Impact of Radiation Dose on the Survival of Patients With Non-small Cell Lung Cancer Treated With Palliative Intent: Results of a Multicenter Prospective Study.

Background/aim: Many patients with non-small cell lung cancer (NSCLC) receive palliative radiotherapy (RT). Several factors were analyzed to aid in prescribing an optimal treatment for these patients.

Patients And Methods: This prospective observational multicenter study investigated several potential factors for associations with overall survival (OS) in 61 patients with NSCLC receiving palliative RT with or without chemotherapy (CT).

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.

Brain-machine interface based on deep learning to control asynchronously a lower-limb robotic exoskeleton: a case-of-study.

Background: This research focused on the development of a motor imagery (MI) based brain-machine interface (BMI) using deep learning algorithms to control a lower-limb robotic exoskeleton. The study aimed to overcome the limitations of traditional BMI approaches by leveraging the advantages of deep learning, such as automated feature extraction and transfer learning. The experimental protocol to evaluate the BMI was designed as asynchronous, allowing subjects to perform mental tasks at their own will.

Exploring EEG-based motor imagery decoding: a dual approach using spatial features and spectro-spatial Deep Learning model IFNet.

Introduction: In recent years, the decoding of motor imagery (MI) from electroencephalography (EEG) signals has become a focus of research for brain-machine interfaces (BMIs) and neurorehabilitation. However, EEG signals present challenges due to their non-stationarity and the substantial presence of noise commonly found in recordings, making it difficult to design highly effective decoding algorithms. These algorithms are vital for controlling devices in neurorehabilitation tasks, as they activate the patient's motor cortex and contribute to their recovery.

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.

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.

Design and Evaluation of a Potential Non-Invasive Neurostimulation Strategy for Treating Persistent Anosmia in Post-COVID-19 Patients.

A new pandemic was declared at the end of 2019 because of coronavirus disease 2019 (COVID-19). One of the effects of COVID-19 infection is anosmia (i.e.

An EEG database for the cognitive assessment of motor imagery during walking with a lower-limb exoskeleton.

One important point in the development of a brain-machine Interface (BMI) commanding an exoskeleton is the assessment of the cognitive engagement of the subject during the motor imagery tasks conducted. However, there are not many databases that provide electroencephalography (EEG) data during the use of a lower-limb exoskeleton. The current paper presents a database designed with an experimental protocol aiming to assess not only motor imagery during the control of the device, but also the attention to gait on flat and inclined surfaces.

Brain-computer interface enhanced by virtual reality training for controlling a lower limb exoskeleton.

This study explores the use of a brain-computer interface (BCI) based on motor imagery (MI) for the control of a lower limb exoskeleton to aid in motor recovery after a neural injury. The BCI was evaluated in ten able-bodied subjects and two patients with spinal cord injuries. Five able-bodied subjects underwent a virtual reality (VR) training session to accelerate training with the BCI.

Brain-machine interface based on transfer-learning for detecting the appearance of obstacles during exoskeleton-assisted walking.

Introduction: Brain-machine interfaces (BMIs) attempt to establish communication between the user and the device to be controlled. BMIs have great challenges to face in order to design a robust control in the real field of application. The artifacts, high volume of training data, and non-stationarity of the signal of EEG-based interfaces are challenges that classical processing techniques do not solve, showing certain shortcomings in the real-time domain.

EEG Evaluation in a Neuropsychological Intervention Program Based on Virtual Reality in Adults with Parkinson's Disease.

Nowadays, several strategies for treating neuropsychologic function loss in Parkinson’s disease (PD) have been proposed, such as physical activity performance and developing games to exercise the mind. However, few studies illustrate the incidence of these therapies in neuronal activity. This work aims to study the feasibility of a virtual reality-based program oriented to the cognitive functions’ rehabilitation of PD patients.

Assessing user experience with BMI-assisted exoskeleton in patients with spinal cord injury.

Spinal Cord Injury (SCI) refers to damage to the spinal cord that can affect different body functionalities. Recovery after SCI depends on multiple factors, being the rehabilitation therapy one of them. New approaches based on robot-assisted training offer the possibility to make training sessions longer and with a reproducible pattern of movements.

Riemannian classification analysis for model EEG intention speed patterns.

