AIMC Topic: Electrodes
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Grasping Force Control of Multi-Fingered Robotic Hands through Tactile Sensing for Object Stabilization.
Sensors (Basel, Switzerland)
Feb 14, 2020
Grasping force control is important for multi-fingered robotic hands to stabilize the grasped object. Humans are able to adjust their grasping force and react quickly to instabilities through tactile sensing. However, grasping force control through t...
An Optimal Electrical Impedance Tomography Drive Pattern for Human-Computer Interaction Applications.
IEEE transactions on biomedical circuits and systems
Jan 20, 2020
In this article, we presented an optimal Electrical Impedance Tomography (EIT) drive pattern based on feature selection and model explanation, and proposed a portable EIT system for applications in human-computer interaction for gesture recognition a...
A Deep Transfer Learning Approach to Reducing the Effect of Electrode Shift in EMG Pattern Recognition-Based Control.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Dec 25, 2019
An important barrier to commercialization of pattern recognition myoelectric control of prostheses is the lack of robustness to confounding factors such as electrode shift, skin impedance variations, and learning effects. To overcome this challenge, ...
Parallel Signal Processing of a Wireless Pressure-Sensing Platform Combined with Machine-Learning-Based Cognition, Inspired by the Human Somatosensory System.
Advanced materials (Deerfield Beach, Fla.)
Dec 16, 2019
Inspired by the human somatosensory system, pressure applied to multiple pressure sensors is received in parallel and combined into a representative signal pattern, which is subsequently processed using machine learning. The pressure signals are comb...
Computational analysis of non-invasive deep brain stimulation based on interfering electric fields.
Physics in medicine and biology
Dec 5, 2019
Neuromodulation modalities are used as effective treatments for some brain disorders. Non-invasive deep brain stimulation (NDBS) via temporally interfering electric fields has emerged recently as a non-invasive strategy for electrically stimulating d...
DESIGN AND DEVELOPMENT OF HUMAN COMPUTER INTERFACE USING ELECTROOCULOGRAM WITH DEEP LEARNING.
Artificial intelligence in medicine
Nov 21, 2019
Today's life assistive devices were playing significant role in our life to communicate with others. In that modality Human Computer Interface (HCI) based Electrooculogram (EOG) playing vital part. By using this method we can able to overcome the con...
Electroencephalogram based communication system for locked in state person using mentally spelled tasks with optimized network model.
Artificial intelligence in medicine
Nov 19, 2019
Due to growth in population, Individual persons with disabilities are increasing daily. To overcome the disability especially in Locked in State (LIS) due to Spinal Cord Injury (SCI), we planned to design four states moving robot from four imagery ta...
Communication Devices for People with Disabilities
Aged, 80 and over
Middle Aged
Computer Simulation
Young Adult
Electroencephalography
Locked-In Syndrome
Adult
Female
Electrodes
Male
Healthy Volunteers
Reproducibility of Results
Sex Characteristics
Brain-Computer Interfaces
Aged
Wavelet Analysis
Humans
Spinal Cord Injuries
Neural Networks, Computer
Algorithms
Adaptive Calibration of Electrode Array Shifts Enables Robust Myoelectric Control.
IEEE transactions on bio-medical engineering
Nov 11, 2019
OBJECTIVE: The objective of this work is to develop a novel method for adaptive calibration of the electrode array shifts toward achieving robust myoelectric pattern-recognition control.
Signal identification system for developing rehabilitative device using deep learning algorithms.
Artificial intelligence in medicine
Nov 8, 2019
Paralyzed patients were increasing day by day. Some of the neurodegenerative diseases like amyotrophic lateral sclerosis, Brainstem Leison, Stupor and Muscular dystrophy affect the muscle movements in the body. The affected persons were unable to mig...
Feasibility of a Sensor-Based Gait Event Detection Algorithm for Triggering Functional Electrical Stimulation during Robot-Assisted Gait Training.
Sensors (Basel, Switzerland)
Nov 5, 2019
Technologies such as robot-assisted gait trainers or functional electrical stimulation can improve the rehabilitation process of people affected with gait disorders due to stroke or other neurological defects. By combining both technologies, the pote...
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