Application of the Single Source-Detector Separation Algorithm in Wearable Neuroimaging Devices: A Step toward Miniaturized Biosensor for Hypoxia Detection.

Most currently available wearable devices to noninvasively detect hypoxia use the spatially resolved spectroscopy (SRS) method to calculate cerebral tissue oxygen saturation (StO 2 ). This study applies the single source-detector separation (SSDS) algorithm to calculate StO 2 . Near-infrared spectroscopy (NIRS) data were collected from 26 healthy adult volunteers during a breath-holding task using a wearable NIRS device, which included two source-detector separations (SDSs). These data were used to derive oxyhemoglobin (HbO) change and StO 2 . In the group analysis, both HbO change and StO 2 exhibited significant change during a breath-holding task. Specifically, they initially decreased to minimums at around 10 s and then steadily increased to maximums, which were significantly greater than baseline levels, at 25-30 s ( p -HbO < 0.001 and p -StO 2 < 0.05). However, at an individual level, the SRS method failed to detect changes in cerebral StO 2 in response to a short breath-holding task. Furthermore, the SSDS algorithm is more robust than the SRS method in quantifying change in cerebral StO 2 in response to a breath-holding task. In conclusion, these findings have demonstrated the potential use of the SSDS algorithm in developing a miniaturized wearable biosensor to monitor cerebral StO 2 and detect cerebral hypoxia.