NeuroVR: A Neurofeedback-Based Wearable Headset Enhanced by Machine Learning for Treating Neuro-AIDS

Abstract

Neuro-AIDS presents a complex challenge with neurological complications in HIV/AIDS patients, despite antiretroviral therapy. Current treatments focus on symptoms rather than neurodegenerative processes. This abstract proposes a neurofeedback-based wearable technology enhanced by quantum machine learning (QML) to treat neuro-AIDS. The wearable headset uses neurofeedback and QML algorithms for personalized neurostimulation and cognitive training. Monitoring neural activity and processing data in real time aims to optimize neural plasticity, reduce neuroinflammation, and enhance cognitive function. This approach combines neurofeedback precision with QML's power to improve neurological outcomes and quality of life for Neuro-AIDS patients.

Keywords: Neuro-AIDS, neurofeedback, wearable technology, machine learning, cognitive enhancement, Cognitive enhancement, HIV-associated neurocognitive disorders (HAND), Electroencephalography (EEG), MRI analysis, Multimodal neuroimaging, Deep learning, Generative adversarial networks, CNNs, RNNs, Real-time feedback, Neural plasticity, Neuroinflammation, Cloud-based monitoring