Sophisticated voluntary movements are essential for everyday functioning, making the study of how the brain controls muscle activity a central challenge in neuroscience. Investigating corticomuscular control through non-invasive electrophysiological recordings is particularly complex due to the intricate nature of neuronal signals. To address this challenge, we present a novel experimental methodology designed to study corticomuscular control using electroencephalography (EEG) and electromyography (EMG). Our approach integrates a serious gaming biofeedback system with a specialized experimental protocol for simultaneous EEG-EMG data acquisition, optimized for corticomuscular studies. This work introduces, for the first time, a method for assessing brain–muscle functional connectivity during the execution of a demanding motor task. By identifying neuronal sources linked to muscular activity, this methodology has the potential to advance our understanding of motor control mechanisms. These insights could contribute to improving clinical practices and fostering the development of novel brain–computer interface technologies.

Pre-surgical planning often involves task-based functional magnetic resonance imaging (fMRI) in the context of intractable epilepsy or brain tumors. Resting-state fMRI can be used for the same goal, with the advantage of being a simpler technique that does not require the patient to cooperate in complex cognitive tasks. However, the methods for resting-state fMRI analysis are not yet robust or of practical usage. This work proposes an algorithm for sorting components resulting from independent component analysis (ICA) that emphasizes the language resting-state network. We recruited 20 healthy volunteers and acquired resting-state and task-based fMRI using three linguistic tasks. Task data was processed using general linear model analysis, while resting-state networks were extracted using ICA. An automated IC sorting procedure was developed based on three characteristics: spatial similarity with a probability map, low/high frequency ratio, and IC reliability over several bootstrapping folds. Task-related activation consistent with the language network was identified at the subject-specific level. The algorithm is shown to sort ICs with the resting-state language maps appearing among the first three with an accuracy of 74%. Overall, the Dice coefficient showed a good overlap between the sorted ICs of relevance and the task language maps. Results showed that resting-state networks were more specific and less sensitive than task-based maps. We expect that the proposed algorithm for optimal sorting will contribute towards making ICA usage viable in the clinical context and become a reliable alternative method for pre-surgical planning.

The ageing of the global population, especially in developed countries, is driving significant societal changes. In Portugal, demographic data reflect a marked increase in the ageing index. Understanding gait alterations associated with ageing is essential for the early detection of mobility decline and fall risk. This study aimed to analyse gait patterns in older adults to contribute to a biomechanical ageing profile. Thirty-six community-dwelling older adults (29 female, 7 male; mean age: 74 years) participated. Gait data were collected using the Xsens full-body motion capture system, which combines inertial sensors with biomechanical modelling and sensor fusion. Spatiotemporal and kinematic parameters were analysed using descriptive statistics. Compared to younger adult norms, participants showed increased stance and double support phases, reduced swing phase, and lower gait speed, stride length, and cadence, with greater step width. Kinematic data showed reduced peak plantar flexion, knee flexion, and hip extension, but increased dorsiflexion peaks—adaptations aimed at stability. Despite a limited sample size and lack of clinical subgroups, results align with age-related gait literature. Findings support the utility of wearable systems like Xsens in capturing clinically relevant gait changes, contributing to normative biomechanical profiling and future mobility interventions.

Objective: In recent years the psychophysiological benefits of Mindfulness meditation on emotional processing have drawn great interest in scientific research. Currently, the effects of this meditation practice on stress, anxiety and well-being have been mostly evaluated using self-reporting questionnaires, which lead to a quite subjective assessment. This study assesses the effect of Mindfulness practice on the reaction to emotionally charged visual stimuli through Electrodermal Activity (EDA) data.Methods: Twenty-five healthy volunteers, without any previous experience of meditation techniques completed a 12-week Mindfulness-Based Stress Reduction (MBSR) course. EDA and psychological measures were collected longitudinally in 4 scheduled sessions. Statistical analysis was performed to find changes in the most relevant EDA parameters throughout the 4 sessions of data collection.Results: We found an increase in response latency, and a decrease in amplitude, area, number of specific re-sponses, and skin conductance level along Mindfulness training. Both outcomes might suggest a reduction in the reactivity to the presented stimuli and an improvement in the emotional well-being of the practitioners. Furthermore, this study showed preliminary evidence that women improve more their attitude towards stressful stimuli than man, after the mindfulness practice.The statistical analysis also showed a correlation between the main EDA parameters and the scores reported by each participant in the depression, anxiety, and stress scale (DASS) questionnaire.Conclusion and Significance: This study contributed to a more objective evaluation of the physiological changes observed during Mindfulness practice, and so to understand the underlying mechanisms that explain the benefits of meditation training.

