• Corpus ID: 37879858

A Study on EMG-based Biometrics

  title={A Study on EMG-based Biometrics},
  author={Jin-Jyh Su},
Biometrics is a technology that recognizes user’s information by using unique physical features of his or her body such as face, fingerprint, and iris. It also uses behavioral features such as signature, electrocardiogram (ECG), electromyogram (EMG), and electroencephalogram (EEG). Among them, the EMG signal is a sign generated when the muscles move, which can be used in various fields such as motion recognition, personal identification, and disease diagnosis. In this paper, we analyze EMG… 



EMG signal based finger movement recognition for prosthetic hand control

This paper has worked on recognizing the 9 classes of individual and combined finger movement captured using 2 channel EMG sensor using two different classification techniques such as Artificial Neural Network (ANN), and k- nearest neighbors (KNN), to classify the test samples.

GMM modeling of person information from EMG signals

Preliminary results indicate that with well-chosen feature extraction, and modeling approach an identification rate of up to 97.9592% is achievable and high person identification accuracy is achievable.

Evaluation of EMG feature extraction for hand movement recognition based on Euclidean distance and standard deviation

A statistical criterion method using the ratio between Euclidean distance and standard deviation, which can response the distance between two scatter groups and directly address the variation of feature in the same group as a selection tool to find the optimal EMG feature.

EMG 신호 기반 Artificial Neural Network을 이용한 사용자 인식 ( Human Identification using EMG Signal based Artificial Neural Network )

The experimental results show that the rectus femoris, semitendinous, vastus lateralis are appropriate muscles for human identification and MAV, ZC, IEMG, MMAV1, MAVSLP are adaptable features for human Identification.

Improving EMG based classification of basic hand movements using EMD

The results suggest that the use of EMD can increase the discrimination ability of the conventional feature sets extracted from the raw EMG signal.

Recognition of basic hand movements using Electromyography

The aim of this work was to identify six basic movements of the hand using two systems, including an EMG system of Delsys initially for an individual and then for six people with the average successful classification, for these six movements at rates of over 80%.

Real-Time American Sign Language Recognition System Using Surface EMG Signal

  • Celal SavurF. Sahin
  • Computer Science
    2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA)
  • 2015
The proposed Real-Time Sign Language recognition system was proposed by using the surface Electromyography (sEMG) data acquired from subject right forearm for all twenty six American Sign Language gestures, showing that sEMG signal can be used for Real- time SLR systems.

Human Arm Motion Tracking based on sEMG Signal Processing

This paper proposes the human arm motion tracking algorithm based on the signal processing for surface EMG (electromyogram) sensors attached on both upper arm and shoulder and shows the validity of the suggested algorithms through the experiments.

A Control of Electric Wheelchair Using an EMG Based on Degree of Muscular Activity

Two new methods to determine the target angle of the joy-stick based on both the degree and duration of the muscular activity during straining the corresponding muscle are proposed to verify the maneuverability of the EWC.

The Effect of the Signal Stationarity on the EMG Frequency Analysis

ABSTRACT The purpose of this study is to investigate the stationarity of the electromyographic signal in various flexion angles, loads, and window sizes, which influence the result of the mean power