787 results about "Stimulation Parameter" patented technology

The invention discloses an intelligent orthopedic rehabilitation self-adaptive evaluation method and device based on multi-modal physiological feedback. The method comprises the steps that multi-modal physiological data including electromyographic signals, knee joint three-dimensional motion trails, plantar pressure distribution and cognitive input degree of a subject are synchronously collected; constructing a three-dimensional baseline vector according to the MMT muscle force test, knee joint ROM measurement and VAS pain score of the subject; inputting the multi-modal physiological data and the three-dimensional baseline vector into a personalized orthopedic rehabilitation model, and outputting a knee joint function index prediction value and personalized rehabilitation adjustment parameters; dynamically adjusting electrical stimulation parameters according to rehabilitation adjustment parameters output by the personalized orthopedic rehabilitation model; if the cognitive load index exceeds the early warning line, the electrical stimulation intensity is reduced; otherwise, activating the hippocampus body wave stimulation mode. Adjustment is carried out according to the real-time state of the subject, blindness and subjectivity in the rehabilitation process are avoided, and the rehabilitation efficiency and success rate are improved.

The invention relates to the technical field of biomedical engineering and neuroscience, and discloses an in-ear vagus nerve stimulation control method, system and device based on scalp electroencephalography, and the method comprises the steps: collecting a scalp electroencephalogram signal, a body movement signal and a pulse signal of a to-be-detected user; performing preprocessing and frequency domain separation on the signal; calculating a sleep coupling score, and dividing a physiological state according to the sleep coupling score; dynamically adjusting the intensity and frequency of intra-ear vagus nerve stimulation of the user according to the physiological state, and generating feedback data; in-ear vagus nerve stimulation is performed and the dynamic adjustment parameters are updated based on the feedback data. According to the method, accurate sleep recognition is realized through multi-source signal parallel processing and SCS modeling, and the classification precision is remarkably improved; lSTM prediction and biphase modulation are combined to optimize stimulation parameters, sleep time is shortened, and side effects are reduced; a GPU acceleration and low-power-consumption framework is adopted, and efficient self-adaptive closed-loop regulation and control are achieved.

The invention discloses a nerve regulation system for cognitive impairment, and the system comprises a cognitive behavior evaluation module which is used for recognizing a cognitive defect field which needs to be improved by a target object; the image data acquisition module is used for acquiring and preprocessing task state nuclear magnetic data and T1 weighted structure images of a target object; the brain region activation analysis module is used for determining a neural regulation potential target spot according to the preprocessed task state nuclear magnetic data; the brain network analysis module is used for identifying key nodes related to cognitive defects; the stimulation target screening module is used for determining an individualized stimulation target of the target object according to the nerve regulation potential target and the key node of the target object; the time domain interference electrical stimulation simulation and implementation module is used for performing electrical stimulation on the individualized stimulation target spot; and the dynamic feedback adjustment module is used for dynamically adjusting the stimulation parameters and enhancing the personalized regulation and control effect. By adopting the method and the device, the specific brain region directly related to the cognitive impairment can be determined, so that the targeting and the accuracy of treatment are enhanced.

A system for restoring muscle function to the lumbar spine to treat low back pain is provided. The system may include electrodes coupled to an implantable pulse generator (IPG), a handheld activator configured to transfer a stimulation command to the IPG, and an external programmer configured to transfer programming data to the IPG. The stimulation command directs the programmable controller to stimulate the tissue in accordance with the programming data. The system may include a software-based programming system run on a computer such that the treating physician may program and adjust stimulation parameters.

