It is not rare in philosophy and psychology to see theorists fall into dichotomous thinking about mental phenomena. On one side of the dichotomy there are processes that I will label “unintelligent.” These processes are thought to be unconscious, implicit, automatic, unintentional, involuntary, procedural, and non-cognitive. On the other side, there are “intelligent” processes that are conscious, explicit, controlled, intentional, voluntary, declarative, and cognitive. Often, if a process or behavior is characterized by one of the features from either of the (...) above lists, the process or behavior is classified as falling under the category to which the feature belongs. For example, if a process is implicit this is usually considered sufficient for classifying it as “unintelligent” and for assuming that the remaining features that fall under the “unintelligent” grouping will apply to it as well. Accordingly, if a process or behavior is automatic, philosophers often consider it to be unintelligent. It is my goal in this paper to challenge the conceptual slip from “automatic” to “unintelligent”. I will argue that there are a whole range of properties highlighted by the existing psychological literature that make automaticity a much more complex phenomenon than is usually appreciated. I will then go on to discuss two further important relationships between automatic processes and controlled processes that arise when we think about automatic processes in the context of skilled behavior. These interactions should add to our resistance to classifying automaticity as unintelligent or mindless. In Sect. 1, I present a few representative cases of philosophers classifying automatic processes and behaviors as mindless or unintelligent. In Sect. 2, I review trends in the psychology of automaticity in order highlight a complex set of features that are characteristic, though not definitive, of automatic processes and behaviors. In Sect. 3, I argue that at least some automatic processes are likely cognitively penetrable. In Sect. 4, I argue that the structure of skilled automatic processes is shaped diachronically by practice, training and learning. Taken together, these considerations should dislodge the temptation to equate “automatic” with “unintelligent”. (shrink)

This paper provides an overview of developments in a dual processing theory of automatic and controlled processing that began with the empirical and theoretical work described by Schneider and Shiffrin (1977) and Shiffrin and Schneider (1977) over a quarter century ago. A review of relevant empirical findings suggests that there is a set of core behavioral phenomena reflecting differences between controlled and automatic processing that must be addressed by a successful theory. These phenomena relate to: consistency in training, serial (...) versus parallel processing, level of effort, robustness to stressors, degree of control, effects on long‐term memory, and priority encoding. We detail a computational model of controlled processing, CAP2, that accounts for these phenomena as emergent properties of an underlying hybrid computational architecture. The model employs a large network of distributed data modules that can categorize, buffer, associate, and prioritize information. Each module is a connectionist network with input and output layers, and each module communicates with a central Control System by outputting priority and activity report signals, and by receiving control signals. The Control System is composed of five processors including a Goal Processor, an Attention Controller, an Activity Monitor, an Episodic Store, and a Gating & Report Relay. The transition from controlled to automatic processing occurs in this model as the data modules become capable of transmitting their output without mediation by the Control System. We describe recent progress in mapping the components of this model onto specific neuroanatomical substrates, briefly discuss the potential for applying functional neuroimaging techniques to test the model's predictions, and its relation to other models. (shrink)

As a theory of skill acquisition, the instance theory of automatization posits that, after a period of training, algorithm‐based performance is replaced by retrieval‐based performance. This theory has been tested using alphabet‐arithmetic verification tasks (e.g., is A + 4 = E?), in which the equations are necessarily solved by counting at the beginning of practice but can be solved by memory retrieval after practice. A way to infer individuals’ strategies in this task was supposedly provided by the opportunistic‐stopping phenomenon, (...) according to which, if individuals use counting, they can take the opportunity to stop counting when a false equation associated with a letter preceding the true answer has to be verified (e.g., A + 4 = D). In this case, such within‐count equations would be rejected faster than false equations associated with letters following the true answers (e.g., A + 4 = F, i.e., outside‐of‐count equations). Conversely, the absence of opportunistic stopping would be the sign of retrieval. However, through a training experiment involving 19 adults, we show that opportunistic stopping is not a phenomenon that can be observed in the context of an alphabet‐arithmetic verification task. Moreover, we provide an explanation of how and why it was wrongly inferred in the past. These results and conclusions have important implications for learning theories because they demonstrate that a shift from counting to retrieval over training cannot be deduced from verification time differences between outside and within‐count equations in an alphabet‐arithmetic task. (shrink)

