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Cybernetics and Upper-Limb Prosthesis: affordable cyborg based augmentation between man and the machine

The hand of a robot pointing an index finger

Cybernetics is the study of automatic control and information exchange between machines and living things. New research looks at how a prosthesis control interface reads an amputees residual limb motion intent signal. The interface then translates the intent and converts it into a trigger to move a bionic limb.

My colleagues and I are in the early stages of our research to develop affordable bionic limbs. In this article we’ll look at the early stage of our research and why there is a need for artificial limbs.

But first, let’s consider what we mean by ‘Cybernetics’. We all think of movie depictions when we think of cybernetics. The word ‘Cybernetics’ has roots in Greek, κυβερνήτης (kybernētēs) and means “the art of steering”. We take inspiration from living things to create machines to do similar jobs for us. The term ‘cyborg’ could be said to be a living organism who has a bionic body part. For example, someone in an accident who loses an arm could have a bionic arm. The bionic arm responds to inputs from the brain and muscle, which enables them to have a functioning arm.

The need for prosthesis is driven by the staggering worldwide amputation statistics. Statistics from over the last 20 years show that countries such as Vietnam, Cambodia, Angola, Mozambique and Uganda reported high numbers of amputations.

Amputation statistics across the last 20 years

*The rehabilitation of the amputee in the developing world: A review of the literature: T. B. Staats *The rehabilitation of the amputee in the developing world: A review of the literature: T. B. Staats

The main causes in developing countries include accidents, landmines, leprosy and snakebites. In developed countries, factors such as disease of the blood vessels (diabetes) and trauma are the key causes of amputations. Although upper-limb amputees account for a small proportion of the world’s total amputations, they have high functional needs as the loss of an upper-limb affects an individual’s ability to work and live independently.

Combined statistics between the UK and Italy suggest that above elbow amputees (transhumeral) are the largest group of upper-limb amputees, but despite this, it has been difficult to design bionic limbs for transhumeral amputees. This is because it is so difficult to interpret signals from the brain once they have reached this part of the body.

My colleagues and I are working on a prosthesis control interface that uses affordable sensors and advanced signal processing with Artificial Intelligence. In order to control a prosthesis arm, the procedure is to take signals sent from the brain, to the muscle and made them into a respective movement. Electromyography (EMG) involves sensing electrical signals sent from the brain to muscles, in order to produce different movements. These signals are often referred to as neuromuscular signals and EMG is capable of recording these signals directly from the muscle contracting. The EMG armband (from Thalmic labs), is a low cost sensor that can pick up the electrical signals in the upper arm.

We collected data from 12 non-amputees, who wore the armband while making several gestures, and recorded the bio-electrical signals. The signals are complex and highly variable, and so need advanced signal processing in order to better describe what the signal is. We then use Artificial Intelligence (AI) to match signals to hand gestures. This part of the prosthesis is known as the Man-Machine interface. One of the most successful type of AI used was Artificial Neural Networks, which are structured much like the cells in the human brain. A flow diagram of the process can be seen below.

*Abstraction of the Signal Processing and AI Classifier Training Phase *Abstraction of the Signal Processing and AI Classifier Training Phase

We have found that by using cheap and affordable sensors, that around 80% of the time, it is possible to recognise eight different hand gestures. The next phase of our research will be to test how good gesture recognition approach is on a group of upper-limb amputees.

Although this is early days for our research, the development of affordable bionic limbs for amputees will be life changing for thousands of people. Particularly in developing countries limited by technology and finance. We look forward to giving an update on our research in a future issue of Catalyst.

Cybernetics – (Greek) kybernētēs: the art of steering
Cyborg – a Cybernetic Organism possessing both organic and bio-mechatronic(Engineered) body parts
Prosthesis – an artificial body part
Tranhumeral – above elbow amputees
Signal Processing – process of analysing an acquired signal using mathematic algorithms
Neuromuscular – link between brain-muscle that produces movement

References – the author has used the following references in his research project.
Cybernetics or Control and Communication in the Animal and the Machine by Norbert Wiener. ISBN: 9780262537841
Carvalko, Joseph (2012). The Techno-human Shell-A Jump in the Evolutionary Gap. Sunbury Press. ISBN 978-1-62006-165-7
The rehabilitation of the amputee in the developing world: A review of the literature, T. B. Staats
‘Limbless Statistics’,
Cordella, F., Ciancio, A. L., Sacchetti, R., et al.: ‘Literature review on needs of upper limb prosthesis users,’ Front. Neurosci., 2016, 10: 209 doi: 10.3389/fnins.2016.00209
Gesture Recognition for Trans-humeral Prosthesis Control Using EMG and NIR by Ejay Nsugbe ; Carol Phillips ; Mike Fraser ; Jess Mcintosh IET Cyber-Systems and Robotics, 14pp. DOI: 10.1049/iet-csr.2020.0008
‘Myo Blog’
Guo, W., Sheng, X., Liu, H., et al.: ‘Development of a Multi-Channel Compact-Size Wireless Hybrid sEMG/NIRS Sensor System for Prosthetic Manipulation,’ IEEE Sens. J., 2016, 16, pp. 447-456

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Dr Ejay Nsugbe
Independent Researcher in Man-Machine Augmentation

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