The invention relates to the technical field of biomedicine, and discloses a female private rehabilitation training system integrating a breathing method and neural motor control, and the system comprises a data collection module which is used for collecting physiological data of a user; the personalized training scheme generation module is used for generating a personalized nerve-muscle-fascia training scheme; the nerve-muscle synchronous resonance training module is used for constructing a time sequence matching model and generating an adaptive training dynamic control instruction; the space-time adaptability training module is used for adjusting training duration, intensity and stimulation frequency; the multi-dimensional nerve-muscle feedback fusion module is used for constructing a feedback response model; and the fascia synchronous activation and relaxation module is used for coordinating the tension relationship between the fascia and the muscle system. According to the method, feature matching is carried out on an electric activation heat map matrix through the convolutional neural network, analysis of a myoelectricity response state transition probability is carried out in combination with a hidden Markov model, and stimulation parameters and respiratory rhythm are optimized in real time according to a training process.

The invention provides a nervous system closed-loop regulation and control system based on transcranial opto-acoustic cooperation. The nervous system closed-loop regulation and control system is composed of EEG monitoring equipment, personal information data, an opto-acoustic cooperation system, a multi-mode large model and a psychological disease database. Aiming at a transcranial infrared light and ultrasonic co-stimulation technology of a patient, through optimization of stimulation parameters, photoacoustic bidirectional regulation and control are realized, a multi-modal large model is used as a base, multi-modal data fusion and reinforcement learning are used as technical means, closed-loop photoacoustic co-stimulation system equipment is designed, and intervention parameters are automatically optimized; an effective regulation and control method for psychological diseases is realized through a non-intrusive brain stimulation technology, and adaptive adjustment and closed-loop feedback of parameters are realized. Brain waves of a patient are detected in real time, personal information of the patient is collected, the information is integrated and transmitted into the system after evaluation, intervention is adjusted in real time according to different brain states, and feedback is utilized to adjust parameters of next intervention and stimulate the precise regulation and control process.

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

The invention belongs to the technical field of nerve regulation and control, and discloses a portable noninvasive brain deep electrical stimulation system based on time interference, and the system comprises an electroencephalogram signal collection unit which is used for obtaining an electroencephalogram signal in a high-quality resting state, and carrying out the signal preprocessing and feature extraction, thereby obtaining an optimal stimulation envelope frequency; the personalized finite element modeling unit is used for constructing a head personalized model and outputting optimal electrode configuration and stimulation parameters for a target brain region target spot; the electrode positioning and stimulation execution unit is used for realizing accurate positioning of an electrode position and implementing time interference electrical stimulation; the MCU unit is used for realizing data management, task scheduling and remote communication; the human-computer interaction unit is used for realizing visual treatment flow and parameter setting; and the power supply management unit provides stable working voltage for the system. According to the invention, the portable, intelligent and personalized modeling of the electrical stimulation treatment equipment is realized, and the precision and efficiency of nerve regulation and control are remarkably improved.

The invention discloses a closed-loop noninvasive spinal cord electrical stimulation regulation and control method and system based on motion data, and the system is provided with a flexible electrode array patch which is attached to the skin surface of a to-be-tested human body; the sensing module is used for collecting electromyographic signals or acceleration signals of a user; the signals are processed, and characteristic values related to actions and motions are extracted; the closed-loop feedback module compares the characteristic value with a model set characteristic / threshold value, and judges whether to start stimulation site and stimulation parameter adjustment or not; automatically selecting an optimal electrode unit and a corresponding stimulation parameter based on a judgment result; the dynamic regulation and control module controls the optimal electrode unit to output stimulation current, and regulates the activity of corresponding spinal cord neurons; and continuously performing closed-loop adjustment on the electrode unit and the stimulation parameters according to the motion feedback data. According to the method and system, precise stimulation and closed-loop regulation and control based on the motion response of the patient are achieved, and the problems that stimulation target positioning depends on artificial experience, parameter adjustment is not timely, and individualized and closed-loop feedback capacity is lacked are solved.

The present disclosure provides systems and methods for providing neurostimulation therapy according to patient features. The patient features may be analyzed to develop a patient model between physiological and / or patient reported features and optimal settings for a neurostimulation therapy using machine learning operations. The model is trained using data corresponding to time intervals in which electrical pulses are applied to the patient, including video kinematic data, patient reported pain levels, implanted or worn sensor patient data, and stimulation parameters. The model is used to control ongoing neurostimulation therapy for the patient.