Brain monitoring combined with automatic analysis of EEGs provides a clinical decision support tool that can reduce time to diagnosis and assist clinicians in real-time monitoring applications (e.g., neurological intensive care units). Clinicians have indicated that a sensitivity of 95% with specificity below 5% was the minimum requirement for clinical acceptance. In this study, a high-performance automated EEG analysis system based on principles of machine learning and big data is proposed. This hybrid architecture integrates hidden Markov models (HMMs) for sequential (...) decoding of EEG events with deep learning-based postprocessing that incorporates temporal and spatial context. These algorithms are trained and evaluated using the Temple University Hospital EEG, which is the largest publicly available corpus of clinical EEG recordings in the world. This system automatically processes EEG records and classifies three patterns of clinical interest in brain activity that might be useful in diagnosing brain disorders: (1) spike and/or sharp waves, (2) generalized periodic epileptiform discharges, (3) periodic lateralized epileptiform discharges. It also classifies three patterns used to model the background EEG activity: (1) eye movement, (2) artifacts and (3) background. Our approach delivers a sensitivity above 90% while maintaining a specificity below 5%. We also demonstrate that this system delivers a low false alarm rate, which is critical for any spike detection application. (shrink)

GoalThis paper presents an immersive Virtual Reality system to analyze and train Executive Functions of soccer players. EFs are important cognitive functions for athletes. They are a relevant quality that distinguishes amateurs from professionals.MethodThe system is based on immersive technology, hence, the user interacts naturally and experiences a training session in a virtual world. The proposed system has a modular design supporting the extension of various so-called game modes. Game modes combine selected game mechanics with specific simulation content to (...) target particular training aspects. The system architecture decouples selection/parameterization and analysis of training sessions via a coaching app from an Unity3D-based VR simulation core. Monitoring of user performance and progress is recorded by a database that sends the necessary feedback to the coaching app for analysis.ResultsThe system is tested for VR-critical performance criteria to reveal the usefulness of a new interaction paradigm in the cognitive training and analysis of EFs. Subjective ratings for overall usability show that the design as VR application enhances the user experience compared to a traditional desktop app; whereas the new, unfamiliar interaction paradigm does not negatively impact the effort for using the application.ConclusionThe system can provide immersive training of EF in a fully virtual environment, eliminating potential distraction. It further provides an easy-to-use analyzes tool to compare user but also an automatic, adaptive training mode. (shrink)

This paper presents a gamified motor imagery brain-computer interface (MI-BCI) training in immersive virtual reality. Aim of the proposed training method is to increase engagement, attention, and motivation in co-adaptive event-driven MI-BCI training. This was achieved using gamification, progressive increase of the training pace, and virtual reality design reinforcing the body ownership transfer (embodiment) into the avatar. From the 20 healthy participants performing 6 runs of 2-class MI-BCI training (left/right hand), 19 were trained for a (...) basic level of MI-BCI operation, with average peak accuracy in the session equal to 75.84\%. This confirms the proposed training method succeeded in improvement of the MI-BCI skills; moreover, participants were leaving the session in high positive affect. Although the performance was not directly correlated to the degree of embodiment, subjective magnitude of the body ownership transfer illusion correlated with the abilities to modulate the sensorimotor rhythm. (shrink)

In this paper, we study the performance of baseline hidden Markov model (HMM) for segmentation of speech signals. It is applied on single-speaker segmentation task, using Hindi speech database. The automatic phoneme segmentation framework evolved imitates the human phoneme segmentation process. A set of 44 Hindi phonemes were chosen for the segmentation experiment, wherein we used continuous density hidden Markov model (CDHMM) with a mixture of Gaussian distribution. The left-to-right topology with no skip states has been selected as it is (...) effective in speech recognition due to its consistency with the natural way of articulating the spoken words. This system accepts speech utterances along with their orthographic “transcriptions” and generates segmentation information of the speech. This corpus was used to develop context-independent hidden Markov models (HMMs) for each of the Hindi phonemes. The system was trained using numerous sentences that are relevant to provide information to the passengers of the Metro Rail. The system was validated against a few manually segmented speech utterances. The evaluation of the experiments shows that the best performance is obtained by using a combination of two Gaussians mixtures and five HMM states. A category-wise phoneme error analysis has been performed, and the performance of the phonetic segmentation has been reported. The modeling of HMMs has been implemented using Microsoft Visual Studio 2005 (C++), and the system is designed to work on Windows operating system. The goal of this study is automatic segmentation of speech at phonetic level. (shrink)

