Wearable Electronic Devices and Artificial Intelligence Technology
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".
Deadline for manuscript submissions: 25 November 2025 | Viewed by 4
Special Issue Editor
Special Issue Information
Dear Colleagues,
The field of Wearable Electronic Devices and Artificial Intelligence (AI) Technology is an interdisciplinary domain that integrates hardware, software, data analytics, and AI technologies. The aim of this Special Issue is to collect original research and review articles in the field of Wearable Electronic Devices and AI Technology, including but not limited to:
- Hardware Design and Development Sensor Technology: Sensors are used to monitor physiological data (e.g., heart rate, blood pressure, body temperature, blood oxygen levels), human activity and gestures and environmental data (e.g., temperature, humidity, air quality). Also, it includes sensors that are used to capture conditions, such as stress and emotions.
Flexible Electronics: Development of flexible, wearable devices such as smartwatches, smart glasses, and smart clothing. Low-Power Design: Optimization of battery life and power management to ensure long-term operation. Material Science: Research into new materials to improve comfort, durability, and biocompatibility of wearable devices.
Sensors measurement reliability: key factors (e.g. uncertainty of measured values, accuracy issues, resolutions, problems with influencing factors such as motion artifacts) that can affect data validity and algorithm performance.
- Data Acquisition and Processing
Real-Time Data Collection: Sensors continuously gather physiological and environmental data from users.
Data Preprocessing: Techniques like noise reduction, filtering, and normalization are applied to ensure data quality.
Data Transmission: Data is transmitted via Bluetooth, Wi-Fi, or 5G to cloud or local devices for further processing.
- Artificial Intelligence and Machine Learning
Data Analysis and Pattern Recognition: Machine learning algorithms analyze user data to identify health anomalies, behavioral patterns, and trends.
Personalized Recommendations: AI provides tailored health advice, fitness plans, or lifestyle adjustments based on user data. Predictive Analytics and Alerts: Deep learning models predict potential health risks (e.g., heart attacks, abnormal glucose levels) and issue timely warnings.
Natural Language Processing (NLP): Enables voice assistants, speech recognition, and natural language interactions to enhance user experience.
Dr. Xiaowen Xu
Guest Editor
Manuscript Submission Information
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Keywords
- wearable devices
- artificial intelligence
- flexible electronics
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