Detecting for carpal tunnel syndrome with a smartphone game: Early diagnosis enabled by identifying syndrome based on thumb movements through machine leaning – Science Daily

A Japanese research group combined motion analysis that uses smartphone application and machine learning that uses an anomaly detection method, thereby developing a technique to easily screen for carpal tunnel syndrome. Carpal tunnel syndrome is common amongst middle-aged women. The disease causes compressed nerves in the wrist, causing numbness and difficulty with finger movements. While an accurate diagnosis can be reached with nerve conduction study, this is not widely used because it requires…

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