# Intra-Reliability of a Wearable Near-Infrared Sensor for Monitoring the Intensity of Exercise
## 2 Materials and Methods
### Statistical Analysis  
The IBM SPSS statistical software (v.23., SPSS Inc., Chicago, IL, USA) was used for data analysis. The results were presented as mean and confidence intervals (95% CI) where appropriate. The Shapiro-Wilk test was used to evaluate normal data distribution, while homogeneity of variance was analyzed by [PERSON]'s test. A repeated-measure ANOVA (within-within-subjects ANOVA) was used, with the session (Test 1/Test 2) and workload (50/100/150/200/250 W) as within factors. A Bonferroni post hoc test was performed when a significant F ratio value was obtained. For significant differences to estimate the meaningfulness, the effect size was calculated as eta-square (n\({}^{2}\)) with small, medium, and large effect sizes classified as 0.01, 0.06, and 0.14, respectively [21]. The Bland-Altman plot analysis was carried out to assess agreement between sessions. Limits of agreement (LoAs), computed as \(\pm\)1.96 SD, illustrate the extent of variability between the measurements under consideration. An ordinary least square regression analysis of the differences was carried out to examining homoscedasticity. If the slope of the regression and the Pearson's correlation coefficient (r) differ significantly from zero at the \(p\)-value level, proportional bias is present [22]. Additionally, relative reliability in each stage was quantified using the intraclass correlation coefficient (ICC) of the 2-way random effects model with single-measure ICC\({}_{2,1}\). Reliability was classified as of [PERSON] and Koch criteria: 0.00-0.20 slight, 0.21-0.40 fair, 0.41-0.60 moderate, 0.61-0.80 substantial, and 0.81-1.00 almost perfect reliability [15; 23].  
Figure 1: Placement of the Q-LAC monitor.  
Absolute reliability was estimated using the standard error of measurement (SEM) and was calculated as follows: SEM = SD\({}_{\text{diff}}\)/\(\surd\)2, where SD\({}_{\text{diff}}\) is the SD of the differences between the tests. To examine the sensitivity of SmO\({}_{2}\), the smallest worthwhile change (SWC) was calculated as between-subject SD multiplied by 0.2 (smallest effect in [24; 25]). Additionally, the SEM was compared with the SWC using the threshold previously proposed by [PERSON] and [PERSON] [17; 26]. This approach examines the ability of the test to detect a change considered as good for an SEM < SWC, satisfactory for an SWC = SEM, and marginal for an SEM > SWC. The minimal detectable change (MDC) was calculated according to [PERSON] [27] from the standard error of measurement (SEM) at a CI 95%: MDC = SEM \(\times\) 1.96 \(\times\)\(\surd\)2. The within-subject absolute reliability or reproducibility of the Q-LAC measurements was determined by a coefficient of variation (CV), which was calculated from the following equation: 100 \(\times\) SEM/mean [28; 29]. Individual values were implemented to assess the mean CV for each SIET stage. Reliability was classified as follows: CV < 10% indicated excellent, 10% \(\leq\) CV < 20% represented good, 20% \(\leq\) CV < 30% signified fair, and CV \(\geq\) 30% denoted poor reliability [15]. For all analyses, a level of \(p\) < 0.05 was considered statistically significant.