Early Detection of External Neurological Symptoms through a Wearable Smart-Glasses Prototype

The Internet of Things (IoT) framework is moving the research community to provide smart systems and solutions aimed at revolutionizing medical sciences healthcare. Given extreme diffusion Alzheimer’s disease (AD) Parkinson’s (PD), demand for a solution early detect neurological symptoms such diseases strongly arose. According literature, detection can be obtained through correlation between PD AD some external symptoms: Essential Tremor (ET) number Eye Blinks (EBs). In this paper, which considered as an extended version [1], we present prototype wearable glasses able presence ET head count EBs same time, in transparent way with respect final user. Numerical results demonstrate reliability proposed approach: algorithms are i) correctly recognize overall accuracy above 97% ii) error around 9%.