Wearable Lactate Threshold Predicting Device is Valid and Reliable in Runners :

Near infrared spectroscopy (NIRS) is becoming a widely used research instrument to measure tissue oxygen (O2) status non-invasively. Continuous-wave spectrometers are the most commonly used devices, which provide semi-quantitative changes in oxygenated and deoxygenated hemoglobin in small blood vessels (arterioles, capillaries and venules). Refinement of NIRS hardware and the algorithms used to deconvolute the light absorption signal have improved the resolution and validity of cytochrome oxidase measurements. NIRS has been applied to measure oxygenation in a variety of tissues including muscle, brain and connective tissue, and more recently it has been used in the clinical setting to assess circulatory and metabolic abnormalities. Quantitative measures of blood flow are also possible using NIRS and a light-absorbing tracer, which can be applied to evaluate circulatory responses to exercise along with the assessment of tissue O2 saturation. The venular O2 saturation can be estimated with NIRS by applying venous occlusion and measuring changes in oxygenated vs. total hemoglobin. These various measurements provide the opportunity to evaluate several important metabolic and circulatory patterns in very localized regions of tissue and may be fruitful in the study of occupational syndromes and a variety of diseases.

Three portable blood lactate analysers, Lactate Pro (LP), Lactate Scout (LS) and Lactate Plus (L(+)), were evaluated. Analyser reliability and accuracy was assessed. For reliability, intra- and inter-analyser comparisons demonstrated that the LP (intra-TE = 0.5 mM, inter-TE = 0.4 mM) and L(+) (intra-TE = 0.4, inter-TE = 0.4 mM) displayed greater overall reliability than the LS (intra-TE = 1.0, inter-TE = 0.8 mM). At BLa 8.0 mM, the LP (intra-TE = 0.5 mM, inter-TE = 0.4 mM) and L(+) (intra- and inter-TE = 0.4 mM) displayed greater reliability than the LS (intra-TE = 1.1 mM, inter-TE = 0.9 mM). For accuracy, the L(+) (SEE = 0.6 mM) compared more favourably to the LP than the LS (SEE = 1.1 mM). At BLa approximately 1.0-18.0 mM, the LS produced values that were up to 0.9 mM higher than the LP; the L(+) produced BLa that were within +/-0.1 mM. All portable analysers tended to under-read the ABL 700 analyser. The suitability of the LP and L(+) as accurate analysers is supported by strong correlations (r = 0.91 and r = 0.94) and limits of agreement

Near infrared spectroscopy (NIRS) is rapidly gaining popularity for functional brain imaging. It is well suited to studies of patients or children; however, in these populations particularly, motion artifacts can present a problem. Here, we propose the use of imaging channels with negligible distance between light source and detector to detect subject motion, without the need for an additional motion sensor. Datasets containing deliberate motion artifacts were obtained from three subjects. Motion artifacts could be detected in the signal from the co-located channels with a minimum sensitivity of 0.75 and specificity of 0.98. Five techniques for removing motion artifact from the functional signals were compared, namely two-input recursive least squares (RLS) adaptive filtering, wavelet-based filtering, independent component analysis (ICA), and two-channel and multiple-channel regression. In most datasets, the median change in SNR across all channels was the greatest using ICA or multiple-channel regression. RLS adaptive filtering produced the smallest increase in SNR. Where sharp spikes were present, wavelet filtering produced the largest SNR increase. ICA and multiple-channel regression are promising ways to reduce motion artifact in functional NIRS without requiring time-consuming manual techniques.