Revolutionizing Human-Computer Interaction: Introducing Predictive Touch with AI Smart Skin Spray

Machine learning enables electronic devices, such as electronic gloves and skins, to follow the motion of human hands and carry out operations like gesture and object recognition. These devices can’t bend to the shape of the body and continue to be bulky.

A recent study that was published in the journal Nature describes how scientists have created a novel substance that can be sprayed onto the back of human hands to track their movements.

Source: https://www.nature.com/articles/s41928-022-00888-7

The researchers have created a prototype that can even predictably type with both hands on an invisible keyboard and recognize basic things by touch.

As the hand moves, a tiny electrical network detects the stretching and bending of the skin, which artificial intelligence (AI) then interprets to identify movements.

The nanomesh mimics human cutaneous sensors by converting electrical resistance changes from minute skin strains into proprioception. It is constructed of biocompatible materials and may be directly printed on a person’s hand. Due to its low computing cost and simple user implementation, a single nanomesh can measure finger movements from several joints at once.

The device can adapt to any hand size or shape because it is sprayed on and might be used to recognize sign language or even objects by manually tracing their external surfaces. In the future, it might also be modified to the face to pick up on nuances in emotional cues, opening up new possibilities for computer animation or even virtual meetings.

Additionally, a portable Bluetooth module is linked to transmit such signal changes wirelessly while machine learning analyzes them.

The program learns to recognize the shifting conductivity patterns by mapping them to particular actions and movements. Using a keyboard to type the letter X, for instance. Additionally, after the algorithm has been properly trained, the physical keyboard is no longer required; simple hand motions are sufficient. This scheme is also more efficient compared to existing technologies.

According to the researchers, this technology may be used in various industries, including robotics, telemedicine, sports, and gaming. This technology can bring about a revolution in the industries mentioned above and help in their growth.Ā 


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Rishabh Jain, is a consulting intern at MarktechPost. He is currently pursuing B.tech in computer sciences from IIIT, Hyderabad. He is a Machine Learning enthusiast and has keen interest in Statistical Methods in artificial intelligence and Data analytics. He is passionate about developing better algorithms for AI.

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