Biomedical Engineering Research Topics

#Artificial_Heart : #A_Breakthrough_Saving #Hundreds_of_Lives 📌Heart failure remains one of the leading causes of death worldwide—but technology is fighting back. 📌Artificial hearts are no longer just science fiction. Today, they are a life-saving reality for hundreds of patients suffering from end-stage heart failure. These sophisticated mechanical devices are designed to completely replace the function of a failing human heart, either temporarily while awaiting a transplant or, in some cases, permanently. 📌Unlike traditional ventricular assist devices (VADs) that support part of the heart’s function, total artificial hearts (TAHs) fully replicate both ventricles' activity, maintaining consistent blood flow to the body. With continuous innovations in bioengineering, materials science, and robotics, artificial hearts have become safer, more durable, and increasingly accessible. 📌Recent success stories include patients who were given only days to live—but with the help of a TAH, they gained months or even years of extended, quality life. Surgeons, cardiologists, and biomedical engineers are now working together more closely than ever to personalize and optimize these devices for long-term use. 📌This isn’t just a medical advancement—it's a revolution in how we view organ failure and recovery. 📌As technology continues to evolve, the artificial heart may one day become a mainstream solution, offering hope where none existed before. #ArtificialHeart #HeartFailure #MedicalInnovation #BiomedicalEngineering #Cardiology #HealthcareTechnology #FutureOfMedicine #LifeSavingTech

Researchers at the City University of Hong Kong have developed miniature, caterpillar-like robots that might change the way we deliver medications and perform surgeries inside the human body. What Are These Millirobots? - Biodegradable and Soft: Made from a gelatin-like material combined with iron oxide microparticles, these tiny robots are about the size of a fingernail. Their soft composition allows them to move through the body without harming delicate tissues. - Magnetic Control: The iron oxide particles make the robots responsive to external magnetic fields. This means doctors can further control the direction their movement precisely, guiding them to specific locations within the body. - Inspired by Insects: Mimicking the walking and gripping abilities of caterpillars, these robots can roll, fold, and even grasp small objects with their claw-like appendages. This flexibility enables them to navigate complex internal environments like the gastrointestinal tract. How Do They Work? The robots can be coated with medications. Once guided to the target area, they unfold their bodies to release the drug directly where it's needed, potentially increasing the treatment's effectiveness and reducing side effects. Their ability to grasp and transport objects opens up possibilities for performing surgical tasks without the need for large incisions or invasive instruments. After completing their mission, the robots naturally break down over a few days into harmless substances, eliminating the need for surgical retrieval. While still in the experimental phase, these tiny robots have shown promise in laboratory tests. The researchers successfully guided them through a model of the gastrointestinal system, demonstrating their potential for real-world medical use. Would you be comfortable with such technology being used in medical treatments? #innovation #technology #future #management #startups

In engineering, connecting hard and soft materials is notoriously difficult, often leading to stress concentrations and failure in joints, implants, and electronic components. We show how Nature solves this challenge through subtle, built-in molecular programming at the nanoscale. At the tendon-bone interface, the enthesis, weak H-bond interactions between collagen and mineral particles prevent a rigid network from forming, preserving compliance, toughness, and durability. Durability comes not from stronger bonds, but from weak hydrogen bonds that tune structure - an unexpected concept, giving us deeper understanding of the design language in protein materials. These findings point toward new ways of designing real-world resilient biomaterials and engineered interfaces, from medical devices to electronic circuits. Proud to share this work, published in ACS Nano, with Guy Genin and Stavros Thomopoulos, led by Amadeus Alcântara, Mario Milazzo and Eesha Khare. Full details in the paper, link below.

Computer Simulation - The Living ❤️ Project One of the most exciting projects in this field is the "Living Heart Project," which brings together leading cardiovascular researchers, educators, medical device developers, regulatory agencies, and practicing cardiologists on a shared mission to develop and validate highly accurate, personalized digital human heart models. These models will establish a unified foundation for cardiovascular in silico medicine and serve as a joint technology base for education and training, medical device design, testing, clinical diagnosis, and regulatory science —creating a practical path for rapidly translating current and future cutting-edge innovations directly into improved patient care. 📝 Open access review paper here: https://lnkd.in/dVYqaDs 🌎 From Kelly Senecal (Simulation done in CONVERGE) #cfd #simulation #engineering

