The water transport in hydrogel has been proven to be critical for water evaporation, water treatment and moisture-wicking. However, confined with the regulation of pore structure, challenges remain ...in constructing fast water transport channels especially in harsh water environment. Herein, we demonstrate a simple strategy for fabrication of fast water transport carbon nanotube/poly (vinyl alcohol) (CNT/PVA) hydrogels via efficiently interior infiltration and decoration of CNT cellular structures with PVA. The CNT/PVA double-network structures favor the generation of hierarchical micro/nanochannels and strong capillary forces, leading to water transport throughout the hydrogel up to ~15.8 g g−1s−1, recorded highest among reported hydrogels. The as-formed elastic hybrid hydrogels present a reversible absorbing/shrinking behavior, an excellent capacity in water absorption (216 g g−1), and high adaptability in salty water, acid and alkaline solutions as well as boiling water. Moreover, a multifunctional sport headband has been designed based on fast water transport and conductive framework, which can perform fantabulous moisture-wicking and health monitor. This work proposes a new route for developing fast water transport hydrogels towards versatile flexible electronic devices and multifunctional sport management systems.
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•CNT/PVA hybrid hydrogel with hierarchical vascular-like micro-nano channels was fabricated.•The hydrogel enabled ultrafast water transport.•The hydrogel featured reversible adaptability to extreme environments.•The hydrogel performed fast moisture-wicking and sport monitoring.
Several stress-related mental disorders are characterised by disturbed sleep, but objective sleep biomarkers are not routinely examined in psychiatric patients. We examined the use of wearable-based ...sleep biomarkers in a psychiatric sample with headband electroencephalography (EEG) including pulse photoplethysmography (PPG), with an additional focus on microstructural elements as especially the shift from low to high frequencies appears relevant for several stress-related mental disorders. We analysed 371 nights of sufficient quality from 83 healthy participants and those with a confirmed stress-related mental disorder (anxiety-affective spectrum). The median value of macrostructural, microstructural (spectral slope fitting), and heart rate variables was calculated across nights and analysed at the individual level (N = 83). The headbands were accepted well by patients and the data quality was sufficient for most nights. The macrostructural analyses revealed trends for significance regarding sleep continuity but not sleep depth variables. The spectral analyses yielded no between-group differences except for a group × age interaction, with the normal age-related decline in the low versus high frequency power ratio flattening in the patient group. The PPG analyses showed that the mean heart rate was higher in the patient group in pre-sleep epochs, a difference that reduced during sleep and dissipated at wakefulness. Wearable devices that record EEG and/or PPG could be used over multiple nights to assess sleep fragmentation, spectral balance, and sympathetic drive throughout the sleep-wake cycle in patients with stress-related mental disorders and healthy controls, although macrostructural and spectral markers did not differ between the two groups.
Abstract
Study Objectives
The COVID-19 pandemic has had dramatic effects on society and people’s daily habits. In this observational study, we recorded objective data on sleep macro- and ...microarchitecture repeatedly over several nights before and during the COVID-19 government-imposed lockdown. The main objective was to evaluate changes in patterns of sleep duration and architecture during home confinement using the pre-confinement period as a control.
Methods
Participants were regular users of a sleep-monitoring headband that records, stores, and automatically analyzes physiological data in real time, equivalent to polysomnography. We measured sleep onset duration, total sleep time, duration of sleep stages (N2, N3, and rapid eye movement REM), and sleep continuity. Via the user’s smartphone application, participants filled in questionnaires on how lockdown changed working hours, eating behavior, and daily life at home. They also filled in the Insomnia Severity Index, reduced Morningness–Eveningness Questionnaire, and Hospital Anxiety and Depression Scale questionnaires, allowing us to create selected subgroups.
Results
The 599 participants were mainly men (71%) of median age 47 (interquartile range: 36–59). Compared to before lockdown, during lockdown individuals slept more overall (mean +3·83 min; SD: ±1.3), had less deep sleep (N3), more light sleep (N2), and longer REM sleep (mean +3·74 min; SD: ±0.8). They exhibited less weekend-specific changes, suggesting less sleep restriction during the week. Changes were most pronounced in individuals reporting eveningness preferences, suggesting relative sleep deprivation in this population and exacerbated sensitivity to societal changes.
Conclusion
This unique dataset should help us understand the effects of lockdown on sleep architecture and on our health.
We present a low-cost and easily accessible adaptation system to perform stereotactic procedures in infants.
We used an adaptive device consisting of a headband with a plaster bandage, cotton bandage ...roll, and gauze bandages. Prior to its clinical application, the device was tested in our neuroscience laboratory using a simulation model of a size similar to that of a 5-month-old infant, during which no complications arose. The headband cast technique was subsequently reproduced in a 5-month-old patient, serving as a fixation point for the placement of a Micromar frame for biopsy of a thalamic lesion.
A stereotactic biopsy was successfully performed in a 5-month-old patient using a headband cast to secure the stereotactic frame. This method enabled precise targeting of the selected site, resulting in a histopathological diagnosis without any associated complications.
The adaptive device is safe, easily accessible, and reproducible, facilitating the performance of stereotactic diagnostic procedures in infants, accurately reaching the planned objective without causing injuries or additional complications.
