HYBRID CLASSIFICATION STRATEGY OF EMG SIGNALS FOR ROBOTIC HAND CONTROL

2021 ◽  
pp. 2150015
Author(s):  
Fazia sbargoud ◽  
Mohamed Djeha ◽  
Mohamed Guiatni ◽  
Noureddine Ababou
Keyword(s):  
Degrees Of Freedom ◽  
Wavelet Packet ◽  
Hybrid Approach ◽  
Human Motion ◽  
Robotic Hand ◽  
User Intention ◽  
Emg Signal ◽  
Hybrid Classification ◽  
Electromyographic Signal ◽  
Artificial Neural Network Ann

Among the different bio-signals modalities, Electromyographic signal (EMG) has been one of the frequently used signals in the bio-robotics applications field. This is due to the fact that the EMG reflects directly the muscle activity of the user following the human motion intention. Consequently, the decoding of this intention is an essential task for controlling devices such as prosthetic hands and exoskeletons, based on EMG signals. This paper deals with the processing of EMG signals of the forearm muscles, in order to control two degrees of freedom (2 DoFs) robotic hand. The main contribution of this paper is the proposal of a hybrid approach that combines a pattern and a non-pattern recognition-based strategy. The proposed approach aims to take advantage of both strategies and overcome their shortcomings leading to a better analysis of the user movement intention. The EMG recorded signals are processed for feature extraction based on a Wavelet Packet Decomposition (WPD) method and classification using an Artificial Neural Network (ANN). Furthermore, we investigate the effect of the various parameters such as the applied force level, the number of the EMG channels and the window length of the EMG signal. The proposed approach is validated experimentally under realistic conditions. Very interesting results have been obtained for user intention decoding.

Human Carrying Simulation With Symmetric and Asymmetric Loads

2012 ◽  
Author(s):  
Yujiang Xiang ◽  
Jasbir S. Arora ◽  
Salam Rahmatalla ◽  
Hyun-Joon Chung ◽  
Rajan Bhatt ◽  
...  
Keyword(s):  
Degrees Of Freedom ◽  
Human Motion ◽  
Human Model ◽  
Physical Constraints ◽  
Digital Human Model ◽  
Load Carrying ◽  
Reaction Forces ◽  
Asymmetric Load ◽  
Optimization Schemes ◽  
Digital Human

Human carrying is simulated in this work by using a skeletal digital human model with 55 degrees of freedom (DOFs). Predictive dynamics approach is used to predict the carrying motion with symmetric and asymmetric loads. In this process, the model predicts joints dynamics using optimization schemes and task-based physical constraints. The results indicated that the model can realistically match human motion and ground reaction forces data during symmetric and asymmetric load carrying task. With such prediction capability the model could be used for biomedical and ergonomic studies.

Miniaturized Pneumatic Artificial Muscles Actuating a Bio-Inspired Robot Hand

2013 ◽  
Author(s):  
Thomas E. Pillsbury ◽  
Ryan M. Robinson ◽  
Norman M. Wereley
Keyword(s):  
Degrees Of Freedom ◽  
Full Scale ◽  
Constitutive Relationship ◽  
Force Density ◽  
Human Hand ◽  
Artificial Muscles ◽  
Specific Work ◽  
Robotic Hand ◽  
Robot Hand ◽  
Pneumatic Artificial Muscles

Pneumatic artificial muscles (PAMs) are used in robotics applications for their light-weight design and superior static performance. Additional PAM benefits are high specific work, high force density, simple design, and long fatigue life. Previous use of PAMs in robotics research has focused on using “large,” full-scale PAMs as actuators. Large PAMs work well for applications with large working volumes that require high force and torque outputs, such as robotic arms. However, in the case of a compact robotic hand, a large number of degrees of freedom are required. A human hand has 35 muscles, so for similar functionality, a robot hand needs a similar number of actuators that must fit in a small volume. Therefore, using full scale PAMs to actuate a robot hand requires a large volume which for robotics and prosthetics applications is not feasible, and smaller actuators, such as miniature PAMs, must be used. In order to develop a miniature PAM capable of producing the forces and contractions needed in a robotic hand, different braid and bladder material combinations were characterized to determine the load stroke profiles. Through this characterization, miniature PAMs were shown to have comparably high force density with the benefit of reduced actuator volume when compared to full scale PAMs. Testing also showed that braid-bladder interactions have an important effect at this scale, which cannot be modeled sufficiently using existing methods without resorting to a higher-order constitutive relationship. Due to the model inaccuracies and the limited selection of commercially available materials at this scale, custom molded bladders were created. PAMs created with these thin, soft bladders exhibited greatly improved performance.

