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This work proposes an intrinsically explainable, straightforward method to decode P300 waveforms from electroencephalography (EEG) signals, overcoming the black box nature of deep learning techniques. The proposed method allows convolutional neural networks to decode information from images, an area where they have achieved astonishing performance. By plotting the EEG signal as an image, it can be both visually interpreted by physicians and technicians and detected by the network, offering a straightforward way of explaining the decision. The identification of this pattern is used to implement a P300-based speller device, which can serve as an alternative communication channel for persons affected by amyotrophic lateral sclerosis (ALS). This method is validated by identifying this signal by performing a brain-computer interface simulation on a public dataset from ALS patients. Letter identification rates from the speller on the dataset show that this method can identify the P300 signature on the set of 8 patients. The proposed approach achieves similar performance to other state-of-the-art proposals while providing clinically relevant explainability (XAI).

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For most patients admitted to a hospital, it is a requirement to continuously monitor their vital signs. Among these are the waveforms from ECG and the pulmonary arterial pulse. At present, there are several electronic devices that can measure the arterial pulse waveform. However, they can be affected by electromagnetic wave radiation, and the fabrication of electronic sensors is complicated and contributes to the e-waste, among other problems. In this paper, we propose an optical method to measure arterial pulse based on a Fabry-Perot interferometer composed of two mirrors. A pulse sensor formed by an acrylic cell with a thin membrane is used to gather the vasodilatation of the wrist, forming an air pulse that is enacted by means of a tube to a metallic cell containing a mirror that is glued to a thin silicone membrane. When the air pulse arrives, a displacement of the mirror takes place and produces a shift of the interference pattern fringes given by the Fabry-Perot. A detector samples the fringe intensity. With this method, an arterial pulse waveform is obtained. We characterize this optical device as a test of concept, and its application to measuring artery pulse is presented. The optical device is compared to other electronic devices.

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BACKGROUND: Numerous trials have addressed intracranial pressure (ICP) management in neurocritical care. However, identifying its harmful thresholds and controlling ICP remain challenging in terms of improving outcomes. Evidence suggests that an individualized approach is necessary for establishing tolerance limits for ICP, incorporating factors such as ICP waveform (ICPW) or pulse morphology along with additional data provided by other invasive (e.g., brain oximetry) and noninvasive monitoring (NIM) methods (e.g., transcranial Doppler, optic nerve sheath diameter ultrasound, and pupillometry). This study aims to assess current ICP monitoring practices among experienced clinicians and explore whether guidelines should incorporate ancillary parameters from NIM and ICPW in future updates. METHODS: We conducted a survey among experienced professionals involved in researching and managing patients with severe injury across low-middle-income countries (LMICs) and high-income countries (HICs). We sought their insights on ICP monitoring, particularly focusing on the impact of NIM and ICPW in various clinical scenarios. RESULTS: From October to December 2023, 109 professionals from the Americas and Europe participated in the survey, evenly distributed between LMIC and HIC. When ICP ranged from 22 to 25 mm Hg, 62.3% of respondents were open to considering additional information, such as ICPW and other monitoring techniques, before adjusting therapy intensity levels. Moreover, 77% of respondents were inclined to reassess patients with ICP in the 18-22 mm Hg range, potentially escalating therapy intensity levels with the support of ICPW and NIM. Differences emerged between LMIC and HIC participants, with more LMIC respondents preferring arterial blood pressure transducer leveling at the heart and endorsing the use of NIM techniques and ICPW as ancillary information. CONCLUSIONS: Experienced clinicians tend to personalize ICP management, emphasizing the importance of considering various monitoring techniques. ICPW and noninvasive techniques, particularly in LMIC settings, warrant further exploration and could potentially enhance individualized patient care. The study suggests updating guidelines to include these additional components for a more personalized approach to ICP management.

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Resumen: El oxímetro de pulso, un dispositivo común en diferentes áreas hospitalarias, sobre todo en áreas críticas, es utilizado la mayoría de las ocasiones para evaluar el estado respiratorio del paciente; sin embargo, la evidencia actual muestra que este dispositivo nos puede brindar información valiosa del comportamiento hemodinámico, la respuesta del sistema nervioso autónomo y la terapéutica que se realiza al paciente crítico. Es por este motivo, que conocer los fundamentos de la oximetría, los valores más allá de la oxigenación como la forma de onda pletismográfica y el índice de perfusión resulta en una cantidad de información importante para la toma de decisiones y la respuesta a los tratamientos realizados.

