Human factor engineering of point-of-care near infrared spectroscopy device for intracranial hemorrhage detection in Traumatic Brain Injury: A multi-center comparative study using a hybrid methodology.

ABSTRACT

OBJECTIVE: This study assessed machine learning powered Near-infrared spectroscopy based (mNIRS) device's usability and human factor ergonomics in four distinct healthcare provider groups. BACKGROUND: Traumatic Brain Injury (TBI) is a global concern with significant well-being implications. Timely intracranial hemorrhage (ICH) detection is crucial. mNIRS offers efficient non-invasive TBI screening. METHODS: Two device utilization stages involved operators (N = 21) and TBI-suspected subjects (n = 120). A hybrid approach used qualitative and quantitative methods, utilizing a 57-item survey and task completion time. RESULTS: All groups positively perceived user-interface, physical, cognitive, and organizational ergonomics. The device's ease of use, calibration, size, cognitive support, and integration gained appreciation. Training reduced task completion time from 16.5 to 13.2 s. CONCLUSION: mNIRS-based CEREBO® proves usable for TBI point-of-care assessment. Positive feedback from diverse healthcare groups validates design and cost-effectiveness alignment. A hybrid approach, training, and practice scans enhance usage and experience.