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Sensors to monitor health!

The device continuously measures how a person's fingernail bends and moves, which is a key indicator of grip strength.

In an attempt to introduce an innovation in medical field, IBM has developed a small sensor that sits on a person's fingernail to help monitor the effectiveness of drugs used to combat the symptoms of different diseases.

The working of the fingernail sensor has been designed in accordance with grip strength, which according to the researchers is a useful metric in a broad set of health issues like the effectiveness of medication in individuals with Parkinson's disease, the degree of cognitive function in schizophrenics and regarding the state of an individual's cardiovascular health.

The wearable, wireless device continuously measures how a person's fingernail bends and moves, which is a key indicator of grip strength. According to the company the sensor has been developed keeping in mind the people with Parkinson's disease. However the attempt to capture the medication state of such people is a challenging task as majority of people with Parkinson's are older and have increasingly brittle and friable skin. Therefore, at times, it is difficult to quantify the capacity of the sensor.

The researchers say, “We interact with objects throughout the day using our hands, such as the tactile sensing of pressure, temperature, surface textures and more. Our team realised 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.” The sensor is glued to the nail as fingernails are pretty tough and there is very little risk in doing so, especially when compared to a sensor that would sit on the skin.

The sensor then talks to a smart watch that runs machine learning models to detect tremors and other symptoms of Parkinson's disease. Though there is no word on when this sensor could make it onto the market, the team hopes that it can extend this prototype and the models that analyse the data to recognize other diseases as well can be introduced in near future.

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