We investigated the automaticity of implicit sequence learning by varying perceptual load in a pure perceptual sequence learning paradigm. Participants responded to the randomly changing identity of a target, while the irrelevant target location was structured. In Experiment 1, the target was presented under low or high perceptual load during training, whereas testing occurred without load. Unexpectedly, no sequence learning was observed. In Experiment 2, perceptual load was introduced during the test phase to determine whether load is required to (...) express perceptual knowledge. Learning itself was unaffected by visuospatial demands, but more learning was expressed under high load test conditions. In Experiment 3, we demonstrated that perceptual load is not required for the acquisition of perceptual sequence knowledge. These findings suggest that perceptual load does not mediate the perceptual sequence learning process itself, supporting the automaticity of implicit learning, but is mandatory for the expression of pure perceptual sequence knowledge. (shrink)

This paper implements the continuous Hindi Automatic Speech Recognition (ASR) system using the proposed integrated features vector with Recurrent Neural Network (RNN) based Language Modeling (LM). The proposed system also implements the speaker adaptation using Maximum-Likelihood Linear Regression (MLLR) and Constrained Maximum likelihood Linear Regression (C-MLLR). This system is discriminatively trained by Maximum Mutual Information (MMI) and Minimum Phone Error (MPE) techniques with 256 Gaussian mixture per Hidden Markov Model(HMM) state. The training of the baseline system has been done (...) using a phonetically rich Hindi dataset. The results show that discriminative training enhances the baseline system performance by up to 3%. Further improvement of ~7% has been recorded by applying RNN LM. The proposed Hindi ASR system shows significant performance improvement over other current state-of-the-art techniques. (shrink)

The brain’s ability to recognize acoustic changes occurring in rapid temporal succession is important for speech and successful language development. Children with specific language impairment (SLI) are characterized by deficient dynamics of temporal information processing (TIP) in the millisecond time range accompanied by disordered language development. Furthermore, previous studies have found that intervention based on amelioration of TIP resulted in improvement of both language and other cognitive functions. This study aimed to explain the changes associated with TIP training from (...) the perspective of event-related potentials (ERPs). Thirty-six children aged 5–8 years (26 boys, 10 girls) diagnosed with SLI underwent two types of intense audio-visual computer intervention: experimental TIP training targeted at the millisecond time range ( n = 18) or control non-TIP training ( n = 18). Paired 50 ms tones of 1000 Hz and 1200 Hz were presented with inter-stimulus intervals (ISIs) of either 50 ms (Short ISI Condition) or 200 ms (Long ISI Condition). Auditory ERPs were measured in a passive oddball paradigm before and after each type of training. The mismatch negativity (MMN) paradigm was applied as an electrophysiological indicator of the brain’s ability to automatically detect violations of regularity in paired tones presented in rapid succession. Moreover, the P3a component was also analyzed. After 24 sessions of temporal training (in the experimental group) MMN amplitude enhancement was observed in both ISI conditions, reflecting increased efficiency in perceiving changes in rapid auditory sequences. In both experimental and control groups, P3a amplitude was enhanced in both ISIs. This may be due to the improvement of involuntary attention shifting to the auditory events involved in each training type. To conclude, temporal training, compared to non-temporal control training, improved the ability to detect changes in a rapid auditory stream in children with SLI. (shrink)

Higher education in the 21st century faces the challenge of changing the way in which knowledge is conveyed and how teachers and students interact in the teaching-learning process. The current pandemic caused by SARS-CoV-2 has hastened the need to face up to this challenge and has furthered the need to approach the issue from the perspective of digitalisation. To achieve this, it is necessary to design training programmes geared towards teaching staff and which address both the use of technology (...) and instructional design aimed at promoting the development of self-regulated learning and automatic feedback systems. In this study, work was carried out with 23 teachers in a training programme conducted through Moodle. The aims were: to test whether there were any significant differences between the behaviour patterns of new teachers compared to experienced teachers, to determine whether clusters of behaviour patterns corresponded to the type of teacher and to ascertain whether the level of teacher satisfaction with the training activity in digital teaching will depend on the type of teacher. A quantitative as well as a qualitative design was applied. Differences were found in the behaviour patterns in the training activities for the development of rubrics and use of learning analytics systems in virtual learning environments. It was also found that the type of teacher did not correspond exactly to the behaviour cluster in the learning platform. In addition, no significant differences were found in the level of satisfaction between the two kinds of teacher. The main contribution this study makes is to provide a detailed description of the training stage as well as the materials required for its repetition. Further analytical studies are required on teacher perception of training programmes in digital teaching in order to provide personalised training proposals that lead to an effective use of teaching in digital environments. (shrink)

