RESUMEN

PURPOSE: Individuals with walking impairment, such as those with cerebral palsy, often face challenges in leading physically active lives due to the high energy cost of movement. Assistive devices like powered exoskeletons aim to alleviate this burden and improve mobility. Traditionally, optimizing the effectiveness of such devices has relied on time-consuming laboratory-based measurements of energy expenditure, which may not be feasible for some patient populations. To address this, our study aimed to enhance the state-of-the-art predictive model for estimating steady-state metabolic rate from 2-min walking trials to include individuals with and without walking disabilities and for a variety of terrains and wearable device conditions. METHODS: Using over 200 walking trials collected from eight prior exoskeleton-related studies, we trained a simple linear machine learning model to predict metabolic power at steady state based on condition-specific factors, such as whether the trial was conducted on a treadmill (level or incline) or outdoors, as well as demographic information, such as the participant's weight or presence of walking impairment, and 2 minutes of metabolic data. RESULTS: We demonstrated the ability to predict steady-state metabolic rate to within an accuracy of 4.71 ± 2.7% on average across all walking conditions and patient populations, including with assistive devices and on different terrains. CONCLUSION: This work seeks to unlock the use of in-the-loop optimization of wearable assistive devices in individuals with limited walking capacity. A freely available MATLAB application allows other researchers to easily apply our model.

RESUMEN

Brain-computer interface (BCI) based on steady-state visual evoked potential (SSVEP) have attracted much attention in the field of intelligent robotics. Traditional SSVEP-based BCI systems mostly use synchronized triggers without identifying whether the user is in the control or non-control state, resulting in a system that lacks autonomous control capability. Therefore, this paper proposed a SSVEP asynchronous state recognition method, which constructs an asynchronous state recognition model by fusing multiple time-frequency domain features of electroencephalographic (EEG) signals and combining with a linear discriminant analysis (LDA) to improve the accuracy of SSVEP asynchronous state recognition. Furthermore, addressing the control needs of disabled individuals in multitasking scenarios, a brain-machine fusion system based on SSVEP-BCI asynchronous cooperative control was developed. This system enabled the collaborative control of wearable manipulator and robotic arm, where the robotic arm acts as a "third hand", offering significant advantages in complex environments. The experimental results showed that using the SSVEP asynchronous control algorithm and brain-computer fusion system proposed in this paper could assist users to complete multitasking cooperative operations. The average accuracy of user intent recognition in online control experiments was 93.0%, which provides a theoretical and practical basis for the practical application of the asynchronous SSVEP-BCI system.

Asunto(s)

RESUMEN

This study investigates a brain-computer interface (BCI) system based on an augmented reality (AR) environment and steady-state visual evoked potentials (SSVEP). The system is designed to facilitate the selection of real-world objects through visual gaze in real-life scenarios. By integrating object detection technology and AR technology, the system augmented real objects with visual enhancements, providing users with visual stimuli that induced corresponding brain signals. SSVEP technology was then utilized to interpret these brain signals and identify the objects that users focused on. Additionally, an adaptive dynamic time-window-based filter bank canonical correlation analysis was employed to rapidly parse the subjects' brain signals. Experimental results indicated that the system could effectively recognize SSVEP signals, achieving an average accuracy rate of 90.6% in visual target identification. This system extends the application of SSVEP signals to real-life scenarios, demonstrating feasibility and efficacy in assisting individuals with mobility impairments and physical disabilities in object selection tasks.

Asunto(s)

RESUMEN

The purpose of this study was to confirm that blood lactate concentrations can be maintained at moderate to high steady state values during an entire interval training (IT) session (repetitions + rest). Forty-eight trained swimmers and track athletes performed four IT protocols consisting of 6-10 bouts between 1 and 3-min at ~5-10 mmol/L blood lactate concentrations with a passive recovery of 60 to 180-sec. Performance times were measured at every bout, while blood lactate concentrations and heart rate during recovery every other bout. One-way ANOVA was performed for comparisons and r-squared for the effect size (ES). Performance times were stable throughout each IT protocol (75 ± 8 and 77 ± 5-sec [swimmers and track athletes]; 67 ± 3-sec [swimmers]; 64 ± 3-sec [swimmers]; and 135 ± 6-sec [swimmers]). Despite some minor differences (p<0.05; ES, 0.28 to 0.37, large), blood lactate concentrations were maintained stable at moderate to high values during each IT protocol (5.85 ± 1.47 mmol/L; 5.64 ± 1.03 mmol/L; 9.29 ± 1.07 mmol/L; and 9.44 ± 1.12 mmol/L). HR decreased significantly from the beginning to the end of recovery (p<0.05; ES, 0.93 to 0.96, large). In conclusion, moderate to high blood lactate steady state concentrations can be sustained for ~20 to 60-min during an entire IT session (repetitions + rest) at a stable performance. This approach can optimize performance by stimulating the metabolic demands and the pace strategy during the middle section of endurance competitive events.

