Towards Internet-of-Things for Wearable Neurotechnology

Abstract

This paper outlines the prevalent challenges for the emerging wearable neurotechnology in modern IoT systems. We underline the recent insights in neuroscience and the ability to decode the brain circuitry with high confidence. We address the imminent challenges of translating the advanced high-cost medical setup for neural activity recording to a commodity IoT system. Emphasis is placed on non-invasive wearable sensing technology and the advances in data analytic for neurosignals. In particular, we focus on human-in-the-loop IoT systems where privacy concerns of leaking private human state and energy limitations for local data processing lay significant constraints on such systems' architecture. Along the way, we envision applications that will reach their full potential and provide the promised functionality by embedding wearable neurotechnology in their design. We end the paper by highlighting the prominent research opportunities and challenges for designing and developing the next generation of low-cost, energy-efficient, privacy-aware, and ubiquitous wearable neurotechnology. Most of these research challenges need to be addressed from a multi-disciplinary approach. Researchers from various communities need to coordinate and collaborate to successfully advance the research, development, and standardization of such neurotechnologies for the larger benefit of society.