ReviewSensors (Basel, Switzerland)2021
Trends and Challenges of Wearable Multimodal Technologies for Stroke Risk Prediction.
Review in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 2 of them syntheses 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
19 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- AI-integrated smartwatch monitoring for early detection of stroke and hemorrhage: A systematic review.Medicine · 2026Pooled it
- Revolutionizing stroke prediction: a systematic review of AI-powered wearable technologies for early detection of stroke.Neurosurgical review · 2025Pooled it
- mHealth-Enabled Stroke Screening for Pediatric Sickle Cell Disease in Low-Resource Settings: Systematic Literature Review of Critical Barriers, Emerging Technologies, and AI-Driven Solutions.JMIR pediatrics and parenting · 2026Review
- Automated vertigo diagnosis using video-oculography and artificial intelligence for clinic-based triage: Preliminary results.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2026Article
- Revolutionizing Stroke Management with Wearable Technology: A Narrative Review of Clinical Applications, Opportunities, Challenges, and the Future Path Towards Equitable Implementation.Annals of Indian Academy of Neurology · 2025Article
- Enhanced stroke risk prediction in hypertensive patients through deep learning integration of imaging and clinical data.BMC medical informatics and decision making · 2025Article
- Current Status and Future Aspect of Digital Health Innovation in Stroke Prevention and Management.Journal of atherosclerosis and thrombosis · 2025Review
- Transforming Cardiovascular Risk Prediction: A Review of Machine Learning and Artificial Intelligence Innovations.Life (Basel, Switzerland) · 2025Review
- Current implications of EEG and fNIRS as functional neuroimaging techniques for motor recovery after stroke.Medical review (2021) · 2024Review
- Intelligent Stroke Disease Prediction Model Using Deep Learning Approaches.Stroke research and treatment · 2024Article
- SmartWear body sensors for neurological and neurosurgical patients: A review of current and future technologies.World neurosurgery: X · 2024Review
- Detection and Diagnostic Accuracy of Cardiac Arrhythmias Using Wearable Health Devices: A Systematic Review.Cureus · 2023Review
- Thoughts and Considerations of Studies on Smart Devices for Cerebrovascular Disease Detection and Progression Monitoring.Mayo Clinic proceedings. Digital health · 2023Article
- Stroke analysis and recognition in functional near-infrared spectroscopy signals using machine learning methods.Biomedical optics express · 2023Article
- NeuroCARE: A generic neuromorphic edge computing framework for healthcare applications.Frontiers in neuroscience · 2023Article
- Emerging Wearable Biosensor Technologies for Stress Monitoring and Their Real-World Applications.Biosensors · 2022Article
- Longitudinal Data to Enhance Dynamic Stroke Risk Prediction.Healthcare (Basel, Switzerland) · 2022Article
- Photoacoustic imaging for monitoring of stroke diseases: A review.Photoacoustics · 2021Review
- Energy Solutions for Wearable Sensors: A Review.Sensors (Basel, Switzerland) · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
We review in this paper the wearable-based technologies intended for real-time monitoring of stroke-related physiological parameters. These measurements are undertaken to prevent death and disability due to stroke. We compare the various characteristics, such as weight, accessibility, frequency of use, data continuity, and response time of these wearables. It was found that the most user-friendly wearables can have limitations in reporting high-precision prediction outcomes. Therefore, we report also the trend of integrating these wearables into the internet of things (IoT) and combining electronic health records (EHRs) and machine learning (ML) algorithms to establish a stroke risk prediction system. Due to different characteristics, such as accessibility, time, and spatial resolution of various wearable-based technologies, strategies of applying different types of wearables to maximize the efficacy of stroke risk prediction are also reported. In addition, based on the various applications of multimodal electroencephalography-functional near-infrared spectroscopy (EEG-fNIRS) on stroke patients, the perspective of using this technique to improve the prediction performance is elaborated. Expected prediction has to be dynamically delivered with high-precision outcomes. There is a need for stroke risk stratification and management to reduce the resulting social and economic burden.
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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.