RESUMEN

Objective.Steady-state visual evoked potentials (SSVEPs) in response to flickering stimuli are popular in brain-computer interfacing but their implementation in virtual reality (VR) offers new opportunities also for clinical applications. While traditional SSVEP target selection relies on single-frequency stimulation of both eyes simultaneously, further called congruent stimulation, recent studies attempted to improve the information transfer rate by using dual-frequency-coded SSVEP where each eye is presented with a stimulus flickering at a different frequency, further called incongruent stimulation. However, few studies have investigated incongruent multifrequency-coded SSVEP (MultiIncong-SSVEP).Approach.This paper reports on a systematical investigation of incongruent dual-, triple-, and quadruple-frequency-coded SSVEP for use in VR, several of which are entirely novel, and compares their performance with that of congruent dual-frequency-coded SSVEP.Main results.We were able to confirm the presence of a summation effect when comparing monocular- and binocular single-frequency congruent stimulation, and a suppression effect when comparing monocular- and binocular dual-frequency incongruent stimulation, as both tap into the binocular vision capabilities which, when hampered, could signal amblyopia.Significance.In sum, our findings not only evidence the potential of VR-based binocularly incongruent SSVEP but also underscore the importance of paradigm choice and decoder design to optimize system performance and user comfort.

Asunto(s)

RESUMEN

Bioaugmentation regimes (i.e., dosage, repetition, and timing) in AD must be optimized to ensure their effectiveness. Although previous studies have investigated these aspects, most have focused exclusively on short-term effects, with some reporting conflicting conclusions. Here, AD experiments of three consecutive repeated batches were conducted to determine the effect of bioaugmentation regimes under ammonium/salt inhibition conditions. A positive correlation between reactor performance and inoculum dosage was confirmed in the first batch, which diminished in subsequent batches for both inhibitors. Moreover, a diminishing marginal effect was observed with repeated inoculum introduction. While the bacterial community largely influenced the reactor performance, the archaeal community exhibited only a minor impact. Prediction of the key enzyme abundances suggested an overall decline in different AD steps. Overall, repeated batch experiments revealed that a homogeneous bacterial community deteriorated the AD process during long-term operation. Thus, a balanced bacterial community is key for efficient methane production.

RESUMEN

Quantum entanglement is essential in performing many quantum information tasks. Here, we theoretically investigate the stationary entanglement between a Laguerre-Gaussian (LG) cavity field and a rotating end mirror in an LG-cavity optorotational system with a nonlinear cross-Kerr (CK) interaction and a degenerate optical parametric amplifier (OPA). We calculate the logarithmic negativity of the system to quantify the stationary entanglement. We examine the influence of various system parameters such as the cavity detuning, the strength of the nonlinear CK interaction, the parametric gain and phase of the OPA, the power of the input Gaussian laser, the topological charge of the LG-cavity field, the mass of the rotating end mirror, and the ambient temperature on the stationary entanglement. Under the combined effect of the nonlinear CK interaction and the OPA, we find that the stationary entanglement can be substantially enhanced at lower Gaussian laser powers, smaller topological charges of the LG-cavity field, and larger masses of the rotating end mirror. We show that the combination of the nonlinear CK interaction and the OPA can make the stationary entanglement more robust against the ambient temperature.

