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1.
Sensors (Basel) ; 21(7)2021 Mar 29.
Artigo em Inglês | MEDLINE | ID: mdl-33805522

RESUMO

Fatigued driving is one of the main causes of traffic accidents. The electroencephalogram (EEG)-based mental state analysis method is an effective and objective way of detecting fatigue. However, as EEG shows significant differences across subjects, effectively "transfering" the EEG analysis model of the existing subjects to the EEG signals of other subjects is still a challenge. Domain-Adversarial Neural Network (DANN) has excellent performance in transfer learning, especially in the fields of document analysis and image recognition, but has not been applied directly in EEG-based cross-subject fatigue detection. In this paper, we present a DANN-based model, Generative-DANN (GDANN), which combines Generative Adversarial Networks (GAN) to enhance the ability by addressing the issue of different distribution of EEG across subjects. The comparative results show that in the analysis of cross-subject tasks, GDANN has a higher average accuracy of 91.63% in fatigue detection across subjects than those of traditional classification models, which is expected to have much broader application prospects in practical brain-computer interaction (BCI).


Assuntos
Algoritmos , Interfaces Cérebro-Computador , Eletroencefalografia , Humanos , Aprendizado de Máquina , Redes Neurais de Computação
2.
Sensors (Basel) ; 21(7)2021 Mar 26.
Artigo em Inglês | MEDLINE | ID: mdl-33810613

RESUMO

The capability of monitoring user's performance represents a crucial aspect to improve safety and efficiency of several human-related activities. Human errors are indeed among the major causes of work-related accidents. Assessing human factors (HFs) could prevent these accidents through specific neurophysiological signals' evaluation but laboratory sensors require highly-specialized operators and imply a certain grade of invasiveness which could negatively interfere with the worker's activity. On the contrary, consumer wearables are characterized by their ease of use and their comfortability, other than being cheaper compared to laboratory technologies. Therefore, wearable sensors could represent an ideal substitute for laboratory technologies for a real-time assessment of human performances in ecological settings. The present study aimed at assessing the reliability and capability of consumer wearable devices (i.e., Empatica E4 and Muse 2) in discriminating specific mental states compared to laboratory equipment. The electrooculographic (EOG), electrodermal activity (EDA) and photoplethysmographic (PPG) signals were acquired from a group of 17 volunteers who took part to the experimental protocol in which different working scenarios were simulated to induce different levels of mental workload, stress, and emotional state. The results demonstrated that the parameters computed by the consumer wearable and laboratory sensors were positively and significantly correlated and exhibited the same evidences in terms of mental states discrimination.


Assuntos
Laboratórios , Dispositivos Eletrônicos Vestíveis , Frequência Cardíaca , Humanos , Reprodutibilidade dos Testes , Carga de Trabalho
3.
Brain Sci ; 11(2)2021 Feb 18.
Artigo em Inglês | MEDLINE | ID: mdl-33670698

RESUMO

Scents have the ability to affect peoples' mental states and task performance with to different extents. It has been widely demonstrated that the lemon scent, included in most all-purpose cleaners, elicits stimulation and activation, while the lavender scent elicits relaxation and sedative effects. The present study aimed at investigating and fostering a novel approach to evaluate users' experience with respect to scents' effects through the joint employment of Virtual Reality and users' neurophysiological monitoring, in particular Electroencephalography. In particular, this study, involving 42 participants, aimed to compare the effects of lemon and lavender scents on the deployment of cognitive resources during a daily life experience consisting in a train journey carried out in virtual reality. Our findings showed a significant higher request of cognitive resources during the processing of an informative message for subjects exposed to the lavender scent with respect to the lemon exposure. No differences were found between lemon and lavender conditions on the self-reported items of pleasantness and involvement; as this study demonstrated, the employment of the lavender scent preserves the quality of the customer experience to the same extent as the more widely used lemon scent.

