Human Activity Recognition Based on Sensors: Challenges and Perspectives
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Biomedical Sensors".
Deadline for manuscript submissions: 30 November 2025 | Viewed by 3364
Special Issue Editor
Interests: artificial intelligence; human activity recognition; automated learning; guidance; assistive technologies; smart homes equipped with ubiquitous sensors
Special Issue Information
Dear Colleagues,
Human activity recognition (HAR) is an increasingly active and interdisciplinary field of research that focuses on identifying and analyzing human actions through various sensing technologies. The ability to recognize what a person is doing, determine the current step of a task, and detect whether assistance is needed is fundamental for the development of intelligent and responsive systems. This capability is particularly valuable in applications where automation, real-time monitoring, and adaptive assistance can enhance human performance, safety, and well-being.
HAR leverages a variety of artificial intelligence techniques, including machine learning and deep learning, to process data collected from multiple sensing modalities. These include wearable sensors (e.g., accelerometers, gyroscopes, and physiological sensors), vision-based systems (e.g., cameras and depth sensors), and ambient sensors (e.g., motion detectors and pressure sensors). The fusion of these technologies enables a more accurate and context-aware understanding of human behavior in real-world environments.
The applications of HAR are vast and span multiple domains. In healthcare and ambient assisted living (AAL), HAR plays a crucial role in monitoring elderly individuals, detecting falls, and providing timely intervention in cases of health emergencies. In industrial settings, HAR can assist workers by identifying ergonomic risks, improving workplace safety, and optimizing task efficiency. The field also has significant applications in sports and fitness, where personalized coaching systems analyze movement patterns to enhance performance and prevent injuries.
Moreover, HAR is integral to the advancement of augmented and virtual reality, where it enhances user interaction by enabling gesture-based controls and immersive experiences. In security and surveillance, HAR is used to detect abnormal behaviors, identify potential threats, and improve public safety measures. Military and defense applications include soldier monitoring, combat simulation, and real-time threat assessments.
As HAR continues to evolve, new research directions are emerging, such as self-supervised learning for activity recognition, multimodal sensor fusion, and real-time activity tracking using edge computing. This Special Issue aims to compile cutting-edge research in the field of human activity recognition, highlighting recent advancements, innovative methodologies, and emerging applications that are shaping the future of this technology.
Prof. Dr. Bruno Bouchard
Guest Editor
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Keywords
- human activity recognition (HAR)
- sensor-based activity recognition
- machine learning for HAR
- wearable sensors
- ambient assisted living (AAL)
- multimodal sensor fusion
- deep learning for activity recognition
- real-time activity monitoring
- gesture and motion recognition
- smart surveillance and security
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