June 30, 2023
Tokyo Medical and Dental University (TMDU)
Keio University
Key Points
We have developed a technology for the early diagnosis of cervical myelopathy, a condition for which diagnosis and treatment are often delayed due to a lack of early symptoms, by analyzing the everyday act of "writing" using artificial intelligence.
By analyzing hand movements while tracing simple shapes displayed on the screen of a commercial tablet device, we were able to determine the presence or absence of cervical myelopathy with high accuracy.
This is expected to lead to disease screening through unconscious movements in daily life, contributing to early detection and treatment.
A research group led by Lecturer Koji Fujita of the Department of Functional Morphology of Locomotor Organ and graduate student Eriku Yamada of the Department of Orthopaedic Surgery, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, in a joint study with a group led by Associate Professor Yuta Sugiura of the Department of Information and Computer Science, Faculty of Science and Technology, Keio University, has demonstrated the potential for screening for cervical myelopathy by focusing on the act of writing. In this study, hand movements are recorded while tracing simple shapes displayed on a tablet device, and a machine learning algorithm estimates the presence or absence of the disease. This research was conducted with support from JSPS KAKENHI, JST PRESTO (Precursory Research for Embryonic Science and Technology), the Foundation for Research in Orthopaedic and Traumatologic Surgery, and the National Mutual Insurance Federation of Agricultural Cooperatives. The research findings were published online in the international scientific journal Scientific Reports on June 20, 2023.
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