Digital Twins in healthcare

Introduction

A digital twin is a digital version of a real-world physical product, system, or process that acts as its virtually indistinguishable digital counterpart for practical reasons such as simulation, integration, testing, monitoring, and maintenance.

A digital twin is a virtual model created to precisely replicate a physical thing. The device under investigation, such as a wind turbine, is furnished with different sensors relevant to critical areas of functionality. These sensors generate information regarding various aspects of a physical object's performance, such as energy output, temperature, weather conditions, and so on. This information is subsequently transmitted to a processing system and applied to the digital copy.

Once such data is available, the virtual model may be used to run simulations, investigate performance concerns, and produce potential changes, all with the purpose of creating important insights that can later be brought back to the original physical device.

Remote visibility of assets, systems, and processes, as well as understanding the behaviour of physical devices, are major advantages of Digital Twins. It uses asset behaviour insights to run a prediction algorithm in order to forecast the future. Furthermore, these insights facilitate improved decision making and automate the decision-making process, hence increasing efficiency and profitability. Furthermore, it does risk analysis on various what-if situations and assists firms in maximising operational efficiency. When comparing Digital Twin to Digital Simulation, the former is static and does not receive real-time updates, but the latter is dynamic and receives real-time updates from a physical asset, system, or process. As a result, it generates more accurate results for business decisions.

Types of digital twins

Depending on the extent of product magnification, there are many sorts of digital twins. The primary distinction between these twins is their field of application. Different sorts of digital twins frequently coexist within a system or process. Let's look over the many sorts of digital twins to understand the differences and how they are used.

Parts twins/Component twins - Component twins are the fundamental unit of a digital twin, representing the smallest example of a working component. Parts twins are roughly the same thing, except they refer to significantly less important components.

Twins of assets - An asset is formed when two or more components work together to form a unit. Asset twins allow you to investigate the interaction of those components, resulting in a wealth of performance data that can be analyzed and transformed into meaningful insights.

System twins or Unit twins - The next degree of magnification involves system or unit twins, which allow you to see how various assets interact to build a fully functional system. System twins provide visibility into asset interactions and may identify performance improvements.

Twins in the process - Process twins, the macro level of magnification, show how systems interact to produce an entire manufacturing complex. Are all of those systems synchronized to run at peak efficiency, or will delays in one system have an impact on others? Process twins can assist in determining the specific timing schemes that influence overall effectiveness.

Advantages of digital twins

Improved R&D - The utilization of digital twins allows for more effective product research and creation, with an abundance of data generated concerning expected performance outcomes. This data can lead to insights that can help businesses make necessary product improvements before going into production.

Increased effectiveness - Even after a new product has entered production, digital twins can assist in mirroring and monitoring production systems in order to achieve and maintain optimal efficiency throughout the manufacturing process.

Product obsolescence - Digital twins can even assist producers in determining what to do with products that have reached the end of their product lifecycle and require final processing, such as recycling or other measures. They can decide which product materials can be gathered by employing digital twins.

Are you prepared to face your digital immune system

The creation of the first digital twin of the human immune system demonstrates the immense societal implications of physical-digital fusion. This ongoing research has the potential to make us safer, healthier, and more prepared for the next health crisis. Discover the limitless possibilities of genuine immunity modelling.

We tend to think of the real world -'real life' - as something physical and solid, distinct from what we encounter via a virtual box. However, this is not totally correct. Much of the real world is hidden, such as the seafloor, car interiors, or the inner workings of our bodies.

Digital-physical fusion generates dynamic representations of real-world objects, systems, and processes in the digital realm, which can help to clarify these things. In many ways, the human immune system is the ultimate example.

Immunity is a difficult subject. The NHS in the United Kingdom produced a 3.7 million-strong official ‘shielding' list of anyone it judged at risk at the start of 2020. "It was terrifying, and I had no idea how bad my immunity really was," says Sarah [name changed], a fit and healthy cancer survivor who appeared on the list in her late 30s.

"Even my nurse wasn't sure." "My immunity could have been weakened by the initial [blood] cancer, the previous chemotherapy treatment, or the ongoing maintenance injections," Sarah explains.

