Search

Background: The management of patients with disorders of consciousness (DOC) presents substantial challenges in clinical practice. Deep brain stimulation (DBS) has emerged as a potential therapeutic approach, but the lack of standardized regulatory parameters for DBS in DOC hinders definitive conclusions. Objective: This comprehensive review aims to provide a detailed summary of the current issues concerning patient selection, target setting, and modulation parameters in clinical studies investigating the application of DBS for DOC patients. Methods: A meticulous systematic analysis of the literatures was conducted, encompassing articles published from 1968 to April 2023, retrieved from reputable databases (PubMed, Embase, Medline, and Web of Science). Results: The systematic analysis of 21 eligible articles, involving 146 patients with DOC resulting from acquired brain injury or other disorders, revealed significant insights. The most frequently targeted regions were the Centromedian‐parafascicular complex (CM‐pf) nuclei and central thalamus (CT), both recognized for their role in regulating consciousness. However, other targets have also been explored in different studies. The stimulation frequency was predominantly set at 25 or 100 Hz, with pulse width of 120 μs, and voltages ranged from 0 to 4 V. These parameters were customized based on individual patient responses and evaluations. The overall clinical efficacy rate in all included studies was 39.7%, indicating a positive effect of DBS in a subset of DOC patients. Nonetheless, the assessment methods, follow‐up durations, and outcome measures varied across studies, potentially contributing to the variability in reported efficacy rates. Conclusion: Despite the challenges arising from the lack of standardized parameters, DBS shows promising potential as a therapeutic option for patients with DOC. However, there still remains the need for standardized protocols and assessment methods, which are crucial to deepen the understanding and optimizing the therapeutic potential of DBS in this specific patient population. [ABSTRACT FROM AUTHOR]

The main goal of this paper is to give the basic principles of hyperbolic function theory. First, we discuss the Green identity for H k ¯ H k . Second, we also deal with the integral representations for hyperbolic harmonic function in the Clifford algebra C l n + 1 , 0. [ABSTRACT FROM AUTHOR]

The main goal of this paper is to give the basic principles of hyperbolic function theory. First, we discuss the Green identity for H k ¯ H k . Second, we also deal with the integral representations for hyperbolic harmonic function in the Clifford algebra C l n + 1 , 0. [ABSTRACT FROM AUTHOR]

Background: Disorders of consciousness (DoC) represent a spectrum of neurological conditions that pose significant treatment challenges. Percutaneous short-term spinal cord stimulation (SCS) has emerged as a promising experimental diagnostic treatment to assess and potentially improve consciousness levels. However, the effectiveness of this intervention is frequently compromised by the shift of electrodes, particularly in the cervical region, which can negatively affect therapeutic outcomes., Methods: This retrospective study aimed to study if electrodes shift in percutaneous short-term SCS in patients with DoC would affect the outcome. We analyzed the relationship between electrode shift length and patient outcome, as well as the correlation with various anatomical parameters, including the actual length of the cervical spine, linear length, spinal canal transverse diameter, spinal canal diameter, and C2 cone height, in a cohort of patients undergoing the procedure., Results: Our findings revealed that in patients with better outcome, there are significant less patient with electrode shift ( p  = 0.019). Further, a linear correlation was found between the length of electrode shift and patients' outcome (Rho = 0.583, p  = 0.002), with longer shift lengths associated with poorer outcomes. Contrary to our expectations, there was no significant association between the measured anatomical parameters and the extent of electrode shift. However, a trend was found between the actual length of the cervical spine and the shift of the electrode ( p  = 0.098). Notably, the shorter spinal canal transverse diameter was found to be significantly associated with better outcome in patients with DoC receiving percutaneous short-term SCS ( p  = 0.033)., Conclusion: These results highlight the clinical importance of electrode stability in the cervical region during SCS treatment for patients with DoC. Ensuring secure placement of electrodes may play a crucial role in enhancing patients' outcome and minimize postoperative complications. Given the lack of association with expected anatomical parameters, future research should investigate other factors that could impact electrode stability to optimize this therapeutic intervention., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 He, Yang, Xu, Niu, Wu, Huang, Chai, Cao, Wang, Wong, He, Yang and Zhao.)