El ensayo rememora las raíces fenomenológicas que comparten las obras Filosofía para hacer las paces de Vicent Martínez Guzmán, La paz imperfecta de Francisco Muñoz y la filosofía de las paces transracionales en la que se enfoca la escuela de Estudios de Paz de la Universidad de Innsbruck. Sobre esta base me refiero después a la aplicación pedagógica y didáctica de dichas raíces en la educación académica para la paz. Este trabajo hace referencia a las experiencias metodológicas del aprendizaje académico (...) en grupos, y sus consecuencias para el desarrollo del currículo de los Estudios de Paz, entendiendo estos como una formación en la construcción estratégica de capacidades y relaciones. Finalmente resalto las etapas del aprendizaje, en el sentido de ‘pelar la cebolla del Ego’ y de proveer el marco para el desarrollo libre de los grupos y los temas.This essay retraces the shared phenomenological root of Vicent Martínez Guzmán’s Filosofía para Hacer las Paces, Francisco Muñoz La Paz Imperfecta and the Innsbruck School’s Transracional Peace Philosophy. From there it forges ahead to the pedagogical and didactical application of these roots in academic peace education. It refers to the methodological experiences of academic learning in T-groups and its consequence for curricula development if Peace Studies is understood as Strategic Capacity and Rela-tionship Training. Finally, it highlights the stages of learning in the sense of `Peeling the Ego’s Onion´ and providing the frame for the team’s and the theme’s free development. (shrink)

Studies by Gardiner and colleagues connecting musical pitch and arithmetic learning support Rips et al.'s proposal that natural number concepts are constructed on a base of innate abilities. Our evidence suggests that innate ability concerning sequence ( or BSC) is fundamental. Mathematical engagement relating number to BSC does not develop automatically, but, rather, should be encouraged through teaching.

In the exploratory study reported here, we tested the efficacy of an intervention designed to train teenagers with Möbius syndrome (MS) to increase the use of alternative communication strategies (e.g., gestures) to compensate for their lack of facial expressivity. Specifically, we expected the intervention to increase the level of rapport experienced in social interactions by our participants. In addition, we aimed to identify the mechanisms responsible for any such increase in rapport. In the study, five teenagers with MS interacted with (...) three naïve participants without MS before the intervention, and with three different naïve participants without MS after the intervention. Rapport was assessed by self-report and by behavioral coders who rated videos of the interactions. Individual non-verbal behavior was assessed via behavioral coders, whereas verbal behavior was automatically extracted from the sound files. Alignment was assessed using cross recurrence quantification analysis and mixed-effects models. The results showed that observer-coded rapport was greater after the intervention, whereas self-reported rapport did not change significantly. Observer-coded gesture and expressivity increased in participants with and without MS, whereas overall linguistic alignment decreased. Fidgeting and repetitiveness of verbal behavior also decreased in both groups. In sum, the intervention may impact non-verbal and verbal behavior in participants with and without MS, increasing rapport as well as overall gesturing, while decreasing alignment. (shrink)

Perceptual expertise refers to learning that is specific to a domain, that transfers to new items within the trained domain, and that leads to automatic processing in the sense that expertise effects can be measured across a variety of tasks. It can be argued that most of us possess some degree of perceptual expertise in a least one, if not several domains, thereby giving the study of perceptual expertise broad application. Some object categories may in fact be objects of perceptual (...) expertise to the majority of people: Faces appear to be one such example. Thus, the use of face stimuli, or the comparison of face and object perception, can be a powerful way to ask whether a given process is influenced by perceptual expertise. Here, we emphasize one characteristic way that face processing appears to differ from nonface processing: that is, the degree to which they recruit a “holistic” rather than a “featural” perceptual strategy. This review brings evidence that expertise influences perceptual processing together with recent findings that the capacity of visual short-term memory is greater in perceptual experts and explores the relationship between the two. (shrink)

