June 6, 2023
Tokyo Medical and Dental University
Keio University
Key Points
For cervical myelopathy, early detection and appropriate intervention are crucial for improving prognosis, and the development of a simple and accurate screening method has been long-awaited.
By recording and analyzing finger movements with a smartphone camera, patients with cervical myelopathy could be identified with very high accuracy.
The goal is to build a system that can be used even in environments without medical specialists, such as in daily life, creating opportunities for early disease detection.
A research group led by Lecturer Koji Fujita and Assistant Professor Takuya Ihara of the Department of Motor Function and Morphology, 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 disease screening and severity estimation of cervical myelopathy using a smartphone. In this study, a simple motion of repeatedly opening and closing the fingers is video-recorded on a smartphone placed on a desk, and a machine learning algorithm estimates the presence and severity of the disease. This research was conducted with support from JSPS KAKENHI, the AIP Acceleration PRISM Research Program, and the JST Strategic Basic Research Programs PRESTO, and its results were published in the online edition of the international scientific journal Digital Health on June 6, 2023.
For the full press release, please see below.