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A neuroadaptive non-invasive BCI: Virtual Reality and Transcutaneous Electrical Nerve Stimulation to treat pain

Arianna Damiani

A neuroadaptive non-invasive BCI: Virtual Reality and Transcutaneous Electrical Nerve Stimulation to treat pain.

Rel. Valentina Agostini. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Biomedica, 2021


Chronic pain is a costly and disabling health issue, affecting one person out of five of the European population. Among the alarming consequences it implicates, the impact on workforce productivity and quality of life are worrisome. Its proper treatment remains challenging. This is due to the poor understanding of its exact neurobiological mechanisms, the lack of reliable biomarkers and the fact that current therapies do not target the several components of pain, which is a multisensory phenomenon implicating also emotional and psychological factors. The aim of this thesis is to develop a neuroadaptive non-invasive brain computer interface to treat pain, based on objective biomarkers and able to address both sensory and emotional components of pain thanks to a combination of innovative technologies. To achieve this, a data analysis on publicly available electrophysiological signals has been performed to identify robust correlates of pain perception. Thereafter, the technological framework for pain treatment has been developed: attentional mechanisms of pain are modulated through Virtual Reality, while the sensory aspects are addressed by means of Transcutaneous Electrical Nerve Stimulation. Pain, induced experimentally on healthy subjects, is decoded from electroencephalography and electrodermal activity recordings. The therapeutic benefit of the VR and TENS system has been tested and validated on five healthy subjects, evaluating both objective and subjective measurements. Lastly, the system has been implemented in real-time, in order to event-lock the therapy delivery to the pain onset. The proposed work paves the way towards the development of thorough pain treatments, which consider individualized and multifaceted therapeutic solutions.

Relators: Valentina Agostini
Academic year: 2020/21
Publication type: Electronic
Number of Pages: 159
Additional Information: Tesi secretata. Full text non presente
Corso di laurea: Corso di laurea magistrale in Ingegneria Biomedica
Classe di laurea: New organization > Master science > LM-21 - BIOMEDICAL ENGINEERING
Ente in cotutela: ETH, Neuroengineering Laboratory (SVIZZERA)
Aziende collaboratrici: ETH Zurich
URI: http://webthesis.biblio.polito.it/id/eprint/17626
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