A brain-computer interface (BCI) serves as a direct communication channel between brain activity and external devices, typically a computer or robotic limb. Advances in technology have led to the increasing use of intracranial electrical recording or stimulation in the treatment of conditions such as epilepsy, depression, and movement disorders. This indicates that BCIs can offer clinical neurological rehabilitation for patients with disabilities and functional impairments. They also provide a means to restore consciousness and functionality for patients with sequelae from major brain diseases. Whether invasive or non-invasive, the collected cortical or deep signals can be decoded and translated for communication. This review aims to provide an overview of the advantages of endovascular BCIs compared with conventional BCIs, along with insights into the specific anatomical regions under study. Given the rapid progress, we also provide updates on ongoing clinical trials and the prospects for current research involving endovascular electrodes., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

To explore the effectiveness of using Electro- encephalogram (EEG) spectral power and multiscale sample entropy for accessing mental workload in different tasks, working memory tasks with different information types (verbal, object and spatial) and various mental loads were designed based on the N-Back paradigm. Subjective scores, accuracy and response time were used to verify the rationality of the tasks. EEGs from 18 normal adults were acquired when tasks were being performed, an independent component analysis (ICA) based artifact removal method were applied to get clean data. Linear (relative power in Theta and Alpha band, etc.) and nonlinear (multiscale sample entropy) features of EEGs were then extracted. Indices that can effectively reflect mental workload levels were selected by using multivariate analysis of variance statistical approach. Results showed that with the increment of task load, power of frontal Theta, Theta/Alpha ratio and sample entropies at scale more than 10 in parietal regions increased significantly first and decreased slightly then, while the power of central-parietal Alpha decreased significantly first and increased slightly then. Considering the difference between task types, no difference in power of frontal Theta, central-parietal Alpha and sample entropies at scales more than 10 of parietal regions were found between verbal and object tasks, as well as between two spatial tasks. No difference of frontal Theta/Alpha ratio was found in all the four tasks. The results can provide evidence for the mental workload evaluation in tasks with different information types.

More and more hybrid brain-computer interfaces (BCI) supplement traditional single-modality BCI in practical applications. Combinations based on steady-state visual evoked potential (SSVEP) and electromyography (EMG) are the widely used hybrid BCIs. The EMG of jaw clench is commonly used together with SSVEP. This article explored the interference with SSVEP from occipital electrodes by the jaw clench-related EMG so that SSVEP with specific frequency can be identified even during occlusal movements. The experiment was divided into three sets base on the jaw clench patterns (no clenches, chew, and long clench). In each set, the subjects used the same visual stimuli, which were realized by the three flashing targets at different frequencies (6.2Hz, 9.8Hz, and 14.6Hz). After collecting the SSVEP at 4 sites in the occipital region, the SSVEP response spectrum of each stimulus was observed under the three jaw clench patterns. Then, the SSVEP signal was identified by the canonical correlation analysis method for accuracy statistics. Spectrum responses showed that the interference of the jaw clench EMG on SSVEP could be avoided when the stimulation frequency is lower than 20Hz. SSVEP could be identified based on the frequency domain characteristics of these signals. During steady-state visual stimulation with jaw clenches, the recognition rate of SSVEP was still high (no clenches: 100.0%, chew: 94.7%, and long clench: 100.0%). Through reasonable frequency selecting and signal processing, the influence of the jaw clench movement on the SSVEP could be reduced and a high recognition accuracy could be achieved, even the jaw clench actions and the SSVEP stimulation occur simultaneously.

Objective: To propose a square's ring motion stimulation based on steady-state motion visual evoked potential, and compare it with the commonly used visual stimulation modes (Newton's ring motion, square flicker and circular flicker)., Methods: EEG signals were collected while 9 experimental subjects gazing at four stimulation and pattern analyzed by Canonical Correlation Analysis (CCA). Stimulation were evaluated by recognition accuracy and subjective scores., Results: The classification accuracies of SSVEP elicited by the square's ring motion(82.8%±14.1%) and Newton's ring(83.3%±11.5%) have no significant difference between them, which are lower than that of the square flicker(98.3%±4.1%) and the circular flicker(99.2%±1.8%). The shape of the figure has no significant influence on the classification accuracy either in motion mode or flicker mode. The comfort of the square's ring motion is higher than the other three stimulation according to subjective scores., Conclusions: The square's ring motion can elicit EEG and reduce the discomfort caused by flicker modes. The square's ring motion can be used as a visual stimulation in SSMVEP-based BCI system.

