Data-Driven Goal Recognition in Transhumeral Prostheses Using Process Mining Techniques-Reference-Cited by-同舟云学术

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Data-Driven Goal Recognition in Transhumeral Prostheses Using Process Mining Techniques

Published:2023-10-23 Issue: Volume: Page:
ISSN:
Container-title:2023 5th International Conference on Process Mining (ICPM)
language:
Short-container-title:

Author:

Su Zihang¹,Yu Tianshi²,Lipovetzky Nir¹,Mohammadi Alireza²,Oetomo Denny²,Polyvyanyy Artem¹,Sardiña Sebastian³,Tan Ying²,van Beest Nick⁴

Affiliation:

1. The University of Melbourne,School of Computing and Information Systems,Australia

2. The University of Melbourne,Department of Mechanical Engineering,Australia

3. RMIT University,School of Computing Technologies,Australia

4. Data61 | CSIRO,Software Systems Group,Australia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10271932/10271938/10271945.pdf?arnumber=10271945

Reference29 articles.

1. Comparing the Outcomes of Population-averaged and Personalised Input Feature Selection for Transhumeral Prosthetic Interfaces

2. Sensor Selection With Composite Features in Identifying User-Intended Poses for Human-Prosthetic Interfaces

3. Multiple Binary Classifications via Linear Discriminant Analysis for Improved Controllability of a Powered Prosthesis

4. Development and Continuous Control of an Intelligent Upper-Limb Neuroprosthesis for Reach and Grasp Motions Using Biological Signals

5. Simultaneous Control of 2DOF Upper-Limb Prosthesis With Body Compensations-Based Control: A Multiple Cases Study

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