Basic Hand Gestures Classification Based on Surface Electromyography
نویسندگان
چکیده
This paper presents an innovative classification system for hand gestures using 2-channel surface electromyography analysis. The system developed uses the Support Vector Machine classifier, for which the kernel function and parameter optimisation are conducted additionally by the Cuckoo Search swarm algorithm. The system developed is compared with standard Support Vector Machine classifiers with various kernel functions. The average classification rate of 98.12% has been achieved for the proposed method.
منابع مشابه
Spectral Collaborative Representation based Classification for Hand Gestures recognition on Electromyography Signals
In this study, we introduce a novel variant and application of the Collaborative Representation based Classification in spectral domain for recognition of the hand gestures using the raw surface Electromyography signals. The intuitive use of spectral features are explained via circulant matrices. The proposed Spectral Collaborative Representation based Classification (SCRC) is able to recognize...
متن کاملPreliminary Testing of a Hand Gesture Recognition Wristband Based on EMG and Inertial Sensor Fusion
Electromyography (EMG) is well suited for capturing static hand features involving relatively long and stable muscle activations. At the same time, inertial sensing can inherently capture dynamic features related to hand rotation and translation. This paper introduces a hand gesture recognition wristband based on combined EMG and IMU signals. Preliminary testing was performed on four healthy su...
متن کاملHand Gestures Recognition Based on SEMG Signal Using Wavelet and Pattern Recognisation
In this paper, we introduced a novel and simple methods of extracting the general features of the hand gestures from surface EMG signal patterns: Hand Extension (H.E), Hand Grasp(H.G),Wrist Extension(W.E),Wrist Flexion(W.F)Pinch(P),Thumb Flexion (T.F). Hand gesture EMG signal classification is demonstrated as a method for prosthesis applications. Recorded electrode signals from the Abductor Pol...
متن کاملOnline Finger Gesture Recognition Using Surface Electromyography Signals
The analysis on the online finger gesture recognition using multi-channel sEMG signals was explored in this paper. Nine types of gestures were applied to be identified, involving six kinds of numerical finger gestures and three kinds of hand gestures. The time domain parameters were extracted to be the features. And then, the probabilistic neural network was utilized to classify the proposed ge...
متن کاملSelection of suitable hand gestures for reliable myoelectric human computer interface
BACKGROUND Myoelectric controlled prosthetic hand requires machine based identification of hand gestures using surface electromyogram (sEMG) recorded from the forearm muscles. This study has observed that a sub-set of the hand gestures have to be selected for an accurate automated hand gesture recognition, and reports a method to select these gestures to maximize the sensitivity and specificity...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره 2016 شماره
صفحات -
تاریخ انتشار 2016