Description
Thesis title: "FMG Based Upper Limb Motion Detection Methods, Performance Analysis and Control of Assistive Exoskeletons"Exoskeletons are wearable devices designed to assist humans according to their needs. Their applications can be found in rehabilitation, assistance and power augmentation. For assistive powered exoskeletons human motion intention detection is an important element for implementing assistive control strategies.
The aim of this thesis is to develop novel methods of motion intention detection for control of exoskeletons. The focus of this thesis is to analyze the performance of force myography (FMG) to detect upper limb movements and based on it develop control methods for upper limb assistive exoskeletons.
In this thesis a method of FMG-based intention detection method is first presented and its performance was analyzed by comparing with sEMG for detecting forearm motions i.e. forearm flexion, extension, pronation, supination and rest. The study showed the feasibility of FMG when implemented for assistive powered exoskeleton control. Afterwards, FMG is further used to develop hand motion detection and payload estimation algorithms for the control of different assistive exoskeletons, namely, a soft hand exoskeleton for grasping and a upper limb exoskeleton, with active elbow and shoulder joints, for load carrying tasks. The developed methods are validated by testing on healthy subjects.
This thesis contributes to the state-of-the-art of upper limb motion intention detection using FMG. Studies verify that FMG, being an accurate and convenient method to interpret motion intention, has great potential for application of assistive exoskeletons. A contribution of this thesis is performance analysis of muscle activity detection methods that compares FMG and sEMG in terms of accuracy/repeatability. Another contribution is the novel methods for grasping and load carrying. The proposed techniques are able to reduce system complexity for convenient and robust use in actual environments.
| Period | 14 Oct 2021 |
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| Examinee | |
| Degree of Recognition | International |
Keywords
- Exoskeleton
- motion detection
- Force myography (FMG)
- Robotics
- Artificial Intelligence