RESUMEN

Human primary visual cortex (V1) responds more strongly, or resonates, when exposed to ∼10, ∼15-20, and ∼40-50 Hz rhythmic flickering light. Full-field flicker also evokes the perception of hallucinatory geometric patterns, which mathematical models explain as standing-wave formations emerging from periodic forcing at resonant frequencies of the simulated neural network. However, empirical evidence for such flicker-induced standing waves in the visual cortex was missing. We recorded cortical responses to flicker in awake mice using high-spatial-resolution widefield imaging in combination with high-temporal-resolution glutamate-sensing fluorescent reporter (iGluSnFR). The temporal frequency tuning curves in the mouse V1 were similar to those observed in humans, showing a banded structure with multiple resonance peaks (8, 15, and 33 Hz). Spatially, all flicker frequencies evoked responses in V1 corresponding to retinotopic stimulus location, but some evoked additional peaks. These flicker-induced cortical patterns displayed standing-wave characteristics and matched linear wave equation solutions in an area restricted to the visual cortex. Taken together, the interaction of periodic traveling waves with cortical area boundaries leads to spatiotemporal activity patterns that may affect perception.

RESUMEN

Unlike other natural disasters, drought is one of the most severe threats to all living beings globally. Due to global climate change, the frequency and duration of droughts have increased in many parts of the world. Therefore, accurate prediction and forecasting of droughts are essential for effective mitigation policies and sustainable research. In recent research, the use of ensemble global climate models (GCMs) for simulating precipitation data is common. The objective of this research is to enhance the multi-model ensemble (MME) for improving future drought characterizations. In this research, we propose the use of relative importance metric (RIM) to address collinearity effects and point-wise discrepancy weights (PWDW) in GCMs. Consequently, this paper introduces a new statistical framework for weighted ensembles called the discrepancy-enhanced beta weighting ensemble (DEBWE). DEBWE enhances the weighted ensemble data of precipitation simulated by multiple GCMs. In DEBWE, we addressed uncertainties in GCMs arising from collinearity and outliers. To evaluate the effectiveness of the proposed weighting framework, we compared its performance with the simple average multi-model ensemble (SAMME), Taylor skill score ensemble (TSSE), and mutual information ensemble (MIE). Based on the Kling-Gupta efficiency (KGE) metric, DEBWE outperforms all competitors across all evaluation criteria. These inferences are based on the analysis of historical simulated data from 22 GCMs in the CMIP6 project. The quantitative performance indicators strongly support the superiority of DEBWE. The median and mean KGE values for DEBWE are 0.2650 and 0.2429, compared to SAMME (0.1000, 0.0991), TSSE (0.2600, 0.2397), and MIE (0.1550, 0.1511). For drought assessment, we computed the adaptive standardized precipitation index (SPI) for three future scenarios: SSP1-2.6, SSP2-4.5, and SSP5-8.5. The steady-state probabilities suggest that normal drought (ND) is the most frequent condition, with extreme events (dry or wet) being less probable.

Asunto(s)

RESUMEN

Objective.Potential usage of dry electrodes in emerging applications such as wearable devices, flexible tattoo circuits, and stretchable displays requires that, to become practical solutions, issues such as easy fabrication, strong durability, and low-cost materials must be addressed. The objective of this study was to propose soft and dry electrodes developed from polydimethylsiloxane (PDMS) and carbon nanotube (CNT) composites.Approach.The electrodes were connected with both conventional and in-house NTAmp biosignal instruments for comparative studies. The performances of the proposed dry electrodes were evaluated through electromyogram, electrocardiogram, and electroencephalogram measurements.Main results.Results demonstrated that the capability of the PDMS/CNT electrodes to receive biosignals was on par with that of commercial electrodes (adhesive and gold-cup electrodes). Depending on the type of stimuli, a signal-to-noise ratio of 5-10 dB range was achieved.Significance.The results of the study show that the performance of the proposed dry electrode is comparable to that of commercial electrodes, offering possibilities for diverse applications. These applications may include the physical examination of vital medical signs, the control of intelligent devices and robots, and the transmission of signals through flexible materials.