This book deals with solving a pressing organizational challenge of bringing employees up to speed faster. In the fast-paced business world, organizations need faster readiness of employees to handle the complex responsibilities of their jobs. The author conducted an extensive doctoral research study with 85 global experts across 66 project cases to explore the practices and strategies that were proven to reduce time to proficiency of employees in a range of organizations worldwide. This book provides the readers with a (...) first-hand account of findings exclusively related to training and learning strategies, instructional methods, and curriculum design. This book delivers over 21 training and learning strategies across online learning, classroom instructions, and on-the-job learning. These strategies will allow training designers and learning specialists to design workplace training programs that hold the potential to shorten time to proficiency of employees. The book not only describes findings of the study and theoretical underpinnings, but it also provides practical guidance for implementation to equip corporate learning specialists, HR professionals, training leaders, performance consultants, and direct managers. (shrink)

To shorten the travel time and improve comfort, the automatic train driving system is considered to replace manual driving. In this article, an automatic control method of computer application data-processing system based on artificial intelligence is proposed. An automatic train operation (ATO) introduced the structure and function of an autopilot system (train), optimized the train running on the target curve, introduced the basic principle of fuzzy generalized predictive control (PC) algorithm, and combined with the characteristics of ATO system design the (...) speed controller based on optimization algorithm, the target curve to make use of the designed controller to track and simulation validation. The experimental outcomes demonstrate that when the train runs to 90 s, the displacement difference reaches about 40 m, which proves that the fuzzy PC has better displacement tracking, punctual arrival, and higher stopping accuracy. (shrink)

Advances in technology have transformed and expanded the ways in which policing is run. One new manifestation is the mass acquisition and processing of private facial images via automatic facial recognition by the police: what we conceptualise as AFR-based policing. However, there is still a lack of clarity on the manner and extent to which this largely-unregulated technology is used by law enforcement agencies and on its impact on fundamental rights. Social understanding and involvement are still insufficient in the context (...) of AFR technologies, which in turn affects social trust in and legitimacy and effectiveness of intelligent governance. This article delineates the function creep of this new concept, identifying the individual and collective harms it engenders. A technological, contextual perspective of the function creep of AFR in policing will evidence the comprehensive creep of training datasets and learning algorithms, which have by-passed an ignorant public. We thus argue individual harms to dignity, privacy and autonomy, combine to constitute a form of cultural harm, impacting directly on individuals and society as a whole. While recognising the limitations of what the law can achieve, we conclude by considering options for redress and the creation of an enhanced regulatory and oversight framework model, or Code of Conduct, as a means of encouraging cultural change from prevailing police indifference to enforcing respect for the human rights violations potentially engaged. The imperative will be to strengthen the top-level design and technical support of AFR policing, imbuing it with the values implicit in the rule of law, democratisation and scientisation-to enhance public confidence and trust in AFR social governance, and to promote civilised social governance in AFR policing. (shrink)

Like other science, technology, engineering, and mathematics fields, ecological research needs ethics. Given the rapid pace of technological developments and social change, it is important for scientists to have the vocabulary and critical-thinking skills necessary to identify, analyze, and communicate the ethical issues generated by the research and practices within their fields of specialization. The goal of introducing ethics education for ecological researchers would be to promote a discipline in which scientists are willing and able to engage in ethical questions (...) and problem solving, even if they do so inadequately at first. Practicing ecologists ought to be able to identify and critically evaluate the ethical dimensions of their field studies because ecologists are at the forefront of important interfaces between humans and other-than-human organisms and natural systems. They are among the first to identify the impact of anthropogenic changes to the environments. Rapidly changing local and global environments mean that ecologists will be on the front line of any efforts to create a sustainable lifestyle for humans on this planet. (shrink)

