When Wellness Stress Detection Enters Healthcare Workflows: An Iso-Heart-Rate, Cross-Corpus Evaluation of Wrist Wearables.

Background/

Objectives

Benchmark performance does not establish that a wrist-wearable stress measure is valid in healthcare workflows. We tested whether binary stress-versus-non-stress performance reflects stress-specific physiology rather than heart-rate (HR) arousal, as well as whether models generalize from wellness-like corpora to a clinical workforce context.

Methods

We analyzed three public wrist Empatica E4 corpora: Wearable Stress and Affect Detection (WESAD), Stress-Predict, and a real-world Nurse dataset. An iso-heart-rate (iso-HR) evaluation balanced the HR within subjects before measuring non-cardiac discriminability. We compared a continuous skin conductance response (SCR) count with logistic regression, gradient boosting, four unsupervised domain-adaptation methods, and an accelerometer context-aware variant, under leave-one-subject-out and leave-one-dataset-out evaluation with subject-cluster bootstrap intervals.

Results

The single SCR score was statistically indistinguishable from logistic regression in paired cross-corpus tests, and no adaptation method moved a weak corpus into a usable range: across all evaluated models, the transfer area under the receiver operating characteristic curve (AUROC) was approximately 0.90 with WESAD as the target but 0.52-0.57 with Stress-Predict or Nurse. Adding activity context raised the within-corpus AUROC yet lowered cross-corpus transfer, because the movement-stress association reverses across protocols. On Nurse, source-trained models reached AUROC 0.541-0.559 against prevalence 0.796 with poor calibration, and conditioning on movement or on distance to the source distribution removed the residual discrimination. Iso-HR evidence was diagnostic mainly in WESAD.

Conclusions

Neither shallow unsupervised adaptation nor wrist activity context established reliable transfer to Nurse, and sparse retrospective labels prevent attributing this solely to physiological non-transfer. Cross-corpus and iso-HR controls, not model complexity, determine what can be concluded for healthcare workflows.