In this paper, the paradigm of the intention of speed changes from EEG signals with Riemannian classifiers methods is studied in 10 subjects. In addition, the best frequency band and how different electrode configurations affect the accuracy of the model are analyzed. In the prediction of the intention to change speed, results of 68.

Comorbidities and the right dose: antipsychotics.

Introduction: The effects of antipsychotic drugs are dose-dependent, which is particularly true for their efficacy, each antipsychotic having a specific dose-response curve. This may justify individualizing doses for these agents.

Areas Covered: We review the pharmacokinetic profiles of seven oral antipsychotics: haloperidol, risperidone, olanzapine, clozapine, quetiapine, ziprasidone, and aripiprazole.

Decoding of Turning Intention during Walking Based on EEG Biomarkers.

In the EEG literature, there is a lack of asynchronous intention models that realistically propose interfaces for applications that must operate in real time. In this work, a novel BMI approach to detect in real time the intention to turn is proposed. For this purpose, an offline, pseudo-online and online analysis is presented to validate the EEG as a biomarker for the intention to turn.

Expert consensus recommendations on the use of randomized clinical trials for drug approval in psychiatry- comparing trial designs.

The use of randomized clinical trials, in particular placebo-controlled trials, for drug approval, is the subject of long-standing debate in the scientific community and beyond. This study offers consensus recommendations from clinical and academic experts to guide the selection of clinical trial design in psychiatry. Forty-one highly cited clinical psychiatrists and/or researchers participated in a Delphi survey.

A Robot-Assisted Therapy to Increase Muscle Strength in Hemiplegic Gait Rehabilitation.

This study examines the feasibility of using a robot-assisted therapy methodology based on the Bobath concept to perform exercises applied in conventional therapy for gait rehabilitation in stroke patients. The aim of the therapy is to improve postural control and movement through exercises based on repetitive active-assisted joint mobilization, which is expected to produce strength changes in the lower limbs. As therapy progresses, robotic assistance is gradually reduced and the patient's burden increases with the goal of achieving a certain degree of independence.

Biomechanical Assessment of Post-Stroke Patients' Upper Limb before and after Rehabilitation Therapy Based on FES and VR.

Stroke is a medical condition characterized by the rapid loss of focal brain function. Post-stroke patients attend rehabilitation training to prevent the degeneration of physical function and improve upper limb movements and functional status after stroke. Promising rehabilitation therapies include functional electrical stimulation (FES), exergaming, and virtual reality (VR).

Effect of heating rate on MgBO: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 MgBO activated by Tm and Dy ions (MgBO:Tm.

Review of tDCS Configurations for Stimulation of the Lower-Limb Area of Motor Cortex and Cerebellum.

This article presents an exhaustive analysis of the works present in the literature pertaining to transcranial direct current stimulation(tDCS) applications. The aim of this work is to analyze the specific characteristics of lower-limb stimulation, identifying the strengths and weaknesses of these works and framing them with the current knowledge of tDCS. The ultimate goal of this work is to propose areas of improvement to create more effective stimulation therapies with less variability.

The Impact of Bipolar Disorder on Couple Functioning: Implications for Care and Treatment. A Systematic Review.

If there is an abundant literature on the impact of bipolar illness on the family and/or caregivers of patients, few studies have addressed its impact on marital relationship and couple functioning. Uncovering information relating specifically to this topic may be particularly relevant due to the unusually high divorce rate among individuals with bipolar disorder. We therefore conducted a systematic literature search to evaluate the existing data on bipolar disorder and marital issues, with a special focus on the help and support that can be provided by mental health professionals in this regard.

Gender, age at onset, and duration of being ill as predictors for the long-term course and outcome of schizophrenia: an international multicenter study.

Background: The aim of the current study was to explore the effect of gender, age at onset, and duration on the long-term course of schizophrenia.

Methods: Twenty-nine centers from 25 countries representing all continents participated in the study that included 2358 patients aged 37.21 ± 11.

The Actuation System of the Ankle Exoskeleton T-FLEX: First Use Experimental Validation in People with Stroke.

Robotic devices can provide physical assistance to people who have suffered neurological impairments such as stroke. Neurological disorders related to this condition induce abnormal gait patterns, which impede the independence to execute different Activities of Daily Living (ADLs). From the fundamental role of the ankle in walking, Powered Ankle-Foot Orthoses (PAFOs) have been developed to enhance the users' gait patterns, and hence their quality of life.