4.
Sensors (Basel) ; 21(5)2021 Feb 25.
Artigo em Inglês | MEDLINE | ID: mdl-33668921

RESUMO

Current telemedicine and remote healthcare applications foresee different interactions between the doctor and the patient relying on the use of commercial and medical wearable sensors and internet-based video conferencing platforms. Nevertheless, the existing applications necessarily require a contact between the patient and sensors for an objective evaluation of the patient's state. The proposed study explored an innovative video-based solution for monitoring neurophysiological parameters of potential patients and assessing their mental state. In particular, we investigated the possibility to estimate the heart rate (HR) and eye blinks rate (EBR) of participants while performing laboratory tasks by mean of facial-video analysis. The objectives of the study were focused on: (i) assessing the effectiveness of the proposed technique in estimating the HR and EBR by comparing them with laboratory sensor-based measures and (ii) assessing the capability of the video-based technique in discriminating between the participant's resting state (Nominal condition) and their active state (Non-nominal condition). The results demonstrated that the HR and EBR estimated through the facial-video technique or the laboratory equipment did not statistically differ (p > 0.1), and that these neurophysiological parameters allowed to discriminate between the Nominal and Non-nominal states (p < 0.02).


Assuntos
Frequência Cardíaca , Telemedicina , Gravação em Vídeo , Adulto , Piscadela , Feminino , Humanos , Masculino
5.
Sci Rep ; 11(1): 4831, 2021 Mar 01.
Artigo em Inglês | MEDLINE | ID: mdl-33649348

RESUMO

Real-world experience is typically multimodal. Evidence indicates that the facilitation in the detection of multisensory stimuli is modulated by the perceptual load, the amount of information involved in the processing of the stimuli. Here, we used a realistic virtual reality environment while concomitantly acquiring Electroencephalography (EEG) and Galvanic Skin Response (GSR) to investigate how multisensory signals impact target detection in two conditions, high and low perceptual load. Different multimodal stimuli (auditory and vibrotactile) were presented, alone or in combination with the visual target. Results showed that only in the high load condition, multisensory stimuli significantly improve performance, compared to visual stimulation alone. Multisensory stimulation also decreases the EEG-based workload. Instead, the perceived workload, according to the "NASA Task Load Index" questionnaire, was reduced only by the trimodal condition (i.e., visual, auditory, tactile). This trimodal stimulation was more effective in enhancing the sense of presence, that is the feeling of being in the virtual environment, compared to the bimodal or unimodal stimulation. Also, we show that in the high load task, the GSR components are higher compared to the low load condition. Finally, the multimodal stimulation (Visual-Audio-Tactile-VAT and Visual-Audio-VA) induced a significant decrease in latency, and a significant increase in the amplitude of the P300 potentials with respect to the unimodal (visual) and visual and tactile bimodal stimulation, suggesting a faster and more effective processing and detection of stimuli if auditory stimulation is included. Overall, these findings provide insights into the relationship between multisensory integration and human behavior and cognition.

6.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 584-587, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018056

RESUMO

Sports activity is characterised by the influence of different factors, which relate to both psychological and emotional stress of athletes. As a consequence, mental and physical preparations are fundamental in pre-competition and competition activities. In fact, being able to manage the reactions to stressful events and high demanding conditions, and adapt the strategy depending on the ongoing situation and opponent's reactions allow the athletes to properly process the surrounding information, evaluate all the possible solutions, and finally take the right decision. In this regard, the Skin Conductance (SC), Heart Rate (HR), and Skin Temperature (ST) signals were recorded during a grappling tournament from ten athletes with the aim to investigate if physiological assessments could provide an objective measure of athletes' attitude. The results proved that individual training programs can be tailored accordingly to the neurophysiological state of the athletes, but also that their awareness about both mental and physical preparations and attitudes could be improved.


Assuntos
Esportes , Dispositivos Eletrônicos Vestíveis , Animais , Atletas , Atitude , Frequência Cardíaca , Humanos
7.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 851-854, 2020 07.
Artigo em Inglês | MEDLINE | ID: mdl-33018118

RESUMO

Air Traffic Control (ATC) has been classified as the fourth most stressful job. In this regard, sixteen controllers were asked to perform ecological ATC simulation during which behavioral (Radio Communications with pilots - RCs), subjective (stress perception) and neurophysiological signals (brain activity and skin conductance - SC) were collected. All the considered parameters reported significant changes under high stress conditions. In particular, the theta, alpha, and beta brain rhythms increased significantly (all p<0.05) all over the brain areas, and both the SC components exhibited higher values (p<0.01). Additionally, the number of speech under high stress decreased significantly (p<10-4) while both the mean and median value of the F0 component of the RC increased (p<0.01). The results can be employed to objectively measure and track the controller's stress level while dealing with ATC activities to better tailoring the workshift and maintaining high safety levels.


