Design of a brain-machine interface for reducing false activations of a lower-limb exoskeleton based on error related potential.

BACKGROUND AND OBJECTIVE: Brain-Machine Interfaces (BMIs) based on a motor imagination paradigm provide an intuitive approach for the exoskeleton control during gait. However, their clinical applicability remains difficulted by accuracy limitations and sensitivity to false activations. A proposed improvement involves integrating the BMI with methods based on detecting Error Related Potentials (ErrP) to self-tune erroneous commands and enhance not only the system accuracy, but also its usability. The aim of the current research is to characterize the ErrP at the beginning of the gait with a lower limb exoskeleton to reduce the false starts in the BMI system. Furthermore, this study is valuable for determining which type of feedback, Tactile, Visual, or Visuo-Tactile, achieves the best performance in evoking and detecting the ErrP. METHODS: The initial phase of the research concentrates on detecting ErrP at the beginning of gait to improve the efficiency of an asynchronous BMI based on motor imagery (BMI-MI) to control a lower limb exoskeleton. Initially, an experimental protocol is designed to evoke ErrP at the start of gait, employing three different stimuli: Tactile, Visual, and Visuo-Tactile. An iterative selection process is then utilized to characterize ErrP in both time and frequency domains and fine-tune various parameters, including electrode distribution, feature combinations, and classifiers. A generic classifier with 6 subjects is employed to configure an ensemble classification system for detecting ErrP and reducing the false starts. RESULTS: The ensembled system configured with the selected parameters yields an average correction of false starts of 72.60 % ± 10.23, highlighting its corrective efficacy. Tactile feedback emerges as the most effective stimulus, outperforming Visual and Visuo-Tactile feedback in both training types. CONCLUSIONS: The results suggest promising prospects for reducing the false starts when integrating ErrP with BMI-MI, employing Tactile feedback. Consequently, the security of the system is enhanced. Subsequent, further research efforts will focus on detecting error potential during movement for gait stop, in order to limit undesired stops.

Analysis of Error Potentials generated by a lower limb exoskeleton feedback in a BMI for gait control.

Brain-machine interfaces (BMIs) based on motor imagery (MI) for controlling lower-limb exoskeletons during the gait have been gaining importance in the rehabilitation field. However, these MI-BMI are not as precise as they should. The detection of error related potentials (ErrP) as a self-tune parameter to prevent wrong commands could be an interesting approach to improve their performance. For this reason, in this investigation ErrP elicited by the movement of a lower-limb exoskeleton against subject's will is analyzed in the time, frequency and time-frequency domain and compared with the cases where the exoskeleton is correctly commanded by motor imagery (MI). The results of the ErrP study indicate that there is statistical significative evidence of a difference between the signals in the erroneous events and the success events. Thus, ErrP could be used to increase the accuracy of BMIs which commands exoskeletons.Clinical Relevance- This investigation has the purpose of improving brain-machine interfaces (BMIs) based on motor imagery (MI) by means of the detection of error potentials. This could promote the adoption of robotic exoskeletons commanded by BMIs in rehabilitation therapies.

Transfer Learning with CNN Models for Brain-Machine Interfaces to command lower-limb exoskeletons: A Solution for Limited Data.

This study evaluates the performance of two convolutional neural networks (CNNs) in a brain-machine interface (BMI) based on motor imagery (MI) by using a small dataset collected from five participants wearing a lower-limb exoskeleton. To address the issue of limited data availability, transfer learning was employed by training models on EEG signals from other subjects and subsequently fine-tuning them to specific users. A combination of common spatial patterns (CSP) and linear discriminant analysis (LDA) was used as a benchmark for comparison. The study's primary aim is to examine the potential of CNNs and transfer learning in the development of an automatic neural classification system for a BMI based on MI to command a lower-limb exoskeleton that can be used by individuals without specialized training.Clinical Relevance- BMI can be used in rehabilitation for patients with motor impairment by using mental simulation of movement to activate robotic exoskeletons. This can promote neural plasticity and aid in recovery.