Abstract: The pulse oximeter, a common device in different hospital areas, especially in critical areas, is used most of the time to assess the patient's respiratory status; however, current evidence shows that this device can provide us with valuable information on hemodynamic behavior, the response of the autonomic nervous system, and the therapy given to critically ill patients. It is for this reason that knowing the fundamentals of oximetry, values beyond oxygenation such as the plethysmographic waveform and the perfusion index results in an important amount of information for decision making and the response to the treatments performed.

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ABSTRACT BACKGROUND: Among the complications related to chronic kidney disease (CKD), those of a neurological nature stand out, and for a better quality of life for patients, the diagnosis and treatment of these complications is fundamental. OBJECTIVES: This study aimed to assess the effect of hemodialysis on intracranial pressure waveform (ICPw) in patients with chronic kidney disease undergoing hemodialysis and those who are not yet undergoing substitutive therapy. DESIGN AND SETTING: An observational study was conducted in two stages at a kidney replacement therapy center in Brazil. The first was a longitudinal study and the second was a cross-sectional study. METHODS: Forty-two patients on hemodialysis were included in the first stage of the study. In the second stage, 226 participants were included. Of these, 186 were individuals with chronic kidney disease (who were not undergoing substitutive therapy), and 40 did not have the disease (control group). The participants' intracranial compliance was assessed using the non-invasive Brain4care method, and the results were compared between the groups. RESULTS: There was a significant difference between the hemodialysis and non-hemodialysis groups, with the former having better ICPw conditions. CONCLUSIONS: Hemodialysis influenced the improvement in ICPw, probably due to the decrease in the patients' extra-and intracellular volumes. Furthermore, ICPw monitoring can be a new parameter to consider when defining the moment to start substitutive therapy.

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Synchronous excitatory discharges from the entorhinal cortex (EC) to the dentate gyrus (DG) generate fast and prominent patterns in the hilar local field potential (LFP), called dentate spikes (DSs). As sharp-wave ripples in CA1, DSs are more likely to occur in quiet behavioral states, when memory consolidation is thought to take place. However, their functions in mnemonic processes are yet to be elucidated. The classification of DSs into types 1 or 2 is determined by their origin in the lateral or medial EC, as revealed by current source density (CSD) analysis, which requires recordings from linear probes with multiple electrodes spanning the DG layers. To allow the investigation of the functional role of each DS type in recordings obtained from single electrodes and tetrodes, which are abundant in the field, we developed an unsupervised method using Gaussian mixture models to classify such events based on their waveforms. Our classification approach achieved high accuracies (> 80%) when validated in 8 mice with DG laminar profiles. The average CSDs, waveforms, rates, and widths of the DS types obtained through our method closely resembled those derived from the CSD-based classification. As an example of application, we used the technique to analyze single-electrode LFPs from apolipoprotein (apo) E3 and apoE4 knock-in mice. We observed that the latter group, which is a model for Alzheimer's disease, exhibited wider DSs of both types from a young age, with a larger effect size for DS type 2, likely reflecting early pathophysiological alterations in the EC-DG network, such as hyperactivity. In addition to the applicability of the method in expanding the study of DS types, our results show that their waveforms carry information about their origins, suggesting different underlying network dynamics and roles in memory processing.

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This study aimed to characterize and correlate the stylet penetration behaviors of nymphs of the Neotropical brown stink bug, Euschistus heros (F.), on immature soybean pods. Waveforms were obtained using electropenetrography (EPG). The findings revealed that the nymphs exploited the xylem vessels and the seed tegument or endosperm. Primarily 4 phases were characterized: nonfeeding, pathway, salivation, and ingestion. The waveforms of each phase were similar in appearance across instars. The biological meanings of waveforms were based on visual observations, comparison with waveforms of adults, and histological studies. Np represents the insect resting or walking on soybean pod surface. Eh1 represents the first contact between the mouthparts (stylets) and plant tissue. Eh2 represents xylem sap ingestion, and Eh3 represents seed activities (including tegument and endosperm). The number of waveform events did not differ among instars for all waveforms. However, for Eh3, fifth instars performed more activities than other instars. The second instars had the smallest value, and third and fourth instars had intermediate values. For total duration, all waveforms differed among instars. Np duration was shorter for third compared with second and fourth instars and intermediate for fifth instar. For Eh1, second and third instars had the longest duration (1.5× to 2× greater) compared with fourth and fifth instars. For Eh2 and Eh3, the second-instar showed the longest (~2× greater) and shortest durations, respectively. Overall, this study provides important insights into the feeding behavior of E. heros nymphs so that effective pest management programs can be developed to contain this pest.

