Brainwave Optimization

BACKGROUND: There is a significant need to monitor human cognitive performance in complex environments, with one example being pilot performance. However, existing assessments largely focus on subjective experiences (e.g., questionnaires) and the evaluation of behavior (e.g., aircraft handling) as surrogates for cognition or utilize brainwave measures which require artificial setups (e.g., simultaneous auditory stimuli) that intrude on the primary tasks. Blink-related oscillations (BROs) are a recently discovered neural phenomenon associated with spontaneous blinking that can be captured without artificial setups and are also modulated by cognitive loading and the external sensory environment-making them ideal for brain function assessment within complex operational settings...

Prostate cancer (PCa) survivors often experience post-treatment challenges that impact their well-being and mental health. The Prostate Cancer Patient Empowerment Program (PC-PEP) aims to address these issues through a comprehensive intervention, involving daily meditation/breathing exercises, physical activity, pelvic floor exercises, emotional connection strategies, and peer support. This study presents a secondary analysis of a Phase 2 feasibility study that evaluated the effects of a 28-day PC-PEP intervention on stress reduction...

PURPOSE: Human emotion recognition using electroencephalograms (EEG) is a critical area of research in human-machine interfaces. Furthermore, EEG data are convoluted and diverse; thus, acquiring consistent results from these signals remains challenging. As such, the authors felt compelled to investigate EEG signals to identify different emotions. METHODS: A novel deep learning (DL) model stacked long short-term memory with attention (S-LSTM-ATT) model is proposed for emotion recognition (ER) in EEG signals...

It is hypothesized that being mindfully aware is a spontaneous state of being. It is imbued with joy, peace and happiness. Such a state is periodically revealed during restful attentiveness or presence. It is also associated with spontaneous brain alpha activity of 8-13 Hz. In deep nonrapid eye movement sleep, there is synchronous delta activity at a coherent frequency of 0.1 Hz. Both of these brainwave ground states are spontaneous, calm and effortless. When any physical or mental effort is made, the alpha rhythm is desynchronized, and it is superposed by faster brain waves of beta (13-30 Hz) and gamma frequencies (30-150 Hz)...

Sleep electroencephalogram (EEG) signals likely encode brain health information that may identify individuals at high risk for age-related brain diseases. Here, we evaluate the correlation of a previously proposed brain age biomarker, the "brain age index" (BAI), with cognitive test scores and use machine learning to develop and validate a series of new sleep EEG-based indices, termed "sleep cognitive indices" (SCIs), that are directly optimized to correlate with specific cognitive scores. Three overarching cognitive processes were examined: total, fluid (a measure of cognitive processes involved in reasoning-based problem solving and susceptible to aging and neuropathology), and crystallized cognition (a measure of cognitive processes involved in applying acquired knowledge toward problem-solving)...

Insufficient sleep impairs glucose regulation, increasing the risk of diabetes. However, what it is about the human sleeping brain that regulates blood sugar remains unknown. In an examination of over 600 humans, we demonstrate that the coupling of non-rapid eye movement (NREM) sleep spindles and slow oscillations the night before is associated with improved next-day peripheral glucose control. We further show that this sleep-associated glucose pathway may influence glycemic status through altered insulin sensitivity, rather than through altered pancreatic beta cell function...

Acoustic stimulation can improve motor symptoms in Parkinson's disease (PD) and might therefore represent a potential non-invasive treatment option. Scalp electroencephalography studies in healthy subjects indicate that specifically binaural beat stimulation (BBS) in the gamma frequency range is associated with synchronized cortical oscillations at 40 Hertz (Hz). Several studies suggest that oscillations in the gamma-frequency range (>30 Hz) serve a prokinetic function in PD. In this double-blind, randomized study, 25 PD patients were recruited...

BACKGROUND: Brain injuries are a common problem in combat sports, especially in disciplines such as kickboxing. Kickboxing is a combat sport that has several variations of competition, with the most contact-oriented fights being carried out under the format of K-1 rules. While these sports require a high level of skill and physical endurance, frequent micro-traumas to the brain can have serious consequences for the health and well-being of athletes. According to studies, combat sports are one of the riskiest sports in terms of brain injuries...

Cyber-attack is one of the most challenging aspects of information technology. After the emergence of the Internet of Things, which is a vast network of sensors, technology started moving towards the Internet of Things (IoT), many IoT based devices interplay in most of the application wings like defence, healthcare, home automation etc., As the technology escalates, it gives an open platform for raiders to hack the network devices. Even though many traditional methods and Machine Learning algorithms are designed hot, still it "Have a Screw Loose" in detecting the cyber-attacks...

