The soft robotic model of the human heart, developed at UNSW. Credit: UNSW/Richard Freeman.
UNSW researchers have developed a soft robotic model of the human heart that can mimic disease and provide a realistic environment for testing the next generation of cardiac devices.
Researchers at UNSW Sydney have developed a fully synthetic soft robotic heart that reproduces the complex movements and internal structures of the human heart, opening the door to better treatments, safer medical devices and more personalised care.
Published in Nature Communications and Advanced Science, the research introduces a beating model of the left side of the heart that includes artificial valves, papillary muscles and chordae tendineae – structures that are critical to healthy heart function and are frequently affected by disease.
The device is able to accurately reproduce the process in a real heart where cardiac valves leak and blood flows backwards, which increases the risk of heart failure and other life-threatening complications.
In that way, the research team say the new soft robot can eventually help provide a better understanding of heart conditions, reduce reliance on animal testing and provide doctors with patient-specific models to plan treatments before procedures are performed.
Team leader, Scientia Associate Professor Thanh Nho Do, from UNSW’s School of Biomedical Engineering and UNSW Medical Robotics Lab, says the work is important because cardiovascular disease remains the world’s leading cause of death.
“Heart failure with preserved ejection fraction (HFpEF) is a complex heart condition that often occurs alongside other health problems such as high blood pressure, irregular heartbeats, kidney disease, obesity, and diabetes,” Professor Do says.
“Because it affects people in different ways, developing medical devices to improve heart function is challenging.
“The valves in the heart are also crucial for cardiac efficiency, but disease can cause them to become leaky or stiff. This can increase the workload of the heart and contribute to heart failure.
“Our broader goal is to build realistic artificial heart models that can help researchers understand disease and develop safer, more effective devices before they are tested on animals or reach patients.”
Recreating the beating heart
The model developed at UNSW is a soft, flexible replica of the left side of the heart. Silicone membranes form the internal chambers, while soft robotic artificial muscles wrapped around the structure reproduce the way the heart naturally contracts and twists.
Unlike conventional laboratory models, the soft robotic heart contains the structures responsible for controlling the mitral valve, which in real life acts like a pair of swinging doors that open and close with each heartbeat to ensure oxygen-rich blood flows to the body while preventing backward leakage.
The inclusion of this specific physiological feature of the heart in the model will allow researchers to reproduce diseases in which the valve does leak and blood starts to flow backwards.
“The model is made from flexible materials and powered by artificial muscles that are arranged to mimic the layered muscle architecture of the human heart,” Dr James Davies, a postdoc in Do’s group, says.
“We found a way to model this muscle fibre architecture using soft robotic artificial muscle fibres. They are powered by hydraulic pressure which we control to make our ventricular muscle model move like the real thing.
“We then wrap this artificial musculature around silicone membranes which model the inner surface of the human left heart, forming our left heart, atrioventricular model. These membranes contain the simulated blood within the left heart allowing simulated pumping of blood in and out of the model.”
The system allows researchers to actively adjust the tension in the artificial papillary muscles that support the mitral valve.
By doing so, the team was able to recreate disease-like conditions including mitral valve prolapse and regurgitation, where blood leaks backwards instead of flowing efficiently through the heart.
Mimicking human heart disease
Using ultrasound imaging and measurements of pressure and blood flow, the researchers showed that the artificial heart behaves in ways remarkably similar to a human heart.
Healthy valve function produced normal pressure and flow patterns, while introducing disease caused characteristic changes seen in patients.
“In the first study reproducing the internal valving of the human heart, we were able to generate pressure and flow waveforms similar to that of the real thing,” Professor Do says.
“Critically, we were able to adjust mitral valve function by controlling papillary muscle length.
“We validated this using invasive pressure and flow measurements in and out of the heart, but we were also able to demonstrate compatibility of the model with non-invasive clinical measures of heart function such as ultrasound imaging, or echocardiography.
“Simulated healthy mitral valve function followed physiological expectations in heart pressure and flow, while inducing disease showed increased regurgitation, or backflow, and a decrease in outlet pressure and flow, also consistent with human heart valve disease.”
