Micaela De Simmeo
SEPLab: an EEGLAB Plugin to Compute Somatosensory Evoked Potentials.
Rel. Gabriella Olmo, Vito De Feo, Cristina Del Prete. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Biomedica, 2024
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Abstract: |
The somatosensory system detects changes in the surrounding environment through the five sensory modalities. Somatosensory evoked potentials (SEPs) are electrical signals elicited by the ascending sensory pathways in response to peripheral nerve stimulation. SEPs can be triggered by different sensory stimuli, such as pain, touch, vibration, or mechanical devices, which stimulate specific sensory receptors and elicit modality-specific SEPs. Stimulation of the median or ulnar nerve of the wrist is used to elicit SEPs related to the upper limb, while the SEP of the lower limb is elicited by stimulating the tibial nerve of the ankle or the peroneal nerve at the popliteal fossa. SEPs are versatile and important tools in various fields, from clinical to research, with possible future improvements in diagnostic and therapeutic procedures. In the clinical field, they are used as intraoperative monitoring during surgery in which the integrity of the somatosensory nerve pathways may be damaged. They are also used to diagnose and monitor numerous neurological diseases, such as multiple sclerosis and peripheral neuropathies, providing critical information on nervous system activity. In neuroscientific research, SEPs contribute to understanding neural plasticity processes and sensory integration mechanisms. The proposed project aims to develop an EEGLAB plugin for calculating somatosensory evoked potentials (SEPs). EEGLAB is an interactive and opensource MATLAB toolbox for processing continuous and event-related EEGs. In this thesis, a pre-processing chain of EEG data was developed with the following steps: temporal filtering, artifacts corrections with Independent Component Analysis (ICA), epoching and baseline correction, jitter compensation, and extrapolation of SEPs with the averaging technique. The data used to develop the plugin were recorded at Macquarie University with medial nerve stimulation. |
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Relators: | Gabriella Olmo, Vito De Feo, Cristina Del Prete |
Academic year: | 2023/24 |
Publication type: | Electronic |
Number of Pages: | 104 |
Subjects: | |
Corso di laurea: | Corso di laurea magistrale in Ingegneria Biomedica |
Classe di laurea: | New organization > Master science > LM-21 - BIOMEDICAL ENGINEERING |
Aziende collaboratrici: | UNSPECIFIED |
URI: | http://webthesis.biblio.polito.it/id/eprint/32178 |
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