Older Adult
Research on older adults focuses on improving their quality of life and well-being through technological interventions and better understanding of their unique needs. Current research employs machine learning models, including deep learning architectures like convolutional neural networks and transformers, and federated learning approaches to analyze diverse data sources such as electronic health records, wearable sensor data, and even synthetic data generated by large language models. These efforts aim to enhance healthcare accessibility, personalize interventions (e.g., for cognitive decline, diabetes management, and pain assessment), and improve the effectiveness of assistive technologies like robots and virtual coaches.
Papers
Perplexed by Quality: A Perplexity-based Method for Adult and Harmful Content Detection in Multilingual Heterogeneous Web Data
Tim Jansen, Yangling Tong, Victoria Zevallos, Pedro Ortiz Suarez
Evaluating Multimodal Interaction of Robots Assisting Older Adults
Afagh Mehri Shervedani, Ki-Hwan Oh, Bahareh Abbasi, Natawut Monaikul, Zhanibek Rysbek, Barbara Di Eugenio, Milos Zefran