ReviewACS nano2024
Advances in Machine Learning for Wearable Sensors.
Review in ACS nano, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 1 of them a synthesis that pooled it.
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
33 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Wearable Sweat Biosensors for Inflammatory Biomarkers (CRP, IL-6 and TNF-α): A Systematic Review of Analytical and Clinical Evidence.Biosensors · 2026Pooled it
- Artificial intelligence and wearable sensors in sports injury risk prediction: current status and future perspectives.Annals of medicine · 2026Review
- Technology-Enhanced Health Care in Smart Homes: Scoping Review of Sensor Technologies, Clinical Applications, Integration Challenges, and Future Directions.JMIR medical informatics · 2026Article
- Tailoring Chemiresistive Nanomaterials Toward Integrated Circuit Compatible Fabrication of Gas Sensors.Advanced materials (Deerfield Beach, Fla.) · 2026Article
- The Applications of Machine Learning in Micro-Nano Materials Research: From High-Throughput Screening to Intelligent Design.Small (Weinheim an der Bergstrasse, Germany) · 2026Review
- Digital Phenotyping in Health Research: Scoping Review of Methods, Gaps, and Opportunities.Journal of medical Internet research · 2026Article
- A wearable acoustofluidic patch for rapid reversal of opioid overdose.Nature communications · 2026Article
- Advances and Challenges in Wearable Sensors for Health Monitoring.ACS applied materials & interfaces · 2026Review
- Carbon based functional materials enable multifunctional flexible strain sensors for wearable and implantable applications.Discover nano · 2026Review
- Clarifying the landscape of mechanical sensors from stress to strain.Nature sensors · 2026Article
- Convergence of Soft Electronics and Artificial Intelligence: From Materials to Intelligent Systems.Nano-micro letters · 2026Review
- From IMU Streams to Real-Time Decisions: Past-Only Next-Window Badminton Action Prediction.Sensors (Basel, Switzerland) · 2026Article
- Seamless Human-Computer Interaction Enabled by Wearable Biointerfaces and Intelligent Systems.Biomimetics (Basel, Switzerland) · 2026Review
- Machine-Learning-Enabled Hydrogel Biosensors for Wearable Health Monitoring.Gels (Basel, Switzerland) · 2026Review
- A time-stamping tactile sensor enabled by pseudoconductive interface design at dielectric heterojunctions.Science advances · 2026Article
- AI-Assisted Molecular Biosensors: Design Strategies for Wearable and Real-Time Monitoring.International journal of molecular sciences · 2026Review
- Flexible and Wearable Sensors-Design, Fabrication Methods, and Applications.Sensors (Basel, Switzerland) · 2026Article
- Bioinspired periodic mesoporous tin oxides enable steady nonequilibrium chemical sensing for enhanced gas discrimination.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Advances in flexible wearable pressure/strain sensors for motion monitoring in orthopaedic sports medicine.Journal of orthopaedic translation · 2026Review
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Recent years have witnessed tremendous advances in machine learning techniques for wearable sensors and bioelectronics, which play an essential role in real-time sensing data analysis to provide clinical-grade information for personalized healthcare. To this end, supervised learning and unsupervised learning algorithms have emerged as powerful tools, allowing for the detection of complex patterns and relationships in large, high-dimensional data sets. In this Review, we aim to delineate the latest advancements in machine learning for wearable sensors, focusing on key developments in algorithmic techniques, applications, and the challenges intrinsic to this evolving landscape. Additionally, we highlight the potential of machine-learning approaches to enhance the accuracy, reliability, and interpretability of wearable sensor data and discuss the opportunities and limitations of this emerging field. Ultimately, our work aims to provide a roadmap for future research endeavors in this exciting and rapidly evolving area.
Indexed as
Identifiers
What OpenQuestion holds
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.