The invention relates to the technical field of rehabilitation medicine, in particular to a body carving slimming method for fat metabolism based on bioelectricity feedback and acupoint stimulation. The invention provides a body carving slimming method based on bioelectricity feedback and acupoint stimulation. The body carving slimming method comprises the four steps of obtaining, processing, acupoint stimulation and outputting. Bioelectricity signals and weight data of body parts of a user are collected through a bioelectricity and weight detection device. The muscle activity state and fat distribution are analyzed, a posture improvement value is calculated, and a personalized body carving training scheme is generated. In an acupoint stimulation link, electrical stimulation is performed on a specific acupoint according to the scheme, bioelectricity feedback is monitored in real time, and stimulation parameters are dynamically adjusted. And generating a personalized report containing the posture change and the training effect evaluation, and providing suggestions to the user. According to the method, the effect, safety and individuation are remarkably improved, and a new direction is opened up for development of the body carving and slimming field.

The invention relates to the technical field of medical rehabilitation, and particularly discloses a finger rehabilitation electrical stimulation parameter control method and system, and the method comprises the steps: obtaining a multi-channel surface electromyogram signal and finger joint kinematics data of a patient; according to the multi-channel surface electromyogram signals, target fine actions of the patient are recognized; according to the target fine motion and the finger joint kinematics data, a multi-muscle group cooperative activation mode and an expected motion trail are obtained through analysis; generating an electrical stimulation parameter combination for different muscle groups according to a multi-muscle group collaborative activation mode; outputting multi-channel electrical stimulation to the patient based on the electrical stimulation parameter combination, and continuously adjusting the electrical stimulation parameter combination on line according to the deviation between the kinematics data of the finger joints and the expected motion trail; the method solves the problems that an existing method is difficult to effectively simulate complex multi-muscle group coordination, complex in parameter adjustment and difficult to adapt to dynamic changes of a patient, and the effect of assisting the patient in complex and fine finger action training is achieved.

The invention relates to the technical field of neural engineering and brain-computer interfaces, in particular to a closed-loop multi-modal nerve stimulation system and method based on time interference, and the system comprises a multi-modal stimulation module which is used for integrating electrical stimulation, magnetic stimulation and optical genetic stimulation, and generating a time interference field domain; the neural state sensing module is used for collecting real-time electroencephalogram signals, blood oxygen concentration and neural metabolite level data; the neural control center is used for fusing neural state data and stimulation parameters, and dynamically adjusting time interference frequency and stimulation intensity through an adaptive algorithm; the time sequence cooperation engine predicts a neural response time phase based on a deep learning model, and optimizes a stimulation time sequence and a mode switching strategy; and the visual interaction platform is used for rendering the nerve activation thermodynamic diagram and the stimulation parameter adjustment curve in real time. Therefore, the problems of adjustment strategy solidification, low adjustment precision, insufficient energy conversion efficiency and the like in the prior art are solved.

The invention discloses a transcutaneous electrical stimulation device based on a large language model, and relates to the technical field of wearable devices. The transcutaneous electrical stimulation equipment based on the large language model comprises a data acquisition and preprocessing module, a feature extraction and fusion module, a model training and prediction module and a real-time information processing and response module, real-time data processing and intervention capabilities are integrated, human body data can be analyzed in real time, electrical stimulation parameters can be automatically adjusted, an instant treatment or adjustment scheme is provided for the problems of arrhythmia, chronic pain and the like, and the timeliness and effectiveness of treatment are greatly improved. And secondly, by fusing the physiological signal features and the symptom text features, the equipment can more comprehensively understand the health condition of the user, so that a more accurate treatment scheme is provided. Besides, the equipment also has the functions of anomaly detection and trend analysis, can predict potential health risks, and triggers an alarm in time when a serious anomaly is detected, thereby effectively guaranteeing the life safety of the user.