Asunto(s)

RESUMEN

Open heart surgery requires a proper understanding of the endocardial surface of the heart and vascular structures. While modern four-dimensional (4D) imaging enables excellent dynamic visualization of the blood pool, endocardial surface anatomy has not routinely been assessed. 4D image data were post-processed using commercially available virtual reality (VR) software. Using thresholding, the blood pool was segmented dynamically across the imaging volume. The segmented blood pool was further edited for correction of errors due to artifacts or inhomogeneous signal intensity. Then, a surface shell of an even thickness was added to the edited blood pool. When the cardiac valve leaflets and chordae were visualized, they were segmented separately using a different range of signal intensity for thresholding. Using an interactive cutting plane, the endocardial surface anatomy was reviewed from multiple perspectives by interactively applying a cutting plane, rotating and moving the model. In conclusions, dynamic three-dimensional (3D) endocardial surface imaging is feasible and provides realistic simulated views of the intraoperative scenes at open heart surgery. As VR is based on the use of all fingers of both hands, the efficiency and speed of postprocessing are markedly enhanced. Although it is limited, visualization of the cardiac valve leaflets and chordae is also possible.

RESUMEN

This paper evaluates the performance of two different types of long combination vehicles (A-double and DuoCAT) using naturalistic driving data across four scenarios: lane changes, manoeuvring through roundabouts, turning in intersections, and negotiating tight curves. Four different performance-based standards measures are used to assess the stability and tracking performance of the vehicles: rearward amplification, high-speed transient offtracking, low-speed swept path, and high-speed steady-state offtracking. Also, the steering reversal rate metric is employed to estimate the cognitive workload of the drivers in low-speed scenarios. In the majority of the identified cases of the four scenarios, both combination types have a good performance. The A-double shows slightly better stability in high-speed lane changes, while the DuoCAT has slightly better manoeuvrability at low-speed scenarios like roundabouts and intersections.

Asunto(s)

RESUMEN

Task-related studies have consistently reported that listening to speech sounds activate the temporal and prefrontal regions of the brain. However, it is not well understood how functional organization of auditory and language networks differ when processing speech sounds from its resting state form. The knowledge of language network organization in typically developing infants could serve as an important biomarker to understand network-level disruptions expected in infants with hearing impairment. We hypothesized that topological differences of language networks can be characterized using functional connectivity measures in two experimental conditions (1) complete silence (resting) and (2) in response to repetitive continuous speech sounds (steady). Thirty normal-hearing infants (14 males and 16 females, age: 7.8 ± 4.8 months) were recruited in this study. Brain activity was recorded from bilateral temporal and prefrontal regions associated with speech and language processing for two experimental conditions: resting and steady states. Topological differences of functional language networks were characterized using graph theoretical analysis. The normalized global efficiency and clustering coefficient were used as measures of functional integration and segregation, respectively. We found that overall, language networks of infants demonstrate the economic small-world organization in both resting and steady states. Moreover, language networks exhibited significantly higher functional integration and significantly lower functional segregation in resting state compared to steady state. A secondary analysis that investigated developmental effects of infants aged 6-months or below and above 6-months revealed that such topological differences in functional integration and segregation across resting and steady states can be reliably detected after the first 6-months of life. The higher functional integration observed in resting state suggests that language networks of infants facilitate more efficient parallel information processing across distributed language regions in the absence of speech stimuli. Moreover, higher functional segregation in steady state indicates that the speech information processing occurs within densely interconnected specialized regions in the language network.

Asunto(s)

RESUMEN

Schizophrenia is believed to be, at least in part, a dysfunction of the glutamatergic system. In line with anatomical evidence, suppressing N-methyl-D-aspartate (NMDA) neurotransmission leads to symptoms that are characteristic of schizophrenia. Rodent models of schizophrenia often involve the acute application of NMDA antagonists, which produce both behavioural and brain activity changes that closely resemble symptoms observed in schizophrenia. It is, however, important to note that the full spectrum of schizophrenia symptoms may not be manifested following the acute suppression of NMDA receptors. This has led to the proposal of a chronic model where NMDA receptors are suppressed for prolonged periods. Although the chronic model has shown promising results from a behavioural perspective and alterations in metabolic processes in the brain, its impact on brain oscillations remains largely unknown. The aim of this study is to examine the impact of acute and chronic NMDA neurotransmission suppression on brains' oscillatory activity. To achieve this, chronic brain activity recordings in mice of both sexes were used to assess both spontaneous and evoked brain oscillations. The study demonstrates that an acute suppression of NMDA receptors alters brain oscillations across a wide frequency spectrum and diminishes the oscillatory potency in evoked responses, paralleling changes observed in schizophrenia. However, the chronic suppression of NMDA receptors did not have the expected cumulative effect on brain activity. This research highlights the robust yet similar impacts of acute and chronic NMDA receptor suppression on brain activity, contributing to the nuanced understanding of rodent models of schizophrenia.

