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The Potential of Cognitive Circles to Measure Mental Load

Talkat UIST 2025 · 2025-09-28..10-01· [machine-learning]
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Finger kinematics from tracing circles on a tablet while doing arithmetic, reading, or spatial tasks predict task difficulty: 40 participants yield 240 two‑minute series for training and 8 participants 48 series for testing. Features include X/Y, velocity, acceleration and angular velocity; models tested: LSTM on raw series, Random Forest on channel means and MiniRocket, and MobileNet on trace images. Results show 75% average accuracy, up to 94% for spatial reasoning and near 50% for reading, so per‑task calibration is required.

AI-written summary · about

  1. 0:00Introduction to cognitive circles
  2. 1:48Traditional workload measurement methods
  3. 3:13Experiment design and task types
  4. 6:49Data representations and models
  5. 7:51Results and accuracy findings
  6. 9:14Implications for HCI and future work
  7. 10:40Q&A: Model transferability
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