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Sensors (Basel, Switzerland) Dec 2023Coupling brain-computer interfaces (BCIs) and robotic systems in the future can enable seamless personal assistant systems in everyday life, with the requests that can...
Coupling brain-computer interfaces (BCIs) and robotic systems in the future can enable seamless personal assistant systems in everyday life, with the requests that can be performed in a discrete manner, using one's brain activity only. These types of systems might be of a particular interest for people with locked-in syndrome (LIS) or amyotrophic lateral sclerosis (ALS) because they can benefit from communicating with robotic assistants using brain sensing interfaces. In this proof-of-concept work, we explored how a wireless and wearable BCI device can control a quadruped robot-Boston Dynamics' Spot. The device measures the user's electroencephalography (EEG) and electrooculography (EOG) activity of the user from the electrodes embedded in the glasses' frame. The user responds to a series of questions with YES/NO answers by performing a brain-teaser activity of mental calculus. Each question-answer pair has a pre-configured set of actions for Spot. For instance, Spot was prompted to walk across a room, pick up an object, and retrieve it for the user (i.e., bring a bottle of water) when a sequence resolved to a YES response. Our system achieved at a success rate of 83.4%. To the best of our knowledge, this is the first integration of wireless, non-visual-based BCI systems with Spot in the context of personal assistant use cases. While this BCI quadruped robot system is an early prototype, future iterations may embody friendly and intuitive cues similar to regular service dogs. As such, this project aims to pave a path towards future developments in modern day personal assistant robots powered by wireless and wearable BCI systems in everyday living conditions.
Topics: Humans; Animals; Dogs; Robotics; Brainwashing; Proof of Concept Study; Amyotrophic Lateral Sclerosis; Brain
PubMed: 38202942
DOI: 10.3390/s24010080 -
Clinical Neurophysiology Practice 2024Parasomnias are due to a transient unstable state dissociation during entry into sleep, within sleep, or during arousal from sleep, and manifest with abnormal sleep... (Review)
Review
Parasomnias are due to a transient unstable state dissociation during entry into sleep, within sleep, or during arousal from sleep, and manifest with abnormal sleep related behaviors, perceptions, emotions, dreams, and autonomic nervous system activity. Rapid eye movement (REM) parasomnias include REM sleep behavior disorder (RBD), isolated recurrent sleep paralysis and nightmare disorder. Neurophysiology is key for diagnosing these disorders and provides insights into their pathophysiology. RBD is very well characterized from a neurophysiological point of view, also thank to the fact that polysomnography is needed for the diagnosis. Diagnostic criteria are provided by the American Academy of Sleep Medicine and video-polysomnography guidelines for the diagnosis by the International REM Sleep Behavior Disorder Study Group. Differences between the two sets of criteria are presented and discussed. Availability of polysomnography in RBD provides data on sleep electroencephalography (EEG), electrooculography (EOG) and electromyography (EMG). Sleep EEG in RBD shows e.g. changes in delta and theta power, in sleep spindles and K complexes. EMG during REM sleep is essential for RBD diagnosis and is an important neurodegeneration biomarker. RBD patients present alterations also in wake EEG, autonomic function, evoked potentials, and transcranial magnetic stimulation. Clinical neurophysiological data on recurrent isolated sleep paralysis and nightmare disorder are scant. The few available data provide insights into the pathophysiology of these disorders, demonstrating a state dissociation in recurrent isolated sleep paralysis and suggesting alterations in sleep macro- and microstructure as well as autonomic changes in nightmare disorder.
PubMed: 38328386
DOI: 10.1016/j.cnp.2023.10.003 -
Nature and Science of Sleep 2023The recommendations for identifying sleep stages based on the interpretation of electrophysiological signals (electroencephalography [EEG], electro-oculography [EOG],...
