Table 3.

Coefficients of the polynomial fit of the ${\mathrm{StO}}_2$ datasets.

${\mathrm{StO}}_2$ dataset ID	$p\times {10}^{-4}$	$q\times {10}^{-3}$	$r\times {10}^{-1}$	$s$	$t$
1	3	$-0.9$	$-3.480$	6.1064	50.5524
2	12	$-4.7$	6.881	$-3.0004$	5.7266
3	$-2$	2.8	0.951	$-0.8766$	50.3069
4	$-1$	5.8	$-1.195$	0.8802	48.6621
5	0	1.5	$-0.667$	0.7655	50.9731
6	$-12$	40.5	$-5.455$	2.7363	50.8872
7	1	−2.5	$-0.040$	0.4956	52.5724
8	7	−20.2	2.093	0.4914	49.2953
9	$-6$	22.0	$-3.580$	2.5699	46.4645
10	$-1$	-5.5	2.223	$-2.0088$	58.9165
11	$-4$	19.0	$-3.850$	3.1210	45.7532
12	$-3$	10.8	$-1.479$	1.4691	38.5091
13	0	4.2	$-1.169$	1.0991	60.6927
14	$-9$	35.6	$-5.313$	2.6641	46.7815
15	11	$-21.0$	0.525	1.2129	50.31287
16	$-3$	12.4	$-2.117$	0.5980	50.6841
Averaged coefficients synchronized	$-4$	6.2	$-0.979$	1.1452	47.3182
Data	$-6$	29.6	$-6.746$	5.6842	50.9053
Fitted pattern	$-2$	18.5	$-6.901$	8.1902	48.7902

The 4-deg polynomial fit is derived as ${\mathrm{StO}}_2\%=p*{\mathrm{time}}^4+q*{\mathrm{time}}^3+r*{\mathrm{time}}^2+s*\mathrm{time}+t$, with $\forall p,q,r,s,t\in \mathbb{R}$.