Implantable AI System for Early Detection and Treatment of Illnesses Detects Pathological Changes without Medical Supervision
By HospiMedica International staff writers Posted on 27 Aug 2021 |

Image: Artificial polymer-based neural network. The strongly nonlinear behavior of these networks enables their use in reservoir computing (Photo courtesy of TU Dresden)
Researchers have developed an implantable Artificial Intelligence (AI) system for the early detection and treatment of illnesses.
For the first time ever, scientists at the Chair of Optoelectronics at TU Dresden (Dresden, Germany) have succeeded in developing a bio-compatible implantable AI platform that classifies in real time healthy and pathological patterns in biological signals such as heartbeats. It detects pathological changes even without medical supervision.
AI will fundamentally change medicine and healthcare: Diagnostic patient data, e.g. from ECG, EEG or X-ray images, can be analyzed with the help of machine learning, so that diseases can be detected at a very early stage based on subtle changes. However, implanting AI within the human body is still a major technical challenge. The TU Dresden scientists have demonstrated an approach for real-time classification of healthy and diseased bio-signals based on a biocompatible AI chip. They used polymer-based fiber networks that structurally resemble the human brain and enable the neuromorphic AI principle of reservoir computing. The random arrangement of polymer fibers forms a so-called "recurrent network," which allows it to process data, analogous to the human brain. The nonlinearity of these networks enables to amplify even the smallest signal changes, which - in the case of the heartbeat, for example - are often difficult for doctors to evaluate. However, the nonlinear transformation using the polymer network makes this possible without any problems.
In trials, the AI was able to differentiate between healthy heartbeats from three common arrhythmias with an 88% accuracy rate. In the process, the polymer network consumed less energy than a pacemaker. The potential applications for implantable AI systems are manifold: For example, they could be used to monitor cardiac arrhythmias or complications after surgery and report them to both doctors and patients via smartphone, allowing for swift medical assistance.
"The vision of combining modern electronics with biology has come a long way in recent years with the development of so-called organic mixed conductors," explained Matteo Cucchi, PhD student and a member of the research team. "So far, however, successes have been limited to simple electronic components such as individual synapses or sensors. Solving complex tasks has not been possible so far. In our research, we have now taken a crucial step toward realizing this vision. By harnessing the power of neuromorphic computing, such as reservoir computing used here, we have succeeded in not only solving complex classification tasks in real time but we will also potentially be able to do this within the human body. This approach will make it possible to develop further intelligent systems in the future that can help save human lives."
Related Links:
TU Dresden
For the first time ever, scientists at the Chair of Optoelectronics at TU Dresden (Dresden, Germany) have succeeded in developing a bio-compatible implantable AI platform that classifies in real time healthy and pathological patterns in biological signals such as heartbeats. It detects pathological changes even without medical supervision.
AI will fundamentally change medicine and healthcare: Diagnostic patient data, e.g. from ECG, EEG or X-ray images, can be analyzed with the help of machine learning, so that diseases can be detected at a very early stage based on subtle changes. However, implanting AI within the human body is still a major technical challenge. The TU Dresden scientists have demonstrated an approach for real-time classification of healthy and diseased bio-signals based on a biocompatible AI chip. They used polymer-based fiber networks that structurally resemble the human brain and enable the neuromorphic AI principle of reservoir computing. The random arrangement of polymer fibers forms a so-called "recurrent network," which allows it to process data, analogous to the human brain. The nonlinearity of these networks enables to amplify even the smallest signal changes, which - in the case of the heartbeat, for example - are often difficult for doctors to evaluate. However, the nonlinear transformation using the polymer network makes this possible without any problems.
In trials, the AI was able to differentiate between healthy heartbeats from three common arrhythmias with an 88% accuracy rate. In the process, the polymer network consumed less energy than a pacemaker. The potential applications for implantable AI systems are manifold: For example, they could be used to monitor cardiac arrhythmias or complications after surgery and report them to both doctors and patients via smartphone, allowing for swift medical assistance.