Near-infrared spectroscopy (NIRS) is an important technique that percutaneously and noninvasively monitors the changes in hemoglobin concentration of cerebral blood flow. We have developed ...headband-type NIRS devices using a light-emitting diode (LED) power source and a photodiode detector (PD) to reduce the burden in diagnosis preparation and the price of the NIRS module. The ten-channel nonreal-time headband-type NIRS device with PD and one-package three-wavelength LED as well as the two-channel real-time wireless NIRS headband that is controlled using a tablet PC were manufactured in house. The two developed headband NIRS devices were evaluated using an existing LABNIRS system using a verbal fluency task, and they exhibited the same tendency with NIRS signals of the different levels at the rest and task stages. The measurement of the real-time NIRS signals revealed that the voice and breath caused the source of low-frequency fluctuations superimposed on the NIRS signals.
Sleep disturbances are common in Alzheimer’s disease and other neurodegenerative disorders, and together represent a potential therapeutic target for disease modification. A major barrier for ...studying sleep in patients with dementia is the requirement for overnight polysomnography (PSG) to achieve formal sleep staging. This is not only costly, but also spending a night in a hospital setting is not always advisable in this patient group. As an alternative to PSG, portable electroencephalography (EEG) headbands (HB) have been developed, which reduce cost, increase patient comfort, and allow sleep recordings in a person’s home environment. However, naïve applications of current automated sleep staging systems tend to perform inadequately with HB data, due to their relatively lower quality. Here we present a deep learning (DL) model for automated sleep staging of HB EEG data to overcome these critical limitations. The solution includes a simple band-pass filtering, a data augmentation step, and a model using convolutional (CNN) and long short-term memory (LSTM) layers. With this model, we have achieved 74% (±10%) validation accuracy on low-quality two-channel EEG headband data and 77% (±10%) on gold-standard PSG. Our results suggest that DL approaches achieve robust sleep staging of both portable and in-hospital EEG recordings, and may allow for more widespread use of ambulatory sleep assessments across clinical conditions, including neurodegenerative disorders.
We developed a clinical sign that improves the sensitivity, specificity, and predictive values of the Head Impulse Paradigm (HIMP) Test by adding the Suppression Head Impulse Paradigm (SHIMP) Test ...using a diagnostic headband.
Prospective and descriptive study analyzing the function of 1,255 horizontal semicircular canals of subjects with differing vestibulo-ocular reflex (VOR) gains who showed-up with symptoms related to neurotology (Montevideo, Uruguay, March 2017 to March 2019). The clinical HIMP and SHIMP tests were assessed and the amplitudes of overt saccades were compared to each other. Clinical findings were contrasted against vHIT gains.
The HIMP and SHIMP combined test using the H/S headband has high specificity and low sensibility. This test association can identify healthy individuals among individuals typically misdiagnosed as ill by the conventional HIT or HIMP maneuver of the HIMP test, as originally described by Halmagyi and Curthoys. Therefore, we recommend using the headband assisted HIMP/SHIMP test, instead of exclusively relying on positive HIMP results.
According to the World Health Organization (WHO), around 70 million people are affected by Epilepsy. Accurate prediction of seizures well before its commencement alarms the epileptic patients to take ...necessary actions to reduce the consequence of these seizures. The major objective of this work is the real-time prediction of the epileptic seizures well before its onset. A smart, bio-inspired, self-cognizant and proactive seizure predictor called ForeSeiz is designed for the purpose of forecasting of seizures. This design is suitably constructed on the basis of the Internet of Medical Things (IoMT) framework. The front-end circuitry and Seizure Predictor Tag (SPT) are designed and integrated together into a seizure predictor headband, which totally weighing of 30 grams and dissipating 52.74 mW power dissipation. The proposed ForeSeiz predictor has an Enhanced Convolutional Neural Network (ECNN) classification model, optimized using Fletcher Reeves Algorithm (FRA) along with a Phase Transition Predictor (PTP) based on the Kullback-Leibler divergence for the prediction of real-time seizures. The model is trained and tested using CHB-MIT, NINC and SRM EEG recordings via transfer learning method and yielded 97% accuracy, 0.12 FP/h false prediction rate, along with Premium Seizure Prediction Horizon (PSPH) of 66.52 minutes, prior to the onset of seizures. A compatible Seizure Prediction mobile application (SeizPred APP) is designed for the interaction to the Firebase cloud, for recording the states of the epileptic patients for further reference for the doctors and if any onset of seizure is predicted, it is immediately informed to the caretakers for further intervention actions.
According to their site: “Our experiments with real-time sleep stage detection have proven very accurate with 90% of our experimental subjects”; however, the developers do not provide enough ...scientific information on how their algorithm calculates accuracy, nor make the data supporting this claim accessible. According to their site: “Using a series of smart timers, light patterns are displayed throughout the night…” ...when the dreamer perceives the cues, the dreamer can move the eyes in such a predetermined manner that the device would sense this movement and stop generating the stimuli. Besides measuring EEG activity, Neuroon has a pulse oximeter (PPG) and sensors for temperature and ocular movements, which would allow for online detection of REM sleep.
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