Large language models (LLMs) have the potential to transform digital healthcare, as
evidenced by recent advances in LLM-based virtual doctors. However, current approaches …

Self-supervised learning (SSL) has emerged as a promising alternative to purely supervised
learning, since it can learn from labeled and unlabeled data using a pre-train-then-fine-tune …

Deep learning models have achieved significant success in human activity recognition,
particularly in assisted living and telemonitoring. However, training these models requires …

The millimeter-wave (mmWave) radar has been exploited for gesture recognition. However,
existing mmWave-based gesture recognition methods cannot identify different users, which …

Due to the scarcity of labeled sensor data in HAR, prior research has turned to video data to
synthesize Inertial Measurement Units (IMU) data, capitalizing on its rich activity annotations …

The integration of machine learning (ML) algorithms with edge sensor systems has
fundamentally transformed numerous industries. This convergence empowers real-time data …

Question Answering (QA) establishes a natural and intuitive way for humans to interpret and
understand multimodal sensor data. However, existing sensor-based QA systems are limited …