Evolution of prosthetics: From ancient Egypt to the use of AI today

The importance of prosthetics for people requiring amputations cannot be understated. Every year, there are 1 million new amputees who have to adapt to a completely different lifestyle. Yet, despite flagship campaigns to make public transportation and infrastructure more friendly for disabled people, only 3% of the buildings in India have improved accessibility. However, even if the world does not provide the necessary support for those with disabilities, advances in prosthetics can help them have a less challenging life.

Evolution of prosthetics

The oldest prosthetics discovered by researchers is a false wooden toe that passed successfully the test of whether it could have been used as a walking aid. They were found along with Egyptian mummies and are around 3000 years old. However, the field of prosthetics has come a long way since these ancient relics.

Currently, prosthetics are available that respond to the user’s thoughts. They can do that by keeping track of electrical impulses between the brain and the target muscles, then interpreting the signal to perform the desired action. However, these prosthetics are limited by the number of brain signals the software can recognise per second and how accurately it interprets the user’s intentions. With new strides in AI and robotics, new prosthetics are being developed and tested with greater capabilities and better real-world applications.

Time for smart prosthetics

Incorporating AI algorithms for building new prosthetics will make use of the vast amounts of data being captured by researchers. With enough available data, these AI-based systems can achieve precision levels previously impossible to attain. Many prototypes have been developed for AI-based upper body prosthetics, with fewer applications made of AI for lower limb prosthetics.

New techniques based on regenerative peripheral nerve interface (RPNI) implanted in upper limbs amplify the generated nerve signals. This allows machine learning algorithms to have a more robust signal source to interpret into actions. Not only are experts trying to develop highly dexterous, precise prosthetics, but some researchers are taking it a step further. They are using machine learning algorithms to allow prosthetic users to have a sense of touch. Researchers want to develop a natural prosthetic device that can feel and respond to the environment.

Image: BBC Science Focus Magazine

The only caveat of using AI is that it substantially increases the cost of prosthetics. Also, there is a substantial time gap between developing a prototype to getting approval for use by the general public. However, hopefully, these limitations will be overcome with the decrease in the cost of electronics and a better pipeline between academia and industry.