A new University of Glasgow (UofG) project is researching new ways that prosthetic limbs respond directly to instructions from users’ muscles.

The EU-funded research project, called MAGNABLE, will monitor and measure small signals created when nerve cells transmit information to skeletal muscles.

If successful, the technology could enable improved control of digital spaces, removing the need for handheld controllers in virtual or extended reality in favour of wearable devices.

Over the next two years, a new human-machine interface will be developed which can produce high-resolution, low-noise scans of muscle activity by measuring muscles’ magnetic fields.

Currently, the most widely used method of monitoring muscle activity is electromyography (EMG) which takes its readings from electrodes placed on the skin.

However, the sensitivity of those readings is limited by the need to read the signals through muscle and skin, which dampens the clarity of the signal. That limitation makes it difficult for EMG to be used in human-machine interface devices like prosthetics.

One proposed solution is to surgically implant EMG sensors directly into muscle tissue to improve their ability to detect signals. However, this kind of implantation carries with it associated risks of infection, which could lead to irreversible muscle damage, making it unsuitable for widespread adoption.

An alternative to EMG for muscle activity recording is magnetomyography (MMG) which has the potential to provide improved resolution imagery without the requirement of invasive surgery.

Currently, MMG is challenging to use for muscle activity monitoring because the amplitude of magnetic signals from muscles is small enough that the geomagnetic field can interfere with readings.

However, the MAGNABLE system will build on recent developments from the UofG’s James Watt School of Engineering.

At the School’s Microelectronics Lab, researchers have developed miniaturised magnetic sensors to measure the magnetic field with the sensitivity required to enable muscle activity monitoring.

The team said they would build upon that breakthrough to develop a microchip which can read MMG data from muscles while screening out environmental background noise.

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Professor Hadi Heidari, UofG James Watt School of Engineering, and MAGNABLE’s principal investigator, commented: “MMG has a great deal of potential to produce the kind of high-resolution data that we’ll need in order to create highly capable neural interfaces which can be controlled by muscle movements, just like real limbs.

“The technology we’re developing could also be incorporated into arm bands or other wearable devices to enable realistic interactions with virtual and extended reality.

“I’m looking forward to solving some difficult challenges with my colleagues at the UofG and Neuranics Ltd over the next couple of years and making this technology available to the market.”

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