The motor circuit in Parkinson's disease (PD) involves the basal ganglia, thalamus, motor cortex, and cerebellum. Hence, subthalamic nucleus (STN) or globus pallidus internus deep brain stimulation is commonly used in treating refractory Parkinson's patients. During the procedure, the local field potential (LPF) is commonly made along the trajectory of the STN. Two cases were assessed, where an electroencephalographic recording at the sensorimotor cortices was also performed with and without stimulation at the optimal STN electrode site...

Managing the health and wellbeing of full-time professional athletes is a multifaceted task. In elite high-performance environments, medical staff and strength training coaches attempt to identify improved methods to monitor player health. Monitoring player health could indicate potential injury risk and assist in adjustments to training and workload management. Measuring fatigue is a notable component of monitoring player readiness before and after training sessions, and after competitive fixtures. In the present study, a novel method of gathering non-invasive player data was investigated by utilizing the Omegawave (OW) to monitor direct current (DC) potential brainwave activity...

Conventional biometrics have been employed in high-security user-authentication systems for over 20 years now. However, some of these modalities face low-security issues in common practice. Brainwave-based user authentication has emerged as a promising alternative method, as it overcomes some of these drawbacks and allows for continuous user authentication. In the present study, we address the problem of individual user variability, by proposing a data-driven Electroencephalography (EEG)-based authentication method...

According to the working scenes, a proper light environment can enable people to maintain greater attention and meditation. A posture detection system in different working scenes is proposed in this paper, and different lighting conditions are provided for changes in body posture. This aims to stimulate the nervous system and improve work efficiency. A brainwave acquisition system was used to capture the participants' optimal attention and meditation. The posture data are collected by ten miniature inertial measurement units (IMUs)...

In this paper, the algorithm of the deep convolutional neural network is used to conduct in-depth research and analysis of sports health big data, and an intelligent analysis system is designed for the practical process. A convolutional neural network is one of the most popular methods of deep learning today. The convolutional neural network has the feature of local perception, which allows a complete image to be divided into several small parts, by learning the characteristic features of each local part and then merging the local information at the high level to get the full representation information...

[Purpose] Stroke patients are unable to move on their own and must be rehabilitated to allow the nervous system to trigger and restore its function. Traditional practice is to use electrode caps to extract brain wave features and combine them with assistive devices. However, there are problems that the electrode cap is not easy to wear, and the potential recognition is not good, and different extraction methods will affect the accuracy of the Brain-Computer Interfaces (BCI), which still has room for improvement...

The aim of this study was to monitor the mental activation training during match pressure imageries using a protocol with (MT) and without mental training (wMT) performed in the office and on the tennis court based on the analysis of heart rate, brain waves and subjective ratings in a professional tennis player with high imagery experience. Results showed that both in the office (MTo/wMTo) and on the court (MTc/wMTc) the tennis player's heart rate increased in the match pressure imagery (I.3-8), being higher in the MTo...

We present a systematic evaluation and optimization of a complex bio-medical signal processing application on the BrainWave prototype system, targeted towards ambulatory EEG monitoring within a tiny power budget of 1 mW. The considered BrainWave processor is completely programmable, while maintaining energy-efficiency by means of a Coarse-Grained Reconfigurable Array (CGRA). This is demonstrated through the mapping and evaluation of a state-of-the-art non-convulsive epileptic seizure detection algorithm, while ensuring real-time operation and seizure detection accuracy...

A Brain-Computer Interface (BCI) is a system used to communicate with an external world through the brain activity. The brain activity is measured by electroencephalography (EEG) signal and then processed by a BCI system. EEG source reconstruction could be a way to improve the accuracy of EEG classification in EEG based brain-computer interface (BCI). The source localization of the human brain activities can be an important resource for the recognition of the cognitive state, medical disorders, and a better understanding of the brain in general...

To ensure the direct delivery of therapeutic hypothermia at a selected constant temperature to the injured brain, a newly innovated direct brain cooling system was constructed. The practicality, effectiveness, and safety of this system were clinically tested in our initial series of 14 patients with severe head injuries. The patients were randomized into two groups: direct brain cooling at 32°C and the control group. All of them received intracranial pressure (ICP), focal brain oxygenation, brain temperature, and direct cortical brainwave monitoring...

BACKGROUND: Brain-computer interfaces (BCI) permits humans to interact with machines by decoding brainwaves to command for a variety of purposes. Convolutional neural networks (ConvNet) have improved the state-of-the-art of motor imagery decoding in an end-to-end approach. However, shallow ConvNets usually perform better than their deep counterparts. Thus, we aim to design a novel ConvNet that is deeper than the existing models, with an increase in terms of performances, and with optimal complexity...