Flow, an optimal mental state merging action and awareness, significantly impacts performance, emotion and wellbeing in real-world contexts. However, capturing its fluctuations on a sub-minute timescale is challenging due to the sparsity of the existing flow measuring tools. Here we present a virtual reality fine fingertip force control (F3C) task to induce flow, wherein the task challenge is set at a compatible level with personal skill, and to track the flow fluctuations from the synchronous force control performance. We extract eight performance metrics from the fingertip force sequence and reveal their significant differences under distinct flow states. Further, we built a flow decoder and demonstrated that the flow variations can be decoded using selected metrics. The predicted values reach significant correlation with the self-reported flow intensity (r=0.81). This study showcases the feasibility of tracking intrinsic flow variations with high temporal resolution using task performance measures.

翻译：心流，一种将行动与意识融为一体的最佳心理状态，在现实情境中显著影响表现、情绪及幸福感。然而，由于现有心流测量工具的稀疏性，捕捉其在亚分钟时间尺度上的波动极具挑战性。本文提出一项虚拟现实指尖精细力控（F3C）任务，通过将任务挑战设定在与个人技能相匹配的水平上诱发心流，并基于同步的力控表现追踪心流波动。我们从指尖施力序列中提取了八项表现指标，揭示了不同心流状态下这些指标的显著差异。进而构建了一个心流解码器，证明可利用选定指标解码心流变化。预测值与自报告心流强度达到显著相关（r=0.81）。本研究展示了利用任务表现测量以高时间分辨率追踪内在心流波动的可行性。