Why the study?
Assessing pain in non-verbal patients is challenging and unreliable, with a notable absence of objective diagnostic tests to aid healthcare practitioners.
Does the fusion of fNIRS measures (ΔHBO2 and ΔHHB) combined with machine learning improve the accuracy of objective pain assessment?
Comparison
Fusion of ΔHBO2 and ΔHHB measures vs independent measures
Authors
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May aid objective pain assessment in non-verbal patients; hypothesis-generating and requires prospective validation before clinical adoption.
Does the fusion of fNIRS measures (ΔHBO2 and ΔHHB) combined with machine learning improve the accuracy of objective pain assessment?
Fusion of fNIRS measures (ΔHBO2 and ΔHHB) with machine learning provides a potential objective biomarker for assessing pain levels, achieving 68.5% accuracy.
Khan et al. (2024) studied this question.
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