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Electrical treeing is one of the main degradation mechanisms in high-voltage polymeric insulation. Epoxy resin is used as insulating material in power equipment such as rotating machines, power transformers, gas-insulated switchgears, and insulators, among others. Electrical trees grow under the effect of partial discharges (PDs) that progressively degrade the polymer until the tree crosses the bulk insulation, then causing the failure of power equipment and the outage of the energy supply. This work studies electrical trees in epoxy resin through different PD analysis techniques, evaluating and comparing their ability to identify tree bulk-insulation crossing, the precursor of failure. Two PD measurement systems were used simultaneously-one to capture the sequence of PD pulses and another to acquire PD pulse waveforms-and four PD analysis techniques were deployed. Phase-resolved PD (PRPD) and pulse sequence analysis (PSA) identified tree crossing; however, they were more sensible to the AC excitation voltage amplitude and frequency. Nonlinear time series analysis (NLTSA) characteristics were evaluated through the correlation dimension, showing a reduction from pre- to post-crossing, and thus representing a change to a less complex dynamical system. The PD pulse waveform parameters had the best performance; they could identify tree crossing in epoxy resin material independently of the applied AC voltage amplitude and frequency, making them more robust for a broader range of situations, and thus, they can be exploited as a diagnostic tool for the asset management of high-voltage polymeric insulation.

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For decades, one of the main targets in the management of severe acute brain injury (ABI) has been intracranial hypertension (IH) control. However, the determination of IH has suffered variations in its thresholds over time without clear evidence for it. Meanwhile, progress in the understanding of intracranial content (brain, blood and cerebrospinal fluid) dynamics and recent development in monitoring techniques suggest that targeting intracranial compliance (ICC) could be a more reliable approach rather than guiding actions by predetermined intracranial pressure values. It is known that ICC impairment forecasts IH, as intracranial volume may rapidly increase inside the skull, a closed bony box with derisory expansibility. Therefore, an intracranial compartmental syndrome (ICCS) can occur with deleterious brain effects, precipitating a reduction in brain perfusion, thereby inducing brain ischemia. The present perspective review aims to discuss the ICCS concept and suggest an integrative model for the combination of modern invasive and noninvasive techniques for IH and ICC assessment. The theory and logic suggest that the combination of multiple ancillary methods may enhance ICC impairment prediction, pointing proactive actions and improving patient outcomes.

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Arterial stiffness is a major condition related to many cardiovascular diseases. Traditional approaches in the assessment of arterial stiffness supported by machine learning techniques are limited to the pulse wave velocity (PWV) estimation based on pressure signals from the peripheral arteries. Nevertheless, arterial stiffness can be assessed based on the pressure-strain relationship by analyzing its hysteresis loop. In this work, the capacity of deep learning models based on generative adversarial networks (GANs) to transfer pressure signals from the peripheral arterial region to pressure and area signals located in the central arterial region is explored. The studied signals are from a public and validated virtual database. Compared to other works in which the assessment of arterial stiffness was performed via PWV, in the present work the pressure-strain hysteresis loop is reconstructed and evaluated in terms of classical machine learning metrics and clinical parameters. Least-square GAN (LSGAN) and Wasserstein GAN with gradient penalty (WGAN-GP) adversarial losses are compared, yielding better results with LSGAN. LSGAN mean ± standard deviation of error for pressure and area pulse waveforms are 0.8 ± 0.4 mmHg and 0.1 ± 0.1 cm2, respectively. Regarding the pressure-strain elastic modulus, it is achieved a mean absolute percentage error of 6.5 ± 5.1%. GAN-based deep learning models can recover the pressure-strain loop of central arteries while observing pressure signals from peripheral arteries.

