Wearable and Intelligent (Bio)Electronics for Healthcare: From Sensors to AI

Dear Colleagues,

Wearable and intelligent (bio)electronics are transforming healthcare by enabling the continuous, real-time monitoring of physiological and biochemical signals outside the clinic. Advances in flexible materials, low-power electronics, and miniaturized sensors have made it possible to capture high-fidelity ECG, EMG, EEG, metabolites in interstitial fluid, lacrimal fluids, and sweat with devices that comfortably conform to the body. At the same time, breakthroughs in on-device signal processing and machine learning are turning raw data streams into actionable insights—detecting arrhythmias, predicting glycemic excursions, classifying movement patterns, and more. This convergence of hardware innovation and AI promises to shift healthcare from episodic, reactive interventions to proactive, personalized management.

This Special Issue of Electronics seeks to showcase cutting-edge research and comprehensive reviews that span the full pipeline “from sensors to artificial intelligence” We invite contributions that not only push the boundaries of sensor design, materials, and integration but also demonstrate how embedded intelligence and cloud analytics can deliver clinically relevant outcomes. By focusing on wearable and (bio)electronic systems within the journal’s remit of biomedical engineering and translational research, we aim to assemble a cohesive collection that highlights both technological breakthroughs and application-driven studies.

To illustrate the Special Issue’s scope, potential topics include—but are not limited to—the following themes:

• Flexible and Stretchable Sensor Technologies: Novel materials and fabrication methods for skin-conformal devices, textile integration, and biocompatible interfaces.
• Physiological Sensor Arrays: ECG, EMG, EEG, SpO₂, and skin temperature.
• Biochemical Sensing Platforms: Wearable assays and minimally invasive (bio)sensors for metabolites (glucose, lactate, electrolytes), hormones, and biomarkers in sweat, tears, or interstitial fluids.
• Power Management and Energy Harvesting: Ultra-low-power circuit design, energy-scavenging modules (thermoelectric, piezoelectric), and innovations in batteries resulting in extended runtimes.
• Embedded Signal Conditioning and Artifact Removal: Analog front-ends, filtering strategies, and motion artifact suppression algorithms suitable for ambulatory monitoring.
• Edge AI and On-Device Analytics: Lightweight machine learning models for real-time feature extraction, event detection (e.g., arrhythmia, seizure), and adaptive personalization.
• Wireless Connectivity and Data Security: BLE, NFC, and UWB protocols, secure data transmission, encryption, and privacy-preserving architectures compliant with GDPR/HIPAA.
• Cloud-Based Platforms and Deep Learning: Scalable architectures for longitudinal data aggregation, deep learning models for health trajectory prediction, and clinician dashboards.
• Clinical Validation and Regulatory Considerations: In vivo studies, pilot trials, pathways to FDA/CE approval, and standardization efforts for wearable diagnostics.
• Applications in Chronic Disease and Rehabilitation: Continuous glucose monitoring, heart failure management, neurorehabilitation, gait analysis, and remote patient monitoring.
• User Experience and Adoption: Ergonomics, usability studies, and strategies to integrate wearables into everyday life and clinical workflows.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

1. Flexible and Conformal electronics
– Ultrathin/stretchable electrode design;
– Hydrogel‐based skin interfaces;
– Textile‐integrated sensors and biosensors.

2. Physiological Sensors and Sensor Arrays
– Multi-modal ECG/EMG/EEG patch arrays;
– Integrated SpO₂ and skin‐temperature mapping;
– Capacitance-based respiratory and motion sensors.

3. Biochemical Sensing in Wearables
– Sweat metabolite assays (glucose, lactate);
– Tear‐fluid biomarker detection;
– The continuous monitoring of interstitial fluid;
– Microfluidic platforms for biofluid sampling.

4. Power Management and Energy Harvesting
– Thermoelectric generators for body-heat scavenging;
– Piezoelectric and triboelectric harvesters in wearables;
– Bioresorable, disposable power sources;
– Ultra-low-power power-management ICs and battery chemistries.

5. Embedded Signal Conditioning and Artifact Removal
– Analog front-end design for low-noise amplification;
– Adaptive filtering and motion artifact suppression;
– On-chip calibration and self-diagnostics.

6. Edge AI and On-Device Analytics
– Lightweight neural nets for arrhythmia detection;
– Event-triggered data compression and transmission;
– Personalized model tuning and continual learning.

7. Wireless Connectivity and Data Security
– BLE-Mesh and UWB protocols for body area networks;
– Hardware-accelerated encryption and secure enclaves;
– GDPR/HIPAA-compliant privacy architectures.

8. Cloud Platforms and Deep Learning Frameworks
– Scalable architectures for longitudinal patient data;
– Federated learning for collaborative model training;
– Dashboard and visualization tools for clinicians.

9. Clinical Validation and Regulatory Pathways
– In vivo pilot studies and cohort trial design;
– Biocompatibility testing and ISO/FDA guidance;
– Standardization efforts and interoperability frameworks.

10. Applications in Chronic Disease and Rehabilitation
– Closed-loop glucose–insulin management systems;
– Heart failure monitoring and early-warning algorithms;
– Neurorehabilitation robotics with sensor feedback.

11. User Experience and Adoption
– Ergonomic form factors and wearability studies;
– Human–machine interfaces and feedback modalities;
– Workflow integration and clinician–patient co-design.

I look forward to receiving your contributions.

Prof. Dr. Sergey Shleev
Guest Editor

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• (bio)electronics
• wearables
• sensors
• analytics
• machine learning
• connectivity
• energy
• validation
• usability