Neuranics aims to develop a disruptive neurotechnology for human-machine interfacing through nanoscale sensing technology with a small footprint, excellent sensitivity, and high spatial resolution.

Utilising the skills from academia and industry, we strive towards revolutionising Extended Reality (XR) wearable devices for education, gaming, consumer electronics, and healthcare applications.


Neuranics has assembled a world-class team of engineers, neuroscientists, and physicists to create a full-stack neurotech company who are building a platform to realize that brighter future now.

Prof. Hadi Heidari

Chief Executive Officer

Darian Brookes


Maria Cerezo Sanchez

Business Development Manager

Prof. Kia Nazarpour

Chief Strategy Officer

Negin Ghahramani

Chief Medical Officer

Dr. Siming Zuo

Lead Engineer

Huxi Wang

Hardware Engineer

Asfand Tanwear

Hardware Engineer


A wearable myomagnetic system from the lab to the real world

Our product offers underpinning sensing microsystems to enable next-generation wearable bionic devices for recording muscle activities. The first miniaturised and non-cryogenic product to the end-user market will replace the bulky, invasive and expensive laboratory instruments with easy-to-use wearable XR platforms.

First Wearable Prototype

We implemented a prototype demo integrated magnetic sensor array, microchips, shielded layer and battery etc. into a wearable device for continuous monitoring MMG of the human muscle to work complementary with existing EMG sensors. We pursued the non-invasive on-skin clinical testing with healthy human subjects (5-10) who volunteered for the study and signed informed consent and ethical approval.

Fisrt Wearable MMG Recording

We demonstrated an experimentally proof of concept and small scale prototype built in a laboratory environment. Our prototype offers a small footprint, excellent sensitivity, ultralow noise, and high spatial resolution for recording muscle activities. This new miniaturised magnetic sensing system will replace the bulky, invasive and expensive laboratory instruments with easy-to-use wearable platforms.

MMG Proof of Concept

We showed, for the first time, identification, characterization and quantification of the MMG signals at room temperature by utilising highly miniaturised and sensitive magnetic sensors. The sensor array was precisely placed on the hand skin of the abductor pollicis brevis muscle to record the lateral component of the magnetic signal. The signal-to-noise ratio is over 20 among all the bandpass frequencies.

Readout Circutry & Noise Control

We developed a real-time measurement system including a large array of sensors and an on-chip analog front-end to realise signal amplification, filtering, noise and drift cancellation. We also designed a dynamic geomagnetic field cancellation technique to reduce noise sources such as the acoustic noise and disturbances of magnetic and electric fields from the earth and surrounding equipment.

Sensor Development

We optimised the performance and size of the muscle sensors. According to finite-element analysis and experiment outcomes, the best overall noise performance is obtained with large arrays of large-area sensors. In addition, we introduce a low-profile magnetoelectric sensor with analogue frontend circuitry that has the sensitivity to measure pico-Tesla MMG signals at room temperature.

Sensor & Signal Simulations

We developed a finite-element method model of muscle sensors and evaluated its performance of the sensitivity and linearization range. It provided a reliable benchmark for modelling future hybrid magnetic-CMOS developments. We believe that this structure can offer a platform to develop ultra-sensitive, smart and scalable sensors for muscle sensing.

Idea Introduced
Miniaturised MMG Idea

Magnetomyography (MMG) is the study of muscle function through the inquiry of the magnetic signal that a muscle generates when contracted, first formally proposed in 1972. Within the last few decades, extensive effort has been invested to identify, characterise and quantify the MMG signals. However, it is still far from miniaturised, sensitive, inexpensive and low-power muscle sensors.