Assuntos
Aviação , Neurofisiologia , Ritmo beta , Encéfalo , Humanos , Fala
8.
Brain Sci ; 10(8)2020 Aug 13.
Artigo em Inglês | MEDLINE | ID: mdl-32823582

RESUMO

Analysis of physiological signals, electroencephalography more specifically, is considered a very promising technique to obtain objective measures for mental workload evaluation, however, it requires a complex apparatus to record, and thus, with poor usability in monitoring in-vehicle drivers' mental workload. This study proposes a methodology of constructing a novel mutual information-based feature set from the fusion of electroencephalography and vehicular signals acquired through a real driving experiment and deployed in evaluating drivers' mental workload. Mutual information of electroencephalography and vehicular signals were used as the prime factor for the fusion of features. In order to assess the reliability of the developed feature set mental workload score prediction, classification and event classification tasks were performed using different machine learning models. Moreover, features extracted from electroencephalography were used to compare the performance. In the prediction of mental workload score, expert-defined scores were used as the target values. For classification tasks, true labels were set from contextual information of the experiment. An extensive evaluation of every prediction tasks was carried out using different validation methods. In predicting the mental workload score from the proposed feature set lowest mean absolute error was 0.09 and for classifying mental workload highest accuracy was 94%. According to the outcome of the study, it can be stated that the novel mutual information based features developed through the proposed approach can be employed to classify and monitor in-vehicle drivers' mental workload.

9.
Sci Rep ; 10(1): 8600, 2020 05 25.
Artigo em Inglês | MEDLINE | ID: mdl-32451424

RESUMO

Stress is a word used to describe human reactions to emotionally, cognitively and physically challenging experiences. A hallmark of the stress response is the activation of the autonomic nervous system, resulting in the "fight-freeze-flight" response to a threat from a dangerous situation. Consequently, the capability to objectively assess and track a controller's stress level while dealing with air traffic control (ATC) activities would make it possible to better tailor the work shift and maintain high safety levels, as well as to preserve the operator's health. In this regard, sixteen controllers were asked to perform a realistic air traffic management (ATM) simulation during which subjective data (i.e. stress perception) and neurophysiological data (i.e. brain activity, heart rate, and galvanic skin response) were collected with the aim of accurately characterising the controller's stress level experienced in the various experimental conditions. In addition, external supervisors regularly evaluated the controllers in terms of manifested stress, safety, and efficiency throughout the ATM scenario. The results demonstrated 1) how the stressful events caused both supervisors and controllers to underestimate the experienced stress level, 2) the advantage of taking into account both cognitive and hormonal processes in order to define a reliable stress index, and 3) the importance of the points in time at which stress is measured owing to the potential transient effect once the stressful events have ceased.

10.
Brain Sci ; 10(4)2020 Apr 08.
Artigo em Inglês | MEDLINE | ID: mdl-32276318

RESUMO

The need for automatic detection and classification of high-frequency oscillations (HFOs) as biomarkers of the epileptogenic tissue is strongly felt in the clinical field. In this context, the employment of artificial intelligence methods could be the missing piece to achieve this goal. This work proposed a double-step procedure based on machine learning algorithms and tested it on an intracranial electroencephalogram (iEEG) dataset available online. The first step aimed to define the optimal length for signal segmentation, allowing for an optimal discrimination of segments with HFO relative to those without. In this case, binary classifiers have been tested on a set of energy features. The second step aimed to classify these segments into ripples, fast ripples and fast ripples occurring during ripples. Results suggest that LDA applied to 10 ms segmentation could provide the highest sensitivity (0.874) and 0.776 specificity for the discrimination of HFOs from no-HFO segments. Regarding the three-class classification, non-linear methods provided the highest values (around 90%) in terms of specificity and sensitivity, significantly different to the other three employed algorithms. Therefore, this machine-learning-based procedure could help clinicians to automatically reduce the quantity of irrelevant data.

