Artificial Intelligence and Human–Computer Interaction: Foundations, Innovations and Applications for Healthcare and Personalized Systems

Dear Colleagues,

This Special Issue focuses on the integration of artificial intelligence (AI) and human–computer interaction (HCI) for healthcare and personalized systems. It aims to explore how intelligent systems can model individual differences in behavior, physiology and context, with particular emphasis on personalized human activity recognition (HAR) and human–robot interaction (HRI). Topics include adaptive and personalized HAR using wearable and ambient sensors, multimodal data fusion and real-time activity understanding for health monitoring and intervention. The issue also considers the integration of medical imaging data with sensor-based and behavioral data to enable more comprehensive and personalized healthcare solutions. In addition, it addresses human–robot interaction in assistive and clinical settings, such as rehabilitation, elderly care and socially assistive robotics. Contributions on explainable AI, privacy-preserving learning and ethical considerations are encouraged. This Special Issue seeks to bridge foundational research and real-world healthcare applications, promoting intelligent systems that are human-centered, adaptive and trustworthy.

(1) Introduction

Recent advances in artificial intelligence (AI), big data analytics and cognitive computing have significantly transformed the field of human–computer interaction (HCI), particularly in healthcare and personalized systems. The increasing availability of multimodal data from wearable sensors, ambient devices and medical imaging technologies has enabled a more comprehensive modeling of human behavior and health conditions. In this context, human activity recognition (HAR) and human–robot interaction (HRI) play a crucial role in understanding user behavior, supporting clinical decision-making and enabling intelligent assistive systems. At the same time, the demand for personalized and adaptive healthcare solutions continues to grow, driven by aging populations and the need for continuous monitoring and intervention. Despite these advances, challenges remain in multimodal data fusion, real-time processing, explainability, privacy and user-centered system design. Therefore, further research is needed to develop intelligent systems that are adaptive, trustworthy and human-centered.

(2) Aim and Relevance to the Journal Scope

This Special Issue aims to explore the integration of AI and HCI for healthcare and personalized systems, with particular focus on personalized human activity recognition and human–robot interaction. It seeks to highlight novel methodologies, system designs and applications that leverage big data and cognitive computing to model human behavior and enable adaptive interaction. The topic aligns closely with the scope of the journal by addressing data-driven intelligence, multimodal information processing and real-world applications of AI in complex environments. By bridging foundational techniques and applied research in healthcare, this Special Issue contributes to advancing intelligent, human-aware systems within the broader context of big data and cognitive computing.

(3) Suggested Themes

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

• Personalized human activity recognition in healthcare
• Multimodal data fusion from wearable, ambient and medical imaging data
• Context-aware and adaptive intelligent systems
• Human–robot interaction in healthcare and assistive environments
• Socially assistive robotics and rehabilitation systems
• Explainable and trustworthy AI for human-centered applications
• Privacy-preserving and secure machine learning in healthcare
• Edge AI and real-time processing for healthcare monitoring
• User-centered design and evaluation in intelligent systems
• Applications in smart healthcare, elderly care and digital health environments

We look forward to receiving your contributions.

Dr. Bangli Liu
Dr. Tongxue Zhou
Prof. Dr. Junyi Wang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Big Data and Cognitive Computing is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• personalized human activity recognition
• healthcare AI
• human–robot interaction
• wearable sensors
• multimodal data fusion
• adaptive systems
• explainable AI
• privacy-preserving learning
• assistive robotics
• smart healthcare
• medical imaging