During the summer of 2017, GE predicted that digital twins could eventually provide a deeper insight into our bodies. A report shared on social media indicated that in the future, everyone might have a digital twin capable of monitoring heart rates, blood pressure, and respiration.
By 2017, GE had already developed a patient monitoring platform that allowed doctors to check on patients using sensors.
GE engineers were working on wireless tools to stream patient data to the Cloud in real-time.
One engineering director at GE Healthcare stated that as the world becomes more wireless and wearable, wireless sensors and data analytics will enhance accurate diagnoses in ambulances, ultimately improving care and reducing costs.
GE had already created 800,000 digital twins to monitor manufacturing machines.
In these virtual models of physical machines——such as jet engines, turbines, or factory parts——the digital twins continuously learn from the data gathered by their sensors.
They utilize this knowledge to alert engineers about wear and tear, helping to extend the lifespan of the machines.
Colin Parris demonstrated how engineers could use virtual reality headsets to inspect the machines.
A brief conversation with a digital twin could identify issues with hardware and even suggest solutions based on historical and financial data.
“We are reaching the next level with machines by combining digital twins to predict business outcomes and opportunities,” said Parris, then vice president of GE Software Research.
In October 2024, the National Science Foundation (NSF) announced that digital twins are starting to deliver significant real-world benefits.
In collaboration with the National Institutes of Health (NIH) and the Food and Drug Administration (FDA), the NSF revealed over $6 million in research funding for seven projects aimed at developing digital twins—dynamic virtual representations of physical objects or processes—for healthcare and biomedical research.
These projects represent the first initiatives supported by the Foundations for Digital Twins as Catalyzers of Biomedical Technological Innovation program (FDT-BioTech), a partnership among the NSF, NIH, and FDA.
This program seeks to advance fields such as mathematics, statistics, computational sciences, and engineering, which are essential for creating responsive digital twin models that leverage artificial intelligence (AI).
The awarded research projects address a range of topics, including:
- Developing mathematical models for virtual clinical trials of cardiovascular medical devices.
- Creating statistical tools for analyzing the ethical use of artificial intelligence (AI).
- Conducting studies based on digital twins for neurodegenerative diseases.
- Exploring AI-informed decision-making in relation to glucose metabolism in individuals with Type 1 diabetes.
Importantly, one of the awarded institutions participates in the NSF Established Program to Stimulate Competitive Research, which aims to enhance research capacity in states that have historically received lower levels of funding.
Yulia Gel, the program director in the NSF Division of Mathematical Sciences that oversees the FDT-BioTech program, emphasizes that digital twins could significantly reduce common medical risks associated with patient monitoring and treatment.
They offer a framework for optimal decision-making. The practical application of these complex models could also streamline clinical trials, ensuring safer development of drugs and medical devices.