Due to existence of a huge amount of textual data either on the World Wide Web or in textual databases like PubMed, the development of novel automatic keyphrase extraction methods has emerged as one of the key research problems in recent past. Consequently, a number of machine learning techniques, mostly supervised, have been proposed to extract keyphrases from text documents. But, one of the main bottlenecks that hinders the success of such systems is the requirement of annotated corpora for (...) class='Hi'>training purpose. In this paper, we propose the design of a deep text mining system to identify keyphrases in text documents that are either unstructured or semi-structured in nature. The novelty of our system lies in its applicability on a single document, instead of demanding a collection of annotated texts for training, to identify keyphrases embedded within it. The proposed system applies parsing techniques to identify candidate phrases. After mapping the original set of candidate phrases into a low-dimensional space using Singular Value Decomposition, the Markov Clustering technique is applied to cluster related sentences together. Finally, considering each cluster as a document, Latent Dirichlet Allocation is applied to identify feasible keyphrases that are presented to users in non-increasing order of their relevance score values. The efficacy of the proposed system is established through experimentation on datasets from two different domains. On comparative evaluation, we found that the proposed system outperforms KEA and KEA that apply the supervised machine learning approach for automatic keyphrase extraction from text documents. (shrink)

Available corpora for Argument Mining differ along several axes, and one of the key differences is the presence (or absence) of discourse markers to signal argumentative content. Exploring effective ways to use discourse markers has received wide attention in various discourse parsing tasks, from which it is well-known that discourse markers are strong indicators of discourse relations. To improve the robustness of Argument Mining systems across different genres, we propose to automatically augment a given text with discourse markers such (...) that all relations are explicitly signaled. Our analysis unveils that popular language models taken out-of-the-box fail on this task; however, when fine-tuned on a new heterogeneous dataset that we construct (including synthetic and real examples), they perform considerably better. We demonstrate the impact of our approach on an Argument Mining downstream task, evaluated on different corpora, showing that language models can be trained to automatically fill in discourse markers across different corpora, improving the performance of a downstream model in some, but not all, cases. Our proposed approach can further be employed as an assistant tool for better discourse understanding. (shrink)

The aim of this study was to test the effect of face cooling with cold water vs. face cooling with neutral water during high-intensity swimming training on both the core temperature and thermal perceptions in internationally ranked long-distance swimmers during 2 randomized swimming sessions. After a standardized warm-up of 1,200 m, the athletes performed a standardized training session that consisted of 2,000 m at a best velocity then 600 m of aerobic work. Heart rate was continuously monitored during (...) 5 × 400 m, whereas Tco, thermal comfort, and thermal sensation were measured before and after each 400 m. Before and after each 400 m, the swimmers were asked to flow 200 mL of cold water or neutral water packaged in standardized bottles on their face. The swimmers were asked don’t drink during exercise. The velocity was significantly different between cold water and neutral water. The Tco was increased by ±0.5°C at race pace, under both face cooling conditions with no significant difference. No significant changes were noted in mean HR. TC was higher with Cold Cooling than Neutral Cooling and TS was lower with Cold cooling compared with Neutral cooling. The changes in perceptual parameters caused by face cooling with cold water reflect the psychological impact on the physical parameters. The mean velocity was less important with face cooling whereas the heat rate and Tco were the same in the both conditions. The mechanism leading to these results seems to involve brain integration of signals from physiological and psychological sources. (shrink)

This essay examines the relationship between William James’s radical empiricism and Gilles Deleuze’s transcendental empiricism by considering how dominant technologies of locomotion and travel in their respective historical times influenced their thinking and the style of their prose. Highlighting the imagery of trains and ground movement in James and planes and flight in Deleuze, I suggest that each constructs an empiricism that resonates with and reacts to the emerging forms of mass movement in his own time. The essay serves as (...) an invitation to read James and Deleuze together with attention to the aesthetic qualities of their writing and as united in an ongoing project of honing philosophy to the pace of its time. (shrink)

Research on cognitive control has sparked increasing interest in recent years, as it is an important prerequisite for goal oriented human behavior. The paced auditory serial addition task has been used to test and train cognitive control functions. This adaptive, challenging task includes continuous performance feedback. Therefore, additional cognitive control capacities are required to process this information along with the already high task-load. The underlying neural mechanisms, however, are still unclear. To explore the neural signatures of the PASAT and (...) particularly the processing of distractive feedback information, feedback locked event-related potentials were derived from 24 healthy participants during an adaptive 2-back version of the PASAT. Larger neural activation after negative feedback was found for feedback related negativity, P300, and late positive potential. In early stages of feedback processing, a larger difference between positive and negative feedback responses was associated with poorer overall performance. This association was inverted in later stages. Together, our findings indicate stage-dependent associations between neural activation after negative information and cognitive functioning. Conceivably, increased early responses to negative feedback signify distraction, whereas higher activity at later stages reflects cognitive control processes to preserve ongoing performance. (shrink)

