A body without limits

Disruptive neurotechnology for
human machine interfacing

Mission


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

Revolutionise Extended Reality (XR) wearable devices for education, gaming, consumer electronics, and healthcare applications.

About


Neuranics is a knowledge-enterprise that has gathered an exciting team with the balanced skills and expertise from academia and industry needed to achieve the business aims.

Dr Hadi Heidari

Founder & CEO

Ms Bonnie Dean

Director

Prof Kia Nazarpour

Scientific Advisor

Prof Dario Farina

Scientific Advisor

Negin Ghahramani

Medical Scientist

Dr Siming Zuo

Technical Director

Mr Asfand Tanwear

Hardware Engineer

Ms Maria Cerezo Sanchez

Business Development Manager

Journey


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 miniaturized 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.

2021

First 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 miniaturized magnetic sensing systems will replace the bulky, invasive and expensive laboratory instruments with easy-to-use wearable platform.

2020

MMG proof of concept

We showed, for the first time, identification, characterization and quantification of the MMG signals at room temperature by utilizing highly miniaturized 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.

2019

Readout Circuitry & Noise Control

We developed a real-time measurement system including a large array of sensors and an on-chip analog front-end to realize 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.

2018

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.

2017

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.

2016

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, characterize and quantify the MMG signals. However, it is still far from miniaturized, sensitive, inexpensive and low-power muscle sensors.

Join Us


Join a world-leading team working at the forefront of scalable human-machine interfacing

For the appointment, we seek candidates to join the Neuranics Engineering Team with experience in the area of integrated circuits and systems for biomedical and sensing applications, ideally with knowledge of analog, digital or mixed-signal integrated circuit design, including the practical aspects of such circuits, such as chip layout and measurement. Candidates with expertise in ultra-low power hardware realization of signal processing / machine learning / control algorithms for use in smart sensors, including biomedical wearables, will also be considered.

Contact Us


If you'd like to discuss business opportunities or reach our customer and technical support, please fill out the form below so that we can get back to you as soon as possible.

To enquire about how Neuranics could help with your project, complete the enquiry form below and we’ll be get back to you as soon as we can. Alternatively email us at Email: This email address is being protected from spambots. You need JavaScript enabled to view it.and Tel: 0141 330 8762. 

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