IBM Develops Fingernail Sensor That Uses AI to Track Patient Health, Disease Progressions
IBM researchers have developed a first-of-a-kind “fingernail sensor” prototype that uses artificial intelligence and machine learning to monitor and analyse human health as well as disease progression.
The wearable, wireless device continuously measures how a person’s fingernail bends and moves, which is a key indicator of grip strength.
Although skin-based sensors can help capture things like motion, the health of muscles and nerve cells, and can also reflect the intensity of a person’s emotional state, these can often cause problems, including infection with older patients.
But the new system uses signals from the fingernail bends such as the tactile sensing of pressure, temperature, surface textures.
“Our fingernails deform – bend and move – in stereotypic ways when we use them for gripping, grasping, and even flexing and extending our fingers. This deformation is usually on the order of single digit microns and not visible to the naked eye,” said Katsuyuki Sakuma, from IBM’s Thomas J. Watson Research Center in New York.
The watch also runs machine learning models to rate bradykinesia, tremor, and dyskinesia which are all symptoms of Parkinson’s disease.
“By pushing computation to the end of our fingers, we’ve found a new use for our nails by detecting and characterising their subtle movements,” Sakuma said.
“With the sensor, we can derive health state insights and enable a new type of user interface. This work has also served as the inspiration for a new device modelled on the structure of the fingertip that could one day help quadriplegics communicate,” Sakuma noted.