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This book offers a comprehensive and forward-looking exploration of cochlear implant systems, covering foundational principles such as electrical stimulation, sound coding, and mechanical design, as well as the latest advances in artificial intelligence, surgical robotics, and optogenetics. It connects the dots between technical design and clinical care, highlighting how engineering advances contribute to more effective hearing restoration for cochlear implant patients.
While cochlear implants have restored hearing to over a million people worldwide, the knowledge surrounding their design, function, and optimization remains fragmented, spread across engineering literature, clinical studies, and specialized research. This volume aims to contribute toward addressing that gap by unifying these perspectives into a single, accessible resource focused on improving patient outcomes.
Written for engineers, clinicians, graduate students, and innovators working at the intersection of hearing science and neurotechnology, the book traces the evolution of cochlear implants from early concepts to emerging technologies. Readers will gain insight into how performance is evaluated in both clinical and real-world settings, and discover how objective measures, computational modeling, medical imaging, and neuroplasticity are driving personalized care.
Whether you're developing next-generation auditory devices or seeking a deeper understanding of the science behind cochlear implants, this book serves as both a technical reference and an inspiring guide to the future of hearing restoration for patients.
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Behnam Molaee-Ardekani, Ph.D., is a Senior Scientist in the Advanced Innovation Department at Cochlear Ltd. Since 2016, he has led research initiatives on cochlear implants, with a focus on audio processing, sound-coding strategies, objective measures, and the integration of machine learning into implant fitting and cochlear imaging workflows. His contributions have resulted in multiple patents and peer-reviewed scientific publications. He previously held postdoctoral positions across multiple European research projects, investigating biomarkers and brain activity dynamics in anesthesia, transcranial stimulation, epilepsy, and neurodegenerative disorders. He completed his Ph.D. in Biomedical Engineering in 2008 through a joint doctoral program between the University of Rennes 1 in France and Aryamehr (Sharif) University of Technology in Iran.
Manuel Segovia-Martinez, Ph.D., is an Audiology and Signal Processing scientist with over 20 years of experience and a demonstrated track record in the medical device industry. He earned his Ph.D. in 3D medical image processing for the diagnosis of Alzheimer’s at the University of Surrey in 2001, under the supervision of the late Prof. Maria Petrou. He is currently working on the development of assisting technology for the Neurodivergent Community. Previously, he led the Oticon Medical Research and Technology and Embedded Systems departments, with a track record of releasing several generations of implantable medical devices. He has been involved in a series of intellectual developments and is the author or co-author of several patents that form the basis of Oticon Medical’s CI audiology strategy.
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