Mejora de la adherencia al tratamiento en el paciente con síndrome metabólico / Improving adherence to treatment in the patient with metabolic syndrome

JUSTIFICACIÓN: síndrome metabólico se puede definir como un conjunto de trastornos metabólicos asociados al desarrollo de enfermedad cardiovascular aterosclerótica. Está asociado a múltiples factores de riesgo cardiovascular entre los que destacan diabetes mellitus tipo II, hipertensión arterial y dislipemia. Debido a la gran variedad de factores de riesgo implicados en el desarrollo de síndrome metabólico, el tratamiento tiene varios objetivos, como promover estilos de vida saludables, disminuir la obesidad visceral y controlar las patologías asociadas que se relacionan con un mayor riesgo cardiovascular. Existen varias alternativas que incluyen en primer lugar cambios enfocados en la disminución de peso y aumento de la actividad física mediante dieta y ejercicio. En aquellos casos en los que sea necesario es fundamental la combinación con fármacos. Hasta el momento, no existe un tratamiento farmacológico único para el síndrome metabólico, se trata cada componente por separado mediante terapia combinada con el objetivo de disminuir el desarrollo de eventos cardiovasculares.OBJETIVOS: el principal objetivo de este trabajo es el tratamiento de pacientes con síndrome metabólico mediante la administración de una única dosis que engloba el tratamiento de cada una de las patologías asociadas, de este modo, se disminuye el número de administraciones mejorando la adherencia al tratamiento y facilitando la deglución en aquellos pacientes en los que se vea más limitada.MATERIALES Y METODOS: el tratamiento en dosis única se lleva a cabo mediante el desarrollo de tres minicomprimidos incluidos en una cápsula. Los fármacos seleccionados fueron hipolipemiantes, antihipertensivos y fármacos insulinosensibilizadores, en concreto, rosuvastatina, olmesartan y repaglinida, respectivamente. (AU)

El farmacéutico y la alimentación del paciente oncológico / The pharmacist and nutrition for cancer patients

JUSTIFICACIÓN: el farmacéutico tiene que ser parte activa en el tratamiento y recuperación del paciente oncológico, y puede convertirse en una pieza clave en el cuidado pluridisciplinar de estos pacientes. La desnutrición se asocia a esta enfermedad por factores relacionados con las particularidades del paciente, el tumor o los tratamientos. La desnutrición empeora la evolución clínica de estos pacientes, por ello se debe actuar promoviendo una modificación y adaptación de la dieta a cada situación patológica y necesidad del paciente. Muchos de los tratamientos oncológicos pueden producir efectos adversos gastrointestinales, como mucositis, diarreas y malabsorción, íleo paralítico, náuseas y vómitos, y dolor abdominal. Por todo ello, resulta de especial importancia la inclusión de intervenciones nutricionales.OBJETIVOS: el objetivo de esta comunicación es impulsar la atención farmacéutica del profesional de farmacia en el asesoramiento de la nutrición de las personas con cáncer.MATERIALES Y METODOS: para el presente trabajo se ha realizado una revisión de la literatura sobre la actuación nutricional en pacientes oncológicos desde la farmacia comunitaria. (AU)

Effect of heating rate on MgB4O7:Tm,Dy glow curve and its kinetic parameters calculated with different methods.

This paper presents the results of a long experimental work carried out to study the influence of the heating rate (H.R.) on thermally stimulated light emission phenomenon, well known as thermoluminescence (TL) of MgB4O7 activated by Tm and Dy ions (MgB4O7:Tm.Dy) in pellet form. The kinetics parameters, i.e. the activation energy, E, the frequency factor, s, the kinetics order, b and the number of trapped electrons, n0, were determined using the algorithm of sequential quadratic programming glow curve deconvolution (SQPGCD). The results obtained for the kinetics parameters, were compared with those obtained by other methods like Initial Rise (IR), Chen General-Order Kinetics (PS-GOK) and variable heating rate (VHR). These results suggest that SQPGCD method gives more accurate kinetics parameters values for the experimental glow curves.

Monte Carlo calculation of charge collection efficiencies in ionization chambers.

