Traditional methods, such as the Glasgow Coma Scale (GCS), are prone to errors and subjective interpretations, while imaging techniques require specialised infrastructure, trained personnel and are cost-intensive. To address this issue, CEREBO, a portable, non-invasive brain injury diagnostic tool, has been developed using advanced near-infrared spectroscopy technology powered by machine learning.