Decoding brain rhythms with peripheral wearable technologies
File(s)
Author(s)
Zicher, Blanka
Type
Thesis
Abstract
The ability to interact with the environment is fundamental to life. Some even argue that without movement, consciousness itself would have no function—suggesting that perception, thought, and even self-awareness are deeply rooted in our capacity to act. The field that studies the mechanisms of movement is rapidly evolving, alongside the development of new ways of interaction with the world around us. Brain-machine interfaces aim at creating a communication channel between the nervous system and external devices. By extracting and translating neural control signals, these systems can enable users to drive assistive technologies. Muscle signals, which represent the output of our nervous system, are a popular way of
extracting motor commands to be used in peripheral interfaces. This PhD work investigated information transmitted to the muscles that is not directly driving movement, thus opening up a new avenue of peripheral interfaces that is worth exploring. More specifically, it looked at high frequency rhythmic activity transmitted from the cortex, which is above the bandwidth of force production. I mainly focused on exploring the beta activity (13-30 Hz), as this bandwidth has been previously linked to motor control. Through a combination of computer simulations and experimental data, I explored how cortical beta sent to the muscles is modulated and tested its potential role in force production. I showed that beta activity has minimal effect on force, but large changes can be observed in static contractions when participants are going through covert actions. Moreover, these changes can be predicted on a trial-by-trial basis from muscle signals. Overall, this work provides an initial proof-of-concept of the possibility using high frequency muscle activity to decode motor-related patterns of brain activity that do not result in motor output changes.
extracting motor commands to be used in peripheral interfaces. This PhD work investigated information transmitted to the muscles that is not directly driving movement, thus opening up a new avenue of peripheral interfaces that is worth exploring. More specifically, it looked at high frequency rhythmic activity transmitted from the cortex, which is above the bandwidth of force production. I mainly focused on exploring the beta activity (13-30 Hz), as this bandwidth has been previously linked to motor control. Through a combination of computer simulations and experimental data, I explored how cortical beta sent to the muscles is modulated and tested its potential role in force production. I showed that beta activity has minimal effect on force, but large changes can be observed in static contractions when participants are going through covert actions. Moreover, these changes can be predicted on a trial-by-trial basis from muscle signals. Overall, this work provides an initial proof-of-concept of the possibility using high frequency muscle activity to decode motor-related patterns of brain activity that do not result in motor output changes.
Version
Open Access
Date Issued
2025-04-01
Date Awarded
2025-07-01
Copyright Statement
Attribution-NonCommercial 4.0 International Licence (CC BY-NC)
License URL
Advisor
Farina, Dario
Ibáñez, Jaime
Sponsor
UK Research and Innovation
Grant Number
EP/S023283/1
Publisher Department
Department of Computing
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)