11.
Handb Clin Neurol ; 168: 199-205, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32164853

RESUMO

The human capacity to simultaneously perform several tasks depends on the quantity and the mode of mentally processing the information imposed by the tasks. Since operational environments are highly dynamic, priorities across tasks will be expected to change as the mission evolves, thus the capability to reallocate the mental resources dynamically depending on such changes is very important. The resources required in very complex situations, such as air traffic management (ATM), can exceed the user's available resources leading to increased workload and performance impairments. In this regard, the availability of information concerning the workload experienced by the operators while dealing with tasks will be fundamental for both warning them when overload conditions are approaching and improving interactions with the system. The idea of our work was to use neurophysiologic data collected from professional air traffic controllers (ATCOs) to provide additional information to standard measures with which to assess the ATCOs' expertise and a machine learning electroencephalography-based index to evaluate their mental workload during the execution of ATC tasks. The results showed that the proposed method was able to track the workload alongside the execution of the realistic ATM scenario, and provide added values to objectively assess the expertise of the ATCOs.

12.
Brain Sci ; 10(1)2020 Jan 15.
Artigo em Inglês | MEDLINE | ID: mdl-31952181

RESUMO

Vigilance degradation usually causes significant performance decrement. It is also considered the major factor causing the out-of-the-loop phenomenon (OOTL) occurrence. OOTL is strongly related to a high level of automation in operative contexts such as the Air Traffic Management (ATM), and it could lead to a negative impact on the Air Traffic Controllers' (ATCOs) engagement. As a consequence, being able to monitor the ATCOs' vigilance would be very important to prevent risky situations. In this context, the present study aimed to characterise and assess the vigilance level by using electroencephalographic (EEG) measures. The first study, involving 13 participants in laboratory settings allowed to find out the neurophysiological features mostly related to vigilance decrements. Those results were also confirmed under realistic ATM settings recruiting 10 professional ATCOs. The results demonstrated that (i) there was a significant performance decrement related to vigilance reduction; (ii) there were no substantial differences between the identified neurophysiological features in controlled and ecological settings, and the EEG-channel configuration defined in laboratory was able to discriminate and classify vigilance changes in ATCOs' vigilance with high accuracy (up to 84%); (iii) the derived two EEG-channel configuration was able to assess vigilance variations reporting only slight accuracy reduction.

13.
Comput Intell Neurosci ; 2019: 1976847, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31641346

RESUMO

The new technological advances achieved during the last decade allowed the scientific community to investigate and employ neurophysiological measures not only for research purposes but also for the study of human behaviour in real and daily life situations. The aim of this review is to understand how and whether neuroscientific technologies can be effectively employed to better understand the human behaviour in real decision-making contexts. To do so, firstly, we will describe the historical development of neuromarketing and its main applications in assessing the sensory perceptions of some marketing and advertising stimuli. Then, we will describe the main neuroscientific tools available for such kind of investigations (e.g., measuring the cerebral electrical or hemodynamic activity, the eye movements, and the psychometric responses). Also, this review will present different brain measurement techniques, along with their pros and cons, and the main cerebral indexes linked to the specific mental states of interest (used in most of the neuromarketing research). Such indexes have been supported by adequate validations from the scientific community and are largely employed in neuromarketing research. This review will also discuss a series of papers that present different neuromarketing applications, such us in-store choices and retail, services, pricing, brand perception, web usability, neuropolitics, evaluation of the food and wine taste, and aesthetic perception of artworks. Furthermore, this work will face the ethical issues arisen on the use of these tools for the evaluation of the human behaviour during decision-making tasks. In conclusion, the main challenges that neuromarketing is going to face, as well as future directions and possible scenarios that could be derived by the use of neuroscience in the marketing field, will be identified and discussed.


