ReviewJournal of advanced research2026
Flexible wearable medical devices: from material innovations and data processing to intelligent healthcare applications.
Review in Journal of advanced research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- Tumor Exposomics: A New Paradigm for Individualized Continuous Exposure Monitoring.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Article
- ABCG2 transporter: Structural and functional associations with gout (Review).International journal of molecular medicine · 2026Review
- Advances in detecting category A biothreat agents: Toward symptom-driven sensing strategies.Synthetic and systems biotechnology · 2026Review
- Research progress in exercise-induced fatigue monitoring and injury early warning based on flexible sensing textiles and deep learning.Frontiers in bioengineering and biotechnology · 2026Review
- Integrating Artificial Intelligence Into Digital Health-Optimized Therapeutics for the Remote Cardiac Rehabilitation.Clinical Medicine Insights. Cardiology · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundFlexible wearable medical devices drive healthcare transformation via non-invasive, real-time physiological monitoring and personalized management. Traditional rigid devices lack long-term comfort, while chronic disease care and telemedicine demand reliable, patient-centered solutions. Advances in materials (carbon nanomaterials, liquid metals, hydrogels) enable stretchable, biocompatible substrates adapting to bodily movements. Innovative sensing (PPG, EEG, sweat-based detection) tracks blood pressure, glucose, and neural signals accurately. Key challenges include insufficient sensor flexibility, lagging supervision, data security issues, and large-scale production difficulties, requiring interdisciplinary collaboration. AIM OF REVIEW: This review integrates cutting-edge advances in flexible wearable medical devices, covering material innovations, sensing breakthroughs, power management, and AI-driven data analysis. It evaluates strategies to enhance biocompatibility of carbon composites, liquid metals, and hydrogels, analyzing improvements in device sensitivity, biocompatibility, and real-world applicability. It critically discusses machine learning's role and limitations in chronic disease management, telemedicine, and sports optimization. Key unresolved challenges include lagging regulations, privacy risks in multi-source data fusion, mismatched sensing development, and large-scale production difficulties. The aim is to provide a scalable, secure, and clinically translatable roadmap for future research. KEY SCIENTIFIC CONCEPTS OF REVIEW: Core technologies involve carbon nanomaterials (e.g., graphene), liquid metals (structurally optimized for balanced conductivity and flexibility), and hydrogels (preferred as flexible substrates for mimicking natural soft tissues' mechanics and biocompatibility). Sensing technologies (PPG, EEG, sweat-based detection) enable non-invasive, real-time monitoring of vital parameters like blood pressure, glucose, and neural signals. AI decodes complex physiological data for predictive diagnosis, while IoT/5G integration advances telemedicine. Current limitations include poor sensor flexibility, lagging regulations, and large-scale production hurdles, contrasting with trends like advanced sensing, new materials, and hybrid diagnostic-therapeutic systems-highlighting flexible wearables' potential in intelligent healthcare.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.