Please wait ...
0% Complete
Home
/
12th International Conference on Computer and Knowledge Engineering
Taguchi Design of Experiments Application in Robust sEMG Based Force Estimation
Authors :
Mohsen Ghanaei
1
Hadi Kalani
2
Alireza Akbarzadeh
3
1- Ferdowsi university of mashhad
2- Sadjad University
3- Ferdowsi university of mashhad
Keywords :
Grasp force،Robust estimation،sEMG،DOE،Taguchi
Abstract :
This paper investigates the impact of the parameters that affect the accuracy of the force estimation from sEMG signals, including signal acquisition factors, pre-processing and training ones. It offers a procedure for developing a reliable estimation approach to deal with uncertainties, such as the signal deviation while performing various daily tasks using the hand. For doing this, the Taguchi design of experiments (DOE) approach is used to determine appropriate levels of the factors to decrease the regression error. Factors such as the number of electrodes placed on the forearm and the arm, extracted features, the cropping window length and the training regularization term have been categorized as either controllable or uncontrollable in the DOE table. The experiments are conducted on four subjects who perform six different tasks. The L225 mixed-level orthogonal array is used to specify the levels of factors in each experiment. The orthogonal array drastically reduces the required number of executions compared to a full-factorial analysis. Using the Minitab software, the signal-to-noise ratios (SNR) are calculated to determine the optimum levels and significance of the factors. Results indicate that the number of forearm electrodes and their placements are the most influential factors. Moreover, the SNR delta for including the arm biceps muscle is about 0.66, which considering its placement difficulties, it does not justify its additional expense.
Papers List
List of archived papers
Sports News Summarization Using Ensebmle Learning
Moein Sartakhti.salimi@gmail.com - Mohammad Javad Maleki Kahaki - Ahmad Yoosofan - Seyyed Vahid Moravvej
LightFedSelect: A Lightweight Framework for Byzantine-Robust Federated Learning
Seyed Saeed Razavi - Seyed Arsalan Vasegh Rahim Parvar - Soroosh Dadashi Pakdeh - Mohammad Matin Rezaeifard - Morteza Mollaie Chafi - Reza Ebrahimi Atani
Bipartite link prediction improvement using the effective utilization of edge betweenness centrality
Sadegh Sulaimany Sulaimany - Yasin Amini
TCAR: Thermal and Congestion-Aware Routing Algorithm in a Partially Connected 3D Network on Chip
Majid Nezarat - Masoomeh Momeni
A Weighted TF-IDF-based Approach for Authorship Attribution
Ali Abedzadeh - Reza Ramezani - Afsaneh Fatemi
SASIAF, An Scalable Accelerator For Seismic Imaging on Amazon AWS FPGAs
Mostafa Koraei - S.Omid Fatemi
Efficient Object Detection using Deep Reinforcement Learning and Capsule Networks
Sobhan Siamak - Eghbal Mansoori
Non-Functional Requirement Extracting Methods for AI-based Systems: A Survey
Reza Damirchi - Amineh Amini
Transformer-Gather, Fuzzy-Reconsider: A Scalable Hybrid Framework for Entity Resolution
Mohammadreza Sharifi - Danial Ahmadzadeh
An Energy-efficient Clustering Method based on Butterfly Optimization Algorithm by Considering the Criterion of Intra-cluster Distances in WSNs
Fariba Saghi Hadi S. Aghdasi
more
Samin Hamayesh - Version 44.9.3