Abstract

Muscle pH is an important indicator of inadequate blood flow and available oxygen. Muscle pH can be used to triage and help treat trauma victims and indicate poor peripheral blood flow in diabetic patients. Muscle pH can also be used to indicate exercise intensity and fatigue. We have developed methods to non-invasively measure muscle pH using Near-Infrared Spectroscopy (NIRS) and Partial Least Squares (PLS) analysis. A multi-subject PLS model correlating near infrared tissue spectra, acquired from healthy subjects during repetitive hand-grip exercise, to invasive tissue pH measurements, has been developed and validated. Subject related variations in the spectral signal; impede the development of viable multi-subject model. Within-subject variations in tissue NIR spectra often result from uncontrolled motion or blood volume changes during exercise, while subject-to-subject variations arise from differences in skin pigmentation and the fat layer thickness. We have developed signal processing techniques to account for these mitigating factors. By incorporating this signal processing techniques with PLS calibration, we can generate a pH model that has a relative standard error of prediction of 1.7%

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