scholarly journals Optimal strategy of sEMG feature and measurement position for grasp force estimation

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0247883
Author(s):  
Changcheng Wu ◽  
Qingqing Cao ◽  
Fei Fei ◽  
Dehua Yang ◽  
Baoguo Xu ◽  
...  
Keyword(s):  
Time Domain ◽  
Absolute Error ◽  
Estimation Accuracy ◽  
Generalized Regression Neural Network ◽  
Prosthetic Hand ◽  
Data Sets ◽  
Force Estimation ◽  
Optimal Measurement ◽  
Actual Force ◽  
Grasp Force

Grasp force estimation based on surface electromyography (sEMG) is essential for the dexterous control of a prosthetic hand. Nowadays, although increasing the number of sEMG measurement positions and extracting more features are common methods to increase the accuracy of grasp force estimation, it will increase the computational burden. In this paper, an approach based on analysis of variance (ANOVA) and generalized regression neural network (GRNN) for optimal measurement positions and features is proposed, with the purpose of using fewer measurement positions or features to achieve higher estimation accuracy. Firstly, we captured six channels of sEMG from subjects’ forearm and grasp force synchronously. Then, four kinds of features in time domain are extracted from each channel of sEMG. By combining different measurement position sets (MPSs) and feature set (FSs), we construct 945 data sets. These data sets are fed to GRNN to realize grasp force estimation. Normalized root mean square error (NRMS), normalized mean of absolute error (NMAE), and correlation coefficient (CC) between estimated grasp force and actual force are introduced to evaluate the performance of grasp force estimation. Finally, ANOVA and Tukey HSD testing are introduced to analyze grasp force estimation results so as to obtain the optimal measurement positions and features. We obtain the optimal MPSs for grasp force estimation when different FSs are employed, and the optimal FSs when different MPSs are utilized.

Inverse calculation of biochemical oxygen demand models based on time domain for the tidal Foshan River

2014 ◽  
Vol 70 (1) ◽  
pp. 15-23
Author(s):  
Li Er ◽  
Zeng Xiangying
Keyword(s):  
Time Domain ◽  
Biochemical Oxygen Demand ◽  
Dispersion Coefficient ◽  
Oxygen Demand ◽  
Tidal River ◽  
Data Sets ◽  
Longitudinal Dispersion Coefficient ◽  
Demand Models ◽  
Flow Directions ◽  
Derivatives Of

To simulate the variation of biochemical oxygen demand (BOD) in the tidal Foshan River, inverse calculations based on time domain are applied to the longitudinal dispersion coefficient (E(x)) and BOD decay rate (K(x)) in the BOD model for the tidal Foshan River. The derivatives of the inverse calculation have been respectively established on the basis of different flow directions in the tidal river. The results of this paper indicate that the calculated values of BOD based on the inverse calculation developed for the tidal Foshan River match the measured ones well. According to the calibration and verification of the inversely calculated BOD models, K(x) is more sensitive to the models than E(x) and different data sets of E(x) and K(x) hardly affect the precision of the models.

Design and slip prevention control of a multi-sensory anthropomorphic prosthetic hand

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Bo Zeng ◽  
Hongwei Liu ◽  
Hongzhou Song ◽  
Zhe Zhao ◽  
Shaowei Fan ◽  
...  
Keyword(s):  
Real Time ◽  
Upper Limb ◽  
Tactile Feedback ◽  
Prosthetic Hand ◽  
Discrete Wavelet ◽  
Accuracy Rate ◽  
Content Type ◽  
Grasp Stability ◽  
Grasp Force ◽  
Slip Detection

