion is avoided, motion artifacts caused by cable traction are reduced, acquired signals can reflect muscle activity and nerve conduction conditions more truly, the risk of missed diagnosis or misdiagnosis is reduced, and the test efficiency is improved. Secondly, high-precision synchronization of signals and effective noise reduction of the adaptive noise reduction unit are realized through hardware-level timestamps, useful electromyographic signals and nerve conduction signals can be more accurately separated and extracted, interference factors are eliminated, and doctors can more clearly analyze signal characteristics and accurately judge neuromuscular function states; and misjudgment caused by signal interference is avoided.

The embodiment of the invention provides a limb constant-speed motion control method and system based on surface myoelectricity triggering, and belongs to the technical field of constant-speed equipment. The method comprises the following steps: acquiring data of surface myoelectricity; calculating the strength of the electromyographic signals according to the surface electromyographic data to obtain analysis data of muscle activity; adjusting and driving the limbs according to the analysis data of the muscle activity and the data of the surface myoelectricity to obtain activity data; the training condition is analyzed according to the activity data, and limb constant-speed movement control information is obtained. Residual strength of muscles can be fully utilized to actively participate in exercise, and the requirements of users in different rehabilitation stages are met.

The invention discloses a movable muscle magnetic signal detection device, which comprises a magnetic shielding mechanism, an annular sensor array capable of scanning and moving, an arm positioning mechanism and a signal acquisition and processing system, and is characterized in that the magnetic shielding mechanism is used for shielding an environment magnetic field to form a near-zero magnetic measurement environment; the annular sensor array is used for surrounding an arm to collect multi-channel muscle magnetic signals generated by muscle movement, and the arm positioning mechanism is used for fixing the arm and determining a measurement position range. And the signal acquisition and processing system is used for synchronously acquiring a stimulation signal triggered by external stimulation, a multi-channel muscle magnetic signal from the annular sensor array and position information of the annular sensor array, and processing, tracing and positioning the multi-channel muscle magnetic signal. According to the device, miniaturization and mobility of muscle magnetic signal detection equipment are achieved, three-dimensional space distribution information of a muscle magnetic field can be obtained, the spatial resolution is remarkably improved, integrated analysis from signal detection to source positioning is achieved, and a reliable tool is provided for quantitative evaluation of neuromuscular functions.

The invention belongs to the technical field of correction intelligent control, and discloses an intelligent correction evaluation system and method for scoliosis, based on an intelligent multi-module sensor, a scoliosis intelligent correction system is built; based on a human body three-dimensional surface topography measurement technology, establishing an intelligent scoliosis evaluation system; based on an intelligent multi-module sensor and wearable ultrasonic image equipment, internal forms and activity characteristics of spine related muscles during spine correction are evaluated; and comprehensively analyzing a scoliosis correction mechanism by combining a scoliosis correction strategy, a scoliosis correction effect and related muscle activity characteristics of the spine, and determining an optimal biomechanical correction strategy. The external force is applied to the spine to control spine deformity, correction effects generated by different correction strategies are disclosed by analyzing a scoliosis correction mechanism, the conservative treatment effect of a scoliosis patient can be improved, and the device has great significance in improving the life quality of the patient, reducing the family economic burden and relieving the pressure of a medical system.

Method for visualizing multiple sensor signals derived via electrodes from a limb or amputation stump to detect muscle activity, comprising the following steps: • Each signal is assigned a display direction and a display amount • The display direction represents exactly one signal • The displayed value represents the intensity of motor activity of either the respective muscle or its nerve. • The direction and magnitude of all signals are simultaneously displayed in real time on a display device as a single graphical object. • On the display device, reference objects that were saved during previous analysis sessions are displayed simultaneously with the object. • Reference contractions are used as reference objects. • Simultaneously with the visualization, a prosthetic or orthotic device is controlled with the signals, whereby the reference objects are used to parameterize the prosthetic or orthotic control.

An assembly and a method is described. The assembly includes a platform, a motive source, a sensor, a controller and a computerized system. The computerized system has logic configured to cause a processor to send a signal to the controller to cause the motive source to move the platform through at least a portion of a range of inclination angles and to receive data indicating at least one of muscle activity, movement, and ground reaction force applied to the platform at a determined angle, and to cause the processor to analyze the data to determine an orthotic angle for a user's foot.

A muscle activity sensor includes a base textile, an electrode, and an interconnect. The base textile is configured to apply a compression force against a dermal surface of the user. The electrode is coupled to the base textile and includes a sensor layer including a conductive textile coupled to a dermal side of the base textile. The sensor layer is configured to receive electrical signals associated with muscle activity of the user. The electrode may also be configured to provide the electrical signals as an output signal. The interconnect may be coupled to the base textile over a distance from the electrode to an interconnect junction contact such that the interconnect moves with the base textile as the user moves. The interconnect may be further configured to deliver the output signal from the electrode to the interconnect junction contact.

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.

Systems and methods are provided for receiving input via an input device. A first signal is received via a muscle activity sensor. It is determined that the first signal corresponds to a movement of a user digit that does not correspond to a first interaction with an input element of the input device. A digit movement direction is identified, and a prediction of a second interaction with an input element is generated. A first confidence level associated with the prediction is below a threshold, and a second signal is received via a proximity sensor. A velocity of the user digit is determined, and a prediction of the second interaction with a first input element is made. It is identified that a second confidence level associated with the prediction is above the threshold, and a third signal associated with the first input element of the input device is generated for output.

