A pilot study on essential oil aroma stimulation for enhancing slow-wave EEG in sleeping brain.

Sleep quality is important to health and life quality. Lack of sleep can lead to a variety of health issues and reduce in daytime function. Recent study by Fultz et al. also indicated that sleep is crucial to brain metabolism. Delta power in sleep EEG often indicates good sleep quality while alpha power usually indicates sleep interruptions and poor sleep quality. Essential oil has been speculated to improve sleep quality. Previous studies also suggest essential oil aroma may affect human brain activity when applied awake. However, those studies were often not blinded, which makes the effectiveness and mechanism of aroma a heavily debated topic. In this study, we aim to explore the effect of essential oil aroma on human sleep quality and sleep EEG in a single-blinded setup. The aroma was released when the participants are asleep, which kept the influence of psychological expectation to the minimum. We recruited nine young, healthy participants with regular lifestyle and no sleep problem. All participants reported better sleep quality and more daytime vigorous after exposing to lavender aroma in sleep. We also observed that upon lavender aroma releases, alpha wave in wake stage was reduced while delta wave in slow-wave sleep (SWS) was increased. Lastly, we found that lavender oil promote occurrence of SWS. Overall, our study results show that essential oil aroma can be used to promote both subjective and objective sleep quality in healthy human subjects. This makes aroma intervention a potential solution for poor sleep quality and insomnia.

Knowledge-based identification of sleep stages based on two forehead electroencephalogram channels.

Sleep quality is important, especially given the considerable number of sleep-related pathologies. The distribution of sleep stages is a highly effective and objective way of quantifying sleep quality. As a standard multi-channel recording used in the study of sleep, polysomnography (PSG) is a widely used diagnostic scheme in sleep medicine. However, the standard process of sleep clinical test, including PSG recording and manual scoring, is complex, uncomfortable, and time-consuming. This process is difficult to implement when taking the whole PSG measurements at home for general healthcare purposes. This work presents a novel sleep stage classification system, based on features from the two forehead EEG channels FP1 and FP2. By recording EEG from forehead, where there is no hair, the proposed system can monitor physiological changes during sleep in a more practical way than previous systems. Through a headband or self-adhesive technology, the necessary sensors can be applied easily by users at home. Analysis results demonstrate that classification performance of the proposed system overcomes the individual differences between different participants in terms of automatically classifying sleep stages. Additionally, the proposed sleep stage classification system can identify kernel sleep features extracted from forehead EEG, which are closely related with sleep clinician's expert knowledge. Moreover, forehead EEG features are classified into five sleep stages by using the relevance vector machine. In a leave-one-subject-out cross validation analysis, we found our system to correctly classify five sleep stages at an average accuracy of 76.7 ± 4.0 (SD) % [average kappa 0.68 ± 0.06 (SD)]. Importantly, the proposed sleep stage classification system using forehead EEG features is a viable alternative for measuring EEG signals at home easily and conveniently to evaluate sleep quality reliably, ultimately improving public healthcare.

[Efficacy comparison of different stimulation therapies for periarthritis of shoulder].

OBJECTIVE: To compare clinical efficacy differences among electroacupuncture (EA), transcutaneous electrical nerve stimulation (TENS) therapy and acupoint massage (AM) on periarthritis of shoulder. METHODS: One hundred and twenty cases were randomly divided into an EA group, a TENS group and an AM group, 40 cases in each one. The selection of acupoints in the three groups were all the same, which were Jianqian (Extra), Xiabai (LU 4), Jianyu (LI 15), Binao (LI 14), Jianliao (TE 14), Naohui (TE 13), Xiaohai (SI 8) and Houxi (SI 3). EA was applied in the EA group with dense-disperse wave for 30 min, TENS therapy with dense-disperse wave for 30 min in the TENS group and AM combined with mobilization manipulation of Tuina on the shoulder in the AM group. All of the treatment was given once a day, six times a week and totally 4 weeks were required. The score of visual analogue scale (VAS) and improvement of shoulder joint activities in the three groups before and after the treatment were observed. RESULTS: After the treatment, the VAS score and activities of shoulder joint were all improved in the three groups (all P < 0.001) and AM group had more obvious improvement than TENS group and EA group (all P < 0.05). The effective and curative rate was 61.50 (24/39) in the AM group, which was superior to 42.9% (15/35) in the EA group and 44.4% (16/36) in the TENS group (both P < 0.05). The effective and curative rate of shoulder joint activities in the AM group was 61.5% (24/39), which was superior to 48.6% (17/35) in the EA group and 44.4% (16/36) in the TENS group (both P < 0.05). CONCLUSION: The acupoint massage has obvious clinical efficacy on periarthritis of shoulder, which could effectively relieve the pain and improve activities of shoulder joint, and it is superior to EA and TENS therapy.