eHealth Platforms and Sensors for Monitoring Health and Human Activity—Second Edition
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Biomedical Sensors".
Deadline for manuscript submissions: 31 January 2026 | Viewed by 48
Special Issue Editors
Interests: digital signal processing; generative AI; deepfake detection; AI interpretability; cyber resilience and privacy protection in digital healthcare and wellbeing
Special Issues, Collections and Topics in MDPI journals
Interests: neuromorphic computing; brain-computer interfaces; machine intelligence; AI-powered health and wellbeing; speech signal processing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The proliferation of eHealth platforms has been largely motivated by the emergence of viable solutions to the immense pressures on healthcare systems, which are struggling to cope with growing health management demands across the globe. Through digital transformation, the world’s nations have adopted varying degrees of digitalisation in their healthcare systems. These digital health platforms are employed for building and managing patient data records, which include those collated through the monitoring of human health and activity, which relies on a multitude of multi-modal sensor and actuation technologies, smart wearables, and Internet of Things (IoT) networks. Through health analytics methods, the collated data can be analysed to establish the next steps for patients. To further reduce the growing pressure and costs for healthcare systems while increasing their efficiency and effectiveness in responding to patients’ needs, remote health monitoring and self-managed care for the proactive prevention of poor wellbeing are deemed key. Yet, this comes with caveats, as eHealth platforms, particularly sensor-based health data, contain personal information, which is susceptible to cybersecurity threats and privacy compromises. Further, in a digital transformation scenario, not all stakeholders may be able or willing to adopt these technology-enhanced solutions, which should be kept in mind when considering the adoption of these technologies.
Accordingly, given the considerable interest in the first edition of our Special Issue, in the second edition, we call for innovative research on how to establish eHealth platforms for remote care, self-management, assisted living, human health and activity monitoring, and health analytics and informatics while considering security, trust, privacy, and user acceptance and adoption. As such, we encourage the submission of original research and novel work on a wide range of topics, including (but not limited to) the following:
- eHealth and mHealth platforms;
- Multi-modal sensor technologies for human health and activity monitoring;
- Actuator technologies for remote and predictive healthcare and management;
- Sensor data fusion and smart health diagnostics;
- Health analytics and informatics, including AI, deep learning, and machine learning techniques and their application to wearable and sensor data;
- Smart wearable and mobile technologies, the Internet of Things (IoT), brain–computer interfaces (BCIs), and sensor networks for physiological signal monitoring;
- Robotics in health monitoring and management applications, including sensor-based human–AI collaboration;
- Assisted living technologies, such as autonomous agents and digital companions;
- Emotion and wellbeing recognition using data from wearable and mobile systems, e.g., speech recognition, social signal processing, facial expression analysis, and Natural Language Processing (NLP);
- Personalised health management and self-managed care;
- Cybersecurity and privacy protection on eHealth and mHealth platforms;
- User acceptance and adoption of digital healthcare technologies;
- Energy-aware solutions in wearable, sensor, and IoT networks for eHealth/mHealth platforms;
- Quality-of-life monitoring, management, and improvement.
Dr. Safak Dogan
Dr. Xiyu Shi
Guest Editors
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Keywords
- digital health (eHealth/mHealth) platforms
- remote and predictive healthcare
- self-managed care
- health monitoring and management
- human activity monitoring
- sensing and actuation
- smart wearables, brain–computer interfaces (BCIs), and Internet of Things (IoT) networks
- health analytics and AI, sensor-based human–AI collaboration, and Natural Language Processing (NLP)
- assisted living
- cybersecurity and privacy protection
- user acceptance and adoption
- robotics in health monitoring and management
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