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Personalization Techniques in HCI: Leveraging Multimodal Physiological and Behavioral Data for Adaptive Interfaces
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Author(s): Sanjib Kundu (Academy of Technology, Hooghly, India)and Sourav Kayal (Academy of Technology, Hooghly, India)
Copyright: 2026
Pages: 40
Source title:
Driving Smarter Human-Computer Interaction With Multidisciplinary Personalized Systems
Source Author(s)/Editor(s): Subrata Tikadar (Amity University, Kolkata, India), Joel JosĂ© Puga Coelho Rodrigues (Federal University of PiauĂ, Brazil), Rabi Shaw (Dr. B.R. Ambedkar National Institute of Technology, India), Ahdi Hassan (Global Institute for Research Education and Scholarship, The Netherlands)and Bidyut Kumar Patra (Indian Institute of Technology, India)
DOI: 10.4018/979-8-3373-1444-0.ch005
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Abstract
The chapter investigates the development of HCI field specifically focused on adaptive interfaces. The approach develops personalization methods which combine multimodal behavioral and physiological data from EEG along with EMG and touch and gesture data to improve usability along with user fulfilment. The research describes the technical methodology by explaining sensor information collection together with processing approaches and information integration methods. The paper delves into several personalization strategies which contain supervised learning in addition to unsupervised learning together with reinforcement learning and context-specific interface design and user profiles for dynamic adaptation systems. These interfaces transform different environments through real-world case examples which include healthcare domains along with educational systems and smart environments. The chapter also critically addresses challenges like data privacy, algorithmic bias, and computational limitations.
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