Figure 1.
Body location of all sensors and simplistic representations of variables extracted.
The activity data logger is placed in a sport band, on the upper non-dominant arm and the temperature data logger on the wrist of the non-dominant hand. Here it is shown the three variables selected for the study and a simplistic representation of their behaviour. Motor activity and body position show their higher levels during day-time, when the subject is active. Wrist temperature (T) profile, on the contrary, show its higher levels during the night, when the subject is resting. Then, to calculate TAP, we reversed T profile.
Figure 2.
Individual weekly recording of all variables.
Wrist temperature (A) in red, motor activity (B) in green, body position (C) in orange and TAP (D) in violet of a subject taken as an example, on the left. On the right it is represented the mean waveform of every variable for the same subject. Shaded blue areas coincide with sleep declared by subjects. On the right every variable is represented as value ± SEM.
Figure 3.
Complete week recording for every variable evaluated for the entire experimental group.
On the left it is shown the weekly evolution of each variable and on the right its correspondent mean waveform. Wrist temperature (A) is represented in red, motor activity (B) in green, body position (C) in orange and TAP (D) in violet. On the right, every point is represented as value ± SEM. Please note that scales vary in mean waveforms representations on the right and representations on the left lack of SEM for a better understanding.
Table 1.
Non-parametric analysis for every measured variable and TAP.
Figure 4.
Correlations between every variable with respect to rest declared by subjects.
Wrist temperature (A), motor activity (B), body position (C) and TAP (D). Please note correlations coefficients and its probability value on the upper right of every pannel.
Table 2.
Sensitivity, specificity and agreement rates results.
Table 3.
Contingency tables, chi squared and p values for sensitivity, specificity and agreement rates results presented in Table 2.
Figure 5.
On the first column, TAP patterns obtained from simulations performed on Syntesi (Diez-Noguera, Barcelona, 2007) are shown. These simulations are drawn on black and subject's real TAP pattern on red. The noise percentage employed for modelisation (% noise) and percentage of instability in rest-activity ratio (R-A Ins) are shown in the second and third columns, respectively. Calculations of interdaily stability (IS), intradaily variability (IV), relative amplitude (RA) and circadian function index (CFI) for every model or real case are also indicated. Note that IS, IV, RA and CFI's units are AU. Green shadow indicates simulations performed on squared waves under different noise levels (while the same R-A Inst is maintained) and subject's real TAP pattern. Yellow shadow indicates simulations performed on squared waves under a 20% of R-A Inst and two extreme noise levels. Orange shadow indicates simulations performed on sinusoidal waves under two different noise levels (while the same R-A Inst is maintained).