Neuranics, a spin-out from the Universities of Edinburgh and Glasgow in Scotland, has announced the introduction of a new magnetic sensor development kit.
The new kit is designed to record the heart’s magnetic activity and transmit it wirelessly via Bluetooth for round-the-clock recording and analysis on a smartphone, tablet, or laptop.
Featuring a single point of contact on the body or through thin clothing, the company’s magnetocardiography (MCG) sensor can replace existing three-lead electrocardiography (ECG) sensors for use in medical monitoring devices and sports fitness devices.
The MCG signal provides clearer details and resolution when observing the heart’s function, revealing blood flow within the main cardiac valves.
The kit will include the company’s magnetic sensor that can identify tiny magnetic signals from the heart muscle, Bluetooth interface, prototype electronics and software for analysis on a laptop and an app for Android mobile phones and tablets.
Developers can use it to explore magnetic sensors, and both the software and app are easily customisable.
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The development kit will be ready for purchase early next year and includes consultation and technical support.
Neuranics CEO Noel McKenna said: “We are delighted to be launching the MCG development kit so quickly after our funding round.
“With our breakthrough technology sports, fitness and healthcare companies can develop new products based on the benefits of magnetic sensors.
“We look forward to welcoming attendees and fellow exhibitors for a live demonstration at our booth 60255 in Eureka Park at the Venetian Exhibition Centre, during CES on 9-12 Jan 2024.”
Founded in 2021, Neuranics recently obtained £1.9m ($2.4m) in pre-seed funding from Par Equity.
The company is focused on the development of magnetic sensor technology for applications in the health, fitness, and metaverse sectors.
Its patented technology leverages tunnelling magnetic resistance (TMR) for identifying tiny magnetic signals in the muscles of the arms and body. This TMR is believed to significantly enhance health and fitness tracking and human/machine interfaces.