The invention discloses a brain deep nerve stimulation method and system based on adaptive adjustment, and relates to the technical field of brain deep nerve regulation, and the method comprises the steps: collecting a local field potential signal of a brain deep target region of a target patient, and extracting a beta frequency band power spectrum density and a gamma frequency band phase synchronization index as neural activity characteristic parameters; determining an individual baseline value and a preset threshold value based on historical data, and outputting a stimulation adjustment trigger signal when the beta frequency band power spectral density exceeds the individual baseline value and the gamma frequency band phase synchronization index is lower than the preset threshold value; in response to the trigger signal, calculating an optimal stimulation parameter combination through a gradient descent optimization algorithm and executing nerve regulation; and monitoring the signal change after regulation and control, calculating a relative change rate and updating a threshold value. Through a two-parameter joint judgment mechanism and a threshold updating strategy, individualized adaptive adjustment of stimulation parameters is realized, and the stimulation accuracy and the treatment effect are improved.

The invention provides a control method and system for electronic acupuncture equipment, and the method comprises the steps: obtaining the symptoms of a user, and recommending a matched acupoint for the user based on a symptom-acupoint database; the electronic acupuncture device scans a target area where the matched acupoint is located, skin resistance distribution and an infrared thermal image of the target area are obtained, the acupoint matching degree is calculated through a probability model, and the acupoint is positioned based on the acupoint matching degree; and monitoring whether the scanning area of the electronic acupuncture device is aligned with the recommended acupuncture point or not in real time, outputting current stimulation by the electronic acupuncture device when the scanning area is monitored to be stopped, and adjusting the output current according to the symptom of the user after the user is stimulated. By means of the method and the corresponding system, the user can be assisted in accurately positioning the acupuncture points, the stimulation parameters can be dynamically adjusted according to feedback information obtained after acupuncture and moxibustion are conducted on the user, and the optimal curative effect is kept.

The invention discloses an ear and neck percutaneous vagus nerve stimulation device based on an internal feeling signal, which belongs to the related technical field of percutaneous vagus nerve stimulation and is composed of a physiological signal acquisition module, a data transmission module, a signal processing and analyzing module, a control module, ear and neck integrated stimulation equipment, an interaction module and a power supply. The device supports neck or ear vagus nerve stimulation and a stimulation mode of combined use of the neck and the ear vagus nerve. And the same or different stimulation parameters can be used for the vagus nerves of the ears and the neck. According to the non-invasive design, the electrode does not need to be placed in a human body through an operation, nerves are stimulated through an external stimulator, and the risk of injury to the human body is reduced; and meanwhile, the output of two stimulation parameters taVNS and tcVNS can be adjusted adaptively through physiological signals and internal feeling indexes, and the fusion effect is improved.

One aspect of the present disclosure relates to a system for treating obstructive sleep apnea in a subject. The system can include a power source and a neuromuscular stimulator in electrical communications with the power source. The neuromuscular stimulator can include a controller and at least one electrode. The controller can be configured to receive certain power and stimulation parameters associated with a therapy signal from the power source. The at least one electrode can be configured to deliver the therapy signal to a target tissue associated with control of a posterior base of the tongue of the subject.

The invention is suitable for the field of health care treatment, and provides a forest health care activity system and an evaluation method thereof. The multi-sensory collaboration module comprises a cross-modal sensory calibration unit; a physiological sensing module; the intelligent evaluation module is used for calculating immersion degree and healing effect indexes based on a multi-dimensional quantitative model, and dynamically optimizing sensory stimulation parameters according to corresponding calculation results; the multi-dimensional quantitative model comprises a mapping relation between user physiological features and sensory stimulation parameters; the safety interaction module is used for monitoring abnormal fluctuation of the physiological indexes of the user in real time and triggering a sensory stimulation intensity down-regulation mechanism when the abnormal fluctuation exceeds a safety threshold value; regional and body restrictions of traditional forest health care are broken through, and immersive experience is provided for groups such as disabled people through multi-module cooperation. The immersion is enhanced through multi-sensory cooperation, personalized optimization is achieved through intelligent evaluation, user safety is guaranteed through safe interaction, and the universality and effectiveness of forest rehabilitation are further improved.

