Abstract: The disclosed method includes generating first waveform data using near-infrared spectroscopy (NIRS) to measure at least one light-based signal in a plurality of patients, wherein each waveform of the plurality of waveforms of the first waveform data is associated with at least one blood attribute. The method also includes training a machine learning model based on the first waveform data to produce a trained machine learning model. The method further includes generating second waveform data using NIRS to measure at least one light-based signal in a patient. The method further includes determining an estimated ICP in the patient based on the trained machine learning model. Determining the estimated ICP includes inputting the second waveform data to the trained machine learning model and generating an output from the trained machine learning model including the estimated ICP based on a shape feature of a waveform of the second waveform data.