Towards PPG-based anger detection for emotion regulation.
Tuck-Voon How, Robin E A Green, Alex Mihailidis
PMID 37582733WHAT IT FOUND
A smartwatch sensor failed to reliably detect anger in people with and without brain injury.
The signal varied too much day-to-day and person-to-person, making it an unreliable standalone marker for predicting emotional outbursts in a clinical setting.
Key findings
01An anger detection model using only PPG data achieved 56.8% mean accuracy, which the authors describe as only marginally better than chance.
02PPG signal characteristics were dominated by individual differences and day-to-day variations rather than emotional state, making the signal non-stationary.
03While anger could be separated from non-anger within single sessions for most participants, the specific features used for this separation changed drastically between days.
STILL TO COME
How it was doneWhat they found
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What it does not show
The study only included 32 participants, with just 10 having a traumatic brain injury. Data was collected in a laboratory setting, which may not reflect the complexity of real-world environments. The study used a binary view of anger (anger vs. non-anger), ignoring the intensity or different types of anger. Participants were selected for a propensity to anger but did not necessarily have severe anger dyscontrol. The study did not control for factors like skin tone, body mass, or sensor placement tightness, which can affect PPG signals.
Declared interests
The study was funded by the Canadian Institutes of Health Research. No other conflicts of interest are reported in the provided text.
The easy way to misread this
Do not interpret the 56.8% accuracy as evidence that smartwatches can detect anger. This figure is only slightly better than random guessing, and the model failed to improve on the baseline for detecting the specific risk event of anger. The technology is not ready for clinical use.