RESUMEN

PURPOSE: Although Ω-plot-driven quantification of in vivo amide exchange properties has been demonstrated, differences in scan parameters may complicate the fidelity of determination. This work systematically evaluated the use of quasi-steady-state (QUASS) Z-spectra reconstruction to standardize in vivo amide exchange quantification across acquisition conditions and further determined it in vivo. METHODS: Simulation and in vivo rodent brain chemical exchange saturation transfer (CEST) data at 4.7 T were fit with and without QUASS reconstruction using both multi-Lorentzian and model-based fitting approaches. pH modulation was accomplished both in simulation and in vivo by inducing global ischemia via cardiac arrest. Amide parameters were determined via Ω-plots and compared across methods. RESULTS: Simulation showed that Ω-plots using multi-Lorentzian fitting could underestimate the exchange rate, with error increasing as conditions diverged from the steady state. In comparison, model-based fitting using QUASS estimated the same exchange rate within 2%. These results aligned with in vivo findings where multi-Lorentzian fitting of native Z-spectra resulted in an exchange rate of 64 ± 13 s-1 (38 ± 16 s-1 after cardiac arrest), whereas model-based fitting of QUASS Z-spectra yielded an exchange rate of 126 ± 25 s-1 (49 ± 13 s-1). CONCLUSION: The model-based fitting of QUASS CEST Z-spectra enables consistent and accurate quantification of exchange parameters through Ω-plot construction by reducing error due to signal overlap and nonequilibrium CEST effects.

RESUMEN

Fibromyalgia (FM) patients present impaired cardiac autonomic regulation during maximal exercise; however, it is unknown whether these alterations also manifest during submaximal exercise. The aim of this study was to compare the on-transient heart rate (HR) response and HR variability during a constant-load submaximal cycling exercise between FM and control (CON) women. Ten women with FM (age: 45.2±9.3 years) and 10 age-matched CON women (age: 48.4±6.1 years) performed a 15-min cycling exercise, with the work rate fixed at 50% of the individual peak power output attained in a maximal graded exercise test. The time intervals between consecutive heartbeats were recorded regularly during the exercise for subsequent analysis of on-transient HR response and HR variability indices. The on-transient HR time constant was similar (P=0.83) between the FM (41.0±14.1 sec) and CON (42.2±10.4 sec). During the 5-10 and 10-15 min of exercise, HR variability indices indicating sympathetic and parasympathetic activities were similar (P>0.05) between FM and CON groups. In conclusion, women with FM presented a normal cardiac autonomic response to submaximal cycling exercise. These findings have clinical relevance, as submaximal exercises are commonly prescribed for FM patients.

RESUMEN

Mutations in SCN4A gene encoding Nav1.4 channel α-subunit, are known to cause neuromuscular disorders such as myotonia or paralysis. Here, we study the effect of two amino acid replacements, K1302Q and G1306E, in the DIII-IV loop of the channel, corresponding to mutations found in patients with myotonia. We combine clinical, electrophysiological, and molecular modeling data to provide a holistic picture of the molecular mechanisms operating in mutant channels and eventually leading to pathology. We analyze the existing clinical data for patients with the K1302Q substitution, which was reported for adults with or without myotonia phenotypes, and report two new unrelated patients with the G1306E substitution, who presented with severe neonatal episodic laryngospasm and childhood-onset myotonia. We provide a functional analysis of the mutant channels by expressing Nav1.4 α-subunit in Xenopus oocytes in combination with ß1 subunit and recording sodium currents using two-electrode voltage clamp. The K1302Q variant exhibits abnormal voltage dependence of steady-state fast inactivation, being the likely cause of pathology. K1302Q does not lead to decelerated fast inactivation, unlike several other myotonic mutations such as G1306E. For both mutants, we observe increased window currents corresponding to a larger population of channels available for activation. To elaborate the structural rationale for our experimental data, we explore the contacts involving K/Q1302 and E1306 in the AlphaFold2 model of wild-type Nav1.4 and Monte Carlo-minimized models of mutant channels. Our data provide the missing evidence to support the classification of K1302Q variant as likely pathogenic and may be used by clinicians.

