scholarly journals The Current Status of EMG Signals on Kinematics Needed for Precise Online Myoelectric Control and the Development Direction

2021 ◽  
Vol 271 ◽  
pp. 01029
Author(s):  
Tong Kang
Keyword(s):  
Pattern Recognition ◽  
Degrees Of Freedom ◽  
Quantum Control ◽  
Quantum Information Processing ◽  
Current Status ◽  
Prosthetic Control ◽  
Pattern Recognition Problem ◽  
Emg Signal ◽  
Traditional Pattern ◽  
Electric Signals

Widely accepted idea is the prosthetic control problem could be regarded as the pattern recognition problem. The prosthetic control means there are several differences such as distinguishable electric signals between different activation of muscle. However, this conventional method could not provide proper control of the artificial limbs. Kinematics behavior is continuous and needs the coordination of multiple physiological degrees of freedom (DOF) among various joints. Currently, a huge challenge is achieving precise, coherent and elegant coordination protheses which needs many DOFs to rehabilitation of patients with limb deficiency. This article analyzed the principles of control of bionic limbs from the aspect of EMG and traditional pattern recognition. According to the research results, the following conclusions can be given. Since the quantum amplitudes are complex numbers generally, different parameter should be included and analyzed together during the quantum information processing. Besides, the quantum control scheme could be combined with the classic one. What is more, other sensor modes should be applied for robust control instead of the EMG signal only.

INTELLIGENT UPPER-LIMB PROSTHETIC CONTROL (iULP) WITH NOVEL FEATURE EXTRACTION METHOD FOR PATTERN RECOGNITION USING EMG

2021 ◽  
pp. 2150043
Author(s):  
SIDHARTH PANCHOLI ◽  
AMIT M. JOSHI
Keyword(s):  
Pattern Recognition ◽  
Upper Limb ◽  
Classification Accuracy ◽  
Time Derivative ◽  
Machine Learning Algorithms ◽  
Prosthetic Control ◽  
Myoelectric Prosthesis ◽  
Feature Extraction Method ◽  
Similar Work ◽  
Emg Signal

EMG signal-based pattern recognition (EMG-PR) techniques have gained lots of focus to develop myoelectric prosthesis. The performance of the prosthesis control-based applications mainly depends on extraction of eminent features with minimum neural information loss. The machine learning algorithms have a significant role to play for the development of Intelligent upper-limb prosthetic control (iULP) using EMG signal. This paper proposes a new technique of extracting the features known as advanced time derivative moments (ATDM) for effective pattern recognition of amputees. Four heterogeneous datasets have been used for testing and validation of the proposed technique. Out of the four datasets, three datasets have been taken from the standard NinaPro database and the fourth dataset comprises data collected from three amputees. The efficiency of ATDM features is examined with the help of Davies–Bouldin (DB) index for separability, classification accuracy and computational complexity. Further, it has been compared with similar work and the results reveal that ATDM features have excellent classification accuracy of 98.32% with relatively lower time complexity. The lower values of DB criteria prove the good separation of features belonging to various classes. The results are carried out on 2.6[Formula: see text]GHz Intel core i7 processor with MATLAB 2015a platform.

The Principle of Homology Continuity and Geometrical Covering Learning for Pattern Recognition

2018 ◽  
Vol 32 (12) ◽  
pp. 1850042 ◽  
Author(s):  
Xin Ning ◽  
Weijun Li ◽  
Jiang Xu
Keyword(s):  
Neural Network ◽  
Pattern Recognition ◽  
Fundamental Property ◽  
Experimental Results ◽  
New Method ◽  
Recognition Problem ◽  
Pattern Learning ◽  
Learning Method ◽  
Pattern Recognition Problem ◽  
Traditional Pattern

Homology Continuity is a fundamental property of the nature, but few of the traditional pattern recognition algorithms were aware of it. Firstly, this paper gives a brief description to the Principle of Homology Continuity (PHC), and tries to mathematically redefine it. Then, we introduce a PHC-based pattern learning method — Geometrical Covering Learning (GCL), following the Hyper sausage neural network as an instance of GCL. Lastly, we propose a GCL solution to the “two-spirals” pattern recognition problem. The final experimental results show that the new method is feasible and efficient.

SUPPORT VECTOR IDENTIFICATION OF SEISMIC ELECTRIC SIGNALS

2003 ◽  
Vol 17 (04) ◽  
pp. 545-565 ◽  
Author(s):  
A. IFANTIS ◽  
S. PAPADIMITRIOU
Keyword(s):  
Pattern Recognition ◽  
A Priori ◽  
Support Vector ◽  
Mathematical Basis ◽  
Generalization Performance ◽  
Seismic Electric Signals ◽  
Feature Spaces ◽  
Intelligence Models ◽  
Traditional Pattern ◽  
Electric Signals

Traditional pattern recognition approaches usually generalize poorly on difficult tasks as the problem of identification of the Seismic Electric Signals (SES) electrotelluric precursors for earthquake prediction. This work demonstrates that the Support Vector Machine (SVM) can perform well on this application. The a priori knowledge consists of a set of VAN rules for SES signal detection. The SVM extracts implicitly these rules from properly preprocessed features and obtains generalization performance founded upon a robust mathematical basis. The potentiality of obtaining generalization potential even in feature spaces of high dimensionality bypasses the problems due to overtraining of the conventional machine learning architectures. The paper considers the optimization of the generalization performance of the SVM. The results indicate that the SVM outperforms many alternative computational intelligence models for the task of SES pattern recognition.

