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This project introduces a novel AI-powered smart sock designed for continuous, real-world monitoring of Parkinson’s Disease (PD) and Acquired Brain Injury (ABI). These neurological conditions commonly involve gait abnormalities, autonomic dysfunction, and neuromuscular decline, offten undetected by traditional diagnostics. 

The smart sock, embedded with multi-frequency bioimpedance spectroscopy (mfBIS) and plantar pressure sensors, captures real-time data on gait, vascular function, and tissue health.Unlike current wearables, which mostly track heart rate or steps, this sock uniquely combines bioelectrical impedance data (phase angle, resistance) with detailed gait analytics to detect early signs of orthostatic hypotension (OH), freezing of gait (FoG), and neuromuscular fatigue. 

This non-invasive, low-cost solution supports early diagnosis, personalized treatment, and long-term monitoring in home environments.The project is structured across three work packages:WP1: Engineering and integration of the smart sock platform with sensors, wireless communication, and materials optimized for comfort, durability, and signal quality. WP2: Development of AI algorithms to detect physiological and motor anomalies using multimodal data, enabling the discovery of digital biomarkers for disease progression and therapy response. WP3: Clinical validation with PD and ABI patients, comparing sensor data with gold-standard diagnostics and assessing usability, accuracy, and clinical relevance in real-world settings. 

The project aims to optimize real-life monitoring by combining gait and vascular biomarkers into a single wearable, offering new insights into the fluid dynamics and cellular health of the lower limbs. The expected impact includes enhanced clinical decision-making, reduced healthcare costs, and improved quality of life through remote, continuous, and personalized care.