Rhythmic respiratory movement in a deep and slow pattern can be beneficial to cardiovascular system, this paper investigates the effect of step-wise paced breathing procedure on blood oxygen saturation (SpO2). Experiment objects were divided into two groups, the normobaric hypoxia (simulated altitude of 4 500 meters hypoxia environment, 8 persons), normoxia and normobaric group (laboratory environment, 49 persons). The respiratory movements were performed by a high-to-low progressive change in two groups respectively. During the experiment, each object's blood oxygen saturation and heart rate were recorded. Results showed that progressive guided breathing could significantly increase the subjects' blood oxygen saturation level from 90% to 95% under the hypoxic condition. Even under the normobaric and normoxic condition, progressive guided breathing with stable blood oxygen saturation level can also enhance the blood oxygen saturation level. In both groups, mean heart rate declined in the progressive guided breathing. The research showed that the step-wise paced breathing technique could regulate the blood oxygen saturation and effectively improve the level of blood oxygen saturation by adjusting the respiratory motion in the low oxygen environment.

Heart rate variability (HRV) analysis technology based on an autoregressive (AR) model is widely used in the assessment of autonomic nervous system function. The order of AR models has important influence on the accuracy of HRV analysis. This article presents a method to determine the optimum order of AR models. After acquiring the ECG signal of 46 healthy adults in their natural breathing state and extracting the beat-to-beat intervals (RRI) in the ECG, we used two criteria, i. e. final prediction error (FPE) criterion to estimate the optimum model order for AR models, and prediction error whiteness test to decide the reliability of the model. We compared the frequency domain parameters including total power, power in high frequency (HF), power in low frequency (LF), LF power in normalized units and ratio of LF/HF of our HRV analysis to the results of Kubios-HRV. The results showed that the correlation coefficients of the five parameters between our methods and Kubios-HRV were greater than 0.95, and the Bland-Altman plot of the parameters was in the consistent band. The results indicate that the optimization algorithm of HRV analysis based on AR models proposed in this paper can obtain accurate results, and the results of this algorithm has good coherence with those of the Kubios-HRV software in HRV analysis.

In comparison with the measurement of heart rate variability from ECG and from photoplethysmographic signal from 46 healthy adults in their spontaneous breathing state. The beat-to-beat intervals in ECG and pulse-to-pulse intervals in photoplethysmographic signal are extracted, and then the parameters of heart rate variability are calculated. Three kinds of algorithms are chosen to get the pulse-to-pulse intervals, which are the intervals of maximum of second derivative, the maximum of PPG signal and the tangent intersection. The results show that the correlation coefficients of the HRV parameters in the two calculation methods are highly correlated. The Bland-Altman scattered plots show the relative bias results from the algorithm of the maximum of PPG signal are smallest and singular points that deviate from the consistent limits are the least compared with the other two algorithms.

To investigate the effect of stepwise paced breathing (PB) on pulse transit time (PTT), we collected physiological signals of electrocardiogram (ECG), respiration and arterial pulse wave during a procedure of stepwise PB, which consists of 6 different breathing rates changing in a protocol of 14.0-12.5-11.0-9.5-8.0-7.0 breath per minute (BPM), with each breathing rate lasting 3 minutes. Twenty two healthy adults involved in this experiment and the change of PTT was analyzed during the stepwise PB procedure. In our study, the PTT was measured by calculating the time interval from the R-spike of the ECG to the peaks of the second derivative of the arterial pulse wave. Ensemble empirical mode decomposition (EEMD) was applied to PTT to decompose the signal into different intrinsic mode function, and respiratory oscillation and trend component (baseline) in PTT were further extracted. It was found that the respiratory oscillations in the PTT increased with decreasing of the PB rate, and many of the subjects (14 out of 22) showed the phenomena of PTT baseline increasing during the stepwise PB procedure. The results indicated that the stepwise PB procedure induced a high level of cardiovascular oscillation and produced an accumulative effect of PTT baseline increase. As PTT is capable of predicting changes in BP over a short period of time, increase of PTT baseline indicates the decrease of blood pressure. The experiments showed that the stepwise PB procedure could reduce blood pressure for most subjects. For future work, it is necessary to develop certain indices differentiating the effectiveness of the stepwise PB procedure on the PTT baseline change, and to test the effectiveness of this stepwise PB procedure on blood pressure reduction for patients with essential hypertension.

This paper introduces a free and publicly open ICU database: multi-parameter intelligent monitoring in intensive care II: MIMIC-II, which has been built up and maintained by the laboratory of computational physiology at the Massachusetts Institute Technology, Beth Israel Deaconess Medical Center and Philips Healthcare over the past decade. This paper briefly introduces its infrastructure, implementation and applications in clinical studies. Clinical study pertaining to circadian variation in heart rate and blood pressure during sepsis is shown as a typical example of research performed with MIMIC-II. In this study, it was found there was significant difference in circadian variation in both heart rate and blood pressure between survival and non-survival groups in septic patients. This study tackled several important techniques necessary for the investigation of the circadian rhythm.