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1.
Nat Sci Sleep ; 16: 381-388, 2024.
Artigo em Inglês | MEDLINE | ID: mdl-38646463

RESUMO

Purpose: Female athletes with menstrual abnormalities have poor sleep quality. However, whether female athletes with poor sleep quality based on subjective assessment have distinctive changes in objective measures of sleep in association with menses remains unclear. This study aimed to compare changes in objective sleep measurements during and following menses between collegiate female athletes with and without poor subjective sleep quality. Patients and Methods: Female collegiate athletes (age range/mean ± standard deviation: 18-22/ 22.2±1.1) with regular menstrual cycles were recruited. The participants underwent home electroencephalogram monitoring during the first and second nights after the onset of menses and one night between the seventh and 10th nights after menses onset (mid-follicular phase). The Pittsburgh Sleep Quality Index (PSQI) was used to assess the subjective sleep quality. Interactions between the presence of poor subjective sleep quality (ie, PSQI ≥6) and changes in objective measures of sleep in association with menses were analyzed. Results: Data of 45 athletes, including 13 with poor subjective sleep quality, showed that changes in arousal index in athletes with poor subjective sleep quality were distinctive from those in athletes without poor subjective sleep quality (p = 0.036 for interaction). In athletes with poor subjective sleep quality, the arousal index was significantly increased in menses (p for analysis of variance, 0.015), especially on the first night after the onset of menses compared with during the mid-follicular phase (p = 0.016). Conclusion: Collegiate female athletes with regular menstrual cycles are likely to have poor subjective sleep quality in association with more frequent arousal during the first night after the onset of menses than during the mid-follicular phase.

2.
Nat Sci Sleep ; 14: 819-827, 2022.
Artigo em Inglês | MEDLINE | ID: mdl-35502231

RESUMO

Purpose: Sleep is an essential factor for athletes, and it is important to intervene in sleep to manage it. We need a device that can evaluate sleep easily and constantly. Consumer wearable devices can be useful tools for athletes. In order to use consumer wearable devices in clinical research, it is essential to conduct a validation study. Thus, we conducted a validation study to assess the Fitbit Alta HRTM (FBA)- a consumer wearable device with an accelerometer and a heart rate monitor to detect sleep stages and quality against electroencephalographic (EEG) studies in athletes. Patients and Methods: Forty college athletes participated in the study. EEG was applied to participants simultaneously while wearing FBA. Results: Regarding sleep parameters, there was a strong correlation between the total sleep time (TST)-EEG and the TST-Fitbit (r = 0.83; p < 0.001). Regarding the sleep stages, there was a modest correlation between the N3 sleep-EEG and the N3 sleep-Fitbit (r = 0.68; p < 0.001). In addition, there was a strong correlation between the percentage of N3 sleep in between sleep onset and initial rapid eye movement sleep-EEG and those on Fitbit (r = 0.73; p < 0.001). Conclusion: These results demonstrate that FBA facilitates sleep monitoring and exhibits acceptable agreement with EEG. Therefore, FBA is a useful tool in athletes' sleep management.

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