Huilong Fan
Biographic Data
| ID | 10038464 |
|---|---|
| NAME | Huilong Fan |
| GIVEN NAMES | Huilong |
| FAMILY NAME | Fan |
| SIGNATURE | FAN H |
| AFFILIATIONS | University of Electronic Science and Technology of China |
| ORCID | 0000-0003-4350-9299 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2026 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
A nurse-centered edge–server wearable system for real-time monitoring of occupational stress in clinical care
Background and objectives Occupational stress among clinical nurses is a long-standing quality-of-care concern associated with burnout, attrition, lapses in patient safety, and erosion of workforce wellbeing. Continuous, nurse-centered monitoring of within-shift physiological stress states is therefore an emerging priority for nursing innovation and quality improvement (QI), yet routine clinical adoption of wearable monitoring is constrained by a…
Agile human activity recognition for wearable devices based on online incremental learning
Background: Achieving high-precision, low-latency, and continuously adaptive human activity recognition on resource-constrained edge devices represents a core challenge. Existing research primarily focuses on improvements in single directions, such as "online learning," "model sparsification," or "feature extraction," lacking a framework that synergistically optimizes all three. This leads to difficulties in dynamically balancing accuracy, latenc…
No prominent works on this page.
A nurse-centered edge–server wearable system for real-time monitoring of occupational stress in clinical care
Background and objectives Occupational stress among clinical nurses is a long-standing quality-of-care concern associated with burnout, attrition, lapses in patient safety, and erosion of workforce wellbeing. Continuous, nurse-centered monitoring of within-shift physiological stress states is therefore an emerging priority for nursing innovation and quality improvement (QI), yet routine clinical adoption of wearable monitoring is constrained by a…
Agile human activity recognition for wearable devices based on online incremental learning
Background: Achieving high-precision, low-latency, and continuously adaptive human activity recognition on resource-constrained edge devices represents a core challenge. Existing research primarily focuses on improvements in single directions, such as "online learning," "model sparsification," or "feature extraction," lacking a framework that synergistically optimizes all three. This leads to difficulties in dynamically balancing accuracy, latenc…
Wearable computer (2 works) · Wearable technology (2 works) · Activity recognition (1 works) · Agile software development (1 works) · Context-Aware Activity Recognition Systems (1 works) · Data Stream Mining Techniques (1 works) · Emotion and Mood Recognition (1 works) · Incremental learning (1 works) · Non-Invasive Vital Sign Monitoring (1 works) · Sleep and Work-Related Fatigue (1 works)