A5046301859- Neuroscience and Neural Engineering
- EEG and Brain-Computer Interfaces
- Advanced Memory and Neural Computing
- Muscle activation and electromyography studies
- Neural dynamics and brain function
- Tactile and Sensory Interactions
- stochastic dynamics and bifurcation
- Gaze Tracking and Assistive Technology
- Neural Networks and Applications
- Transcranial Magnetic Stimulation Studies
- Neural Networks and Reservoir Computing
- Modular Robots and Swarm Intelligence
- User Authentication and Security Systems
- Silk-based biomaterials and applications
- Automotive and Human Injury Biomechanics
- Anomaly Detection Techniques and Applications
- ECG Monitoring and Analysis
- Neurological disorders and treatments
- Ferroelectric and Negative Capacitance Devices
- Motor Control and Adaptation
- CCD and CMOS Imaging Sensors
- Robotic Locomotion and Control
- Blind Source Separation Techniques
- Autopsy Techniques and Outcomes
- Urinary Bladder and Prostate Research
Johns Hopkins University Applied Physics Laboratory
2015-2025
Johns Hopkins University
2002-2023
Johns Hopkins Medicine
2023
University Medical Center Utrecht
2021-2023
National Institute of Mental Health
2021
University of Chicago
2021
Ajanta Pharma (India)
2013
Upper limb prostheses are increasingly resembling the limbs they seek to replace in both form and functionality, including design development of multifingered hands wrists. Hence, it becomes necessary control large numbers degrees freedom (DOFs), required for individuated finger movements, preferably using noninvasive signals. While existing paradigms typically used drive a single-DOF hook-based configurations, dexterous tasks such as individual movements would require more elaborate...
Significance Our ability to manipulate objects relies fundamentally on sensory signals originating from the hand. To restore motor function with upper-limb neuroprostheses requires that somatosensory feedback be provided tetraplegic patient or amputee. Accordingly, we have developed approaches convey information critical for object manipulation—information about contact location, pressure, and timing—through intracortical microstimulation of cortex. In experiments nonhuman primates, show can...
Brain-computer interfaces (BCIs) that reconstruct and synthesize speech using brain activity recorded with intracranial electrodes may pave the way toward novel communication for people who have lost their ability to speak, or are at high risk of losing this ability, due neurological disorders. Here, we report online synthesis intelligible words a chronically implanted brain-computer interface (BCI) in man impaired articulation ALS, participating clinical trial (ClinicalTrials.gov,...
The fast pace of development upper-limb prostheses requires a paradigm shift in EMG-based controls. Traditional control schemes are only capable providing 2 degrees freedom, which is insufficient for dexterous individual fingers. We present framework where myoelectric signals from natural hand and finger movements can be decoded with high accuracy. 32 surface-EMG electrodes were placed on the forearm an able-bodied subject while performing movements. Using time-domain feature extraction...
Significance Electrical stimulation of sensory structures in the brain is a powerful tool to investigate neural circuits and may provide means restore sensation for patients whom nerve not an option. For both purposes, however, it critical understand how design shapes evoked experience. With this mind, we ability monkeys detect discriminate trains electrical pulses delivered their somatosensory cortex through chronically implanted electrode arrays. We show that artificial touch highly...
Tactile sensation is critical for effective object manipulation, but current prosthetic upper limbs make no provision delivering somesthetic feedback to the user. For individuals who require use of limbs, this lack transforms a mundane task into one that requires extreme concentration and effort. Although vibrotactile motors sensory substitution devices can be used convey gross sensations, direct neural interface required provide detailed intuitive feedback. In light this, we describe...
A low-cost, consumer-grade, EEG-based individual authentication system is proposed in this work. While EEG signals are recorded, the subject performs four mental imagery tasks consisting of a baseline measurement, referential limb movement, counting, and rotation for 150 seconds each. The data divided into one second segments, from which features obtained. Three sets extracted each electrode: 6th order autoregressive (AR) coefficients, power spectral density, total five frequency bands. Two...
<h3>Abstract</h3> Neuronal intracellular Cl<sup>-</sup> concentration ([Cl<sup>-</sup>]<sub>i</sub>) influences a wide range of processes such as neuronal inhibition, membrane potential dynamics, pH (pH<sub>i</sub>) or cell volume. Up to date, [Cl<sup>-</sup>]<sub>i</sub> has predominantly been studied in model systems reduced complexity. Here, we implemented the genetically encoded ratiometric indicator Superclomeleon (SCLM) estimate steady-state cortical neurons from anesthetized and awake...
Abstract Brain‐computer interfaces (BCIs) can be used to control assistive devices by patients with neurological disorders like amyotrophic lateral sclerosis (ALS) that limit speech and movement. For control, it is desirable for BCI systems accurate reliable, preferably minimal setup time. In this study, a participant severe dysarthria due ALS operates computer applications six intuitive commands via chronic electrocorticographic (ECoG) implant over the ventral sensorimotor cortex. Speech...