Collection efficiency is an important quantity in dosimetry with ionization chambers. It can be calculated by solving a hyperbolic system of partial differential equations. This system can be solved only in few, simple, idealized geometries, but for more realistic designs an analytical resolution is no longer possible. In the present work a Monte Carlo scheme that could permit to calculate the collection efficiency for any ionization chamber geometry is proposed. This scheme has been tested against Boag's approach for three chambers with plane-parallel, cylindrical and spherical geometries, operated in the recombination regime. The results obtained in the full Monte Carlo simulation closely agree with the Boag's ones for the three ideal geometries considered. The largest relative difference, ∼0.3%, has been found for the plane-parallel chamber in case of 50 V, the lowest potential difference investigated in this study. Results appear to be stable against changes in the chamber volume, the ion mobility and the recombination constant. The method proposed could be a useful tool to calculate collection efficiencies of ionization chambers, provided the electric field inside them is known.

Minimum clinically important differences for the Functioning Assessment Short Test and a battery of neuropsychological tests in bipolar disorders: results from the FACE-BD cohort.

AIMS: Establishing the minimum clinically important difference (MCID) in functioning and cognition is essential to the interpretation of the research and clinical work conducted in bipolar disorders (BD). The present study aimed to estimate the MCID for the Functioning Assessment Short Test (FAST) and a battery of neuropsychological tests in BD. METHODS: Anchor-based and distributive methods were used to estimate the MCID for the FAST and cognition using data from a large, multicentre, observational cohort of individuals with BD. The FAST and cognition were linked with the Clinical Global Impressions Scale-Severity (CGI-S) and Global Assessment of Functioning (GAF) using an equipercentile method. The magnitude of the standard error measurement (s.e.m.) provided another estimate of the MCID. RESULTS: In total, 570 participants were followed for 2 years. Cross-sectional CGI-S and GAF scores were linked to a threshold ⩽7 on the FAST for functional remission. The MCID for the FAST equalled 8- or 9-points change from baseline using the CGI-S and GAF. One s.e.m. on the FAST corresponded to 7.6-points change from baseline. Cognitive variables insufficiently correlated with anchor variables (all ρ <0.3). One s.e.m. for cognitive variables corresponded to a range of 0.45 to 0.93-s.d. change from baseline. CONCLUSIONS: These findings support the value of the estimated MCID for the FAST and cognition and may be a useful tool to evaluate cognitive and functional remediation effects and improve patient functional outcomes in BD. The CGI-S and GAF were inappropriate anchors for cognition. Further studies may use performance-based measures of functioning instead.

The implications of hypersomnia in the context of major depression: Results from a large, international, observational study.

According to the DSM-5, "reduction in the need for sleep" is the only sleep-related criteria for mixed features in depressive episodes. We aimed at studying the prevalence, clinical correlates and the role of hypersomnia in a sample of acutely depressed patients. Secondarily, we factors significantly increasing the odds of hypersomnia were studied. We conducted a post-hoc analysis of the BRIDGE-II-Mix study. Variables were compared between patients with hypersomnia (SLEEP+) and with insomnia (SLEEP-) with standard bivariate tests. A stepwise backward logistic regression model was performed with SLEEP+ as dependent variable. A total of 2514 subjects were dichotomized into SLEEP+ (n = 423, 16.8%) and SLEEP- (n = 2091, 83.2%). SLEEP+ had significant higher rates of obese BMI (p < 0.001), BD diagnosis (p = 0.027), severe BD (p < 0.001), lifetime suicide attempts (p < 0.001), lower age at first depression (p = 0.004) than SLEEP-. Also, SLEEP+ had significantly poorer response to antidepressants (AD) such as (hypo)manic switches, AD resistance, affective lability, or irritability (all 0<0.005). Moreover, SLEEP+ had significantly higher rates of mixed-state specifiers than SLEEP- (all 0 < 0.006). A significant contribution to hypersomnia in our regression model was driven by metabolic-related features, such as "current bulimia" (OR = 4.21) and "overweight/obese BMI (OR = 1.42)". Globally, hypersomnia is associated with poor outcome in acute depression. Hypersomnia is strongly associated with mixed features and bipolarity. Metabolic aspects could influence the expression of hypersomnia, worsening the overall clinical outcome. Along with commonly used screening tools, detection of hypersomnia has potential, costless discriminative validity in the differential diagnosis unipolar and bipolar depression.

Functional neuroimaging in patients presenting with somatoform disorders: A model for investigating persisting symptoms after tick bites and post-treatment Lyme disease syndrome?