Study of grasp-energy based optimal distribution of contact forces on a humanoid robotic hand during object grasp

Robotica ◽  
2021 ◽  
pp. 1-26
Author(s):  
Sourajit Mukherjee ◽  
Abhijit Mahapatra ◽  
Amit Kumar ◽  
Avik Chatterjee
Keyword(s):  
Optimization Algorithm ◽  
Degrees Of Freedom ◽  
Simulated Data ◽  
Performance Measure ◽  
Contact Forces ◽  
Contact Model ◽  
Robotic Hand ◽  
Net Energy ◽  
Optimal Distribution

Abstract A novel grasp optimization algorithm for minimizing the net energy utilized by a five-fingered humanoid robotic hand with twenty degrees of freedom for securing a precise grasp is presented in this study. The algorithm utilizes a compliant contact model with a nonlinear spring and damper system to compute the performance measure, called ‘Grasp Energy’. The measure, subject to constraints, has been minimized to obtain locally optimal cartesian trajectories for securing a grasp. A case study is taken to compare the analytical (applying the optimization algorithm) and the simulated data in MSC.Adams $^{^{\circledR}}$ , to prove the efficacy of the proposed formulation.

Smart Prosthetic Hand with Object Slippage Detection, Measurement, and Control

2014 ◽  
Vol 5 (3) ◽  
pp. 25-48
Author(s):  
Girish Sriram ◽  
Alex Jensen ◽  
Steve C. Chiu
Keyword(s):  
Control System ◽  
Control Strategy ◽  
Degrees Of Freedom ◽  
Sensory Feedback ◽  
Position Control ◽  
Tactile Feedback ◽  
Human Hand ◽  
Computing Platform ◽  
Emg Signal ◽  
A New Technique

The human hand along with its fingers possess one of the highest numbers of nerve endings in the human body. It thus has the capacity for the richest tactile feedback for positioning capabilities. This article shares a new technique of controlling slippage. The sensing system used for the detection of slippage is a modified force sensing resistor (FSR®). The control system is a fuzzy logic control algorithm with multiple rules that is designed to be processed on a mobile handheld computing platform and integrated/working alongside a traditional Electromyography (EMG) or Electroencephalography (EEG) based control system used for determining position of the fingers. A 5 Degrees of Freedom (DOF) hand, was used to test the slippage control strategy in real time. First a reference EMG signal was used for getting the 5 DOF hand to grasp an object, using position control. Then a slip was introduced to see the slippage control strategy at work. The results based on the plain tactile sensory feedback and the modified sensory feedback are discussed.

scholarly journals Virtualization of Robotic Hands Using Mobile Devices †

Robotics ◽  
2019 ◽  
Vol 8 (3) ◽  
pp. 81
Author(s):  
Santiago T. Puente ◽  
Lucía Más ◽  
Fernando Torres ◽  
and Francisco A. Candelas
Keyword(s):  
Degrees Of Freedom ◽  
Robotic Hand ◽  
Robot Hand ◽  
Real Time Control ◽  
Robotic Hands ◽  
Robot Operating System ◽  
Server Side ◽  
Time Control ◽  
Unity 3D ◽  
Real Robot