Cardiothoracic surgery patients have the risk of developing surgical site infections which cause hospital readmissions, increase healthcare costs, and may lead to mortality. This work aims to tackle the problem of surgical site infections by predicting the existence of worrying alterations in wound images with a wound image analysis system based on artificial intelligence. The developed system comprises a deep learning segmentation model (MobileNet-Unet), which detects the wound region area and categorizes the wound type (chest, drain, and leg), and a machine learning classification model, which predicts the occurrence of wound alterations (random forest, support vector machine and k-nearest neighbors for chest, drain, and leg, respectively). The deep learning model segments the image and assigns the wound type. Then, the machine learning models classify the images from a group of color and textural features extracted from the output region of interest to feed one of the three wound-type classifiers that reach the final binary decision of wound alteration. The segmentation model achieved a mean Intersection over Union of 89.9% and a mean average precision of 90.1%. Separating the final classification into different classifiers was more effective than a single classifier for all the wound types. The leg wound classifier exhibited the best results with an 87.6% recall and 52.6% precision.

Stroke, or cerebrovascular accident, is a major global health problem and one of the leading causes of death and acquired disability worldwide. After a stroke, deficits in perceptual and cognitive functions may arise, with particular emphasis to impairments caused to visuomotor skills. In this way, its stimulation, within a therapeutic rehabilitation context, is truly relevant for the recovery of lost functions. RehabVisual, presented in earlier works, is a digital platform that allows for an objective and standardized assessment of visuomotor skills and specific clinical interventions for each patient. In the current work, new features are added to the platform, to make it more optimized and suitable for use in clinical practice, with adults who suffered a stroke. Herein the platform is also thoroughly validated with healthy subjects.Objective: This work’s goals are twofold: to assess the accuracy of the eye tracking system developed, which is integrated in the platform; and to test and validate the digital platform itself, with a population of healthy subjects.Methodology: 50 healthy subjects tested the RehabVisual digital platform in a laboratory context. In addition to testing the overall visuomotor rehabilitation functions, dynamic stimuli following was collected from both the platform’s own camera and a Tobii Pro Nano Eye Tracker, which is considered as gold standard to assess direction of gaze. The results of both systems were compared.Results: The platform’s own eye tracking apparatus revealed a good performance, in par with the gold standard, following the evolution of visual stimuli with sufficient accuracy, which ensures the suitability of its use in the context of gaze detection during rehabilitation. Conclusions: The validated gaze tracking ability, together with fact that both stimulus delivery and eye tracking is performed with the same device guarantees synchrony between both streams of data. Recorded videos of those signals allows for the design of new and personalized clinical evaluation and intervention strategies, to be applied throughout the rehabilitation program. Those may be used to complement physiotherapist’s evaluation of patients and allow for the identification of possible changes in their visuomotor skills.As an added feature, a new usability questionnaire was filled by a group of occupational therapists, which reinforced the potential use of the new version of RehabVisual, when applied to visuomotor rehabilitation of stroke patients.

Stroke sequelae significantly affect the individual's functionality, namely at the level of their perceptive and cognitive skills. Consequently, these patients require rehabilitation therapies that are adapted to their dysfunctions. Conventional approaches (traditional board and paper games) have the disadvantage of not being suited to the dysfunctions of some patients, making the rehabilitation process unstimulating and demotivating. RehbBrain is a serious gaming platform, adapted for all patients whose rehabilitation process focuses on stimulating, visually, perceptual and cognitive skills. It simulates the individual’s daily activities, in various environments, and with progressive levels of difficulty. The platform aims to help therapists monitor their patients by promoting a systematized and standardized assessment. The games on the platform are intended to complement conventional rehabilitation methods, and render therapy sessions more dynamic, leading to a faster and more patient-oriented stimulation process.RehbBrain’s usability was tested by 5 specialists and 33 subjects with no associated pathologies. They completed separate System Usability Scale (SUS) questionnaire to assess the platform, but reached and combined average score of 88.4, classifying RehbBrain as "Excellent".