"The vision of combining modern electronics with biology has come a long way in recent years with the development of so-called organic mixed conductors," explained Matteo Cucchi, PhD student and a member of the research team. "So far, however, successes have been limited to simple electronic components such as individual synapses or sensors. Solving complex tasks has not been possible so far. In our research, we have now taken a crucial step toward realizing this vision. By harnessing the power of neuromorphic computing, such as reservoir computing used here, we have succeeded in not only solving complex classification tasks in real time but we will also potentially be able to do this within the human body. This approach will make it possible to develop further intelligent systems in the future that can help save human lives."
Related Links:
TU Dresden
Latest Business News
- Bayer and Broad Institute Extend Research Collaboration to Develop New Cardiovascular Therapies
- Medtronic Partners with Corsano to Expand Acute Care & Monitoring Portfolio in Europe
- Expanded Collaboration to Transform OR Technology Through AI and Automation
- Becton Dickinson to Spin Out Biosciences and Diagnostic Solutions Business
- Boston Scientific Acquires Medical Device Company SoniVie
- 2026 World Hospital Congress to be Held in Seoul
- Teleflex to Acquire BIOTRONIK’s Vascular Intervention Business
- Philips and Mass General Brigham Collaborate on Improving Patient Care with Live AI-Powered Insights
- Arab Health 2025 Celebrates Landmark 50th Edition
- Boston Scientific Acquires Medical Device Company Intera Oncology
- MEDICA 2024 to Highlight Hot Topics of MedTech Industry
- Start-Ups To Once Again Play Starring Role at MEDICA 2024
- Boston Scientific to Acquire AFib Ablation Company Cortex
- Hologic Acquires Gynesonics to Strengthen Existing Gynecological Surgical Business
- Smith+Nephew and JointVue Partner on Ultrasound Preoperative Planning in Robotics-Assisted Surgery
- Stryker Completes Acquisition of NICO Corporation
Channels
Critical Care
view channel
Ultra-Thin Implant Helps Patients with Spinal Cord Injury Recover Lost Functions
Spinal cord injuries remain incurable and can have life-altering consequences. These injuries disrupt the communication pathway between the brain and the body, often leading to permanent loss of function.... Read more
Smart Capsule Offers Real-Time Profiling Across GI Tract
Researchers are increasingly recognizing the gastrointestinal (GI) tract as a key player in overall health. While its primary role is in digestion, the GI tract also contributes to the production of hormones,... Read moreSurgical Techniques
view channel
First-Ever Technology Makes Blood Translucent During Surgery
No matter the discipline or scale, bleeding is a regular part of any surgery and can create several challenges. In operating room imaging, seeing through blood in real-time during a surgery has been a... Read more
Tibia Nailing System with Novel Side-Specific Nails to Revolutionize Fracture Surgery
Smith+Nephew (Hull, UK;) has launched its new TRIGEN MAX Tibia Nailing System for stable and unstable fractures of the tibia, including the shaft. It is the only system to now offer trauma surgeons the... Read morePatient Care
view channel
Revolutionary Automatic IV-Line Flushing Device to Enhance Infusion Care
More than 80% of in-hospital patients receive intravenous (IV) therapy. Every dose of IV medicine delivered in a small volume (<250 mL) infusion bag should be followed by subsequent flushing to ensure... Read more
VR Training Tool Combats Contamination of Portable Medical Equipment
Healthcare-associated infections (HAIs) impact one in every 31 patients, cause nearly 100,000 deaths each year, and cost USD 28.4 billion in direct medical expenses. Notably, up to 75% of these infections... Read more
Portable Biosensor Platform to Reduce Hospital-Acquired Infections
Approximately 4 million patients in the European Union acquire healthcare-associated infections (HAIs) or nosocomial infections each year, with around 37,000 deaths directly resulting from these infections,... Read more
First-Of-Its-Kind Portable Germicidal Light Technology Disinfects High-Touch Clinical Surfaces in Seconds
Reducing healthcare-acquired infections (HAIs) remains a pressing issue within global healthcare systems. In the United States alone, 1.7 million patients contract HAIs annually, leading to approximately... Read moreHealth IT
view channel
Printable Molecule-Selective Nanoparticles Enable Mass Production of Wearable Biosensors
The future of medicine is likely to focus on the personalization of healthcare—understanding exactly what an individual requires and delivering the appropriate combination of nutrients, metabolites, and... Read more