Approximately 10% of patients presenting with Lyme disease experience fatigue, musculoskeletal pain, concentration disorders, or short-term memory deficits in the six months following treatment. This entity has been defined as post-Lyme disease syndrome or post-treatment Lyme disease syndrome. The pathophysiology of this syndrome is unknown, but neither persistence of the bacterium nor effectiveness of antibiotics are currently reported in the literature. The French High Council for Public Health (French acronym HCSP) has recently defined a new entity called "persistent polymorphic symptoms after a tick bite" allowing for designing studies to better understand these subjective presentations, for which objective biomarkers are currently lacking. This entity encompasses patients experiencing fatigue and generalized pain in the months following a tick bite and can be associated with several subjective symptoms with major impact on the quality of life. In the field of somatoform disorders, this article reviews functional neuroimaging studies in patients presenting with subjective complaints and discusses potential clinical implications for persisting symptoms after tick bites and post-treatment Lyme disease syndrome.

The relationship between attention deficit hyperactivity disorder, bipolarity and mixed features in major depressive patients: Evidence from the BRIDGE-II-Mix Study.

OBJECTIVE: This study primarily focused on the relationship between comorbid attention deficit-hyperactivity disorder (ADHD), mixed features and bipolarity in major depressive patients. METHODS: The sample comprised 2777 patients with Major Depressive Episode (MDE) enrolled in a multicentre, multinational study originally designed to assess different definitions of mixed depression. Socio-demographic, familial and clinical characteristics were compared in patients with (ADHD + ) and without (ADHD-) comorbid ADHD. RESULTS: Sixty-one patients (2.2%) met criteria for ADHD. ADHD was associated with a higher number of (hypo)manic symptoms during depression. Mixed depression was more represented in ADHD + patients than in ADHD- using both DSM-5 and experimental criteria. Differences were maintained after removing overlapping symptoms between (hypo)mania and ADHD. ADHD in MDE was also associated with a variety of clinical and course features such as onset before the age of 20, first-degree family history of (hypo)mania, past history of antidepressant-induced (hypo)manic switches, higher number of depressive and affective episodes, atypical depressive features, higher rates of bipolarity specifier, psychiatric comorbidities with eating, anxiety and borderline personality disorders. LIMITATIONS: The study was primarily designed to address mixed features in ADHD, with slightly reduced sensitivity to the diagnosis of ADHD. Other possible diagnostic biases due to heterogeneity of participating clinicians. CONCLUSIONS: In a sample of major depressive patients, the comorbid diagnosis of current ADHD is associated with bipolar diathesis, mixed features, multiple psychiatric comorbidity and a more unstable course. Further prospective studies are necessary to confirm the possible mediating role of temperamental mood instability and emotional dysregulation in such a complex clinical presentation.

Effects of an Exoskeleton-Assisted Gait Motor Imagery Training in Functional Brain Connectivity.

Lower-limb exoskeletons have been used in gait rehabilitation to facilitate the restoration of motor skills. These robotics systems could be complemented by Brain-Computer Interfaces (BCIs) to assist or rehabilitate people with walking disabilities. In this preliminary study, electroencephalography-based brain functional connectivity is analyzed during exoskeleton-assisted gait motor imagery (MI) training. Partial Directed Coherence (PDC) analysis was employed to assess the exchange of information flow between EEG signals during gait MI in four healthy subjects, two using an exoskeleton and two without using it. Besides, in order to explore the functional connectivity, an outflow index based on the number of significant directed connectivities revealed by the PDC analysis is proposed. We found that the outflow index increases in the central zone (C2, C3, C4) while decreases in the central-parietal (CP1, CP2) and fronto-central (FC1) zones when the training was assisted by an exoskeleton. The results obtained can be useful to obtain informative features for BCI applications as well as in motor rehabilitation.

[Aripiprazole as dopamine partial agonist model: Basic concepts and clinical impact]. / L'aripiprazole comme modèle d'agoniste dopaminergique partiel : concepts de base et incidence clinique.