This article presents Ortho-Monitorizer, a portable device for temperature and pressure monitorization in three pressure points of the upper limb, while a static orthosis is being used. The purpose of this device is to inform healthcare professionals, not only if the patient has been wearing the orthosis for the prescribed time, but also if it is too tight, or if there is any inflammatory reaction, that leads to an increase in local temperature. The data transfer is done through the Bluetooth Low Energy AT-09 module. Data is shown in an Android application and saved in real time in a database. To start the data acquisition, the user just needs to connect the device to a power bank, register in the application, make the Bluetooth connection with the device, and then select the option of the specific characteristic that will save the values measured by the sensors. The Android application is still under development to improve usability. The orthoses used for the acquisitions were created specifically for Carpal Tunnel Syndrome and used for two consecutive days, by two healthy volunteers. Our findings indicate that, although some care is needed during acquisitions, namely in terms of positioning the active areas of the sensors and the internet connection, the device makes acquisitions correctly. It allows us to identify when the person is using the orthosis and the existing pressure differences. Therefore, in the future this prototype could be incorporated into a clinical setting, to allow therapists to monitor compliance and prevent pressure ulcers and wounds.

In this paper, we evaluate the effects of mindfulness meditation training in electrophysiological signals, recorded during a concentration task. Longitudinal experiments have been limited to the analysis of psychological scores through depression, anxiety, and stress state (DASS) surveys. Here, we present a longitudinal study, confronting DASS survey data with electrocardiography (ECG), electroencephalography (EEG), and electrodermal activity (EDA) signals. Twenty-five university student volunteers (mean age = 26, SD = 7, 9 male) attended a 25-h mindfulness-based stress reduction (MBSR) course, over a period of 8 weeks. There were four evaluation periods: pre/peri/post-course and a fourth follow-up, after 2 months. All three recorded biosignals presented congruent results, in line with the expected benefits of regular meditation practice. In average, EDA activity decreased throughout the course, −64.5%, whereas the mean heart rate displayed a small reduction, −5.8%, possibly as a result of an increase in parasympathetic nervous system activity. Prefrontal (AF3) cortical alpha activity, often associated with calm conditions, saw a very significant increase, 148.1%. Also, the number of stressed and anxious subjects showed a significant decrease, −92.9% and −85.7%, respectively. Easy to practice and within everyone’s reach, this mindfulness meditation can be used proactively to prevent or enhance better quality of life.

This article presents the development of a wearable and portable system, the Ortho-Monitorizer, which allows an objective, continuous and simultaneous monitoration of the temperature and pressure exerted on the skin on the 3 main pressure points derived from the use of a hand and wrist orthosis. It also allows the monitorization of the patient’s compliance to the orthosis, providing its time of use. This way, adjustments to the orthosis can be optimized, reducing the discomfort felt by the patient, increasing compliance, reducing the risk of pressure sores’ formation derived from inadequate levels of pressure applied, and consequently, increasing the effectiveness of orthosis’ use. Therefore, an Arduino Uno, powered by a powerbank, is used as microcontroller. Three force sensors and three temperature sensors are controlled by the microcontroller to detect the pressure and temperature. A Bluetooth Low Energy module is used to send data from the Arduino to an android application under development, which will allow healthcare professionals to consult all the information and clinical history relating to each patient, as well as allowing the patient to develop a greater awareness and sense of responsibility regarding their performance in relation to the guidelines provided by the health professional.

We are constantly exposed to countless visual stimuli that trigger different emotions and reactions in individuals. Assessing one’s own reactions to visual stimuli can be a powerful tool for diagnosing a person’s psychological state, as well as to evaluate, objectively, the effects of one’s interaction with the environment. Currently, the measurement of this emotional responsiveness to visual stimulation is mostly carried out by means of self-reporting questionnaires, which lead to a quite subjective assessment of the emotional impact of the presented stimuli. The aim of this study is to investigate the use of Electrodermal Activity (EDA) to predict the level of emotional response of individuals to negatively charged pictures. With this purpose, we collected EDA signals from 25 participants, while they visualized a sequence of 75 emotional response pictures, from the International Affective Picture System (IAPS). The most relevant EDA parameters, such as amplitude, area, skin conductance levels and the number of specific responses were statistically confronted with the arousal and valence of each image. This analysis showed the expected increase in the first three parameters for high arousal pictures. We also found that more neutral valenced ones had higher amplitude and skin conductance levels than pictures with negative valence. Those results show that the Electrodermal Activity can be used as an objective indicator to evaluate emotional arousal, as a response to viewing negative pictures. In addition, it opens the possibility to use such electrophysiological measurements, in a clinical, social or ludic context and, in such way improve certain forms of diagnosis, as well as assess the efficiency of visual interaction with a particular individual, while allowing for a more objective way to monitor the emotional effects of said interaction.