In the chemical production process, the temperature of the continuous reactor has nonlinear characteristics such as large inertia. An improved autodisturbance control method is proposed. By improving the tracking differentiator with adjustable parameters, the expanded state observer and the control structure obtained an improved automatic disturbance rejection control model and realized the optimal control of the nonlinear and large-delay systems. On the process control training system, the experiment of the continuous system process flow is compared with the anti-interference of (...) the Smith predictive compensation system, which uses an optimal set of data. The reactor temperature fluctuates, but the self-resistance is improved. The optimal overshoot of the disturbance is close to 0. Compared with the original antidisturbance controller, the antidisturbance time is not affected by the number of iterations, which reduces the high requirements on the accuracy of the parameters. Therefore, the improved automatic disturbance rejection control improves the operation and enhances the ability to resist external disturbance that changes the controlled object. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:138 In 2010 the city of Colorado Springs was strapped for cash. Government officials announced that they would either have to raise revenue through increased taxation or cut public services—­ in some cases rather severely—­ including, perhaps, police and fire protection, and even more basic bits of municipal infrastructure. The city shut down one-­ third of residential streetlights and closed public restrooms. Citi­ zens were outraged, but a majority (...) of voters had recently defeated a proposed tax increase. It’s tempting to suppose that the city was trying to teach its citizens a lesson: if you want public services, you have to be willing to pay for them. Colorado Springs is, and has been for some time now, a died-­in-­the-­wool small-­government, anti-­tax-­increase, fiscally conservative town. As Colorado Springs resident Bo Sharifi put it, “As soon as I hear government [say] ‘Oh, we need more money’... I guess I kind of automatically assume there’s probably some other things you could probably cut before firemen, policemen, city lights and that sort of thing.”1 On the surface, that seems reasonable. So... what comes to mind? How about food stamps? What about WIC? Of course these are federal services, not funded by Coloradans alone. There’s government, and then there’s government. Well, how about... well... what? Doesn’t the government spend money on all sorts of things we could very easily do without? Perhaps. Isn’t it part of our job to know or to decide which things these are? If we don’t trust government, even more obviously we don’t trust it with our money, though we pretty clearly have no idea how public funds are actually allocated or spent. When asked whether he remembered the proposed tax increase that the city had voted against, Sharifi replied, “maybe.” Bo and his wife were charged $125 to have Connected: How Trains, Genes, Pineapples, Piano Keys, and a Few Disasters Transformed Americans at the Dawn of the Twentieth Century By Steven Cassedy Stanford: Stanford University Press, 2014 JOHN MARIANA Book Reviews 139 their streetlight turned back on. Bo’s wife Sara viewed this as extortion. “By shoveling out a hundred dollars to turn on a streetlight that we kind of felt was supposed to be on anyway, that it was giving them what they wanted,” she said. They who? One resident wrote the city of Colorado Springs a check for $300 to turn the lights on for his entire neighborhood. City Councilwoman Jan Martin pointed out to him that the total cost to the individual Colorado Springs taxpayer to keep the streetlights on—­and to fund the maintenance of public parks and medians, as well as community centers and pre-­recession-­level police and fire services—­by approving the tax increase would have been: $200. He replied that he would never vote for a tax increase. In other words, as the reporter who covered the story (Robert Smith) observed, he would rather pay more to keep the streetlights on in his own neighborhood than to pay for all city services combined. Smith remarked that “Colorado Springs was stepping away from one of the things that we take for granted in most American cities: that we’re all in it together—­ at least when it comes to basic services.”2 As near as I can tell, this is the moral of Steven Cassedy’s exceptionally timely Connected: that we’re all in it together. For much of the book Cassedy merely traces the history of the emergence in the consciousness of ordinary Americans of the concept of the social network, but he is not so much talking about the notion of a network society as such, as I understand him. Or, at any rate, the network society as such is not really his main concern. He is talking about the idea of social, political, national, and ultimately global and universal human interconnectedness that was a distinct product of the complex networked structures (both concrete and abstract) that came to constitute modern American life in the twentieth century (and of course life pretty much everywhere ), and about our understanding of ourselves as so networked.3 On this... (shrink)

