Machine-Learning Based EEG Biomarkers for Personalized Interventions
Institut Guttmann
58 participants
Oct 5, 2023
OBSERVATIONAL
Conditions
Summary
The goal of this observational study is to develop a machine learning model to predict the outcome of a transcranial direct current stimulation (tDCS) treatment in patients suffering from neuropathic pain derived from a spinal cord injury. The main question it aims to answer is: • Can electroencephalography (EEG) and clinical assessment data predict the success of tDCS treatment in neuropathic pain patients? Participants will: * Undergo EEG recording sessions to collect brain activity data before treatment. * Complete clinical assessments, including medical diagnostics and questionnaires focused on factors related to neuropathic pain before and after treatment.
Eligibility
Plain Language Summary
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This summary was AI-generated to explain the trial in plain language. It is not medical advice. Always discuss eligibility with your doctor before enrolling in a clinical trial.
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Interventions
The treatment follows an approved neuromodulation protocol at our center (approved on Nov. 4 2021, valid until Nov. 4 2024). tDCS will be administered with a battery-powered DC stimulator (Sooma tDCS, Helsinki, Finland), using saline-saturated circular electrodes with a diameter of 6 cm². The anode will be positioned over C3 to stimulate the primary motor cortex (M1), and the cathode over the contralateral supraorbital area (FP2). For asymmetric pain, stimulation targets the M1 contralateral to the more painful side, and for symmetric pain, the dominant hemisphere (C3) is stimulated. The maximum current is 2 mA (current density: 0.06 mA/cm²). Each session lasts 30 minutes, conducted daily for two weeks (Monday to Friday), totaling 10 sessions. All stimulation parameters adhere to general safety guidelines for transcranial electrical stimulation (Bikson et al., 2016).
64-channel active-electrode EEG with impedances kept \~5KOhm
Locations(1)
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NCT06531317