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This paper presents a study of a human-machine interface in the form of three parallel electromyographic bands placed around the user's forearm, with the influence of sEMG electrode layout on gesture recognition performance as the primary focus. Tested electrode configurations included setups ranging from 4 to 24 electrodes, with varying placement on the subject's forearm, using both monopolar and...
This paper presents a method for radial shift estimation of an electrode array located around the forearm. The algorithm is aimed at band-shaped EMG human-machine interfaces recognising hand gestures. Proposed algorithm relies on the approximation of muscle activity in several regions arranged radially around user's forearm. The intensity is represented as a polygon on a polar plane. To estimate current...
This paper presents a study on the feasibility of an interface based on a mechanomyographic signal (MMG). Existing state-of-the-art studies show attempts of utilisation of MMG signal for gesture recognition where the sensors' location is strictly defined with respect to muscle position. A test setup consisting of 5 IMU sensors arranged in a band form was used. The classifier for 5 gestures (fist,...
In this article, a method for kinematic configuration estimation of a structure similar to a human finger, is presented. The method is based on the EKF and a model reflecting kinematic constraints of a finger-like structure (2-DOF metacarpophalangeal joint, and one 1-DOF proximal interphalangeal rotational joint), using 3 low cost IMUs. During tests, the IMUs were attached to a 3D-printed setup equipped...
A Brain-Computer Interface in motion control application requires high system responsiveness and accuracy. SSVEP interface consisted of 2–8 stimuli and 2 channel EEG amplifier was presented in this paper. The observed stimulus is recognized based on a canonical correlation calculated in 1 second window, ensuring high interface responsiveness. A threshold classifier with hysteresis (T-H) was proposed...
A forearm band consisting of 7 EMG sensors was developed. The band is dedicated to serve as a human-machine interface and its applicability as a gesture-based interface was presented. The gesture recognition was performed by ANN with softmax output function. The classifier uses output entropy function to discriminate between known command gestures and unknown gestures. 15 features of low computational...
The problem of identification/tracking of quasi-periodically varying systems is considered. This problem is a generalization, to the system case, of a classical signal processing task of either elimination or extraction of nonstationary sinusoidal signals buried in noise.
The signal tracking properties of two adaptive notch filtering algorithms are studied analytically using a linear filter approximation technique. Even though restricted to a single frequency case, the presented analysis provides valuable insights into the tracking mechanisms, including the speed/accuracy tradeoffs, the achievable performance bounds, and tracking limitations of the analyzed algorithms...
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