The recommendations for identifying sleep stages based on the interpretation of electrophysiological signals (electroencephalography [EEG], electro-oculography [EOG], and electromyography [EMG]), derived from the Rechtschaffen and Kales manual, were published in 2007 at the initiative of the American Academy of Sleep Medicine, and regularly updated over years. They offer an important tool to assess objective markers in different types of sleep/wake subjective complaints. With the aims and advantages of simplicity, reproducibility and standardization of practices in research and, most of all, in sleep medicine, they have overall changed little in the way they describe sleep. However, our knowledge on sleep/wake physiology and sleep disorders has evolved since then. High-density electroencephalography and intracranial electroencephalography studies have highlighted local regulation of sleep mechanisms, with spatio-temporal heterogeneity in vigilance states. Progress in the understanding of sleep disorders has allowed the identification of electrophysiological biomarkers better correlated with clinical symptoms and outcomes than standard sleep parameters. Finally, the huge development of sleep medicine, with a demand for explorations far exceeding the supply, has led to the development of alternative studies, which can be carried out at home, based on a smaller number of electrophysiological signals and on their automatic analysis. In this perspective article, we aim to examine how our description of sleep has been constructed, has evolved, and may still be reshaped in the light of advances in knowledge of sleep physiology and the development of technical recording and analysis tools. After presenting the strengths and limitations of the classification of sleep stages, we propose to challenge the "EEG-EOG-EMG" paradigm by discussing the physiological signals required for sleep stages identification, provide an overview of new tools and automatic analysis methods and propose avenues for the development of new approaches to describe and understand sleep/wake states.
PubMed: 37405208
DOI: 10.2147/NSS.S401270 -
Biosensors Apr 2024Carbon nanotube (CNT)-based nanocomposites have found applications in making sensors for various types of physiological sensing. However, the sensors' fabrication...
Carbon nanotube (CNT)-based nanocomposites have found applications in making sensors for various types of physiological sensing. However, the sensors' fabrication process is usually complex, multistep, and requires longtime mixing and hazardous solvents that can be harmful to the environment. Here, we report a flexible dry silver (Ag)/CNT/polydimethylsiloxane (PDMS) nanocomposite-based sensor made by a solvent-free, low-temperature, time-effective, and simple approach for electrophysiological recording. By mechanical compression and thermal treatment of Ag/CNT, a connected conductive network of the fillers was formed, after which the PDMS was added as a polymer matrix. The CNTs make a continuous network for electrons transport, endowing the nanocomposite with high electrical conductivity, mechanical strength, and durability. This process is solvent-free and does not require a high temperature or complex mixing procedure. The sensor shows high flexibility and good conductivity. High-quality electroencephalography (EEG) and electrooculography (EOG) were performed using fabricated dry sensors. Our results show that the Ag/CNT/PDMS sensor has comparable skin-sensor interface impedance with commercial Ag/AgCl-coated dry electrodes, better performance for noninvasive electrophysiological signal recording, and a higher signal-to-noise ratio (SNR) even after 8 months of storage. The SNR of electrophysiological signal recording was measured to be 26.83 dB for our developed sensors versus 25.23 dB for commercial Ag/AgCl-coated dry electrodes. Our process of compress-heating the functional fillers provides a universal approach to fabricate various types of nanocomposites with different nanofillers and desired electrical and mechanical properties.
Topics: Nanocomposites; Nanotubes, Carbon; Silver; Dimethylpolysiloxanes; Electroencephalography; Electric Conductivity; Biosensing Techniques; Humans; Electrooculography; Electrodes; Signal-To-Noise Ratio
PubMed: 38667181
DOI: 10.3390/bios14040188 -
Scientific Reports Jun 2023Smart eyeglasses with an integrated electrooculogram (EOG) device (JINS MEME ES_R, JINS Inc.) were evaluated as a quantitative diagnostic tool for blepharospasm....
Smart eyeglasses with an integrated electrooculogram (EOG) device (JINS MEME ES_R, JINS Inc.) were evaluated as a quantitative diagnostic tool for blepharospasm. Participants without blepharospasm (n = 21) and patients with blepharospasm (n = 19) undertook two voluntary blinking tests (light and fast) while wearing the smart eyeglasses. Vertical (Vv) and horizontal (Vh) components were extracted from time-series voltage waveforms recorded during 30 s of the blinking tests. Two parameters, the ratio between the maximum and minimum values in the power spectrum (peak-bottom ratio, Fourier transform analysis) and the mean amplitude of the EOG waveform (peak amplitude analysis) were calculated. The mean amplitude of Vh from light and fast blinking was significantly higher in the blepharospasm group than in the control group (P < 0.05 and P < 0.05). Similarly, the peak-bottom ratio of Vv from light and fast blinking was significantly lower in the blepharospasm group than in the control group (P < 0.05 and P < 0.05). The mean amplitude of Vh and peak-bottom ratio of Vv correlated with the scores determined using the Jankovic rating scale (P < 0.05 and P < 0.01). Therefore, these parameters are sufficiently accurate for objective blepharospasm classification and diagnosis.