The invention provides an electronic acupuncture closed-loop control method and system based on multi-modal information feedback. The method comprises the following steps: acquiring long-term, short-term and real-time representation information of a testee under an initial stimulation scheme; the long-term and short-term characterization information is input into a collaborative generative network model for learning, a target stimulation scheme is output, the collaborative generative network model comprises traditional Chinese and western medicine agents, the traditional Chinese and western medicine agents learn the long-term and short-term characterization information, and a corresponding traditional Chinese medicine treatment scheme and an electrical stimulation scheme are output. The collaborative generation network model carries out collaborative training on traditional Chinese and western medicine agents; calculating an index deviation between the real-time characterization information and the standard characterization information to generate a real-time information deviation matrix; inputting the target electrical stimulation scheme and the real-time information deviation matrix into a parameter deviation prediction agent for learning and prediction; and performing parameter adjustment on the target stimulation scheme based on the predicted stimulation parameter deviation matrix to realize long / short time and real-time double-layer closed-loop control of the electronic acupuncture.

An example of a system for delivering neurostimulation may include a programming control circuit and a user interface. The programming control circuit may be configured to generate stimulation parameters controlling delivery of the neurostimulation according to a pulse sequence. The pulse sequence may include a series of neurostimulation pulses and be defined by sequence parameters and one or more modulation functions each modulating an adjustable parameter selected from the sequence parameters. The user interface may be configured to set the pulse sequence to a tonic pulse sequence by determining an initial value for each adjustable parameter and set the pulse sequence to a modulated pulse sequence by selecting one or more adjustable parameters, determining a modulation function for each selected adjustable parameter, and applying the determined modulation function to that selected adjustable parameter to modulate the tonic pulse sequence.

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.

Methods and systems for spinal cord stimulation (SCS) are disclosed. The methods and systems involve the use of electrode leads implanted within the spine of a patient to record nerve responses induced by a stimulus. The disclosed neural responses differ in various aspects from the electrical responses previously measured in the SCS context, such as stimulation artifacts and evoked compound action potentials (ECAPs). The disclosed neural responses typically occur at a later time after inducing the stimulation pulse. Another significant feature is that when the frequency of evoked stimulation is ultra-low, such as about 10 Hz or less, the disclosed neural response is most significantly observed at a consistent, relatively constant amplitude as a whole. The disclosed methods and systems may use these neural responses as indications of pain, treatment, and / or another clinically relevant dimension to guide / confirm stimulation placement, as well as feedback control for stimulation parameters.

The invention discloses a transcranial electrical stimulation control method and system for enhancing working memory, and the method comprises the steps: collecting and preprocessing a multi-channel endogenous electroencephalogram signal of a target object during the execution of a cognitive task, and obtaining a to-be-analyzed electroencephalogram signal; aligning the to-be-analyzed electroencephalogram signal with a behavior expression label generated by the target object during execution of the cognitive task to obtain an associated signal; according to the correlation signal, obtaining a channel pair with the highest phase synchronism between the forehead lobe and the apical lobe of the target object as a target channel pair; based on the associated signal data of the target channel pair, extracting frequency band features to generate stimulation parameters of radial and cranial electrical stimulation; and outputting transcranial electrical stimulation according to the stimulation parameters, and collecting endogenous electroencephalogram signals during stimulation in real time, so that the stimulation parameters are dynamically adjusted, and closed-loop regulation and control on the brain area of the target object are realized. Therefore, by the adoption of the method and device, accurate control over the endogenous phase difference between the prefrontal lobe and the apical lobe can be achieved, and therefore the work memory performance is enhanced.