Assuntos
Encéfalo/fisiologia , Comportamento do Consumidor , Olho , Neurofisiologia , Publicidade/métodos , Humanos , Neurofisiologia/métodos , Neurociências/métodos
14.
Front Hum Neurosci ; 13: 296, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31555113

RESUMO

Increasing the level of automation in air traffic management is seen as a measure to increase the performance of the service to satisfy the predicted future demand. This is expected to result in new roles for the human operator: he will mainly monitor highly automated systems and seldom intervene. Therefore, air traffic controllers (ATCos) would often work in a supervisory or control mode rather than in a direct operating mode. However, it has been demonstrated how human operators in such a role are affected by human performance issues, known as Out-Of-The-Loop (OOTL) phenomenon, consisting in lack of attention, loss of situational awareness and de-skilling. A countermeasure to this phenomenon has been identified in the adaptive automation (AA), i.e., a system able to allocate the operative tasks to the machine or to the operator depending on their needs. In this context, psychophysiological measures have been highlighted as powerful tool to provide a reliable, unobtrusive and real-time assessment of the ATCo's mental state to be used as control logic for AA-based systems. In this paper, it is presented the so-called "Vigilance and Attention Controller", a system based on electroencephalography (EEG) and eye-tracking (ET) techniques, aimed to assess in real time the vigilance level of an ATCo dealing with a highly automated human-machine interface and to use this measure to adapt the level of automation of the interface itself. The system has been tested on 14 professional ATCos performing two highly realistic scenarios, one with the system disabled and one with the system enabled. The results confirmed that (i) long high automated tasks induce vigilance decreasing and OOTL-related phenomena; (ii) EEG measures are sensitive to these kinds of mental impairments; and (iii) AA was able to counteract this negative effect by keeping the ATCo more involved within the operative task. The results were confirmed by EEG and ET measures as well as by performance and subjective ones, providing a clear example of potential applications and related benefits of AA.

15.
Front Hum Neurosci ; 13: 303, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31551735

RESUMO

New solutions in operational environments are often, among objective measurements, evaluated by using subjective assessment and judgment from experts. Anyhow, it has been demonstrated that subjective measures suffer from poor resolution due to a high intra and inter-operator variability. Also, performance measures, if available, could provide just partial information, since an operator could achieve the same performance but experiencing a different workload. In this study, we aimed to demonstrate: (i) the higher resolution of neurophysiological measures in comparison to subjective ones; and (ii) how the simultaneous employment of neurophysiological measures and behavioral ones could allow a holistic assessment of operational tools. In this regard, we tested the effectiveness of an electroencephalography (EEG)-based neurophysiological index (WEEG index) in comparing two different solutions (i.e., Normal and Augmented) in terms of experienced workload. In this regard, 16 professional air traffic controllers (ATCOs) have been asked to perform two operational scenarios. Galvanic Skin Response (GSR) has also been recorded to evaluate the level of arousal (i.e., operator involvement) during the two scenarios execution. NASA-TLX questionnaire has been used to evaluate the perceived workload, and an expert was asked to assess performance achieved by the ATCOs. Finally, reaction times on specific operational events relevant for the assessment of the two solutions, have also been collected. Results highlighted that the Augmented solution induced a local increase in subjects performance (Reaction times). At the same time, this solution induced an increase in the workload experienced by the participants (WEEG). Anyhow, this increase is still acceptable, since it did not negatively impact the performance and has to be intended only as a consequence of the higher engagement of the ATCOs. This behavioral effect is totally in line with physiological results obtained in terms of arousal (GSR), that increased during the scenario with augmentation. Subjective measures (NASA-TLX) did not highlight any significant variation in perceived workload. These results suggest that neurophysiological measure provide additional information than behavioral and subjective ones, even at a level of few seconds, and its employment during the pre-operational activities (e.g., design process) could allow a more holistic and accurate evaluation of new solutions.