Title of the invention: Monitoring of a patient's intercostal muscle activity during assisted ventilation using a patch sensor. The invention relates to a monitoring system (1) for the respiratory muscle activity of a patient (P), in particular intercostal and / or diaphragmatic muscle activity, comprising a patch sensor (10) including mechanomyography measurement means (13) for performing successive measurements of the patient's muscle activity, and a medical ventilator (20) with control means (25) for processing the measurements performed by the mechanomyography measurement means (13). Display means (30) display an MMG curve (31) representing the patient's muscle activity, in particular intercostal and / or diaphragmatic muscle activity, over time (t) obtained from the processed measurements. Abstract figure: Figure 1

Systems and methods for informing a therapeutic procedure are provided. The systems and methods include receiving one or more signals having muscle activity over a duration of time and comparing the muscle activity throughout the duration of time. The systems and methods also include determining muscle activity quality based on the comparison.

In one embodiment of the present invention, first, muscle activity measurement data is acquired at a prescribed muscle site of a target user, and muscle synergy data at the muscle site of the target user is analyzed on the basis of the acquired muscle activity measurement data. Next, the optimal transportation distance between the muscle synergy data of the target user and reference muscle synergy data analyzed and stored in advance for each of a plurality of reference candidate users is calculated, a reference user having the optimal transportation distance that satisfies a preset condition is selected from among the plurality of reference candidate users, and a stimulus is presented to the muscle site of the target user on the basis of the muscle synergy data of the target user and the reference muscle synergy data of the selected reference user.

A conducting composition includes a topological polymer (e.g., a polyrotaxane polymer) and poly(3,4-ethylene-dioxy thiophene):polystyrene sulfonate (PEDOT:PSS). Devices may include a conducting layer including the conducting compositions, e.g., a device comprising a conducting layer, wherein the conducting layer includes a polyrotaxane polymer and a PEDOT:PSS array. The devices are useful in bioelectronics, including high-resolution electrophysiological monitoring of deformable tissues and localized neuromodulation for high-precision control of individual muscle activities.

The invention discloses a motion function rehabilitation training system for a forearm limb disabled patient based on visual and vibratory tactile collaborative feedback. The system comprises a hardware layer, a data processing layer, an application layer and a user interface layer. The training process is guided through visual feedback, the task completion condition and the gripping strength are reflected through vibration stimulation, the forearm amputation patient is helped to achieve integration of visual information and tactile information, and the accuracy of exercise decision making and the training effect are remarkably improved. Besides, on the basis of the electromyographic signal level of the patient, a personalized rehabilitation training scheme is adopted, and the pertinence and the individual adaptability of rehabilitation training are effectively enhanced by evaluating the muscle activity intensity level and the antagonism coefficient of the patient with the forearm limb disability and customizing the difficulty level of a digital large-synthesis electromyographic game and the training types of life scenes and tasks; functional recovery of the patient is promoted.

The chewing assistance system of the present invention comprises: a chewing information storage unit (31b) for storing information on chewing quality; a muscle activity acquisition unit (21) for acquiring muscle activity signals of a person's chewing muscles; an analysis unit (22) for performing frequency analysis on the muscle activity signals acquired by the muscle activity acquisition unit and analyzing the chewing pattern based on the frequency analysis; a quality judgment unit (23) for judging the quality of the chewing pattern based on the information on the chewing pattern analyzed by the analysis unit; and an extraction unit (24) for extracting auxiliary information corresponding to the chewing quality judged by the quality judgment unit from the chewing information storage unit (32).

According to an example aspect of the present invention, there is provided a method for preparing a biomass-based and biodegradable sensor electrode, e.g. for use in a wearable sensor, the method comprising the steps of combining a natural wax with a vegetable oil in a weight ratio of 1:1 to 1:10 melting the wax with stirring to obtain a melted mixture, then gradually incorporating carbon particles at a weight ratio of 1-50% to the melted mixture, solidifying the melted mixture incorporating carbon particles on a biomass-based substrate into a solidified electrically conductive paste thereon. According to another example aspect of the present invention, there is provided a pressure sensor (1) obtainable by said method. The pressure sensor 1 comprises a porous xerogel dielectric material layer 4 sandwiched between two substrates 11 and 12, whereof each one comprises or consists of a layer of a substrate material 2 respectively 6 which are coated on one side with a layer of an electrically conductive paste 3 respectively 5. Copper tape 7 is affixed to the external surface of each substrate film 11 and 12 to establish electrical contacts.

A system for early detection of movement instability includes a wearable device affixed to a body part of a subject, featuring at least one electromyography (EMG) sensor for detecting electrical muscle activity and at least one motion sensor for detecting movement. A computing device, communicatively connected to the wearable device, receives EMG data from the EMG sensor and motion data from the motion sensor. The computing device identifies movement instability patterns using a machine-learning model trained on datasets of known stable and unstable muscle activity data and movement patterns. It determines impairment indicators based on the identified movement instability patterns and generates a user interface displaying these indicators. This system facilitates early detection and monitoring of movement instability.