Yesterday, NVIDIA open sourced its BioNeMo Framework! It is a second open source annoucement in the AI for biology field in just a week (see my previous post for the other one). BioNeMo is a research platform designed to scale biomolecular AI research for drug discovery and molecular design. The platform provides tools to train and deploy large biomolecular models across high-performance computing environments, enabling advanced computation in labs with limited resources. Integration with Leading AI Models: AlphaFold2: Achieves a 5x speedup in protein structure predictions. DiffDock 2.0: Delivers a 6.2x faster prediction of molecular orientations with 16% higher accuracy. RFdiffusion & ProteinMPNN: Speeds up the design of protein therapeutics targeting specific molecules. NIM Microservices: Introduces optimized, secure, and scalable AI inference services deployable on-premises or in cloud environments. BioNeMo Blueprints: Provides modular workflows for virtual screening and small molecule design, reducing time and cost in AI-driven discovery processes. Acceleration Libraries: Includes new libraries like cuEquivariance, optimizing mathematical computations for chemical and biomolecular models. In a PR, NVIDIA sais the tool is already integrated by over 200 biopharma companies and startups. The infrastructure is also supported by partners like AWS, Deloitte, and Accenture for broader enterprise use. With this move, NVIDIA attempts to standardize and accelerate AI-driven workflows in computational biology and drug discovery. While NVIDIA is certainly pushing its own influence with this move and the open source strategy by large software develoers is not new, it is, in my opinion, beneficial for the drug discovery community at this point. Anyway, check the tool and code via a link in the comments 👇 Image credit: NVIDIA

🌟 Revolutionizing Clinical Trials with GenAI 🌟 This publication introduces a transformative framework for leveraging generative AI in clinical trials, addressing inefficiencies and biases to improve outcomes. 💡 The Challenge: Over 40% of clinical trials face significant flaws, wasting resources and delaying progress. Common issues include poor blinding, incomplete data, and inadequate diversity in participant selection. 🛠️ Proposed Solution: Develop Application-Specific Language Models (ASLMs) tailored for clinical trial design. These models, fine-tuned for the domain, can enhance protocol accuracy, reduce errors, and suggest best practices. 📋 Three-Phase Framework: 1️⃣ Regulatory Development: Agencies like the FDA create foundational ASLMs. 2️⃣ Customization: Health Technology Assessment bodies refine models for regional contexts. 3️⃣ Deployment: Researchers and trial designers access tools to improve protocols and submissions. 🌍 Key Benefits: ASLMs can address underrepresentation, predict safety issues, and ensure ethical, inclusive trials. They promise faster drug development, lower costs, and greater accuracy in trial outcomes. 🔗 Open Access and Collaboration: Advocates for open-source models to foster transparency, trust, and innovation, while maintaining rigorous oversight and validation. #GenerativeAI #ClinicalTrials #InnovationInMedicine #AIForGood #HealthcareTech #DiversityInTrials #MedicalInnovation #DrugDevelopment #EthicalAI #DigitalHealth

Revolutionizing clinical trials is no small feat, but it's exactly what we're tackling in our new #AISTATS2025 paper! We introduce RFAN (Randomise First, Augment Next) - a novel two-stage framework that reimagines trial design, making it not only more efficient but also fairer for all patients. By integrating causal deep #Bayesian active learning, RFAN goes beyond conventional #RCTs, dynamically adapting recruitment and treatment assignment to ensure underrepresented populations are better included while maintaining regulatory rigour. Our approach optimises both Post-Trial Mean Benefit (PTMB) and Post-Trial Fairness (PTF), ensuring treatments reach the right people faster, with greater real-world impact, and without compromising trial integrity. This is the future of adaptive, equitable, and efficient clinical trials. by Omer Noy Klein, Alihan Hüyük, Ron Shamir, Uri Shalit, Mihaela van der Schaar Read more: 🔗 https://lnkd.in/gj4CkvXV For more information on our work on Clinical Trials, please find our research pages here: https://lnkd.in/eeay7Qqg https://lnkd.in/eYBVRj5D

We solved half the problem & thought we bridged the gap. Ever worked on a solution that looked perfect on paper… but ended up creating more problems than it solved? That’s exactly what happened when I was called in to review a telehealth solution. It was well-designed, checked all the cybersecurity boxes, & allowed patients to consult doctors remotely. The project requirement was clear: enable remote consultations. And the solution delivered exactly that. But here’s the thing: While healthcare systems often operate in silos, patients experience their care as one continuous journey. And this solution missed critical parts of that journey: 🔸 No easy way to book follow-ups. Patients had to call, leading to missed care. 🔸 Medication collection still required hours of travel, making the platform’s convenience meaningless. 🔸 Administrative staff were overloaded, causing delays in care coordination. We solved one problem & unintentionally created three more. The solution was designed for the system’s convenience, not the patient’s journey. To shift the perspective, we expanded the conversation to include voices we hadn’t considered: 🔸 Pharmacists: To integrate medication delivery into the process 🔸 Community Health Workers: To provide local, hands-on support 🔸 Family Caregivers: To highlight logistical & emotional challenges at home 🔸 IT Teams: To automate follow-ups & reduce administrative burden 🔸 Local Transport Providers: To enable last-mile delivery of medications With these insights, we redesigned the solution into a comprehensive care experience: ✅ Patients could book follow-ups easily & get automated reminders ✅ Medications were delivered directly to their homes ✅ Caregivers & community workers ensured patients didn’t fall through the cracks I later learned that: 🔸 Missed follow-ups dropped by 40%. 🔸 Medication adherence & health outcomes improved significantly. The redesigned platform didn’t just connect patients to doctors, it completed the care journey. Next time you’re working on a solution, consider these points: 1️⃣ Patients see one journey While systems operate in silos, patients experience care as a unified process. 2️⃣ Identify all stakeholders Both direct & indirect voices like caregivers, pharmacists & community workers, are essential to closing gaps. 3️⃣ Design for continuity Address every touchpoint in the patient’s journey, ensuring nothing falls through the cracks. Have you worked on solutions where overlooked stakeholders made all the difference? What’s one gap you discovered that changed everything? #DigitalHealth #Innovation #HealthcareTransformation #PatientExperience #Collaboration 💡This post is part of 'Rethinking Digital Health Innovation' (RDHI), empowering professionals to transform digital health beyond IT and AI myths. 💡Find the ongoing series and resources on our companion website (URL in comments). 💡 Repost if this message resonates with you!

