IBM’s AI-Enabled Fingernail Sensor Can Monitor Your Health All Day Long

IBM has introduced a wearable device, a tiny fingernail sensor prototype, that can continuously measure the wearer’s grip strength and provide AI-interpreted health indicators to clinicians

IBM’s AI-Enabled Fingernail Sensor Can Monitor Your Health All Day Long

IBM Research has developed a “one-of-a-kind” fingernail sensor prototype that is designed to detect deformation of your fingernail through integrated strain gauges as you go through your daily tasks.

It can detect the subtle changes and stresses your fingernail is subjected to as your grab objects, handwrite, type, open a doorknob, turn a key, and so on, all of which give a sense of your grip strength.

Now, grip strength is a great indicator of a person’s overall health and vitality and can serve as an effective screening tool to assess a broad range of health-related issues.

It can even predict the onset of certain conditions such as Parkinson’s Disease, Alzheimer’s Disease, stroke, and death.

“It’s designed to capture everyday movement by people in their daily lives — whether they are at home, outside, or in a car,” Ajay Royyuru, VP Healthcare and Life Sciences Research at IBM, was quoted by Digital Trends as saying.

“It’s lightweight, wireless, and unobtrusive,” he told the tech and lifestyle website, adding that a team was “working to get the device even smaller, so that it is just a speck on your fingertip.”

He went on to say that grip strength can provide valuable insights “into chronic conditions such as schizophrenia and Parkinson’s Disease.”

He also said: “In one cardiovascular disease study, reduced grip strength was a better predictor of death than blood pressure.”

The data collected by the tiny sensor is assimilated by a small computer, which then transfers information related to the wearer’s grip quality to an AI- and machine learning-enabled smartphone app that can detect tremors, bradykinesia (slowness of movement), and dyskinesia (abnormality or impairment of voluntary movement), all of which are fundamental manifestations of Parkinson’s Disease.

The system will allow clinicians to monitor patients as they go about their day-to-day activities and take necessary action based on AI- and Machine Learning-analysed clues and indicators into the progression of their individual conditions.

Skin-based sensors can be equally effective in capturing motion, muscle health and nerve cells to help clinicians monitor patients, in addition to gauging their emotional state by interpreting changes in sweat gland activity.

However, skin sensors are not particularly suitable for older patients as they are likely to cause infections and other problems.

This is one of the main reasons why IBM Research started exploring the possibilities of harnessing information from subtle bends to the fingernail as we use our hands through the day and analyzing the data through artificial intelligence and machine learning to better understand disease progression in patients.

“Our team realized it might be possible to derive interesting signals from how the fingernail bends throughout the course of a day, as we use our fingers to interact with our environment, and tap into the power of AI and machine learning to analyze and derive valuable insights from that data,” said IBM Research in its Dec 21 press release.

“For example, the data can show us if someone is likely to be performing an activity in their home, activities such as holding and operating everyday objects in the kitchen,” Royyuru told Digital Trend.

He added: “Over time, the A.I. system can not only identify what the actions are, but also detect patterns in the data which could reveal insights about the user.

“[For instance], we could see abnormalities in the data that show someone’s medication is wearing off and tremors are increasing or that grip strength is weakening during certain periods of the day.

“This can help provide insights about disease progression or state of well-being, such as spikes in stress.”

The research paper entitled “Wearable Nail Deformation Sensing for Behavioral and Biomechanical Monitoring and Human-Computer Interaction” was published in the journal ‘Scientific Reports’ on Friday (Dec 21).

Lead author of the paper Katsuyuki Sakuma was assisted in the study by his team of researchers from the IBM Thomas J. Watson Research Center in New York.

“By pushing computation to the end of our fingers we’ve found a new use for our nails by detecting and characterizing their subtle movements,” said the IBM Research press release, concluding that the study “has also served as the inspiration for a new device modeled on the structure of the fingertip that could one day help quadriplegics communicate.”

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