Special Session 4:  Intelligent Sensing and Computing for Smart Elderly Care and Health Monitoring


The aging population creates an urgent need for intelligent, unobtrusive, and human-centered healthcare technologies. This special session focuses on emerging sensing and computing methods that can support smart elderly care, including contactless vital sign monitoring, fall detection, physiological signal analysis, and natural human-machine interaction. Millimeter-wave radar offers privacy-preserving and continuous monitoring of heart rate, respiration, and motion, making it well suited for elderly care environments. At the same time, biomedical signal processing of EEG and ECG enables deeper understanding of neurological and cardiac conditions, while affective computing and multimodal large models provide opportunities for empathetic and context-aware interaction. Furthermore, brain-inspired computing such as spiking neural networks can improve energy-efficient real-time processing on edge devices. Technologies from intelligent cockpit sensing, including driver and occupant monitoring systems, can also be adapted for in-home health monitoring and assisted living. This session aims to bring together researchers from radar sensing, biomedical signal processing, brain-inspired intelligence, human-computer interaction, and smart cockpit perception to share novel algorithms, systems, and applications. We welcome original research, case studies, and surveys that bridge these disciplines and advance intelligent, non-intrusive, and user-friendly healthcare for aging populations.

Related topics for this special session (but not limited to) :
1. Millimeter-wave radar and Wi-Fi based contactless physiological monitoring and fall detection
2. Biomedical signal processing for ECG, EEG, and photoplethysmography
3. Biometric recognition and health-state classification for elderly care
4. Brain-inspired computing, spiking neural networks, and low-power edge AI for wearable or ambient sensing
5. Affective computing and emotion recognition for human-centred elderly care
6. Multimodal large models and human-computer interaction in smart home health systems
7. Driver and occupant monitoring systems adapted for in-home health monitoring
8. Multi-sensor fusion using radar, vision, wearable, and physiological signals
9. Real-world deployment, clinical validation, and privacy-preserving smart elderly care
10. Sleep monitoring, stress assessment, and daily activity analysis for older adults


We invite researchers and practitioners from academia and industry to submit original research articles and comprehensive reviews that demonstrate significant advances in Intelligent Sensing and Computing for Smart Elderly Care and Health Monitoring.

Submission Method


Electronic Submission System (.pdf) (Please select and click Special Session 4: Intelligent Sensing and Computing for Smart Elderly Care and Health Monitoring to submit.)

Organizer


Dr Aifei Liu is currently an Associate Professor at the School of Al and Advanced Computing, Xi'an Jiaotong-Liverpool University (XJTLU), Suzhou, China.
Dr Liu received her PhD in June 2012, from the School of Electronic Engineering, Xi’dian University, China. From Feb 2013 to June 2017, she worked as a Research Fellow at the School of Electrical and Electronic Engineering, Nanyang Technological University (NTU). From Aug 2017 to Dec 2021, she worked as an Associate Professor at the College of Underwater Acoustic Engineering, Harbin Engineering University (HEU). From Jan 2021 to Feb 2025, she worked as an Associate Professor in the School of Software at Northwestern Polytechnical University (NPU).
Her research interests are the deep neural network (DNN) theory and signal processing theory and their applications on radar, sonar, and communications, and anomaly detection in different events.

Dr Chunyu Tan is currently a Lecturer and Master’s Supervisor at the School of Artificial Intelligence, Anhui University, China.
Dr Tan received her PhD degree from the University of Macau in 2021. In 2019, she visited the University of Aveiro, Portugal. She also visited the University of Macau in 2023 and 2025. She serves as a reviewer for several academic journals, including TMI, MedIA, and JBHI, and was a Program Committee Member for ICONIP 2023 and ICONIP 2024. She is also a member of the Medical Research Ethics Committee of the First Affiliated Hospital of the University of Science and Technology of China (Anhui Provincial Hospital).
Her research interests include biomedical signal processing, biomedical signal and image coding, and biometric recognition; brain-inspired intelligence, particularly the optimization and applications of spiking neural networks; and human-computer interaction.