Remote patient monitoring via telemedicine enables continuous tracking of vital signs through digital tools. Implementing this system in a business context demands a focus on key aspects like technological infrastructure, data security, and active participation from healthcare professionals and patients. This innovative approach offers significant potential to enhance patient care but requires careful planning and execution: Advanced Technology Integration: Utilize connected medical devices for precise and continuous real-time health data collection. Robust IT Infrastructure: Ensure a secure, reliable IT framework for storing, analyzing, and providing real-time access to patient health data. Data Security and Compliance: Protect sensitive health data with encryption and secure connections to comply with healthcare regulations. Seamless System Integration: Integrate remote monitoring tools with existing healthcare systems for a comprehensive patient health view. Staff Training and Support: Train healthcare professionals to use telemedicine tools and interpret real-time patient data effectively. Patient Engagement and Education: Educate patients on using monitoring devices and the importance of data sharing for the success of telemedicine initiatives. Continuous Technical Support: Provide ongoing technical support to maintain the smooth operation of the monitoring system. Data Analysis and Reporting: Regular analysis and reporting of health data help identify trends, spot anomalies, and enhance patient care. Scalability and Adaptability: Ensure the system can scale and adapt to handle an increasing number of patients and diverse medical conditions efficiently. Implementing these strategies ensures that remote patient monitoring enhances healthcare delivery while maintaining data security and compliance. #Telemedicine #HealthcareInnovation #MedicalTechnology Ring the bell to get notifications 🔔

🤩 Sensor Interface Circuit for Biomedical Devices & Biosensors 💥 💝 Learn How to Interface Glucose, Lactate and other Sensors with MCU 🧐 At the heart of most of these biosensors is LMP91000 by Texas Instruments which is a programmable analog front-end for use in micro-power electrochemical sensing applications. It provides a complete signal path solution between a sensor and a microcontroller that generates an output voltage proportional to the cell current. It supports multiple electrochemical sensors such as: 3-lead toxic gas sensors and 2-lead galvanic cell sensors. The core of the LMP91000 is a potentiostat circuit. It consists of a differential input amplifier used to compare the potential between the working and reference electrodes to a required working bias potential (set by the Variable Bias circuitry). The error signal is amplified and applied to the counter electrode (through the Control Amplifier - A1). Any changes in the impedance between the working and reference electrodes will cause a change in the voltage applied to the counter electrode, in order to maintain the constant voltage between working and reference electrodes. A Transimpedance Amplifier connected to the working electrode, is used to provide an output voltage that is proportional to the cell current. The working electrode is held at virtual ground (Internal ground) by the transimpedance amplifier. The potentiostat will compare the reference voltage to the desired bias potential and adjust the voltage at the counter electrode to maintain the proper working-to-reference voltage. How to build a circuit for your biomedical application? Orlando Hoilett built KickStat, a miniaturized potentiostat using LMP91000 with the processing power of the Arm Cortex-M0+ SAMD21 Microchip Technology Inc. microcontroller on a custom-designed 21.6 mm by 20.3 mm circuit board. By incorporating onboard signal processing via the SAMD21, h he achieved 1mV voltage resolution and an instrumental limit of detection of 4.5nA in a coin-sized form factor. He measured the faradaic current of an anti-cocaine aptamer using cyclic voltammetry and square wave voltammetry and demonstrated that KickStat’s response was within 0.6% of a high-end benchtop potentiostat. To further support others in electrochemical biosensors development, he has made KickStat’s design and firmware available in an online GitHub repository. 📢 KickStat Project: "KickStat: A Coin-Sized Potentiostat for High-Resolution Electrochemical Analysis" doi: https://lnkd.in/eFjdpWjQ GitHub repo: https://lnkd.in/eJAvT_kR Datasheet: https://lnkd.in/eKvkGWCt 💜 Share it with your biosensors, biomedical wearable network 👌 #biosensors #wearables #sensors #electronics #Potentiostat #lmp91000