Generalised machine learning models outperform personalised models for cognitive load classification in real-life settings
Christoph Anders; Ipsita Bhaduri; Bert Arnrich · 2025 · Frontiers in Digital Health
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract (excerpt)
Introduction By issuing work-break reminders, for example, personal assistants for cognitive load could be beneficial in maintaining health and life satisfaction in society. Wearable sensors facilitate the necessary real-time collection of…
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WASTE indexes this work — it does not host or republish it. Failure-type classification is automated and approximate.
Metadata source: Crossref · DOI 10.3389/fdgth.2025.1650085