Development and testing of methods for detecting off-wrist in actimetry recordings.

STUDY OBJECTIVES: In field studies using wrist-actimetry, not identifying/handling off-wrist intervals may result in their misclassification as immobility/sleep and biased estimations of rhythmic patterns. By comparing different solutions for detecting off-wrist, our goal was to ascertain how accurately they detect nonwear in different contexts and identify variables that are useful in the process. METHODS: We developed algorithms using heuristic (HA) and machine learning (ML) approaches. Both were tested using data from a protocol followed by 10 subjects, which was devised to mimic contexts of actimeter wear/nonwear in real-life. Self-reported data on usage according to the protocol were considered the gold standard. Additionally, the performance of our algorithms was compared to that of visual inspection (by 2 experienced investigators) and Choi algorithm. Data previously collected in field studies were used for proof-of-concept analyses. RESULTS: All methods showed similarly good performances. Accuracy was marginally higher for one of the raters (visual inspection) than for heuristically developed algorithms (HA, Choi). Short intervals (especially < 2 h) were either not or only poorly identified. Consecutive stretches of zeros in activity were considered important indicators of off-wrist (for both HA and ML). It took hours for raters to complete the task as opposed to the seconds or few minutes taken by the automated methods. CONCLUSIONS: Automated strategies of off-wrist detection are similarly effective to visual inspection, but have the important advantage of being faster, less costly, and independent of raters' attention/experience. In our study, detecting short intervals was a limitation across methods.

Entraining effects of variations in light spectral composition on the rest-activity rhythm of a nocturnal rodent.

The ability to predict and adjust physiology and behavior to recurring environmental events has been necessary for survival on Earth. Recent discoveries revealed that not only changes in irradiance but also light spectral composition can stimulate the suprachiasmatic nucleus (SCN), ensuring the body's synchronization to the environment. Therefore, using a lighting system that modulates spectral composition during the day using combined red-green-blue (RGB) lights, we evaluated the effect of variations in light spectral composition on the rest-activity rhythm of rodents. Male Wistar rats (n = 17) were gestated and raised under different lighting conditions and exposed to a long photoperiod (16 h light: 8 h dark). The difference between groups was the presence of variations in light spectral composition during the day (RGB-v) to simulate daily changes in natural light, or not (RGB-f). After weaning, spontaneous motor activity was recorded continuously for rhythm evaluation. Our results indicated that animals under RGB-v did not present a reactive peak of activity after the beginning of the light phase, suggesting that this group successfully detected the variations aimed at mimicking daily alterations of natural light. Furthermore, RGB-v animals exhibited an earlier activity acrophase in comparison to animals under RGB-f (RGB-v = 12:16 - "hh:mm", RGB-f = 13:02; p < 0.001), which might have been due to the capability to predict the beginning of the dark phase when exposed to variations in light spectrum. However, this earlier activity acrophase can be also explained by the blue-light peak that occurred in RGB-v. The spectral and waveform analysis of daily patterns of motor activity revealed that rats in the RGB-v group were better entrained to a circadian rhythm throughout the experiment. RGB-v showed higher interdaily stability (IS) values (29.75 ± 6.5, n = 9) than did RGB-f (t(15)  =  2.74, p  =  0.015). Besides, the highest power content (PC) on the first harmonic (circadian) was reached earlier in the RGB-v group. The circadianity index (CI) of the whole period was higher in the RGB-v group (t(15)  =  3.47, p = 0.003). Thus, we could consider that locomotor activity rhythm was entrained to the light-dark cycle in the RGB-v rats earlier compared to the RGB-f rats. Our results provide additional evidence for the effect of variations in light spectral composition on the rest-activity pattern of nocturnal rodents. This suggests that these animals might predict the arrival of the activity phase by its advanced acrophase when exposed to RGB-v, demonstrating a better synchronization to a 24-h rhythm.