Cognitive Predictive Maintenance Tools for Brain Diseases: Design and Analysis, 1st Edition eBook

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This book involves the design, analysis, and application of various cognitive predictive maintenance tests with the help of tools like vibration analysis, ultrasonic analysis, infrared analysis, oil analysis, laser-shaft alignment, and motor circuit analysis in the prediction of various cognitive diseases such as epilepsy, Parkinson’s disease, Alzheimer’s disease, and depression. These are needed since there are no proper medical tests available to predict these diseases in remote areas at an early stage. Various emerging technologies are analyzed for the design of tests. Key features: Incorporates innovative processes for treating cognitive diseases. Early and exact identification and treatment strategies are incorporated. Future technologies like artificial intelligence, machine learning, the IoT, and data science are used to find solutions. Analysis with existing cognitive disease solutions is incorporated and simulations provided. The novelty of the book lies in the accurate prediction of cognitive diseases. Encompassing future technologies and various communication protocols or devices available for cognitive diseases for the design of new equipment are an outcome of the book. Various parameters like power consumption, productivity, and safety should be taken into account during the analysis, design, and application of a product. The book could well be added to the curriculum of medical colleges and biomedical engineering students. Possible vendors include biomedical research centers like Biotechnika and the Indian Council of Medical Research (ICMR). It would be a breakthrough for biomedical companies to launch their new products.

This is a digital product.

Cognitive Predictive Maintenance Tools for Brain Diseases: Design and Analysis 1st Edition and published by Chapman & Hall. The Digital and eTextbook ISBNs for Cognitive Predictive Maintenance Tools for Brain Diseases are 9781000992915, 1000992918 and the print ISBNs are 9781032156828, 1032156821. Additional ISBNs for this eTextbook include 9781032156873, 9781003245346, 9781000992892.