Quantum control and information processing in optical lattices

2001 ◽  
Vol 1 (Special) ◽  
pp. 20-32
Author(s):  
P.S. Jessen ◽  
D.L. Haycock ◽  
G. Klose ◽  
G.A. Smith ◽  
I.H. Deutsch ◽  
...  
Keyword(s):  
Information Processing ◽  
Quantum Logic ◽  
Degrees Of Freedom ◽  
Quantum Control ◽  
Optical Lattices ◽  
Cold Atoms ◽  
Quantum Information Processing ◽  
Full Density ◽  
Experimental Conditions ◽  
Qubit Operations

Neutral atoms offer a promising platform for single- and many-body quantum control, as required for quantum information processing. This includes excellent isolation from the decohering influence of the environment, and the existence of well developed techniques for atom trapping and coherent manipulation. We present a review of our work to implement quantum control and measurement for ultra-cold atoms in far-off-resonance optical lattice traps. In recent experiments we have demonstrated coherent behavior of mesoscopic atomic spinor wavepackets in optical double-well potentials, and carried out quantum state tomography to reconstruct the full density matrix for the atomic spin degrees of freedom. This model system shares a number of important features with proposals to implement quantum logic and quantum computing in optical lattices. We present a theoretical analysis of a protocol for universal quantum logic via single qubit operations and an entangling gate based on electric dipole-dipole interactions. Detailed calculations including the full atomic hyperfine structure suggests that high-fidelity quantum gates are possible under realistic experimental conditions.

THE TRAPPED-ION QUBIT: COHERENT CONTROL IN INFINITE-DIMENSIONAL QUANTUM SYSTEMS

2009 ◽  
Vol 24 (32) ◽  
pp. 2565-2578
Author(s):  
C. RANGAN
Keyword(s):  
Quantum Computing ◽  
Quantum System ◽  
Quantum Control ◽  
Coherent Control ◽  
Quantum Information Processing ◽  
Quantum Systems ◽  
Infinite Dimensional ◽  
Trapped Ion ◽  
Rich Variety ◽  
Control Research

Theories of quantum control have, until recently, made the assumption that the Hilbert space of a quantum system can be truncated to finite dimensions. Such truncations, which can be achieved for most quantum systems via bandwidth restrictions, have enabled the development of a rich variety of quantum control and optimal control schemes. Recent studies in quantum information processing have addressed the control of infinite-dimensional quantum systems such as the quantum states of a trapped-ion. Controllability in an infinite-dimensional quantum system is hard to prove with conventional methods, and infinite-dimensional systems provide unique challenges in designing control fields. In this paper, we will discuss the control of a popular system for quantum computing the trapped-ion qubit. This system, modeled by a spin-half particle coupled to a quantized harmonic oscillator, is an example for a surprisingly rich variety of control problems. We will show how this infinite-dimensional quantum system can be examined via the lens of the Finite Controllability Theorem, two-color STIRAP, the generalized Heisenberg system, etc. These results are important from the viewpoint of developing more efficient quantum control protocols, particularly in quantum computing systems. This work shows how one can expand the scope of quantum control research to beyond that of finite-dimensional quantum systems.

scholarly journals Experimental implementation of precisely tailored light-matter interaction via inverse engineering

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Ying Yan ◽  
Chunyan Shi ◽  
Adam Kinos ◽  
Hafsa Syed ◽  
Sebastian P. Horvath ◽  
...  
Keyword(s):  
Quantum Dynamics ◽  
Quantum Control ◽  
Quantum Information Processing ◽  
Rare Earth Ions ◽  
Adiabatic Process ◽  
Physical Constraints ◽  
Shortcuts To Adiabaticity ◽  
Experimental Implementation ◽  
Speed Up ◽  
Light Matter Interaction

AbstractAccurate and efficient quantum control in the presence of constraints and decoherence is a requirement and a challenge in quantum information processing. Shortcuts to adiabaticity, originally proposed to speed up the slow adiabatic process, have nowadays become versatile toolboxes for preparing states or controlling the quantum dynamics. Unique shortcut designs are required for each quantum system with intrinsic physical constraints, imperfections, and noise. Here, we implement fast and robust control for the state preparation and state engineering in a rare-earth ions system. Specifically, the interacting pulses are inversely engineered and further optimized with respect to inhomogeneities of the ensemble and the unwanted interaction with other qubits. We demonstrate that our protocols surpass the conventional adiabatic schemes, by reducing the decoherence from the excited-state decay and inhomogeneous broadening. The results presented here are applicable to other noisy intermediate-scale quantum systems.

Auditory Systems of Drosophila and Other Invertebrates

2017 ◽  
pp. 302-318
Author(s):  
Yun Doo Chung ◽  
Jeongmi Lee
Keyword(s):  
Pattern Recognition ◽  
Sound Localization ◽  
Current Understanding ◽  
Auditory Information ◽  
Neural Processing ◽  
Recent Event ◽  
Auditory Systems ◽  
Intraspecific Communication ◽  
Basic Features ◽  
Electric Signals

Hearing in invertebrates has evolved independently as an adaptation to avoid predators or to mediate intraspecific communication. Although many invertebrate groups are able to respond to sound stimuli, insects are the only group in which hearing is widely used. Therefore, we will focus here on the auditory systems of some well-known insect models. Appearance of the ability to perceive sound in insects is presumably a quite recent event in evolution. As a result of independent evolution, diverse types of hearing organs are evolved in insects. Here we will introduce basic features of insect ears and the mechanisms through which sound stimuli are converted into neuronal electric signals. We will also summarize our current understanding of neural processing of auditory information, including tonotopy, sound localization, and pattern recognition.

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