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The use of oscillometric methods to determine brachial blood pressure (bBP) can lead to a systematic underestimation of the invasively measured systolic (bSBP) and pulse (bPP) pressure levels, together with a significant overestimation of diastolic pressure (bDBP). Similarly, the agreement between brachial mean blood pressure (bMBP), invasively and non-invasively measured, can be affected by inaccurate estimations/assumptions. Despite several methodologies that can be applied to estimate bMBP non-invasively, there is no consensus on which approach leads to the most accurate estimation. Aims: to evaluate the association and agreement between: (1) non-invasive (oscillometry) and invasive bBP; (2) invasive bMBP, and bMBP (i) measured by oscillometry and (ii) calculated using six different equations; and (3) bSBP and bPP invasively and non-invasively obtained by applanation tonometry and employing different calibration methods. To this end, invasive aortic blood pressure and bBP (catheterization), and non-invasive bBP (oscillometry [Mobil-O-Graph] and brachial artery applanation tonometry [SphygmoCor]) were simultaneously obtained (34 subjects, 193 records). bMBP was calculated using different approaches. Results: (i) the agreement between invasive bBP and their respective non-invasive measurements (oscillometry) showed dependence on bBP levels (proportional error); (ii) among the different approaches used to obtain bMBP, the equation that includes a form factor equal to 33% (bMBP = bDBP + bPP/3) showed the best association with the invasive bMBP; (iii) the best approach to estimate invasive bSBP and bPP from tonometry recordings is based on the calibration scheme that employs oscillometric bMBP. On the contrary, the worst association between invasive and applanation tonometry-derived bBP levels was observed when the brachial pulse waveform was calibrated to bMBP quantified as bMBP = bDBP + bPP/3. Our study strongly emphasizes the need for methodological transparency and consensus for non-invasive bMBP assessment.

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Objectives: To investigate the outcomes of cochlear re-implantation using multi-mode grounding stimulation associated with anodic monophasic pulses to manage abnormal facial nerve stimulation (AFNS) in cochlear implant (CI) recipients. Methods: Retrospective case report. An adult CI recipient with severe AFNS and decrease in auditory performance was re-implanted with a new CI device to change the pulse shape and stimulation mode. Patient's speech perception scores and AFNS were compared before and after cochlear re-implantation, using monopolar stimulation associated with cathodic biphasic pulses and multi-mode stimulation mode associated to anodic monophasic pulses, respectively. The insertion depth angle and the electrode-nerve distances were also investigated, before and after cochlear re-implantation. Results: AFNS was resolved, and the speech recognition scores rapidly increased in the first year after cochlear re-implantation while remaining stable. After cochlear re-implantation, the e15 and e20 electrodes showed shorter electrode-nerve distances compared to their correspondent e4 and e7 electrodes, which induced AFNS in the first implantation. Conclusions: Cochlear re-implantation with multi-mode grounding stimulation associated with anodic monophasic pulses was an effective strategy for managing AFNS. The patient's speech perception scores rapidly improved and AFNS was not detected four years after cochlear re-implantation.

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Analysis of intracranial pressure waveforms (ICPW) provides information on intracranial compliance. We aimed to assess the correlation between noninvasive ICPW (NICPW) and invasively measured intracranial pressure (ICP) and to assess the NICPW prognostic value in this population. In this cohort, acute brain-injured (ABI) patients were included within 5 days from admission in six Intensive Care Units. Mean ICP (mICP) values and the P2/P1 ratio derived from NICPW were analyzed and correlated with outcome, which was defined as: (a) early death (ED); survivors on spontaneous breathing (SB) or survivors on mechanical ventilation (MV) at 7 days from inclusion. Intracranial hypertension (IHT) was defined by ICP > 20 mmHg. A total of 72 patients were included (mean age 39, 68% TBI). mICP and P2/P1 values were significantly correlated (r = 0.49, p < 0.001). P2/P1 ratio was significantly higher in patients with IHT and had an area under the receiving operator curve (AUROC) to predict IHT of 0.88 (95% CI 0.78-0.98). mICP and P2/P1 ratio was also significantly higher for ED group (n = 10) than the other groups. The AUROC of P2/P1 to predict ED was 0.71 [95% CI 0.53-0.87], and the threshold P2/P1 > 1.2 showed a sensitivity of 60% [95% CI 31-83%] and a specificity of 69% [95% CI 57-79%]. Similar results were observed when decompressive craniectomy patients were excluded. In this study, P2/P1 derived from noninvasive ICPW assessment was well correlated with IHT. This information seems to be as associated with ABI patients outcomes as ICP.Trial registration: NCT03144219, Registered 01 May 2017 Retrospectively registered, https://www.clinicaltrials.gov/ct2/show/NCT03144219 .