As development toward multi-fingered dexterous prosthetic hands continues, there is a growing need for more flexible and intuitive control schemes. Through the use of generalized electrode placement well-established methods pattern recognition, we have developed basis asynchronous decoding finger positions. With present method, correlations as large 0.91 mean overall errors approximately 11% been achieved with average between decoded actual conformation metacarpophalangeal joints individual...
Previous efforts in brain-machine interfaces (BMI) have looked at decoding movement intent or hand and arm trajectory, but current cortical control strategies not focused on the of 3 actions such as finger movements. The present work demonstrates asynchronous (i.e., where cues indicating onset are known) individual combined Single-unit activities were recorded sequentially from a population neurons M1 area trained rhesus monkeys during flexion extension movements each wrist. Nonlinear...
Objective. One approach to conveying sensory feedback in neuroprostheses is electrically stimulate neurons the cortex. For this be viable, it critical that intracortical microstimulation (ICMS) causes minimal damage brain. Here, we investigate effects of chronic ICMS on neuronal tissue across a variety stimulation regimes non-human primates. We also examine each animal's ability use their hand—the cortical representation which targeted by ICMS—as further assay possible damage. Approach....
Advances in intelligent robotic systems and brain-machine interfaces (BMI) have helped restore functionality independence to individuals living with sensorimotor deficits; however, tasks requiring bimanual coordination fine manipulation continue remain unsolved given the technical complexity of controlling multiple degrees freedom (DOF) across limbs a coordinated way through user input. To address this challenge, we implemented collaborative shared control strategy manipulate coordinate two...
Individuated finger and wrist movements can be decoded using random subpopulations of neurons that are widely distributed in the primary motor (M1) hand area. This work investigates 1) whether it is possible to decode dexterous spatially-constrained volumes as typically recorded from a microelectrode array; 2) decoding accuracy differs due configuration or location array within M1 Single-unit activities were sequentially task-related two rhesus monkeys they performed individuated fingers...
Current machine learning (ML)-based algorithms for filtering electroencephalography (EEG) time series data face challenges related to cumbersome training times, regularization, and accurate reconstruction. To address these shortcomings, we present an ML filtration algorithm driven by a logistic covariance-targeted adversarial denoising autoencoder (TADA). We hypothesize that the expressivity of targeted, correlation-driven convolutional will enable effective while minimizing compute...
We present a neuromorphic silicon chip that emulates the activity of biological spinal central pattern generator (CPG) and creates locomotor patterns to support walking. The implements ten integrate-and-fire neurons 190 programmable digital-to-analog converters act as synapses. This architecture allows for each neuron make synaptic connections any other well eight external input signals one tonic bias input. chip's functionality is confirmed by series experiments in which it controls motor...
Somatosensation is critical for effective object manipulation, but current upper limb prostheses do not provide such feedback to the user. For individuals who require use of prosthetic limbs, this lack transforms a mundane task into one that requires extreme concentration and effort. Although vibrotactile motors sensory substitution devices can be used convey gross sensations, direct neural interface required detailed intuitive feedback. The viability intracortical microstimulation (ICMS) as...
Existing brain-computer interface (BCI) control of highly dexterous robotic manipulators and prosthetic devices typically rely solely on neural decode algorithms to determine the user's intended motion. Although these approaches have made significant progress in ability high degree freedom (DOF) manipulators, perform activities daily living (ADL) is still an ongoing research endeavor. In this paper, we describe a hybrid system that combines elements autonomous manipulation with maneuver...
Objective. The dexterous manipulation of objects depends heavily on somatosensory signals from the limb. development anthropomorphic robotic arms and algorithms to decode intended movements neuronal has stimulated need restore somatosensation for use in upper-limb neuroprostheses. Without touch proprioception, patients have difficulty controlling prosthetic limbs a level that justifies required invasive surgery. Intracortical microstimulation (ICMS) through chronically implanted electrode...
We describe in detail the behavior of an inhibitory Central Pattern Generator (CPG) network for robot control. A four-neuron, mutual forms basic coordinating pattern locomotion. This then inhibits eight-neuron used to drive patterned movement. show that we can get predictable control important relationships such as phase hip and knee by adjusting tonic parameters. demonstrate concept both a simulation is trotting bipedal well aVLSI CPG chip generates spiking burst patterns. Our results...
Meaningful and repeatable tactile sensations can be evoked by electrically stimulating primary somatosensory cortex. Intracortical microstimulation (ICMS) may thus a viable approach to restore the sense of touch in individuals who have lost it, for example tetraplegic patients. One potential limitations this approach, however, is that high levels current damage neuronal tissue if resulting densities are too high. The limited range safe ICMS amplitudes limits dynamic ICMS-evoked sensations....
The restoration of cutaneous sensation to fingers and fingertips is critical achieving dexterous prosthesis control for individuals with sensorimotor dysfunction. However, localized reproducible fingertip sensations in humans have not been reported via intracortical microstimulation (ICMS) humans. Here, we show that ICMS a human participant was capable eliciting percepts 7 spanning both hands, including 6 regions (i.e., 3 on each hand). Median percept size estimated include 1.40 finger or...