Simple visual stimuli, with bright colours and dynamically evolving over time, are among the most effective mechanisms through which to engage a baby´s attention. In earlier work, we have developed a visual stimulating tool to aid rehabilitation programs, which can be used with infants of up to 2 years of age. The feedback from the early use of the device has been rather positive. Yet, until now, there was no explicit way to assess the degree of engagement of the infant’s attention, or even when the focus of said attention moved away from the stimulus. Hence, it has been difficult to understand whether the proposed specific rehabilitation procedure has failed, for a given infant, or the loss of attention led to a decrease in efficiency in the intervention. In the current work we develop and exploit a simple eye tracking tool, based on a laptop’s own webcam, to evaluate the child’s loss of attention to visual stimuli. The main differentiating criterion, set forth for this eyetracker, is that it should work without an explicit calibration stage. The use of the specific camera is motivated with the fact that the laptop can be used for visual stimuli deliver, as well as a series of data processing steps. The results attained thus far were rather encouraging, leading even to a subsequent study, replacing infants by adults undergoing a rehabilitation program, after suffering from brain stroke.

Currently, pain analysis in a clinical environment is not common and is at fault for being subjective and always dependent on a personal response. Therefore, it is imperative to use physiological signals to quantify pain and make diagnosis more objective. This article aims to study the relationship between pain, through its analog scale, with the electrodermal and cardiac signals of individuals characterized by having a shoulder pathology that gives rise to recurrent pain. This study was carried out on 21 patients from Hospital Curry Cabral, who were part of the Occupational Therapy department’s care in the area of Physical Medicine and Rehabilitation, and 18 individuals without any pathology, thus serving as a control group. All participants followed an experimental protocol consisting in the measurement of electrodermal and cardiac signals and pain level when performing two different movements. The results suggest that there is indeed a relationship between the two measured signals and pain. The greater the pain experienced by the individual, the greater the amplitude of the electrodermic signal and heart rate appears to be.

Visual impairments affect the life of millions of people. Some of these impairments can be corrected or diminished. Visual stimulation is one way of visual rehabilitation, that has produced better results when used in the early years of life. As there is nothing standardized in this field, a platform named RehabVisual was developed (Machado et al., 2018; Santos, 2018). This platform has the objective of creating an individual visuomotor rehabilitation for children under two years old, that were born prematurely. In order to reach a therapists’ need, a video analysis tool was developed. This tool should be capable of following the motion of the patients’ eyes, with the purpose of facilitating and making the analysis of their reactions to the stimuli more objective. The solution developed on this paper consists on the creation of an eye tracker system, that does not need to be pre-calibrated and is low-cost. The eye tracker was tested in healthy individuals and the results show that is very effective in detecting horizontal eye variations.

Spinal cord injuries are one of the most traumatic situations with a major impact on a person's quality of life. This type of injury have a extremely impact in the performance of daily life activities not only due to motor alterations but also due to the appearance of neuropathic pain Throughout the rehabilitation process the evaluation and intervention methodologies are not very systematic and are not personalized. Thus, to bridge this gap, the VR4NeuroPain was developed a technology that associates virtual reality with a glove "GNeuroPathy". The glove "GNeuroPathy" allows the collection of physiological parameters, namely to identify the electrodermic activity (EDA) while the patient carries out activities in an immersive environment. The main objective of this article is to present the validation process of the "GNeuroPathy" in clinical context. "GNeuroPathy" was applied to a group of 17 individuals with incomplete spinal cord injury. The results showed that "GNeuroPathy" is easy to apply and is suitable for comfort and texture. Data were also collected from EDA and it was found that there is a significant difference in signal amplitude in patients with low and high functionality.