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Background: Peripheral arterial disease (PAD) is a risk factor for amputation and systemic atherosclerotic disease. Barbados has a high diabetes prevalence, and 89% of diabetes-related hospital admissions are for foot problems. Foot examination is infrequent in Barbados primary care. The prevalence and potential risk factors for PAD in people with diabetes in Barbados were studied. Methods: Multistage probability sampling was used to select a representative population sample of people ≥25 years of age with known diabetes or fasting blood glucose ≥7 mmol/L or HbA1c ≥6.5%. We administered the Edinburgh claudication questionnaire and assessed the ankle brachial pressure index (ABI) and Doppler waveform in both dorsalis pedis and posterior tibial arteries. Participants were classified into categories based on ABI as follows: PAD ≤0.90 in any leg; borderline 0.91 to 0.99 in one leg and the other not ≤0.90 or >0.4; normal 1.00 to 1.40 in both legs; and non-compressible >1.40 in one leg and the other not ≤0.9. Waveforms crossing the zero-flow baseline were categorised as normal. Multivariable logistic regression assessed the associations of potential risk factors with PAD. Results: Of 236 participants (74% response rate, 33% male, median age 58.6 years), 51% had previously diagnosed diabetes. Of nine people with symptoms of definite or atypical claudication, four had PAD and one had non-compressible arteries. ABI prevalence (95% CI) was PAD 18.6% (13.8, 24.6), borderline 21.9% (16.6, 28.4), normal 55.5% (49.4, 61.5) and non-compressible 3.9% (1.6, 9.3). Increasing age and female gender were independently associated with PAD. Over 80% of normal legs (ABI 1.00 to 1.40) had normal posterior tibial and dorsalis pedis waveforms, while only 23% legs with PAD (ABI ≤0.90) had normal waveforms in both arteries (Kappa = 0.43). Conclusion: Asymptomatic PAD is common in people with diabetes and requires ABI screening to detect it. Female gender is associated with PAD.

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Noise Radar technology is the general term used to describe radar systems that employ realizations of a given stochastic process as transmit waveforms. Originally, carriers modulated in amplitude by a Gaussian random signal, derived from a hardware noise source, were taken into consideration, justifying the adopted nomenclature. With the advances made in hardware as well as the rise of the software defined noise radar concept, waveform design emerges as an important research area related to such systems. The possibility of generating signals with varied stochastic properties increased the potential in achieving systems with enhanced performances. The characterization of random phase and frequency modulated waveforms (more suitable for several applications) has then gained considerable notoriety within the radar community as well. Several optimization algorithms have been proposed in order to conveniently shape both the autocorrelation function of the random samples that comprise the transmit signal, as well as their power spectrum density. Nevertheless, little attention has been driven to properly characterize the stochastic properties of those signals through closed form expressions, jeopardizing the effectiveness of the aforementioned algorithms as well as their reproducibility. Within this context, this paper investigates the performance of several random phase and frequency modulated waveforms, varying the stochastic properties of their modulating signals.

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Studies of pulse-type gymnotiform electric fishes have suggested that electric organ discharge waveforms (EODw) allow individuals to discriminate between conspecific and allospecific signals, but few have approached this experimentally. Here we implement a phase-locked playback technique for a syntopic species pair, Brachyhypopomus gauderio and Gymnotus omarorum. Both species respond to changes in stimulus waveform with a transitory reduction in the interpulse interval of their self-generated discharge, providing strong evidence of discrimination. We also document sustained rate changes in response to different EODws, which may suggest recognition of natural waveforms.