16.
Hear Res ; 379: 31-42, 2019 08.
Artigo em Inglês | MEDLINE | ID: mdl-31042607

RESUMO

Unilateral hearing loss constitutes a field of growing interest in the scientific community. In fact, this kind of patients represent a unique and physiological way to investigate how neuroplasticity overcame unilateral deafferentation by implementing particular strategies that produce apparently next- to- normal hearing behavioural performances. This explains why such patients have been underinvestigated for a long time. Thanks to the availability of techniques able to study the cerebral activity underlying the mentioned behavioural outcomes, the aim of the present research was to elucidate whether different electroencephalographic (EEG) patterns occurred in unilateral hearing loss (UHL) children in comparison to normal hearing (NH) controls during speech-in-noise listening. Given the intrinsic lateralized nature of such patients, due to the unilateral side of hearing impairment, the experimental question was to assess whether this would reflect a different EEG pattern while performing a word in noise recognition task varying the direction of the noise source. Results showed a correlation between the period of deafness and the cortical activity asymmetry toward the hearing ear side in the frontal, parietal and occipital areas in all the experimental conditions. Concerning alpha and beta activity in the frontal and central areas highlighted that in the NH group, the lateralization was always left-sided during the Quiet condition, while it was right-sided in noise conditions; this evidence was not, however, detected also in the UHL group. In addition, focusing on the theta and alpha activity in the frontal areas (Broca area) during noise conditions, while the activity was always left-lateralized in the NH group, it was ipsilateral to the direction of the background noise in the UHL group, and of a weaker extent than in NH controls. Furthermore, in noise conditions, only the UHL group showed a higher theta activity in the temporal areas ipsilateral to the side where the background noise was directed to. Finally, in the case of bilateral noise (background noise and word signal both coming from the same two sources), the theta and alpha activity in the frontal areas (Broca area) was left-lateralized in the case of the NH group and lateralized towards the side of the better hearing ear in the case of the UHL group. Taken together, this evidence supports the establishment of a particular EEG pattern occurrence in UHL children taking place in the frontal (Broca area), temporal and parietal lobes, probably physiologically established in order to deal with different sound and noise source directions.


Assuntos
Percepção Auditiva/fisiologia , Lateralidade Funcional/fisiologia , Perda Auditiva Unilateral/fisiopatologia , Percepção da Fala/fisiologia , Adolescente , Ondas Encefálicas/fisiologia , Estudos de Casos e Controles , Criança , Eletroencefalografia , Feminino , Voluntários Saudáveis , Perda Auditiva Unilateral/psicologia , Humanos , Masculino , Ruído
17.
Sensors (Basel) ; 19(6)2019 Mar 19.
Artigo em Inglês | MEDLINE | ID: mdl-30893791

RESUMO

One century after the first recording of human electroencephalographic (EEG) signals, EEG has become one of the most used neuroimaging techniques. The medical devices industry is now able to produce small and reliable EEG systems, enabling a wide variety of applications also with no-clinical aims, providing a powerful tool to neuroscientific research. However, these systems still suffer from a critical limitation, consisting in the use of wet electrodes, that are uncomfortable and require expertise to install and time from the user. In this context, dozens of different concepts of EEG dry electrodes have been recently developed, and there is the common opinion that they are reaching traditional wet electrodes quality standards. However, although many papers have tried to validate them in terms of signal quality and usability, a comprehensive comparison of different dry electrode types from multiple points of view is still missing. The present work proposes a comparison of three different dry electrode types, selected among the main solutions at present, against wet electrodes, taking into account several aspects, both in terms of signal quality and usability. In particular, the three types consisted in gold-coated single pin, multiple pins and solid-gel electrodes. The results confirmed the great standards achieved by dry electrode industry, since it was possible to obtain results comparable to wet electrodes in terms of signals spectra and mental states classification, but at the same time drastically reducing the time of montage and enhancing the comfort. In particular, multiple-pins and solid-gel electrodes overcome gold-coated single-pin-based ones in terms of comfort.


Assuntos
Encéfalo/fisiologia , Eletroencefalografia/métodos , Adulto , Área Sob a Curva , Artefatos , Eletrodos , Ouro/química , Humanos , Aprendizado de Máquina , Masculino , Curva ROC , Prata/química , Dispositivos Eletrônicos Vestíveis
18.
Sensors (Basel) ; 19(3)2019 Feb 09.
Artigo em Inglês | MEDLINE | ID: mdl-30744081

