Measuring and modeling muscle activation evoked by attention

2021 Fiscal Year Final Research Report

• Project/Area Number: 19K22872
• Research Category: Grant-in-Aid for Challenging Research (Exploratory)
• Allocation Type: Multi-year Fund
• Review Section: Medium-sized Section 61:Human informatics and related fields
• Research Institution: Kyoto University
• Principal Investigator: NAKAMURA YUICHI 京都大学, 学術情報メディアセンター, 教授 (40227947)
• Project Period (FY): 2019-06-28 – 2022-03-31
• Keywords: 注意 / 筋活動 / 注意分配・分割 / 注意による筋活動の変容 / 筋シナジー

Outline of Final Research Achievements

We analyzed the relationship between attention and motions, and investigated inverse problem of estimating attention state from observed motions. We focused on motions around the neck because behaviors for paying attention are often appear on neck and head motions. Through the analyses, we obtained the result that turning around motions, i.e., head rotations, are composed of three muscle synergies for each orientation; the spatial patterns are common among different attention conditions, and the temporal patters are significantly different among attention conditions. Wavelet coherence showed the spatio-temporal patterns of muscle activation are also significantly different among attention conditions. We also investigated muscle synergies are relatively stable over some period, e.g., two weeks. Those results suggest that we can rely on the analyses of muscle synergy and spatio-temporal characteristics for estimating attention states.

Free Research Field

ユーザインタフェース

Academic Significance and Societal Importance of the Research Achievements

注意の状態が動作中の筋協調の発現やその時間的変化に顕著に現れることが確認できた．これらは注意に対する(残存)能力や個人的な特性を測るために筋活動を利用する具体的な方法を提案する新しい知見ととなっている．さらに，「注意を払う動作」が行われていることを別の人が知覚するための，動作の伝達方法やその性能について設計や調査を行った．これらの将来的な応用として，注意状態やその能力の推定があげられるが，それだけでなく，見守りなどへの応用の可能性について確認することができた．