Topics: Humans; Blepharospasm; Blinking; Electrooculography; Eyeglasses; Time Factors
PubMed: 37332074
DOI: 10.1038/s41598-023-36094-4 -
Journal of Current Ophthalmology 2023To determine which mechanisms are operative in releasing the extraocular myofascial tissue in response to extraocular myofascial release (EOMR) and to evaluate the...
PURPOSE
To determine which mechanisms are operative in releasing the extraocular myofascial tissue in response to extraocular myofascial release (EOMR) and to evaluate the effect of EOMR on saccadic velocity and esodeviation angle in patients with convergence spasm.
METHODS
Fourteen patients with convergence spasm aged 20-35 participated in this research. The treatment included touching the medial rectus and its interrelated fascial tissue with the index finger pulp from over the eyelid for at least 300 s and applying very gentle and uniform pressure. We evaluated the saccadic velocity obtained from dynamic electrooculography (EOG) and the angle of deviation. The findings of dynamic EOG were used as a reliable quantitative method to assess eye movement function.
RESULTS
The amount of esodeviation decreased significantly at both far 2.39Δ, 95% confidence interval (CI) (1.27-3.52) ( = 0.002) and near 5.57Δ, 95% CI (4.67-6.47) ( = 0.001) after two sessions of EOMR in a week. There was no significant difference in saccadic velocities before and after treatment.
CONCLUSION
In the short term, the EOMR only affects the static condition of the eye. Therefore, a significant improvement could be seen in the deviometric findings. However, the dynamic properties of the extraocular muscles did not improve and probably needed a more extended treatment period for acting the long-term mechanisms.
PubMed: 38250489
DOI: 10.4103/joco.joco_143_23 -
World Neurosurgery: X Apr 2024The supra-cerebellar infratentorial approach to pineal region tumours is versatile and safe corridor to lesions located below the deep veins. Monitoring of the...
BACKGROUND
The supra-cerebellar infratentorial approach to pineal region tumours is versatile and safe corridor to lesions located below the deep veins. Monitoring of the extra-ocular muscle pathways using the evoked compound muscle action potential can lead to safer resections.
TECHNICAL NOTE
To describe the use of electrooculography and a three handed retractor less method for pineal region tumour surgeries.
MATERIAL AND METHODS
Intraoperative electrooculography uses recording done from two channels (horizontal and vertical)by inserting disposable subdermal needle electrodes along the periorbital area. The oculomotor nerve is being monitored as it exits the midbrain. Retractor-less three-handed-technique allows for minimal handling of the cerebellum while maximizing the operative corridor.
RESULT
The oculomotor nerve was stimulated post resection and correspondingly led to improved symptoms post-operatively.
DISCUSSION AND CONCLUSION
We demonstrate a method for the intraoperative monitoring of the continuity of the oculomotor tracts and a three handed retractor-less method of resection of pineal region tumours. The placement of electrodes and area of stimulation need sound knowledge of anatomy of the region. Haemostasis at every step is absolutely essential to be able to visualize in the narrow corridor.
PubMed: 38455252
DOI: 10.1016/j.wnsx.2024.100292 -
Computer Methods and Programs in... Feb 2024Sleep staging is an essential step for sleep disorder diagnosis, which is time-intensive and laborious for experts to perform this work manually. Automatic sleep stage...
BACKGROUND AND OBJECTIVE
Sleep staging is an essential step for sleep disorder diagnosis, which is time-intensive and laborious for experts to perform this work manually. Automatic sleep stage classification methods not only alleviate experts from these demanding tasks but also enhance the accuracy and efficiency of the classification process.
METHODS
A novel multi-channel biosignal-based model constructed by the combination of a 3D convolutional operation and a graph convolutional operation is proposed for the automated sleep stages using various physiological signals. Both the 3D convolution and graph convolution can aggregate information from neighboring brain areas, which helps to learn intrinsic connections from the biosignals. Electroencephalogram (EEG), electromyogram (EMG), electrooculogram (EOG) and electrocardiogram (ECG) signals are employed to extract time domain and frequency domain features. Subsequently, these signals are input to the 3D convolutional and graph convolutional branches, respectively. The 3D convolution branch can explore the correlations between multi-channel signals and multi-band waves in each channel in the time series, while the graph convolution branch can explore the connections between each channel and each frequency band. In this work, we have developed the proposed multi-channel convolution combined sleep stage classification model (MixSleepNet) using ISRUC datasets (Subgroup 3 and 50 random samples from Subgroup 1).
