• Corpus ID: 8793230

Increasing performance signa

  title={Increasing performance signa},
  author={Minkyu Kim and Keehoon Kim},
This paper proposes a spe pattern classification problems using from human forearm muscles. For classification accuracy, a multi-referen class so that the classifier can cover obtained signals for training. The result accuracy through an off-line simulation validate the proposed concept. 

Figures and Tables from this paper


Multiple Hand Gesture Recognition Based on Surface EMG Signal
For realizing a multi-DOF myoelectric control system with a minimal number of sensors, research work on the recognition of twenty-four hand gestures based on two-channel surface EMG signal measured
Feature reduction and selection for EMG signal classification
In this study, most complete and up-to-date thirty-seven time domain and frequency domain features have been proposed and it is indicated that most time domain features are superfluity and redundancy.
Classification of EMG signals using combined features and soft computing techniques
  • A. Subasi
  • Computer Science
    Appl. Soft Comput.
  • 2012
The usefulness of the different feature extraction methods for describing MUP morphology is investigated and comparative analysis suggests that the ANFIS modelling is superior to the DFNN and MLPNN in at least three points: slightly higher recognition rate; insensitivity to overtraining; and consistent outputs demonstrating higher reliability.
Online remote control of a robotic hand configurations using sEMG signals on a forearm
This study presents an online remote control of a robotic hand using sEMG signals on a forearm and verified that human could control the remote side robot hand in real-time using his or her s EMG signals with less than 50 seconds recorded training data.
Development of a wearable and dry sEMG electrode system for decoding of human hand configurations
A surface EMG interface that employs dry-type electrodes, a single supplied circuit for reduced weight, two voltage followers to improve input impedance, and a modified driven-right-leg circuit using a virtual ground circuit is proposed and developed.
Electromyography Pattern-Recognition-Based Control of Powered Multifunctional Upper-Limb Prostheses
The human history has been accompanied by accidental trauma, war, and congenital anomalies. Consequently, amputation and deformity have been dealt with, one way or another, throughout the ages. More
Surface EMG in advanced hand prosthetics
It is shown that machine learning, together with a simple downsampling algorithm, can be effectively used to control on-line, in real time, finger position as well as finger force of a highly dexterous robotic hand.
" Electromyography PatternRecognitionBased Control of Powered Multifunctional UpperLimb Prostheses
  • 2011