Development of a Reaction Time Measurement Tool Using AI-Based Skeleton Estimation for Collision Avoidance in the Visually Impaired

• Item type: SIG Technical Reports(1)
• 公開日: 2024-12-16
• タイトル: Development of a Reaction Time Measurement Tool Using AI-Based Skeleton Estimation for Collision Avoidance in the Visually Impaired
• タイトル / 言語: en
• タイトル: Development of a Reaction Time Measurement Tool Using AI-Based Skeleton Estimation for Collision Avoidance in the Visually Impaired
• 言語: eng
• キーワード / 主題Scheme: Other
• キーワード / 主題: セッション4
• 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: Gunma Paz University Graduate School of Health Sciences
• 著者所属(英): en
• 著者所属(英): Gunma Paz University Graduate School of Health Sciences
• 著者名: Akira, Kimura
• 著者名(英): Akira, Kimura
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: This study developed an AI-based skeleton estimation program to help visually impaired individuals avoid collisions by providing adequate reaction time. To evaluate the device's effectiveness, baseline reaction times were measured via stimulus-response tasks. Ten visually impaired participants from Gunma Prefecture responded to a recruitment notice and participated in the study. Key measurements included the time from electrical stimulation to collision avoidance reaction and the time to return to an initial posture. A Python-based program was used to process video data, extract coordinates, and record response times. Results showed that, upon detecting an approaching person at a 2-meter distance, the average reaction time was 1.6(0.8) seconds, and the time for posture recovery was 2.8(2.7) seconds. These findings suggest that AI-based skeleton estimation can support future development of safety devices, enhancing independence for visually impaired individuals in real-world settings.
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: This study developed an AI-based skeleton estimation program to help visually impaired individuals avoid collisions by providing adequate reaction time. To evaluate the device's effectiveness, baseline reaction times were measured via stimulus-response tasks. Ten visually impaired participants from Gunma Prefecture responded to a recruitment notice and participated in the study. Key measurements included the time from electrical stimulation to collision avoidance reaction and the time to return to an initial posture. A Python-based program was used to process video data, extract coordinates, and record response times. Results showed that, upon detecting an approaching person at a 2-meter distance, the average reaction time was 1.6(0.8) seconds, and the time for posture recovery was 2.8(2.7) seconds. These findings suggest that AI-based skeleton estimation can support future development of safety devices, enhancing independence for visually impaired individuals in real-world settings.
• 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: AA12752949
• 書誌情報: 研究報告アクセシビリティ（AAC）; 巻 2024-AAC-26, 号 10, p. 1-5, 発行日 2024-12-16
• ISSN / 収録物識別子タイプ: ISSN
• ISSN / 収録物識別子: 2432-2431
• 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