RESULTS
Based on the first expert's label, our generated MixSleepNet yielded an accuracy, F1-score and Cohen kappa scores of 0.830, 0.821 and 0.782, respectively for ISRUC-S3. It obtained accuracy, F1-score and Cohen kappa scores of 0.812, 0.786, and 0.756, respectively for the ISRUC-S1 dataset. In accordance with the evaluations conducted by the second expert, the comprehensive accuracies, F1-scores, and Cohen kappa coefficients for the ISRUC-S3 and ISRUC-S1 datasets are determined to be 0.837, 0.820, 0.789, and 0.829, 0.791, 0.775, respectively.
CONCLUSION
The results of the performance metrics by the proposed method are much better than those from all the compared models. Additional experiments were carried out on the ISRUC-S3 sub-dataset to evaluate the contributions of each module towards the classification performance.
Topics: Sleep; Sleep Stages; Time Factors; Electroencephalography; Electrooculography
PubMed: 38218118
DOI: 10.1016/j.cmpb.2023.107992 -
Frontiers in Neuroscience 2023It is suggested that eye movement recordings could be used as an objective evaluation method of motor imagery (MI) engagement. Our investigation aimed to evaluate MI...
INTRODUCTION
It is suggested that eye movement recordings could be used as an objective evaluation method of motor imagery (MI) engagement. Our investigation aimed to evaluate MI engagement in patients after stroke (PaS) compared with physical execution (PE) of a clinically relevant unilateral upper limb movement task of the patients' affected body side.
METHODS
In total, 21 PaS fulfilled the MI ability evaluation [Kinaesthetic and Visual Imagery Questionnaire (KVIQ-10), body rotation task (BRT), and mental chronometry task (MC)]. During the experiment, PaS moved a cup to distinct fields while wearing smart eyeglasses (SE) with electrooculography electrodes integrated into the nose pads and electrodes for conventional electrooculography (EOG). To verify MI engagement, heart rate (HR) and oxygen saturation (SpO) were recorded, simultaneously with electroencephalography (EEG). Eye movements were recorded during MI, PE, and rest in two measurement sessions to compare the SE performance between conditions and SE's psychometric properties.
RESULTS
MI and PE correlation of SE signals varied between = 0.12 and = 0.76. Validity (cross-correlation with EOG signals) was calculated for MI ( = 0.53) and PE ( = 0.57). The SE showed moderate test-retest reliability (intraclass correlation coefficient) with = 0.51 (95% CI 0.26-0.80) for MI and with = 0.53 (95% CI 0.29 - 0.76) for PE. Event-related desynchronization and event-related synchronization changes of EEG showed a large variability. HR and SpO recordings showed similar values during MI and PE. The linear mixed model to examine HR and SpO between conditions (MI, PE, rest) revealed a significant difference in HR between rest and MI, and between rest and PE but not for SpO. A Pearson correlation between MI ability assessments (KVIQ, BRT, MC) and physiological parameters showed no association between MI ability and HR and SpO.
CONCLUSION
The objective assessment of MI engagement in PaS remains challenging in clinical settings. However, HR was confirmed as a reliable parameter to assess MI engagement in PaS. Eye movements measured with the SE during MI did not resemble those during PE, which is presumably due to the demanding task. A re-evaluation with task adaptation is suggested.
PubMed: 37583419
DOI: 10.3389/fnins.2023.1225440 -
Sensors (Basel, Switzerland) Feb 2024The article outlines various approaches to developing a fuzzy decision algorithm designed for monitoring and issuing warnings about driver drowsiness. This algorithm is...
The article outlines various approaches to developing a fuzzy decision algorithm designed for monitoring and issuing warnings about driver drowsiness. This algorithm is based on analyzing EOG (electrooculography) signals and eye state images with the aim of preventing accidents. The drowsiness warning system comprises key components that learn about, analyze and make decisions regarding the driver's alertness status. The outcomes of this analysis can then trigger warnings if the driver is identified as being in a drowsy state. Driver drowsiness is characterized by a gradual decline in attention to the road and traffic, diminishing driving skills and an increase in reaction time, all contributing to a higher risk of accidents. In cases where the driver does not respond to the warnings, the ADAS (advanced driver assistance systems) system should intervene, assuming control of the vehicle's commands.
Topics: Automobile Driving; Accidents, Traffic; Electrooculography; Algorithms; Wakefulness
PubMed: 38475079
DOI: 10.3390/s24051541