Evaluating Brain Flow Index from a temple-worn wearable against depth-resolved time-domain NIRS during head-down tilt and postural transitions in healthy young men

The significance of the study lies in the potential of wearable optical sensors to enable continuous cerebral hemodynamic monitoring in everyday life. However, since any surface head sensor also captures extracerebral tissue, it is crucial to ascertain the relevance of the observed cerebral activity. This study aimed to determine if the Temple Brain Flow Index (Temple-BF), obtained from a temple-worn photoplethysmographic wearable, exhibited stronger correlation with the deeper cerebral hemodynamics compared to the superficial scalp hemodynamics.

To achieve this, the researchers analyzed 60 sessions from 44 healthy young adult men, each undergoing three physiological challenges: 30-degree head-down tilt, stand-to-squat, and stand-to-supine transitions. The time-domain near-infrared spectroscopy (TD-NIRS) system was used to obtain optical density and mean time of flight data. This data was then inverted using a Monte Carlo-derived two-layer model to derive scalp- and brain-layer hemoglobin time series.

The Temple-BF was then compared with these model-derived signals using various statistical measures. The median lag-adjusted correlations between Temple-BF and the brain-layer deltaHbO traces were found to be significantly higher (0.912, 0.843, and 0.839) for head-down tilt, stand-to-squat, and stand-to-supine transitions, respectively, compared to the scalp-layer medians (0.494, 0.700, and 0.767).

The paired brain-minus-scalp differences were also significant for the head-down tilt challenge (median 0.333, p-value < 0.05), suggesting that the Temple-BF more accurately reflects the deeper cerebral hemodynamics than the superficial scalp hemodynamics.