Scientia Professor Nigel Lovell, Head of School of Biomedical Engineering & Director of Tyree IHealthE, added: “The ultrasound imaging also resembled human cardiac imaging owing to the biomimetic form and function of our model. We were able to observe human-like valve leaflet motion and visualise blood flow across the valves, including the formation of regurgitant jets leaking out of valves with induced disease.”
The researchers also used the system to test a newly developed soft robotic cardiac catheter inside the beating model.
The catheter was able to navigate within the artificial heart and detect when it came into contact with moving cardiac structures, demonstrating how the platform could accelerate development of future surgical tools.
Credit: UNSW/Richard Freeman.
Reducing reliance on animal models
Because the simulator offers a controllable and repeatable environment, the researchers believe it could help reduce the need for animal studies during the early stages of medical device development.
“We hope to bring into existence a platform to comprehensively model cardiac disease and simulate their various treatments, including cardiac implants and surgical tools,” Professor Do says.
“Particularly in the early stages of cardiac device development, such a platform will offer control over heart function while maintaining anatomical and physiological relevance, reducing our reliance on animal models and its associated costs and ethical concerns.
“Being able to induce a broad range of specific cardiac disease such as HFpEF which remains one of the least well understood and hardest heart failure to treat, we hope to aid in the development of new, purpose-built implants and devices that save and improve lives and reduce the burden of cardiovascular disease on healthcare systems.
“HFpEF disease that makes up 50% of heart failure cases deserves its own mechanical treatment options.”
More importantly, the model successfully reproduced many of the changes seen in HFpEF, including changes in heart function and blood flow.
When researchers simulated one of the earliest signs of HFpEF — a reduced ability of the heart to relax between beats — the model showed that blood flowed into the heart more slowly and less efficiently. This delayed filling increased pressure inside the heart, closely matching what is commonly observed in patients with HFpEF.
The researchers also envision a future in which patient-specific versions of the model could be created using medical imaging data.
These personalised models could help clinicians evaluate different devices and treatment approaches before operating, improving surgical planning and potentially leading to better outcomes.
“With the rise of personalised medicine, we also hope to enable better patient-specific cardiovascular modelling that can aid in surgical planning and inform decisions around implant type, size, and functional parameters,” Professor Do says.
“We are looking forward to validating these concepts and pushing towards clinical adoption in the future.”
Dr James Davies and Scientia Associate Professor Thanh Nho Do in their laboratory. Credit: UNSW/Richard Freeman.
Future validation
While the study demonstrates the technology’s potential, the researchers stress that the current model is still a proof of concept rather than a finished clinical tool.
Several challenges remain, including improving materials, refining the control systems and making the device even more compatible with medical imaging. Future versions will also need to better reproduce certain aspects of heart function and use patient-specific geometries rather than simplified structures.
Most importantly, the platform must be validated against real patient data.
“The most important next step is deeper validation against clinical data,” Professor Do says.
“The current studies demonstrate strong proof-of-concept performance.
“The model can reproduce key pressure, flow, motion, valve, and imaging features that align with human heart behaviour. However, before this platform can be used for clinical decision-making, we need to compare it systematically with patient data across a wide range of heart anatomies and disease severities.”
The team, which also includes Professor Christopher Hayward, a heart failure and transplant cardiologist at St Vicent’s Hospital Sydney, as well as Professor Jelena Rnjak-Kovacina and Scientia Associate Professor Hoang-Phuong Phan from UNSW, hope that with further development of this technology it can be adopted in clinical settings.
“Rather than viewing the current model as a finished clinical tool, we see it as an enabling platform,” Dr Davies added.
“It demonstrates that soft robotic artificial hearts can reproduce disease mechanics in ways that conventional benchtop models cannot, and it provides a clear pathway toward patient-specific modelling, device testing, and eventually treatment planning.”
Overview of ABBEL compared to traditional recursive summarization. Beliefs replace the full interaction history as the agent’s working context, and belief grading improves performance by
supervising the contents of each belief state..
A miniature robot developed at the University of Basel could help prepare teeth for a crown. Photo: University of Basel, Catherine Weyer.
Dr Yukiko Tomooka mounting the dental robot on a model patient. Photo: University of Basel, Catherine Weyer.