Asunto(s)

RESUMEN

As the basis of musical emotions, dynamic tension experience is felt by listeners as music unfolds over time. The effects of musical harmonic and melodic structures on tension have been widely investigated, however, the potential roles of metrical structures in tension perception remain largely unexplored. This experiment examined how different metrical structures affect tension experience and explored the underlying neural activities. The electroencephalogram (EEG) was recorded and subjective tension was rated simultaneously while participants listened to music meter sequences. On large time scale of whole meter sequences, it was found that different overall tension and low-frequency (1 ~ 4 Hz) steady-state evoked potentials were elicited by metrical structures with different periods of strong beats, and the higher overall tension was associated with metrical structure with the shorter intervals between strong beats. On small time scale of measures, dynamic tension fluctuations within measures was found to be associated with the periodic modulations of high-frequency (10 ~ 25 Hz) neural activities. The comparisons between the same beats within measures and across different meters both on small and large time scales verified the contextual effects of meter on tension induced by beats. Our findings suggest that the overall tension is determined by temporal intervals between strong beats, and the dynamic tension experience may arise from cognitive processing of hierarchical temporal expectation and attention, which are discussed under the theoretical frameworks of metrical hierarchy, musical expectation and dynamic attention.

RESUMEN

Multivariate synchronization index (MSI), as an effective recognition algorithm for steady-state visual evoked potential (SSVEP) brain-computer interface (BCI), can accurately decode target frequencies without training. To further consider temporal features or extract harmonic components, extended MSI (EMSI), temporally local MSI (TMSI), and filter bank MSI (FBMSI) have been proposed. However, the promotion effects of the above three strategies on MSI have not been compared in detail. In this paper, the performance of EMSI, TMSI, and FBMSI under different time windows was analyzed with the same dataset. The results indicated that the improvement effect of the temporally local method on MSI was better than that of the other two methods under the short time window, and the effect of the filter bank method was better when the time window was greater than 0.8 s. Based on the idea of simultaneously extracting time-frequency features, FBEMSI and FBTMSI were proposed by integrating time delay embedding and temporally local method into FBMSI respectively. The two improved methods, which has no significant difference, can improve the recognition effect of FBMSI. But the computing time of FBEMSI was shorter, which can be a potential method for SSVEP-BCI.

RESUMEN

This study aimed to explore the effect of various noise definition criteria in linear extrapolation technique to noise level baseline on steady-state visual evoked potential (SSVEP)-based visual acuity assessment. Four noise definition criteria on frequency-domain, i.e., the mean amplitude at the two adjacent bins of the target frequency, the mean amplitude of a narrow frequency band on either side of the target frequency, the mean amplitude at a broad frequency band except for the target frequency and its harmonic frequencies, and the mean amplitude at a broad frequency band at resting state, corresponding to noise 1, noise 2, noise 3, and noise 4, were introduced to calculate noise level baselines. Then, two experiments were implemented. In experiment 1, electroencephalography (EEG) signals of resting state were recorded for fourteen subjects. In experiment 2, the visual stimuli of vertical sinusoidal gratings at six spatial frequency steps were used to induce SSVEPs for twelve subjects. Finally, SSVEP visual acuity was obtained via the SSVEP visual acuity threshold estimation of linear extrapolation technique to noise level baseline with various noise definition criteria. The bland-Altman analysis found that the difference between subjective Freiburg Visual Acuity and Contrast Test (FrACT) and objective SSVEP visual acuity was - 0.0892, - 0.1071, - 0.0745, and - 0.0804 logMAR and the 95% limit of agreement was 0.2150, 0.2146, 0.2046, and 0.2189 logMAR for noise 1, noise 2, noise 3, and noise 4, respectively, indicating that visual acuity of noise 3 definition criterion, i.e., the mean amplitude at a broad frequency band except for the target frequency and its harmonic frequencies, showed the best performance. This study recommended noise definition criterion 3 of the mean amplitude at a broad frequency band to calculate the noise level baseline in the linear extrapolation of SSVEP-based visual acuity assessment.