Purpose The purpose of this paper is to design a multi-sensory anthropomorphic prosthetic hand and a grasping controller that can detect the slip and automatically adjust the grasping force to prevent the slip. Design/methodology/approach To improve the dexterity, sensing, controllability and practicability of a prosthetic hand, a modular and multi-sensory prosthetic hand was presented. In addition, a slip prevention control based on the tactile feedback was proposed to improve the grasp stability. The proposed controller identifies slippages through detecting the high-frequency vibration signal at the sliding surface in real time and the discrete wavelet transform (DWT) was used to extract the eigenvalues to identify slippages. Once the slip is detected, a direct-feedback method of adjusting the grasp force related with the sliding times was used to prevent it. Furthermore, the stiffness of different objects was estimated and used to improve the grasp force control. The performances of the stiffness estimation, slip detection and slip control are experimentally evaluated. Findings It was found from the experiment of stiffness estimation that the accuracy rate of identification of the hard metal bottle could reach to 90%, while the accuracy rate of identification of the plastic bottles could reach to 80%. There was a small misjudgment rate in the identification of hard and soft plastic bottles. The stiffness of soft plastic bottles, hard plastic bottles and metal bottles were 0.64 N/mm, 1.36 N/mm and 32.55 N/mm, respectively. The results of slip detection and control show that the proposed prosthetic hand with a slip prevention controller can fast and effectively detect and prevent the slip for different disturbances, which has a certain application prospect. Practical implications Due to the small size, low weight, high integration and modularity, the prosthetic hand is easily applied to upper-limb amputees. Meanwhile, the method of the slip prevention control can be used for upper-limb amputees to complete more tasks stably in daily lives. Originality/value A multi-sensory anthropomorphic prosthetic hand is designed, and a method of stable grasps control based on slip detection by a tactile sensor on the fingertip is proposed. The method combines the stiffness estimation of the object and the real-time slip detection based on DWT with the design of the proportion differentiation robust controller based on a disturbance observer and the force controller to achieve slip prevention and stable grasps. It is verified effectively by the experiments and is easy to be applied to commercial prostheses.

A COMPARISON OF SCORING METRICS FOR PREDICTING THE NEXT NAVIGATION STEP WITH MARKOV MODEL-BASED SYSTEMS

2010 ◽  
Vol 09 (04) ◽  
pp. 547-573 ◽  
Author(s):  
JOSÉ BORGES ◽  
MARK LEVENE
Keyword(s):  
Markov Model ◽  
Prediction Accuracy ◽  
Prediction Models ◽  
Markov Models ◽  
Real Data ◽  
Absolute Error ◽  
Brier Score ◽  
Data Sets ◽  
Extensive Evaluation ◽  
The Impact

The problem of predicting the next request during a user's navigation session has been extensively studied. In this context, higher-order Markov models have been widely used to model navigation sessions and to predict the next navigation step, while prediction accuracy has been mainly evaluated with the hit and miss score. We claim that this score, although useful, is not sufficient for evaluating next link prediction models with the aim of finding a sufficient order of the model, the size of a recommendation set, and assessing the impact of unexpected events on the prediction accuracy. Herein, we make use of a variable length Markov model to compare the usefulness of three alternatives to the hit and miss score: the Mean Absolute Error, the Ignorance Score, and the Brier score. We present an extensive evaluation of the methods on real data sets and a comprehensive comparison of the scoring methods.

Validation of Adaptive Gaussian Process Regression Model Used for SIF Prediction

2018 ◽  
Author(s):  
Arvind Keprate ◽  
R. M. Chandima Ratnayake ◽  
Shankar Sankararaman
Keyword(s):  
Regression Model ◽  
Gaussian Process ◽  
Prediction Accuracy ◽  
Experimental Validation ◽  
Gaussian Process Regression ◽  
Absolute Error ◽  
Coefficient Of Determination ◽  
Data Sets ◽  
Maximum Absolute Error ◽  
Data Points

The main aim of this paper is to perform the validation of the adaptive Gaussian process regression model (AGPRM) developed by the authors for the Stress Intensity Factor (SIF) prediction of a crack propagating in topside piping. For validation purposes, the values of SIF obtained from experiments available in the literature are used. Sixty-six data points (consisting of L, a, c and SIF values obtained by experiments) are used to train the AGPRM, while four independent data sets are used for validation purposes. The experimental validation of the AGPRM also consists of the comparison of the prediction accuracy of AGPRM and Finite Element Method (FEM) relative to the experimentally derived SIF values. Four metrics, namely, Root Mean Square Error (RMSE), Average Absolute Error (AAE), Maximum Absolute Error (MAE), and Coefficient of Determination (R2), are used to compare the accuracy. A case study illustrating the development and experimental validation of the AGPRM is presented. Results indicate that the prediction accuracy of the AGPRM is comparable with and even higher than that of the FEM, provided the training points of the AGPRM are aptly chosen.

