Towards Designing an Information Superhighway for Neurological Disorders

Neurological Disorders impact a subject’s/ person’s nervous system in various ways and include a wide range of neurological conditions. More often than not, the impact is life altering and affects the subject’s communication skills, social interaction capability, etc. If the condition is detected at an early age, it can significantly enhance the quality of life of the subject with focused training, treatment, etc. Detection through brain scans, behavioral analysis, etc. are costly and time consuming. Recently artificial intelligence (AI) models are being increasingly used for detection & classification of neurological disorders based on various parameters and datasets. However, for an end user, it’s still very difficult to realize the power of these models end to end viz., from data acquisition to generating recommendations. Hence, in this paper, we present the architecture of an Information Superhighway in the form of AI pipeline. The task of the Information Superhighway is to enable capturing the multimodal data (image, video, etc.) of a subject from a smartphone of a laptop webcam, and send this through a secure information channel to a cloud storage. On the storage, the data is managed using various Big Data technologies and is acted upon by the DL models. The generated recommendations are sent back through a different secure communication channel back to the mobile or laptop. We feel that our work is first of its kind which makes the technology transfer possible for the end user and utilize full the prowess of powerful AI models.