RGBカメラを用いた頚髄症スクリーニング手法の提案

• Item type: SIG Technical Reports(1)
• 公開日: 2021-10-21
• タイトル: RGBカメラを用いた頚髄症スクリーニング手法の提案
• タイトル / 言語: en
• タイトル: A Screening Method for Cervical Myelopathy Using a Camera
• 言語: jpn
• キーワード / 主題Scheme: Other
• キーワード / 主題: 計測・認証
• 資源タイプ / 資源タイプ識別子: http://purl.org/coar/resource_type/c_18gh
• 資源タイプ: technical report
• 著者所属: 慶應義塾大学大学院理工学研究科
• 著者所属: 東京医科歯科大学大学院医歯学総合研究科
• 著者所属: 東京医科歯科大学大学院医歯学総合研究科
• 著者所属: 慶應義塾大学大学院理工学研究科
• 著者所属: 慶應義塾大学大学院理工学研究科
• 著者所属(英): en
• 著者所属(英): Graduate School of Science and Technology, Keio University
• 著者所属(英): en
• 著者所属(英): Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University
• 著者所属(英): en
• 著者所属(英): Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University
• 著者所属(英): en
• 著者所属(英): Graduate School of Science and Technology, Keio University
• 著者所属(英): en
• 著者所属(英): Graduate School of Science and Technology, Keio University
• 著者名: 松井, 良太; 小山, 恭史; 藤田, 浩二; 斎藤, 英雄; 杉浦, 裕太
• 著者名(英): Ryota, Matsu; Takafumi, Koyama; Koji, Fujita; Hideo, Saito; Yuta, Sugiura
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: Cervical myelopathy (CM) is a pathology caused by cervical spinal cord compression. Spinal surgeons often use the 10-sec grip and release (G&R) test to screen hand disorders, a typical symptom of CM. We propose a screening method for CM based on videos of the G&R test and machine learning. Each patient holds their hand above a smartphone to record the G&R movement as a video with the built-in camera. We use an image-processing framework to obtain feature values of the hand movement. A support vector machine classifier estimates if these feature values suggest any characteristics of CM patients. We conducted a user experiment on 20 CM patients and 15 controls to evaluate our method. As a result, sensitivity, specificity, and area under the curve were 90.0%, 93.3%, and 0.947, respectively. This performance is higher than the conventional methods.; Cervical myelopathy (CM) is a pathology caused by cervical spinal cord compression. Spinal surgeons often use the 10-sec grip and release (G&R) test to screen hand disorders, a typical symptom of CM. We propose a screening method for CM based on videos of the G&R test and ma- chine learning. Each patient holds their hand above a smartphone to record the G&R movement as a video with the built-in camera. We use an image-processing framework to obtain feature values of the hand movement. A support vector machine classifier estimates if these feature values suggest any characteristics of CM patients. We conducted a user experiment on 20 CM patients and 15 controls to evaluate our method. As a result, sensitivity, specificity, and area under the curve were 90.0%, 93.3%, and 0.947, respectively. This performance is higher than the conventional methods.
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: Cervical myelopathy (CM) is a pathology caused by cervical spinal cord compression. Spinal surgeons often use the 10-sec grip and release (G&R) test to screen hand disorders, a typical symptom of CM. We propose a screening method for CM based on videos of the G&R test and machine learning. Each patient holds their hand above a smartphone to record the G&R movement as a video with the built-in camera. We use an image-processing framework to obtain feature values of the hand movement. A support vector machine classifier estimates if these feature values suggest any characteristics of CM patients. We conducted a user experiment on 20 CM patients and 15 controls to evaluate our method. As a result, sensitivity, specificity, and area under the curve were 90.0%, 93.3%, and 0.947, respectively. This performance is higher than the conventional methods.; Cervical myelopathy (CM) is a pathology caused by cervical spinal cord compression. Spinal surgeons often use the 10-sec grip and release (G&R) test to screen hand disorders, a typical symptom of CM. We propose a screening method for CM based on videos of the G&R test and ma- chine learning. Each patient holds their hand above a smartphone to record the G&R movement as a video with the built-in camera. We use an image-processing framework to obtain feature values of the hand movement. A support vector machine classifier estimates if these feature values suggest any characteristics of CM patients. We conducted a user experiment on 20 CM patients and 15 controls to evaluate our method. As a result, sensitivity, specificity, and area under the curve were 90.0%, 93.3%, and 0.947, respectively. This performance is higher than the conventional methods.
• 書誌レコードID / 収録物識別子タイプ: NCID
• 書誌レコードID / 収録物識別子: AA12049625
• 書誌情報: 研究報告エンタテインメントコンピューティング（EC）; 巻 2021-EC-61, 号 6, p. 1-4, 発行日 2021-10-21
• ISSN / 収録物識別子タイプ: ISSN
• ISSN / 収録物識別子: 2188-8914
• Notice: SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc.
• 出版者 / 言語: ja
• 出版者: 情報処理学会