Aripiprazole may be viewed as the prototype of third-generation antipsychotics. This concept is based on the notion of D2 partial agonism, whereas all molecules of first-and second generation were D2 antagonists. After reviewing the basic pharmacological notions linked to such concepts, the mechanisms of action of these molecules are addressed, with a particular focus on functional selectivity and biased ligand. One of the essential pharmacological properties of D2 agonists, and particularity aripiprazole, is their ability to not induce D2 supersensitivity as well as to reverse this supersensitivity when it has been induced by D2 antagonists. In clinical practice, this impacts the choice of treatment in first episode psychosis as well as in refractory schizophrenia. Animal research shows that D2 supersensitivity could contribute to worsen addictive trends. The pharmacokinetic incidence of D2 supersensitivity tends to favour the long-acting forms of partial agonists. The notion of partial agonism could finally lead to design fourth-generation antipsychotics, on the basis on research focusing on functional selectivity.

Comparison of different EEG signal analysis techniques for an offline lower limb motor imagery brain-computer interface.

The use of motion assistance devices improves the rehabilitation process of patients that have motor disabilities. In the case these devices are controlled by brain-machine interfaces, the rehabilitation process can be improved due to neuroplasticity. However, in the case of lower limb rehabilitation, the limited accuracy of the control algorithms is a serious difficulty to overcome. In this research, different EEG signal's processing techniques, based on motor imagery, are tested for a brain-computer interface in an offline scenario, in order to detect the limitations of the models previous to its realtime implementation. The results reveal that motor imagery is very dependent on the subject and that Stockwell Transform provides the best accuracy among the models tested.

Novel tDCS montage favors lower limb motor imagery detection.

This work studies a novel transcranial direct current stimulation (tDCS) montage to improve a brain-machine interface (BMI) lower limb motor imagery detection. The tDCS montage is composed by two anodes and one cathode. One anode is located over the motor cortex and the other one over the cerebellum. Ten healthy subjects participated in this experiment. They were randomly separated into two groups: sham, which received a fake stimulation, and active tDCS, which received a real stimulation. Each subject was experimented on five consecutive days. Results pointed out that there was a significant difference $(p < 0 .05)$ in the classification accuracy between the sham and the active tDCS group. On each of the five days of the experiment the active tDCS group achieved better accuracy results than the sham group: 4%, 10%, 10%, 9% and 7% higher respectively.

Offline Lower-Limb Kinematic Decodification by Segments of EEG Signals.

In this work, hip and knee angles were decoded from low frequency EEG components recorded during the execution of two tasks. In order to compare their performance, three decoders based on multiple linear regression (MLR) models were applied under different conditions; which consisted in considering the processed data as a whole or divided into segments. Results suggest that, when the segments are related to specific tasks, the segmentation provides a better performance than applying the decoding method to unsegmented data.

Central nervous system modulates the neuromechanical delay in a broad range for the control of muscle force.

Force is generated by muscle units according to the neural activation sent by motor neurons. The motor unit is therefore the interface between the neural coding of movement and the musculotendinous system. Here we propose a method to accurately measure the latency between an estimate of the neural drive to muscle and force. Furthermore, we systematically investigate this latency, which we refer to as the neuromechanical delay (NMD), as a function of the rate of force generation. In two experimental sessions, eight men performed isometric finger abduction and ankle dorsiflexion sinusoidal contractions at three frequencies and peak-to-peak amplitudes {0.5, 1, and 1.5 Hz; 1, 5, and 10 of maximal force [%maximal voluntary contraction (MVC)]}, with a mean force of 10% MVC. The discharge timings of motor units of the first dorsal interosseous (FDI) and tibialis anterior (TA) muscle were identified by high-density surface EMG decomposition. The neural drive was estimated as the cumulative discharge timings of the identified motor units. The neural drive predicted 80 ± 0.4% of the force fluctuations and consistently anticipated force by 194.6 ± 55 ms (average across conditions and muscles). The NMD decreased nonlinearly with the rate of force generation ( R2 = 0.82 ± 0.07; exponential fitting) with a broad range of values (from 70 to 385 ms) and was 66 ± 0.01 ms shorter for the FDI than TA ( P < 0.001). In conclusion, we provided a method to estimate the delay between the neural control and force generation, and we showed that this delay is muscle-dependent and is modulated within a wide range by the central nervous system. NEW & NOTEWORTHY The motor unit is a neuromechanical interface that converts neural signals into mechanical force with a delay determined by neural and peripheral properties. Classically, this delay has been assessed from the muscle resting level or during electrically elicited contractions. In the present study, we introduce the neuromechanical delay as the latency between the neural drive to muscle and force during variable-force contractions, and we show that it is broadly modulated by the central nervous system.

