Sensor Fusion for Telemedicine: Advancing Remote Healthcare Through Multi-Modal Data Integration
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".
Deadline for manuscript submissions: 31 December 2025 | Viewed by 338
Special Issue Editors
Interests: medical imaging; computer vision; biomedical signal processing; GPU computing; machine learning
Special Issues, Collections and Topics in MDPI journals
Interests: evaluation and validation of new diagnostics and treatments for active and latent tuberculosis; eHealth in pulmonary disease, with a focus on interstitial lung disease; evidence-based evaluation of interventions in respiratory disease
Special Issue Information
Dear Colleagues,
This Special Issue addresses key challenges in combining heterogeneous sensor data to enhance diagnostic accuracy, real-time health monitoring, and clinical decision support. The scope of this Special Issue includes novel algorithms for multi-sensor data fusion (such as Kalman filtering for the integration of vital signs, deep learning approaches for multi-modal bio-signal analysis), methods for handling temporal and spatial data alignment (including dynamic time warping for bio-signal synchronization), approaches to the management of uncertainty in sensor measurements (through Bayesian inference and confidence estimation), and strategies for secure data transmission and privacy preservation (implementing blockchain-based data sharing and federated learning approaches).
Featured case studies should demonstrate practical implementations across various scenarios; these include the remote monitoring of patients with heart failure using combined ECG, weight, and activity data; the remote monitoring of pulmonary disease by combining lung sound monitoring and local atmospheric pollution; the remote detection of fall detection systems by integrating wearable accelerometers with ambient sensors; automated ultrasound imaging using teleoperated robots; and telerehabilitation platforms that combine motion capture data with force sensor measurements. Submissions should showcase significant improvements in early detection rates, reductions in hospital readmissions, and enhanced patient engagement through comprehensive monitoring solutions.
This collection provides valuable insights into the future of remote healthcare delivery, highlighting both technical innovations (such as edge computing for real-time sensor fusion and 5G-enabled medical IoT platforms) and clinical applications that promise to enhance the quality and accessibility of telemedicine services. Special attention should be paid to implementation challenges, including regulatory compliance, the integration of the clinical workflow, and cost-effectiveness.
Prof. Dr. Pierre Boulanger
Prof. Dr. Giovanni Ferrara
Guest Editors
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Keywords
- sensor fusion
- telemedicine
- multi-modal data
- remote patient monitoring
- healthcare informatics
- wearable sensors
- clinical decision support
- edge computing
- medical IoT
- bio-signal processing
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