Most cancers avoid the immune system in some way. Many blood malignancies, such as lymphoma, alter the function of immune system blood cells. However, this is only a small part of the picture because not everyone who appeared to be at high risk back then was. Sarah was unaffected by the illness, although others who appeared to be healthier on paper were not.

According to an unnamed researcher, "we don't even know what a healthy immune system is." This is because each immune system is unique and depends on a variety of factors. Your age and general health, illnesses you've had, immunizations you've received, and medications you're taking will all play a role in your unique immunity. Drugs may suppress one element of the immune system while having a complex knock-on effect on others.

As a result, modelling the immune system is a necessary first step towards truly understanding it and opening the door to a wealth of new insights. "My [ultimate] goal is to be able to program the immune system to do whatever you want it to do," the researcher said.

Hospital Digital Twin – Improving Operational Efficiency

Initially, Digital Twin could only represent a single device or component, but with the advancement of Artificial Intelligence (AI) technology, Digital Twin may now represent an entire complicated system, process, or location. The use of digital twins for various hospital business activities aids in the optimization and improvement of the entire ecosystem. It simulates several aspects of a hospital institution, including as the mobility of doctors, patients, and equipment, as well as real-time location tracking of systems, assets, and people. The AI model may simulate better efficiency by utilizing real-time data availability from all hospital data points. The model method may combine the results of imaging and non-imaging laboratory diagnosis and provide them to the physician to assist them make a better decision.

After examining their processes and operations, Siemens Healthineers built a Digital Twin model representation for one of their clients' radiology departments. By minimizing long wait times, effectively managing emergency services, optimum utilization of lab and medical equipment, staffing requirements, and managing device downtime, such simulation optimizes the process and improves the patient experience. As a result, hospital administrators can oversee the entire infrastructure from a single platform, from patients to clinicians to data to workflows.

Simulated Medical Training

In medical training and diagnostics, a Digital Twin is a patient model generated prior to actual surgery, and virtual surgery is conducted on it by a multidisciplinary team to avoid damage to human anatomy. This real-time model also enables residents to simulate surgery on patients and better grasp the physiological and anatomical distinctions between individuals. One example of a diagnostic using the Digital Twin paradigm is Medtronic's Cardio Insight mapping system, which collects and integrates patient body surface electrical data with heart-torse anatomical data to generate a 3D image of the heart's electrical activity. This diagnostic procedure has also been approved by the FDA.


 The Proliferation of Medical Digital Twins As-a-Service

The market for outsourced digital twin services provided by large technology companies will grow further. This will broaden the appeal of digital twins and make them more accessible to healthcare organizations of all sizes. The collection of huge volumes of data required to support digital twins will be driven by a continual increase in the number of IoT-enabled devices and endpoints. To improve treatment and outcomes, digital twins will be able to draw information from a wide range of sources, including scans and medical records, as well as tests such as ECGs. The collection of huge volumes of data required to support digital twins will be driven by a continual increase in the number of IoT-enabled devices and endpoints. To improve treatment and outcomes, digital twins will be able to draw information from a wide range of sources, including scans and medical records, as well as tests such as ECGs.

Conclusion: The Digital twin market is poised for growth...

While digital twins are currently in use across many industries, the fast-increasing digital twin industry suggests that demand for digital twins will continue to rise for some time. The digital twin market was worth USD 3.1 billion in 2020. According to some industry analysts, it could continue to rise substantially until at least 2026, reaching an estimated USD 48.2 billion1. Since growing amounts of cognitive power are constantly devoted to their usage, the future of digital twins is almost endless. As a result, digital twins are continually acquiring new skills and capabilities, allowing them to generate the insights required to improve goods and processes.

With the promise of personalized healthcare, remote patient monitoring, and health prediction, demand for Digital Twins in the medical sphere has skyrocketed. Furthermore, using the hospital's Digital Twin model, care sets, operational methods, and personnel assist hospitals in reducing costs and improving patient care.




r. Arivukkarasan

A versatile business professional with over 20 years of experience in Data Analytics, Robotics, IoT, Machine Learning & Human Resource Management.

https://www.linkedin.com/in/arivukkarasan-enterprise-it-solution-expert/