ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
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- All Subjects: Neurosciences
robots with limited sensing and/or actuating capabilities that cooperate (explicitly
or implicitly) based on local communications and sensing in order to complete a
mission. Its inherent redundancy provides flexibility and robustness to failures and
environmental disturbances which guarantee the proper completion of the required
task. At the same time, human intuition and cognition can prove very useful in
extreme situations where a fast and reliable solution is needed. This idea led to the
creation of the field of Human-Swarm Interfaces (HSI) which attempts to incorporate
the human element into the control of robotic swarms for increased robustness and
reliability. The aim of the present work is to extend the current state-of-the-art in HSI
by applying ideas and principles from the field of Brain-Computer Interfaces (BCI),
which has proven to be very useful for people with motor disabilities. At first, a
preliminary investigation about the connection of brain activity and the observation
of swarm collective behaviors is conducted. After showing that such a connection
may exist, a hybrid BCI system is presented for the control of a swarm of quadrotors.
The system is based on the combination of motor imagery and the input from a game
controller, while its feasibility is proven through an extensive experimental process.
Finally, speech imagery is proposed as an alternative mental task for BCI applications.
This is done through a series of rigorous experiments and appropriate data analysis.
This work suggests that the integration of BCI principles in HSI applications can be
successful and it can potentially lead to systems that are more intuitive for the users
than the current state-of-the-art. At the same time, it motivates further research in
the area and sets the stepping stones for the potential development of the field of
Brain-Swarm Interfaces (BSI).
This dissertation evaluates StartReact and the voluntary trials before and after exposure to StartReact during a point-to-point multi-jointed reach task to three different targets covering a large workspace. The results show that multi-jointed reach tasks are susceptible to StartReact in iwS and the distance, muscle and movement onset speed, and muscle activations percentages and amplitude increase during StartReact trials. In addition, the distance, accuracy, muscle and movement onsets speeds, and muscle synergy similarity indices to the norm synergies increase during the voluntary-initiated trials after exposure to StartReact. Overall, this dissertation shows that exposure to StartReact did not impair voluntary-initiated movement and muscle synergy, but even improved them. Therefore, this study suggests that StartReact is safe for more investigations in training studies and therapy.