Bioelectronic Sutures Monitor Deep Surgical Wounds
By HospiMedica International staff writers Posted on 17 Jan 2022 |
Image: Smart surgical sutures with an attached electronic RFID monitoring module (Photo courtesy of NUS)
Battery-free, wireless smart sutures can promote healing and monitor wound integrity, gastric leakage, and tissue micro-motion at the same time, claims a new study.
Developed at National University of Singapore (NUS; Singapore), the new sutures have three key components: a medical-grade multifilament silk suture coated with a conductive polymer to allow it to respond to wireless signals; a battery-free electronic capacitive sensor; and an external wireless reader used to communicate with the suture. During stitching of the wound, the insulating section of the suture is threaded through the electronic module and secured by applying medical silicone to the electrical contacts.
The entire surgical stitch functions as a radio-frequency identification (RFID) tag that can be read by an external reader. The smart sutures can be read up to a depth of 50 mm, depending on the length of stitches involved, and are also able to alert clinicians if they are broken or unraveled, for example by dehiscence of the wound. Similar to existing sutures, clips, and staples, the smart sutures can be removed post-operatively via a minimally invasive procedure when risk of complications has passed. The study was published in the December 2021 issue of Nature Biomedical Engineering.
“Currently, post-operative complications are often not detected until the patient experiences systemic symptoms like pain, fever, or a high heart rate,” said senior author John Ho, PhD, of the NUS department of Electrical and Computer Engineering. “These smart sutures can be used as an early alert tool to enable doctors to intervene before the complication becomes life-threatening, which can lead to lower rates of re-operation, faster recovery, and improved patient outcomes.”
Related Links:
National University of Singapore
Developed at National University of Singapore (NUS; Singapore), the new sutures have three key components: a medical-grade multifilament silk suture coated with a conductive polymer to allow it to respond to wireless signals; a battery-free electronic capacitive sensor; and an external wireless reader used to communicate with the suture. During stitching of the wound, the insulating section of the suture is threaded through the electronic module and secured by applying medical silicone to the electrical contacts.
The entire surgical stitch functions as a radio-frequency identification (RFID) tag that can be read by an external reader. The smart sutures can be read up to a depth of 50 mm, depending on the length of stitches involved, and are also able to alert clinicians if they are broken or unraveled, for example by dehiscence of the wound. Similar to existing sutures, clips, and staples, the smart sutures can be removed post-operatively via a minimally invasive procedure when risk of complications has passed. The study was published in the December 2021 issue of Nature Biomedical Engineering.
“Currently, post-operative complications are often not detected until the patient experiences systemic symptoms like pain, fever, or a high heart rate,” said senior author John Ho, PhD, of the NUS department of Electrical and Computer Engineering. “These smart sutures can be used as an early alert tool to enable doctors to intervene before the complication becomes life-threatening, which can lead to lower rates of re-operation, faster recovery, and improved patient outcomes.”
Related Links:
National University of Singapore
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