ReviewBioengineering (Basel, Switzerland)2024
Digital Twins for Healthcare Using Wearables.
Review in Bioengineering (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 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
18 citing papers in PubMed.
- Healthcare Digital Twins Across Scales: A Narrative Review and Five-Level Conceptual Framework.Healthcare (Basel, Switzerland) · 2026Review
- An Agentic Multimodal Sensing Architecture for CT-Guided Wearable and Respiratory Monitoring in Oncology Care.Sensors (Basel, Switzerland) · 2026Article
- Virtual twins and the future of human developmental biology.NPJ systems biology and applications · 2026Review
- An Agentic LLM Framework for Autonomous Surgical Continuum Monitoring: ReAct-Driven Tool-Use Agents for Presurgical, Intraoperative, and Postsurgical Cardiopulmonary Care.Bioengineering (Basel, Switzerland) · 2026Article
- Digital twins and digital models of the human circulatory system.Nature reviews bioengineering · 2026Article
- Six artificial intelligence innovation strategies applied to autism spectrum disorder research: A narrative review.Pediatric investigation · 2026Review
- Conducting Polymers for Electrochemical Sensing: From Materials and Metrology to Intelligent and Sustainable Biointerfaces.Sensors (Basel, Switzerland) · 2026Review
- Increasing Truck Drivers' Compliance, Retention, and Long-Term Engagement with e-Health & Mobile Applications: A PRISMA Systematic Review.Healthcare (Basel, Switzerland) · 2026Review
- Toward future diagnostics of Parkinson's disease: a perspective on multimodal motor assessment and personalized digital twins.Frontiers in aging neuroscience · 2026Article
- Emerging Technologies for Exploring the Cellular Mechanisms in Vascular Diseases.International journal of molecular sciences · 2025Review
- Wearable nanopatch platforms for real-time miRNA sensing and editing: a vision for next-generation cancer management.Medical oncology (Northwood, London, England) · 2025Review
- Digital Twin Prospects in IoT-Based Human Movement Monitoring Model.Sensors (Basel, Switzerland) · 2025Review
- Digital Cardiovascular Twins, AI Agents, and Sensor Data: A Narrative Review from System Architecture to Proactive Heart Health.Sensors (Basel, Switzerland) · 2025Review
- Research on the Digital Twin System of Welding Robots Driven by Data.Sensors (Basel, Switzerland) · 2025Article
- Development of a personal health management system integrating digital twin technology and smart wearables in China.Frontiers in public health · 2025Article
- Digital Twin of the Female Pelvic Floor.Open journal of obstetrics and gynecology · 2024Article
- Article
- Digital health and metaverse for Alzheimer's disease and related dementia: A scoping review.Digital healthReview
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
No grant is acknowledged in the PubMed record.
Abstract
Digital twins are a relatively new form of digital modeling that has been gaining popularity in recent years. This is in large part due to their ability to update in real time to their physical counterparts and connect across multiple devices. As a result, much interest has been directed towards using digital twins in the healthcare industry. Recent advancements in smart wearable technologies have allowed for the utilization of human digital twins in healthcare. Human digital twins can be generated using biometric data from the patient gathered from wearables. These data can then be used to enhance patient care through a variety of means, such as simulated clinical trials, disease prediction, and monitoring treatment progression remotely. This revolutionary method of patient care is still in its infancy, and as such, there is limited research on using wearables to generate human digital twins for healthcare applications. This paper reviews the literature pertaining to human digital twins, including methods, applications, and challenges. The paper also presents a conceptual method for creating human body digital twins using wearable sensors.
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.