This article presents a multiplatform application for the tele-operation of a robot hand using virtualization in Unity 3D. This approach grants usability to users that need to control a robotic hand, allowing supervision in a collaborative way. This paper focuses on a user application designed for the 3D virtualization of a robotic hand and the tele-operation architecture. The designed system allows for the simulation of any robotic hand. It has been tested with the virtualization of the four-fingered Allegro Hand of SimLab with 16 degrees of freedom, and the Shadow hand with 24 degrees of freedom. The system allows for the control of the position of each finger by means of joint and Cartesian co-ordinates. All user control interfaces are designed using Unity 3D, such that a multiplatform philosophy is achieved. The server side allows the user application to connect to a ROS (Robot Operating System) server through a TCP/IP socket, to control a real hand or to share a simulation of it among several users. If a real robot hand is used, real-time control and feedback of all the joints of the hand is communicated to the set of users. Finally, the system has been tested with a set of users with satisfactory results.

scholarly journals A Novel Hybrid Approach for Chronic Disease Classification

2020 ◽  
Vol 15 (1) ◽  
pp. 1-19 ◽  
Author(s):  
Divya Jain ◽  
Vijendra Singh
Keyword(s):  
Chronic Disease ◽  
Classification Accuracy ◽  
Hybrid Approach ◽  
Substantial Reduction ◽  
Disease Classification ◽  
Computational Time ◽  
Second Phase ◽  
Two Phase ◽  
Hybrid Classification ◽  
Diagnostic Framework

A two-phase diagnostic framework based on hybrid classification for the diagnosis of chronic disease is proposed. In the first phase, feature selection via ReliefF method and feature extraction via PCA method are incorporated. In the second phase, efficient optimization of SVM parameters via grid search method is performed. The proposed hybrid classification approach is then tested with seven popular chronic disease datasets using a cross-validation method. Experiments are then conducted to evaluate the presented classification method vis-à-vis four other existing classifiers that are applied on the same chronic disease datasets. Results show that the presented approach reduces approximately 40% of the extraneous and surplus features with substantial reduction in the execution time for mining all datasets, achieving the highest classification accuracy of 98.5%. It is concluded that with the presented approach, excellent classification accuracy is achieved for each chronic disease dataset while irrelevant and redundant features may be eliminated, thereby substantially reducing the diagnostic complexity and resulting computational time.

Performance Analysis of Nek5000 for Single-Assembly Calculations

2018 ◽  
Author(s):  
Elia Merzari ◽  
Ronald Rahaman ◽  
Misun Min ◽  
Paul Fischer
Keyword(s):  
Degrees Of Freedom ◽  
Hybrid Approach ◽  
Reactor Core ◽  
Navier Stokes ◽  
Benchmark Problems ◽  
Application Development ◽  
Pressurized Water ◽  
Eddy Simulation ◽  
Common Framework ◽  
Full Core

The ExasSMR project focuses on the exascale application of single and coupled Monte Carlo (MC) and computational fluid dynamics (CFD) physics. Work is based on the Shift MC depletion, OpenMC temperature-dependent MC, and Nek5000 CFD codes. The application development objective is to optimize these applications for exascale execution of full-core simulations and to modularize and integrate them into a common framework for coupled and individual execution. Given the sheer scale of nuclear systems, the main algorithmic driver on the CFD side is weak scaling. The focus for the first four years of the project is on demonstrating scaling up to a full reactor core for high-fidelity simulations of turbulence. Full-core fluid calculations aimed at better predicting the steady-state performance will be conducted with a hybrid approach in which large eddy simulation is used to simulate a portion of a core and unsteady Reynolds-averaged Navier-Stokes handles the rest. This zonal hybrid approach provides an additional scaling dimension besides the number of assemblies. The present manuscript focuses on performance assessment using assembly-level simulations with Nek5000. We discuss the development of two benchmark problems: a subchannel (single-rod) problem to assess internode performance and a larger full-assembly problem representative of a small modular reactor (SMR). We note that current SMR assemblies are considerably simpler than pressurized water reactor assemblies since they contain no mixing vanes. This feature allows for considerable reduction in the degrees of freedom required to simulate the full core. We discuss profiling and scaling results with Nek5000, describe current bottlenecks and potential limitations of the approach, and suggest optimizations for future investigation.