Research on the Identification Methods of Friction in Kinematical Joints of Mechanical Systems

2005 ◽  
Author(s):  
Ziying Wu ◽  
Hongzhao Liu ◽  
Lilan Liu ◽  
Pengfei Li ◽  
Daning Yuan
Keyword(s):  
Frequency Domain ◽  
Time Domain ◽  
Time Domain Method ◽  
Estimation Accuracy ◽  
Frequency Domain Method ◽  
Linkage Mechanism ◽  
Identification Methods ◽  
Low Snr ◽  
Domain Method ◽  
The Time Domain

This paper describes two approaches for the simultaneous identification of the coulomb and viscous parameters in kinematical joints. One is a time-domain method (TDM) and the other is a frequency-domain method (FDM). Simulation shows that both of the two methods have good performances in identifying friction at high SNR (90dB). But at low SNR (20dB), the estimation accuracy of the frequency-domain method is higher than that of the time-domain method. A field experiment employing a linkage mechanism driven by motor is also carried out. The experimental results obtained by the two approaches are almost identical under different experiment conditions. It has been concluded that the presented identification methods of friction in kinematical joints are correct and applicable.

scholarly journals Estimation of Emissions at Signalized Intersections Using an Improved MOVES Model with GPS Data

2019 ◽  
Vol 16 (19) ◽  
pp. 3647 ◽  
Author(s):  
Ciyun Lin ◽  
Xiangyu Zhou ◽  
Dayong Wu ◽  
Bowen Gong
Keyword(s):  
Real Time ◽  
Motor Vehicle ◽  
Urban Air Pollution ◽  
Scientific Basis ◽  
Estimation Accuracy ◽  
Transport Sector ◽  
Gps Data ◽  
Data Sets ◽  
Environmental Decision Making ◽  
Pollution Emissions

Emissions from the transport sector are responsible for a large proportion of urban air pollution. Scientific and efficient measurements on traffic pollution emissions have already been a vital concern of decision makers in environmental protection. In China or other counties, many high-technology companies, such as Baidu, DiDi, have a large number of real-time GPS traffic data, but such data have not been fully exploited, especially in purpose of estimation of vehicle fuel consumption and emissions. In this paper, the traditional MOVES (Motor Vehicle Emission Simulator) model has been improved by adding the real-time GPS data and tested in representative signalized intersection in Changchun, China. The results showed that adding the GPS data sets in the MOVES model can effectively improve the estimation accuracy of traffic emissions and provide a strong scientific basis for environmental decision-making, planning and management.

scholarly journals Development of a Seamless Forecast for Solar Radiation Using ANAKLIM++

2020 ◽  
Vol 12 (21) ◽  
pp. 3672
Author(s):  
Isabel Urbich ◽  
Jörg Bendix ◽  
Richard Müller
Keyword(s):  
Solar Radiation ◽  
Weather Prediction ◽  
Software Tool ◽  
Absolute Error ◽  
Shortwave Radiation ◽  
Data Sets ◽  
Climate Data ◽  
Forecast Horizon ◽  
Novel Approach ◽  
Forecasting System

A novel approach for a blending between nowcasting and numerical weather prediction (NWP) for the surface incoming shortwave radiation (SIS) for a forecast horizon of 1–5 h is presented in this study. The blending is performed with a software tool called ANAKLIM++ (Adjustment of Assimilation Software for the Reanalysis of Climate Data) which was originally designed for the efficient assimilation of two-dimensional data sets using a variational approach. A nowcasting for SIS was already presented and validated in earlier publications as seamless solar radiation forecast (SESORA). For our blending, two NWP models, namely the ICON (Icosahedral Non-hydrostatic model) from the German weather Service (DWD) and the IFS (Integrated Forecasting System) from the European Centre for Medium-Range Weather Forecasts (ECMWF), were used. The weights for the input data for ANAKLIM++ vary for every single forecast time and pixel, depending on the error growth of the nowcasting. The results look promising, since the root mean square error (RMSE) and mean absolute error (MAE) of the blending are smaller than the error measures of the nowcasting or NWP models, respectively.

Application of time-domain fitting in the quantification ofin vivo1H spectroscopic imaging data sets

1992 ◽  
Vol 5 (4) ◽  
pp. 171-178 ◽  
Author(s):  
R. de Beer ◽  
A. van den Boogaart ◽  
D. van Ormondt ◽  
W. W. F. Pijnappel ◽  
J. A. den Hollander ◽  
...  
Keyword(s):  
Time Domain ◽  
Spectroscopic Imaging ◽  
Data Sets ◽  
Imaging Data ◽  
Fitting In
Sign in / Sign up

Export Citation Format

Share Document