Overview

This book reports on an inclusive design project aimed at developing IoT-based wearable devices for special populations. Specifically, it covers the design, the implementation and testing of a smart mHealth system that uses sensory cues to monitor and train the gait and posture of people with Parkinson’s disease. It presents a user-centred strategy to better involve the users in defining the most suitable type of sensory cues and their combination, and in the design of the user interface, at the purpose of developing a gait tutoring system that better fits users’ needs and requirements. All in all, this book offers extensive information on the state-of-the-art in the design and testing of innovative user-centred mHealth systems. Giving a particular attention to the explanation of the tools and methodological choices, it provides readers with a timely reference guide to understand and deal with complex inclusive design projects.

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9783031582486

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Silvia Imbesi has gained a Master's Degree in Architecture, and a Bachelor's Degree and Industrial Design in 2008 and 2012, respectively, from the University of Ferrara, Italy, and a Ph.D. in Inclusive Design from the Department of Architecture of the same university, in 2023. Since 2009, Silvia Imbesi has worked as a freelance architect and designer, collaborating with other professionals, companies, industries, and institutions to develop projects and design research. Starting in 2012 to date, she has been working with the University of Ferrara as a temporary professor. In her role of research fellow at this university, she participated in many academic research projects related to: Human and User-Centered methodologies, Inclusive Design of IoT-based Devices and Smart mHealth Systems, Design for the Elderly, and Design for Health and Wellbeing, among others. She attended a few  international conferences as an invited speaker, and is the author and editor of more than 40 international scientific publications about innovative care solutions for fragile users and special populations

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