The invention discloses a nerve regulation and control intervention system based on time domain interference electrical stimulation, and the system comprises a magnetic resonance image registration module which receives and registers an imported magnetic resonance image, and obtains a to-be-processed MRI image; the head model tissue segmentation module is used for performing head model tissue segmentation on the to-be-processed MRI image; the stimulation simulation module is used for performing stimulation simulation based on the tissue segmentation structure to obtain a front lead field matrix; the intervention coordinate selection module is used for determining a target brain region corresponding to a target spot brain region coordinate position needing stimulation intervention and putting the target brain region into a running sequence; the electrode position arrangement optimization module is used for verifying, optimizing and finely adjusting the electric field intensity of the target brain region under different electrode arrangement schemes to obtain an electrode configuration parameter result and displaying the electrode configuration parameter result; the parameter importing module is used for receiving the selected electrode configuration parameters and imported preset electrical stimulation parameters; and the electrical stimulation module is used for performing electrical stimulation on the target brain region of the target object. According to the application, the accuracy and the effectiveness of nerve regulation and control treatment can be realized.

The invention relates to the technical field of electric acupuncture apparatuses, and discloses a method and a system for automatically adjusting stimulation parameters of an electric acupuncture apparatus. According to the method, body surface electromyographic signals, skin impedance and capillary hemodynamic parameters of a user are collected in real time through a sensor set, feature extraction and analysis are conducted through a time sequence prediction model of a Transform architecture, and physiological feature data are generated. And then, constructing a user physiological state characterization model by adopting a multi-modal neural perception fusion algorithm, and carrying out collaborative optimization on the electrical stimulation parameters through an adaptive quantum particle swarm optimization algorithm to generate a stimulation parameter combination matched with the real-time neuromuscular response characteristics of the user. The system drives electrical stimulation output according to the parameter combination, monitors physiological data changes in real time, realizes closed-loop dynamic balance of stimulation parameters and biological feedback signals through the dynamic parameter compensation module, and improves the treatment effect and safety.

A neurostimulation system that has a programmer which has a power supply and processors with processing circuitry and a neurostimulation device which has power supply, processors and communication circuitry for providing communication with a neurostimulation device as well as communication circuitry for communication with the programmer. The neurostimulation system is configured to deliver treatment to a patient in accordance with a clinician prescribed protocol of a regimen. The neurostimulation system compares a delivered therapy treatment which has a treatment protocol to a defined treatment protocol of a prescribed treatment and adjusts the prescribed treatment stimulation parameters to compensate for a difference between the delivered neurostimulation therapy treatment and the prescribed treatment protocol for closely approximating the prescribed treatment protocol.

The invention discloses a patient improvement effect analysis method for controlling spinal cord electrical stimulation through an implantable brain-computer interface, and relates to the technical field of medical rehabilitation, and the method comprises the steps: multi-dimensional collaborative data collection: implanting electrodes in a target brain region and below a spinal cord injury segment, installing a detection element at an exoskeleton key part, and carrying out multi-dimensional collaborative data collection; a sensor is attached to a lower limb preset muscle group, electroencephalogram signals, SCS stimulation parameters, EXS motion data and neuromuscular response data are synchronously collected, and time correlation marks are embedded; according to the method, the reliability of motion intention decoding is remarkably improved by adopting a mode of combining multi-source signal preprocessing and a multi-mode intention recognition model, and in the signal preprocessing stage, the self-adaptive filtering algorithm combining Kalman filtering and wavelet threshold denoising is applied, so that the motion intention decoding efficiency is improved. SCS electrical stimulation interference, EXS motor noise and physiological noise in the electroencephalogram signals are effectively removed.

A system for restoring muscle function to the lumbar spine to treat low back pain is provided. The system may include electrodes coupled to an implantable pulse generator (IPG), a handheld activator configured to transfer a stimulation command to the IPG, and an external programmer configured to transfer programming data to the IPG. The stimulation command directs the programmable controller to stimulate the tissue in accordance with the programming data. The system may include a software-based programming system run on a computer such that the treating physician may program and adjust stimulation parameters.

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.