Development of an artificial intelligent (AI)-based auto-spirometry system

2023 Fiscal Year Final Research Report

• Project/Area Number: 20K12066
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Review Section: Basic Section 62010:Life, health and medical informatics-related
• Research Institution: Iwate Medical University
• Principal Investigator: Suwabe Akira 岩手医科大学, 医学部, 教授 (20241713)
• Project Period (FY): 2020-04-01 – 2024-03-31
• Keywords: 呼吸機能検査 / 人工知能 / 臨床検査技師 / 新型コロナウイルス感染症

Outline of Final Research Achievements

This study was designed to establish the respiratory test system in which the patients undergo the spirometry by themselves under a video- and voice-assist by AI-mounted robot (Unibo), in order to optimize the respiratory function tests and protect the laboratory technicians from Covid 19. Fifty volunteers who had a medical check in Ningen Dock in our university hospital were subjected to this study. As results, the respiratory function test results in this system were not inferior compared to those obtained under assists by medical technicians. However, since several problems, such as monitor indistinct or perplexed explanation, were pointed out, further improvements were required to utilize this system in clinical practice.

Free Research Field

臨床検査医学

Academic Significance and Societal Importance of the Research Achievements

病院における呼吸機能検査は、人手と時間がかかり、かつ熟練した技師を配置する必要があることから、検査部運営の効率化にとって大きな障害となっていた。さらに、2020年から全世界で新型コロナウイルス感染症が蔓延し、潜在的なコロナ陽性患者が呼出努力を伴う呼吸機能検査を行うことで担当の検査技師が感染のリスクに曝されるという問題が生じてきた。本研究の成果として、呼吸機能検査を本システムにより患者自らが行うことで、技師の負担軽減や感染対策に役立つ可能性が示された点で学術的意義がある。
また、医療スタッフ不足が社会的問題となっている昨今において、医療崩壊に対する解決の糸口が示された点で社会的意義も高い。