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BACKGROUND: Biphasic waveform shock has been established as the standard method for cardioversion of atrial fibrillation (AF). Depending on various factors, standard electrical cardioversion for AF may be unsuccessful in some cases, even with biphasic shocks. CASE SUMMARY: We report the safety and efficacy of orthogonal electrical cardioversion (OECV) as an alternative in patients with paroxysmal AF refractory to standard biphasic electrical cardioversion after up to three subsequent shocks of increasing energy and/or two or three initial shocks with maximum energy of 200-Joules. Shocks were delivered with two external defibrillators via two sets of adhesive electrode pads to apply two perpendicular electrical vectors in a simultaneous-sequential mode in antero-lateral and antero-posterior configuration. Five patients, mean age 54.4 ± 11, three with hypertensive heart disease and a body mass index 27.2 ± 2 kg/m2. All individual mean impedance before OECV was 79 ± 5 Ω with a mean peak current applied of 22 ± 4.5 A. Restoration of sinus rhythm with OECV was achieved acutely and sustained in all five patients. No patients developed haemodynamic instability or thromboembolic events. DISCUSSION: Double simultaneous shocks in an orthogonal configuration could theoretically decrease the defibrillation threshold through the ability of sequential pulses applying a more efficient and uniform current density. OECV using lower/medium energy may be another useful rescue strategy in AF refractory to standard biphasic shocks.

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The development of non-invasive screening techniques for early cancer detection is one of the greatest scientific challenges of the 21st century. One promising emerging method is the analysis of volatile organic compounds (VOCs). VOCs are low molecular weight substances generated as final products of cellular metabolism and emitted through a variety of biological matrices, such as breath, blood, saliva and urine. Urine stands out for its non-invasive nature, availability in large volumes, and the high concentration of VOCs in the kidneys. This review provides an overview of the available data on urinary VOCs that have been investigated in cancer-focused clinical studies using mass spectrometric (MS) techniques. A literature search was conducted in ScienceDirect, Pubmed and Web of Science, using the keywords "Urinary VOCs", "VOCs biomarkers" and "Volatile cancer biomarkers" in combination with the term "Mass spectrometry". Only studies in English published between January 2011 and May 2020 were selected. The three most evaluated types of cancers in the reviewed studies were lung, breast and prostate, and the most frequently identified urinary VOC biomarkers were hexanal, dimethyl disulfide and phenol; with the latter seeming to be closely related to breast cancer. Additionally, the challenges of analyzing urinary VOCs using MS-based techniques and translation to clinical utility are discussed. The outcome of this review may provide valuable information to future studies regarding cancer urinary VOCs.

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The Electroencephalography (EEG) is not just a mere clinical tool anymore. It has become the de-facto mobile, portable, non-invasive brain imaging sensor to harness brain information in real time. It is now being used to translate or decode brain signals, to diagnose diseases or to implement Brain Computer Interface (BCI) devices. The automatic decoding is mainly implemented by using quantitative algorithms to detect the cloaked information buried in the signal. However, clinical EEG is based intensively on waveforms and the structure of signal plots. Hence, the purpose of this work is to establish a bridge to fill this gap by reviewing and describing the procedures that have been used to detect patterns in the electroencephalographic waveforms, benchmarking them on a controlled pseudo-real dataset of a P300-Based BCI Speller and verifying their performance on a public dataset of a BCI Competition.

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OBJECTIVE: We developed a new minimally invasive method for intracranial pressure monitoring (ICPMI). The objective of this project is to verify the similarities between the ICPMI and the invasive method (ICPInv), for different components of the intracranial pressure signal-namely, the mean value (trend) as well as its pulsatile component. MATERIALS AND METHODS: A 9 kg anesthetized pig was used for simultaneous ICP monitoring with both methods. ICP was increased by performing ten infusions of 6 ml 0.9% saline into the spinal subarachnoid space, using a catheter implanted in the lumbar region. For correlation analysis, the signals were decomposed into two components-trend and pulsatile signals. Pearson correlation coefficient was calculated between ICPInv and ICPMI. RESULTS: During the infusions, the correlation between the pulsatile components of the signals was above 0.5 for most of the time. The signal trends showed a good agreement (correlation above 0.5) for most of the time during infusions. CONCLUSIONS: The ICPMI signal trends showed a good linear agreement with the signal obtained invasively. Based on the waveform analysis of the pulsatile component of ICP, our results indicate the possibility of using the minimally invasive method for assessing the neuroclinical state of the patient.

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