Sensome has developed impedance-based micro-sensors combined with machine learning algorithms to transform invasive medical devices into connected healthcare tools. Its first application, the Clotild® connected guidewire, enables precise identification of biological tissues during ischemic stroke treatment, enhancing procedural accuracy and patient outcomes.
Funding
$8.9M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
AIBPIFounders
Product
Problem
During ischemic stroke treatment, accurately identifying biological tissues with standard guidewires is challenging, potentially leading to imprecise interventions and suboptimal patient outcomes. Current methods lack real-time, objective feedback on tissue composition at the guidewire tip.
Solution
Sensome has developed a connected guidewire, Clotild®, that incorporates impedance-based micro-sensors and machine-learning algorithms to provide real-time tissue identification during stroke procedures. The micro-sensors instantly analyze the biological tissues in contact with the guidewire tip, relaying data to machine learning models that predict tissue type with high reliability. This technology aims to enhance the precision of clot retrieval and improve overall procedural accuracy in ischemic stroke interventions. The technology has potential applications beyond stroke, including interventional cardiology and oncology.
Target Audience
The primary target audience includes interventional neuroradiologists and hospitals specializing in stroke treatment.
Features
- Impedance-based micro-sensors integrated into the guidewire tip for real-time tissue analysis
- Machine learning algorithms for accurate and immediate identification of biological tissues
- Clotild® connected guidewire designed specifically for ischemic stroke treatment
- Potential applications in interventional cardiology and oncology