An EMG-Based Robot Control Scheme Robust to Time-Varying EMG Signal Features
نویسندگان
چکیده
منابع مشابه
An Adaptive Upper-Arm EMG-Based Robot Control System
The human-assisting robot can be helpful for improving the life quality of the disabled and elderly. As Electromyography (EMG) is a physiological signal generated during muscle contraction, it implicates, to certain extent, the human intention for movement, and is thus very suitable to serve as the control signal for the assisting robot. In this paper, we develop an upper-arm EMG-based robot co...
متن کاملRobust Methods for EMG Signal Processing for Audio-EMG- based Multi-modal Speech Recognition
This paper proposes robust methods for processing EMG (electromyography) signals in the framework of audio-EMGbased speech recognition. The EMG signals are captured when uttered and used as auxiliary information for recognizing speech. Two robust methods (Cepstral Mean Normalization and Spectral Subtraction) for EMG signal processing are investigated to improve the recognition performance. We a...
متن کاملEMG-based Robot Control Interfaces: Past, Present and Future
Despite the fact, robots came to light approximately 50 years ago, the way humans control them is still an important issue. In particular, since the use of robots is increasingly widening to everyday life tasks (e.g. service robots, robots for clinical applications), the human-robot interface plays a role of the utmost significance. A large number of interfaces have been proposed in previous wo...
متن کاملSignal Processing Approaches for EMG-based Hands-off Cursor Control
There are numerous scenarios in which it would be preferred or necessary to manipulate the screen cursor of a computer’s graphic user interface (GUI). Some specialized operators, such as pilots or surgeons may need to interact with computer-based equipment while their hands are committed to tasks with higher priorities. For individuals with severe motor disabilities, who may not be able to perf...
متن کاملUsing EMG Signal Analysis
A signal analysis technique is developed for discriminating a set of lower arm and wrist functions using surface EMG signals. Data wete obtained from four electrodes placed around the proximal forearm. The functions analyzed included wrist flexion/extension, wrist abduction/adduction, and forearm pronation/supination. Multivariate autoregression models were derived for each function; discrimina...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Transactions on Information Technology in Biomedicine
سال: 2010
ISSN: 1089-7771,1558-0032
DOI: 10.1109/titb.2010.2040832