RESUMO

Human tissues own conductive properties, and the electrical activity produced by human organs can propagate throughout the body due to neuro transmitters and electrolytes. Therefore, it might be reasonable to hypothesize correlations and similarities between electrical activities among different parts of the body. Since no works have been found in this direction, the proposed study aimed at overcoming this lack of evidence and seeking analogies between the brain activity and the electrical activity of non-cerebral locations, such as the neck and wrists, to determine if i) cerebral parameters can be estimated from non-cerebral sites, and if ii) non-cerebral sensors can replace cerebral sensors for the evaluation of the users under specific experimental conditions, such as eyes open or closed. In fact, the use of cerebral sensors requires high-qualified personnel, and reliable recording systems, which are still expensive. Therefore, the possibility to use cheaper and easy-to-use equipment to estimate cerebral parameters will allow making some brain-based applications less invasive and expensive, and easier to employ. The results demonstrated the occurrence of significant correlations and analogies between cerebral and non-cerebral electrical activity. Furthermore, the same discrimination and classification accuracy were found in using the cerebral or non-cerebral sites for the user's status assessment.


Assuntos
Ondas Encefálicas/fisiologia , Encéfalo/fisiologia , Condutividade Elétrica , Processamento de Sinais Assistido por Computador , Adulto , Eletroencefalografia , Mãos/fisiologia , Humanos , Aprendizado de Máquina , Pescoço/fisiologia , Adulto Jovem
19.
Annu Int Conf IEEE Eng Med Biol Soc ; 2019: 4554-4557, 2019 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-31946878

RESUMO

According to Human-System Integration analyses, cooperation between humans is one of the most relevant factors in many of today's human activities: do not take it into account in models of working environments is highly farfetched. Although the Human Factor aspects have obtained much benefit from the use of neurophysiological signals to estimate human-machine interaction, very few are the indications about neurophysiological analysis of human cooperation deviating from typical laboratory tasks. Among these, some evidence showed that there is a relationship between the mental workload experienced by the subjects cooperating and some characteristics of the brain network obtained through multi-subjects connectivity analysis. Accordingly, this work aimed to identify common dynamics in time series that describe the EEG-based mental workload of cooperating subjects and to exploit this information to create an index of cooperation. In order to answer the question whether a causality between the workload values of the two subjects can be in some way discerned and related to the cooperation required by the task, Granger's causality test has been performed. This method was applied to two different tasks simulating features of the aerospace domain. The results showed that the causality test was statistically significant for the most collaborating couple. In addition, causality values are modulated by the presence of real couples compared to fake couples. The extension of the experimental sample could open up the possibility for the development of an objective and neurophysiological signals-based cooperation index.


Assuntos
Encéfalo , Eletroencefalografia , Ergonomia , Carga de Trabalho , Encéfalo/fisiologia , Humanos
20.
Annu Int Conf IEEE Eng Med Biol Soc ; 2018: 4619-4622, 2018 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-30441381

RESUMO

This study aims at investigating the possibility to employ neurophysiological measures to assess the humanmachine interaction effectiveness. Such a measure can be used to compare new technologies or solutions, with the final purpose to enhance operator's experience and increase safety. In the present work, two different interaction modalities (Normal and Augmented) related to Air Traffic Management field have been compared, by involving 10 professional air traffic controllers in a control tower simulated environment. Experimental task consisted in locating aircrafts in different airspace positions by using the sense of hearing. In one modality (i.e. "Normal"), all the sound sources (aircrafts) had the same amplification factor. In the "Augmented" modality, the amplification factor of the sound sources located along the participant head sagittal axis was increased, while the intensity of sound sources located outside this axis decreased. In other words, when the user oriented his head toward the aircraft position, the related sound was amplified. Performance data, subjective questionnaires (i.e. NASA-TLX) and neurophysiological measures (i.e. EEG-based) related to the experienced workload have been collected. Results showed higher significant performance achieved by the users during the "Augmented" modality with respect to the "Normal" one, supported by a significant decreasing in experienced workload, evaluated by using EEG-based index. In addition, Performance and EEG-based workload index showed a significant negative correlation. On the contrary, subjective workload analysis did not show any significant trend. This result is a demonstration of the higher effectiveness of neurophysiological measures with respect to subjective ones for Human-Computer Interaction assessment.


Assuntos
Aeronaves , Sistemas Homem-Máquina , Localização de Som , Análise e Desempenho de Tarefas , Carga de Trabalho , Percepção Auditiva , Eletroencefalografia , Audição , Humanos , Monitorização Neurofisiológica , Ocupações
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