The soaring amount of data, especially spatial-temporal data, recorded in recent years demands for advanced analysis methods. Neural networks derived from self-organizing maps established themselves as a useful tool to analyse static and temporal dat...
Abnormal behavior detection in crowd scenes is continuously a challenge in the field of computer vision. For tackling this problem, this paper starts from a novel structure modeling of crowd behavior. We first propose an informative structural contex...
IEEE journal of biomedical and health informatics
Apr 21, 2014
This paper presents a new approach to identify the stroke parameters in handwriting movement data understanding. A two-step analysis by synthesis paradigm is employed to facilitate the coarse-to-fine parameter identification for all strokes. One is t...
IEEE transactions on bio-medical engineering
Dec 1, 2025
Tracking forearm movement via measured physiological signals is crucial for understanding human motor control mechanism. Current methods mainly use muscle-derived signals to predict arm movements while often overlooking the potential role of gaze att...
Motility is a fundamental characteristic of bacteria. Distinguishing between swarming and swimming, the two principal forms of bacterial movement, holds significant conceptual and clinical relevance. Conventionally, the detection of bacterial swarmin...
This review explores modern image registration techniques in the context of managing respiratory-induced motion in the thoracic region. The respiratory cycle introduces anatomic variability that poses challenges for radiation therapy, breathing dynam...
IEEE transactions on bio-medical engineering
Sep 1, 2025
This study investigates a novel approach for analyzing Sit-to-Stand (STS) movements using millimeter-wave (mmWave) radar technology, aiming to develop a non-contact, privacy-preserving, and all-day operational solution for healthcare applications. A ...
Accurate recognition of human motion intention (HMI) is beneficial for exoskeleton robots to improve the wearing comfort level and achieve natural human-robot interaction. A classifier trained on labeled source subjects (domains) performs poorly on u...
PURPOSE: To develop and evaluate a physics-driven, saturation contrast-aware, deep-learning-based framework for motion artifact correction in CEST MRI.
The size of an individual's tongue relative to the oral cavity is associated with articulation speed [Feng, Lu, Zheng, Chi, and Honda, in Proceedings of the 10th Biennial Asia Pacific Conference on Speech, Language, and Hearing (2017), pp. 17-19)] an...
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