Dear Colleagues,

Artificial intelligence (AI)-enhanced wearable technologies serve as a fusion of advanced AI and innovative wearable devices, revolutionizing the way we monitor and manage our health and wellbeing. These intelligent wearable devices are equipped with sophisticated sensors that can continuously collect and analyze vital health data, such as heart rate, sleep patterns, physical activity, and even stress levels. Leveraging the power of AI algorithms, these devices can provide real-time insights and personalized recommendations, empowering individuals to make informed decisions about their health. With the ability to detect anomalies, predict health risks, and offer tailored wellness guidance, AI-enhanced wearables are playing a pivotal role in preventive healthcare, enabling users to proactively manage their health and improve their overall quality of life.

This Special Issue focuses on wearable devices and AI for human physiology monitoring applications, covering the challenges and recent advancements in this field.

• AI algorithms for wearable devices in biomedicine (machine learning, deep learning, natural language processing, recommender systems, predictive analytics, clustering, ensemble learning, etc.);
• Optimization of AI model deployment (AI accelerators on device, edge computing, cloud computing, etc.) for wearable devices;
• Data augmentation techniques for training;
• Wireless wearable systems (smart watches, armbands, chest straps, glasses, rings, patches, smart textiles, hearables, etc.);
• Wearable physical and electrophysiological sensors (EEG, EOG, ECG, EMG, PPG, EIS, skin temperature sensors, strain sensors, electrodermal activity sensors, inertial sensors, acoustic sensors, optical sensors, etc.) and wearable chemical sensors/biosensors (exhaled air-, urine-, sweat-, interstitial fluid-, tears-, blood-based sensors, etc.).

Research related to the other aspects of AI on wearable devices, such as storage and memory management, power consumption, communication protocol, security and privacy, user acceptability, etc.

Dr. Xun Wu 
Prof. Dr. José J. Rieta
Dr. Murat A. Yokus
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Bioengineering is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• Machine learning;
• Deep learning; 
• Model training, deployment, and optimization;
• Algorithms;
• Health wearables;
• Preventive healthcare;
• Sensors;
• Systems;