ArticleInternational journal for numerical methods in biomedical engineering2019
A semi-active human digital twin model for detecting severity of carotid stenoses from head vibration-A coupled computational mechanics and computer vision method.
Article in International journal for numerical methods in biomedical engineering, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
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Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Digital Twins in Neuro-Oncology: A Systematic Review of Current Implementations, Technical Strategies, and Clinical Applications.Radiology. Imaging cancer · 2026Pooled it
- A decade of innovation in healthcare: Automation, bio-printing and digital twin technologies for personalized therapies.International journal of pharmaceutics: X · 2026Review
- Artificial intelligence for improving decision-making in bacterial infection management: a narrative review.The Journal of antimicrobial chemotherapy · 2026Review
- Digital Twins in Personalized Medicine: Bridging Innovation and Clinical Reality.Journal of personalized medicine · 2025Review
- A scoping review of human digital twins in healthcare applications and usage patterns.NPJ digital medicine · 2025Article
- Digital Representation of Patients as Medical Digital Twins: Data-Centric Viewpoint.JMIR medical informatics · 2025Article
- Blockchain-enabled digital twin system for brain stroke prediction.Brain informatics · 2025Article
- Digital Twins for Clinical and Operational Decision-Making: Scoping Review.Journal of medical Internet research · 2025Article
- Medical Digital Twin: A Review on Technical Principles and Clinical Applications.Journal of clinical medicine · 2025Review
- Definitions and Characteristics of Patient Digital Twins Being Developed for Clinical Use: Scoping Review.Journal of medical Internet research · 2024Article
- Recent Advances in Artificial Intelligence to Improve Immunotherapy and the Use of Digital Twins to Identify Prognosis of Patients with Solid Tumors.International journal of molecular sciences · 2024Review
- Using Constrained-Disorder Principle-Based Systems to Improve the Performance of Digital Twins in Biological Systems.Biomimetics (Basel, Switzerland) · 2023Review
- Using the Non-Adoption, Abandonment, Scale-Up, Spread, and Sustainability (NASSS) Framework to Identify Barriers and Facilitators for the Implementation of Digital Twins in Cardiovascular Medicine.Sensors (Basel, Switzerland) · 2023Article
- An AI based digital-twin for prioritising pneumonia patient treatment.Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine · 2022Article
- Dynamic Digital Twin: Diagnosis, Treatment, Prediction, and Prevention of Disease During the Life Course.Journal of medical Internet research · 2022Article
- The health digital twin to tackle cardiovascular disease-a review of an emerging interdisciplinary field.NPJ digital medicine · 2022Review
- A Scoping Review of Digital Twins in the Context of the Covid-19 Pandemic.Biomedical engineering and computational biology · 2022Article
- Digital Twins for Multiple Sclerosis.Frontiers in immunology · 2021Review
- Physiological Vibration Acceleration (Phybrata) Sensor Assessment of Multi-System Physiological Impairments and Sensory Reweighting Following Concussion.Medical devices (Auckland, N.Z.) · 2020Article
- A semi-active human digital twin model for detecting severity of carotid stenoses from head vibration-A coupled computational mechanics and computer vision method.International journal for numerical methods in biomedical engineering · 2019Article
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Authors and funding
4 authors.
Funding
Abstract
In this work, we propose a methodology to detect the severity of carotid stenosis from a video of a human face with the help of a coupled blood flow and head vibration model. This semi-active digital twin model is an attempt to link noninvasive video of a patient face to the percentage of carotid occlusion. The pulsatile nature of blood flow through the carotid arteries induces a subtle head vibration. This vibration is a potential indicator of carotid stenosis severity, and it is exploited in the present study. A head vibration model has been proposed in the present work that is linked to the forces generated by blood flow with or without occlusion. The model is used to generate a large number of virtual head vibration data for different degrees of occlusion. In order to determine the in vivo head vibration, a computer vision algorithm is adopted to use human face videos. The in vivo vibrations are compared against the virtual vibration data generated from the coupled computational blood flow/vibration model. A comparison of the in vivo vibration is made against the virtual data to find the best fit between in vivo and virtual data. The preliminary results on healthy subjects and a patient clearly indicate that the model is accurate and it possesses the potential for detecting approximate severity of carotid artery stenoses.
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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.