scholarly journals Analysis of Upper-Limb and Trunk Kinematic Variability: Accuracy and Reliability of an RGB-D Sensor

2020 ◽  
Vol 4 (2) ◽  
pp. 14
Author(s):  
Alessandro Scano ◽  
Robert Mihai Mira ◽  
Pietro Cerveri ◽  
Lorenzo Molinari Tosatti ◽  
Marco Sacco
Keyword(s):  
Upper Limb ◽  
Gold Standard ◽  
Degrees Of Freedom ◽  
Cost Effective ◽  
Human Motion ◽  
Working Environments ◽  
Wide Range ◽  
Upper Limb Movements ◽  
Clinical Environments ◽  
Point To Point

In the field of motion analysis, the gold standard devices are marker-based tracking systems. Despite being very accurate, their cost, stringent working environments, and long preparation time make them unsuitable for small clinics as well as for other scenarios such as industrial application. Since human-centered approaches have been promoted even outside clinical environments, the need for easy-to-use solutions to track human motion is topical. In this context, cost-effective devices, such as RGB-Depth (RBG-D) cameras have been proposed, aiming at a user-centered evaluation in rehabilitation or of workers in industry environment. In this paper, we aimed at comparing marker-based systems and RGB-D cameras for tracking human motion. We used a Vicon system (Vicon Motion Systems, Oxford, UK) as a gold standard for the analysis of accuracy and reliability of the Kinect V2 (Microsoft, Redmond, WA, USA) in a variety of gestures in the upper limb workspace—targeting rehabilitation and working applications. The comparison was performed on a group of 15 adult healthy subjects. Each subject had to perform two types of upper-limb movements (point-to-point and exploration) in three workspace sectors (central, right, and left) that might be explored in rehabilitation and industrial working scenarios. The protocol was conceived to test a wide range of the field of view of the RGB-D device. Our results, detailed in the paper, suggest that RGB-D sensors are adequate to track the upper limb for biomechanical assessments, even though relevant limitations can be found in the assessment and reliability of some specific degrees of freedom and gestures with respect to marker-based systems.

scholarly journals Test-retest reliability of electromyographic signal parameters used to evaluate neuromuscular fatigue in quadriceps femoris muscle

Kinesiology ◽  
2016 ◽  
Vol 48 (2) ◽  
pp. 174-181 ◽  
Author(s):  
Cristiano Rocha da Silva ◽  
Danilo de Oliveira Silva ◽  
Ronaldo Valdir Briani ◽  
Marcella Ferraz Pazzinatto ◽  
Deisi Ferrari ◽  
...  
Keyword(s):  
Vastus Lateralis ◽  
Rectus Femoris ◽  
Neuromuscular Fatigue ◽  
Median Frequency ◽  
Endurance Time ◽  
Retest Reliability ◽  
Emg Signal ◽  
Electromyographic Signal ◽  
Test Retest Reliability ◽  
Voluntary Contractions

The purpose of this study was to analyze the test-retest reliability of the median frequency (MDF) and root mean square (RMS) used to determine the onset of neuromuscular fatigue (NF) during sustained fatiguing contractions of the quadriceps. Eighteen healthy men were tested on two days, and electromyographic (EMG) signals were recorded from the vastus medialis (VM), rectus femoris (RF) and vastus lateralis (VL) during sustained isometric contractions at 20 and 70% of maximum voluntary contractions (MVC) held until exhaustion. The reliability of endurance time was excellent at 20% MVC and poor at 70% MVC. EMG variables were evaluated: (1) at the beginning of the test; (2) at NF; and (3) at the end of the test. The NF time values presented poor reliability. The MDF has shown, in general, poor reliability at 20 and 70% MVC, whereas the RMS reliability presented better results for both loads, especially for RF, followed by the VM and VL muscles. The MDF and RMS values extracted from NF showed poor reliability at 20 and 70% MVC, which suggests caution in using these variables extracted from the EMG signal to determine the onset of NF.

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