Secular trends in the age at onset of bipolar I disorder - Support for birth cohort effects from interational, multi-centre clinical observational studies.

OBJECTIVE: To examine any association of birth decade, sex and exposure to alcohol and/or substance use disorders (ASUD) with age at onset (AAO) of bipolar I disorder (BD-I). METHODS: Using data from a representative clinical sample of 3896 BD-I cases recruited from 14 European countries, we examined AAO distributions in individuals born in consecutive birth decades. Cumulative probabilities with Mantel-Cox log-rank tests, pairwise comparisons and Odds Ratios (OR) with 95% confidence intervals (95% CI) were employed to analyze AAO according to birth decade, sex, and presence or absence of an ASUD. RESULTS: In the total sample, median AAO of BD-I decreased from about 41 years for those born in the 1930s to about 26 years for those born in the 1960s. In a sub-sample of 1247 individuals (selected to minimize confounding), AAO significantly decreased for males and females born in each consecutive decade between 1930 and 50 (OR: 0.65; 95% CI: 0.51, 0.81), and for cases with an ASUD as compared to without (OR: 0.77, 95% CI: 0.69, 0.87). The best fitting regression model identified an independent effect for each birth decade and an interaction between ASUD status and sex, with a consistently earlier AAO in males with an ASUD (OR: 0.79: 95% CI: 0.70, 0.91). CONCLUSIONS: In BD-I cases diagnosed according to internationally recognized criteria and recruited to pan-European clinical observational studies, the AAO distributions are compatible with a birth cohort effect. A potentially modifiable risk factor, namely ASUD status, was associated with the observed reduction in AAO, especially in males.

Emotional hyper-reactivity and cardiometabolic risk in remitted bipolar patients: a machine learning approach.

OBJECTIVE: Remitted bipolar disorder (BD) patients frequently present with chronic mood instability and emotional hyper-reactivity, associated with poor psychosocial functioning and low-grade inflammation. We investigated emotional hyper-reactivity as a dimension for characterization of remitted BD patients, and clinical and biological factors for identifying those with and without emotional hyper-reactivity. METHOD: A total of 635 adult remitted BD patients, evaluated in the French Network of Bipolar Expert Centers from 2010-2015, were assessed for emotional reactivity using the Multidimensional Assessment of Thymic States. Machine learning algorithms were used on clinical and biological variables to enhance characterization of patients. RESULTS: After adjustment, patients with emotional hyper-reactivity (n = 306) had significantly higher levels of systolic and diastolic blood pressure (P < 1.0 × 10-8 ), high-sensitivity C-reactive protein (P < 1.0 × 10-8 ), fasting glucose (P < 2.23 × 10-6 ), glycated hemoglobin (P = 0.0008) and suicide attempts (P = 1.4 × 10-8 ). Using models of combined clinical and biological factors for distinguishing BD patients with and without emotional hyper-reactivity, the strongest predictors were: systolic and diastolic blood pressure, fasting glucose, C-reactive protein and number of suicide attempts. This predictive model identified patients with emotional hyper-reactivity with 84.9% accuracy. CONCLUSION: The assessment of emotional hyper-reactivity in remitted BD patients is clinically relevant, particularly for identifying those at higher risk of cardiometabolic dysfunction, chronic inflammation, and suicide.

Dosimetric properties of α-Al2O3: Tm+PTFE phosphor.

A new α-Al2O3 doped with Tm3+ ions was obtained by combustion method; doped α-Al2O3 in the powder form was mixed with polytetrafluoroethylene resin (PTFE) to obtain dosimeters in pellet form, in order to be used as radiation dosimeter. The glow curve, linearity, lower detection limit, repeatability and fading, were studied. The kinetic parameters were determined by deconvolution method. Morphological characteristics were studied by low vacuum scanning electron microscopy and X-ray diffraction. Results showed that α-Al2O3+PTFE obtained is a promising material to radiation dosimetry.