Self-Healing, Electrically Conducive, Soft Material Opens Doors to Next-Gen Wearable Devices
By HospiMedica International staff writers Posted on 10 Mar 2023 |
A team of engineers has developed a novel soft material exhibiting metal-like conductivity and self-healing capabilities. The material is the first of its kind to maintain adequate electrical adhesion required to support digital electronics as well as motors. This advance represents a landmark accomplishment in the domains of soft robotics, electronics, and medicine.
Engineers at Carnegie Mellon University (Pittsburgh, PA, USA) have built a new generation of soft machines and robots known as softbotics that are manufactured using multi-functional materials integrated with sensing, actuation, and intelligence. The research team has developed a novel material, composed of a liquid metal-filled organogel composite, characterized by high electrical conductivity, low stiffness, high stretchability, and self-healing properties. The material has been successfully tested in three applications, including a reconfigurable bioelectrode that measures muscle activity on different parts of the body. The research team demonstrated the material's ability to be reconfigured to obtain electromyography (EMG) readings from various areas of the body. Due to its modular design, the organogel can be adjusted to measure hand activity on anterior muscles of the forearm and calf activity on the back of the leg. This breakthrough paves the way for tissue-electronic interfaces like EMGs and EKGs using soft, reusable materials.
“Softbotics is about seamlessly integrating robotics into everyday life, putting humans at the center,” said lead author Carmel Majidi, Professor of Mechanical Engineering. “Instead of being wired up with biomonitoring electrodes connecting patients to bio measurement hardware mounted on a cart, our gel can be used as a bioelectrode that directly interfaces with body-mounted electronics that can collect information and transmit it wirelessly.”
Related Links:
Carnegie Mellon University
Latest Critical Care News
- Stretchable Microneedles to Help In Accurate Tracking of Abnormalities and Identifying Rapid Treatment
- Machine Learning Tool Identifies Rare, Undiagnosed Immune Disorders from Patient EHRs
- On-Skin Wearable Bioelectronic Device Paves Way for Intelligent Implants
- First-Of-Its-Kind Dissolvable Stent to Improve Outcomes for Patients with Severe PAD
- AI Brain-Age Estimation Technology Uses EEG Scans to Screen for Degenerative Diseases
- Wheeze-Counting Wearable Device Monitors Patient's Breathing In Real Time
- Wearable Multiplex Biosensors Could Revolutionize COPD Management
- New Low-Energy Defibrillation Method Controls Cardiac Arrhythmias
- New Machine Learning Models Help Predict Heart Disease Risk in Women
- Deep-Learning Model Predicts Arrhythmia 30 Minutes before Onset
- Breakthrough Technology Combines Detection and Treatment of Nerve-Related Disorders in Single Procedure
- Plasma Irradiation Promotes Faster Bone Healing
- New Device Treats Acute Kidney Injury from Sepsis
- Study Confirms Safety of DCB-Only Strategy for Treating De Novo Left Main Coronary Artery Disease
- Revascularization Improves Quality of Life for Patients with Chronic Limb Threatening Ischemia
- AI-Driven Prediction Models Accurately Predict Critical Care Patient Deterioration