It is said that the eyes are the windows of the soul. Although rather poetic, such a statement becomes clearly more relevant if we acknowledge that dynamic changes in pupillary dimensions convey a great amount of information, regarding the general psychological and neurophysiological condition of the observed person. Most commonly used pupillometers are rather expensive, and may require highly controlled experimental setups to be used. Those can limit greatly the applicability of the devices in practise. Based on a basic smartphone and a cardboard support, originally proposed for virtual reality applications, we developed a portable pupillometer, which can be used in natural, as well as controlled stimuli conditions. The proposed device fits the category of monocular video pupillometers, meaning that it continuously measures one of the user’s eyes, while the other may receive pre-determined visual stimulation. To help validating the use of the pupillometer, we measured the evolution of pupillary dimensions during a standard “ice bucket” hand test. The results followed quite accurately the behaviour reported in literature, with increases of pupillary diameters in the order of 15% to 20%, as a result of placing or removing the subject’s hand. Recorded pupillary reaction response times were about 2.6 s, which suggest an interplay between the sympathetic and parasympathetic nervous system controlling activity.

Spinal cord injuries are among the most traumatic situations, having relevant repercussions on an individual’s occupation performance. Although loss of functionality is considered to be the most significant consequence, neuropathic pain can determine an individual’s inability to return to daily activities. Therefore, it is imperative to develop new technologies with significant impact on the rehabilitation process of the spinal cord injuries. VR4NeuroPain combines virtual reality with a glove “GNeuroPathy”, covered with a variety of biosensors, that allows for the collection of physiological parameters and motor stimulation. The main purpose of this paper is to describe the system VR4NeuroPain, and to validate the “GNeuroPathy” concept. With that in mind, and after calibrating the VR4NeuroPain system using with a group of 16 individuals, the validation results showed that “GNeuroPathy” was comfort, accessibility in place and the collection of physiological parameters was performed as expected.

Humans live in, and interact with, a very complex and multi-sensory environment. Yet, one parcels efficiently the incoming information through attention mechanisms. Even if restricted to the visual sensory system alone, full understanding of one’s perception often implies a suitable identification of that person’s direction of gaze. There is a considerable amount of new and commercially available eye tracking devices. We investigate the use of a mobile phone to acquire precise information on the direction of gaze, in a controlled visual stimulation environment. The main advantages of the proposed new approach are its price, ease of use and ubiquitous availability. The results attained in this proof-of-concept study display fairly high accuracy and precision for the estimation of the direction of gaze.

In the visual cortex, stimuli outside the classical receptive field (CRF) modulate the neural firing rate, without driving the neuron by themselves. In the primary visual cortex (V1), such contextual modulation can be parametrized with an area summation function (ASF): increasing stimulus size causes first an increase and then a decrease of firing rate before reaching an asymptote. Earlier work has reported increase of sparseness when CRF stimulation is extended to its surroundings. However, there has been no clear connection between the ASF and network efficiency. Here we aimed to investigate possible link between ASF and network efficiency. In this study, we simulated the responses of a biomimetic spiking neural network model of the visual cortex to a set of natural images. We varied the network parameters, and compared the V1 excitatory neuron spike responses to the corresponding responses predicted from earlier single neuron data from primate visual cortex. The network efficiency was quantified with firing rate (which has direct association to neural energy consumption), entropy per spike and population sparseness. All three measures together provided a clear association between the network efficiency and the ASF. The association was clear when varying the horizontal connectivity within V1, which influenced both the efficiency and the distance to ASF, DAS. Given the limitations of our biophysical model, this association is qualitative, but nevertheless suggests that an ASF-like receptive field structure can cause efficient population response.

Every stimulus or task activates multiple areas in the mammalian cortex. These distributed activations can be measured with functional magnetic resonance imaging (fMRI), which has the best spatial resolution among the noninvasive brain imaging methods. Unfortunately, the relationship between the fMRI activations and distributed cortical processing has remained unclear, both because the coupling between neural and fMRI activations has remained poorly understood and because fMRI voxels are too large to directly sense the local neural events. To get an idea of the local processing given the macroscopic data, we need models to simulate the neural activity and to provide output that can be compared with fMRI data. Such models can describe neural mechanisms as mathematical functions between input and output in a specific system, with little correspondence to physiological mechanisms. Alternatively, models can be biomimetic, including biological details with straightforward correspondence to experimental data. After careful balancing between complexity, computational efficiency, and realism, a biomimetic simulation should be able to provide insight into how biological structures or functions contribute to actual data processing as well as to promote theory-driven neuroscience experiments. This review analyzes the requirements for validating system-level computational models with fMRI. In particular, we study mesoscopic biomimetic models, which include a limited set of details from real-life networks and enable system-level simulations of neural mass action. In addition, we discuss how recent developments in neurophysiology and biophysics may significantly advance the modelling of fMRI signals.