Neuroadaptive Technologies: Integrating Brain Signals, Artificial Intelligence and Personalized Human–Computer Interaction

Charlene Zietsma

Neuroadaptive Technologies: Integrating Brain Signals, Artificial Intelligence and Personalized Human–Computer Interaction

Author(s)	Charlene Zietsma
Country	United States
Abstract	Neuroadaptive technologies represent an emerging class of intelligent human–computer interaction systems that dynamically adapt to users by interpreting neural and physiological signals. Advances in brain–computer interfaces, artificial intelligence, wearable sensing, neuroimaging and multimodal signal processing are enabling computational systems to infer aspects of cognitive state, attention, workload, affect and user intent. Unlike conventional interfaces, which require users to explicitly provide commands, neuroadaptive systems attempt to continuously estimate user state and modify interaction accordingly. This paper examines the convergence of brain-signal acquisition, artificial intelligence and personalised human–computer interaction, with particular emphasis on electroencephalography, functional near-infrared spectroscopy, eye tracking, electromyography and multimodal physiological sensing. An Integrated Neuroadaptive Interaction Framework is proposed, connecting neural sensing, signal preprocessing, representation learning, cognitive-state estimation, adaptive interface management and continuous user feedback. Applications in assistive technologies, education, healthcare, workplace safety, immersive environments, gaming, rehabilitation and intelligent vehicles are discussed. The paper also examines key challenges involving signal variability, calibration requirements, noise, non-stationarity, privacy, neural-data security, explainability, user autonomy and ethical governance. The analysis suggests that the future of neuroadaptive computing will depend on multimodal sensing and personalised AI rather than reliance on a single neural signal. Responsible development must ensure that systems enhance human agency rather than manipulate users or make unsupported inferences about cognition. The paper concludes that neuroadaptive technologies have the potential to transform human–computer interaction from command-driven interfaces toward context-aware, personalised and continuously adaptive computing environments.
Keywords	Neuroadaptive Technologies, Brain–Computer Interfaces, Artificial Intelligence, Human–Computer Interaction, Electroencephalography, Neural Signals, Personalised Computing, Cognitive State, Adaptive Interfaces, Neurotechnology.
Field	Engineering
Published In	Volume 7, Issue 1, January-February 2025
Published On	2025-01-14

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American Journal of Advanced Multidisciplinary Research and Innovation

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Neuroadaptive Technologies: Integrating Brain Signals, Artificial Intelligence and Personalized Human–Computer Interaction

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