Explainable Computational Intelligence for Neurological Disorders

Artificial intelligence and Explainable computational intelligence are continuously reshaping the detection, monitoring and data-rich diagnostics in neurological disorders. This book brings together recent advances in neuro-focused AI systems, biomedical signal interpretation, multi-modal analytics and explainable AI. The chapters progress from foundational perspectives on AI-enabled neurological and biomedical data to recent machine learning and deep learning frameworks for ECG and EEG-based disease screening, and finally toward assistive and translational technologies such as sign language recognition, virtual reality interventions, regenerative neurology, and cancer AI analytics.

This book:

• Offers a detailed perspective on explainable AI-based systems for neurological diagnosis, and clinical decision support.
• Discusses key physiological and neural biomarkers, including heart rate variability, skin conductance, entropy analytics, ECG, and EEG signals.
• Includes recent AI model designs from wearable sensor analytics and brain connectivity for assistive systems.
• Includes machine learning approaches for conditions such as Alzheimer’s, epilepsy (seizure prediction and surgery outcomes), and other neurological disorders.
• Explores translational technologies and therapies, for different neuro disorders, along with multi-modal AI insights for early tumor detection.

The book is suitable for research scholars, clinicians, and postgraduate students working in biomedical signal analysis, neuro-AI modelling, wearable diagnostics, and intelligent assistive systems.