Cognitive theories of emotion propose that the interpretation of emotion-eliciting situations crucially shapes affective responses. Implicit or automatic biases in these interpretations may hinder emotion regulation and thereby increase risk for the onset and maintenance of psychological disorders. In this study, participants were randomly assigned to a positive or negative interpretation bias training using ambiguous social scenarios. After the completion of the training, a stress task was administered and changes in positive and negative affect and self-esteem were assessed. (...) The results demonstrate that the interpretation bias training was successful in that participants exhibited a tendency to interpret novel scenarios in accordance with their training condition. Importantly, the positive training condition also had a protective effect on self-esteem. Participants in this condition did not exhibit a decrease in self-esteem after the stress task, whereas participants in the negative condition did. These results demonstrate that implicit cognitive biases can be trained and that this training affects self-esteem. Implications of these findings for research on psychopathology and emotion regulation are discussed. (shrink)

Hubert Dreyfus argues that explicit thought disrupts smooth coping at both the level of everyday tasks and of highly-refined skills. However, Barbara Montero criticises Dreyfus for extending what she calls the ‘principle of automaticity’ from our everyday actions to those of trained experts. In this paper, I defend Dreyfus’ account while refining his phenomenology. I examine the phenomenology of what I call ‘esoteric’ expertise to argue that the explicit thought Montero invokes belongs rather to ‘gaps’ between or above moments of (...) reflexive coping. However, I agree that the ‘principle of automaticity’ does not adequately capture the experience of performing such skills. Drawing on examples of expert performance in sport and improvised music and dance, I argue that esoteric action, at its best, is marked by a distinct state of non-conceptual awareness- an experience of spontaneity, flow and ‘owned-ness’- that distinguishes it from the automaticity of everyday actions. (shrink)

Convolutional neural networks, which automatically learn features from raw data to approximate functions, are being increasingly applied to the end-to-end analysis of electroencephalographic signals, especially for decoding brain states in brain-computer interfaces. Nevertheless, CNNs introduce a large number of trainable parameters, may require long training times, and lack in interpretability of learned features. The aim of this study is to propose a CNN design for P300 decoding with emphasis on its lightweight design while guaranteeing high performance, on the (...) effects of different training strategies, and on the use of post-hoc techniques to explain network decisions. The proposed design, named MS-EEGNet, learned temporal features in two different timescales in an efficient and optimized way, and was validated on three P300 datasets. The CNN was trained using different strategies and was compared with several state-of-the-art algorithms. Furthermore, variants of the baseline MS-EEGNet were analyzed to evaluate the impact of different hyper-parameters on performance. Lastly, saliency maps were used to derive representations of the relevant spatio-temporal features that drove CNN decisions. MS-EEGNet was the lightest CNN compared with the tested SOA CNNs, despite its multiple timescales, and significantly outperformed the SOA algorithms. Post-hoc hyper-parameter analysis confirmed the benefits of the innovative aspects of MS-EEGNet. Furthermore, MS-EEGNet did benefit from transfer learning, especially using a low number of training examples, suggesting that the proposed approach could be used in BCIs to accurately decode the P300 event while reducing calibration times. Representations derived from the saliency maps matched the P300 spatio-temporal distribution, further validating the proposed decoding approach. This study, by specifically addressing the aspects of lightweight design, transfer learning, and interpretability, can contribute to advance the development of deep learning algorithms for P300-based BCIs. (shrink)

The aim of this study was to explore the emergence of skilled behaviours, in the form of actions, cognitions and emotions, between professional state level cricket batters and their lesser skilled counterparts. Twenty-two male cricket batsmen (n = 6 state level; n = 8 amateur grade club level, n = 8 junior state representative level) participated in a game scenario training session against right arm pace bowlers (n = 6 amateur senior club). The batsmen were tasked with scoring as (...) many runs as possible during a simulated limited-overs game. The actions, cognitions and emotions of each batsmen were recorded in situ with findings showing differences between state level players and those lesser skilled. State level batsmen played more scoring shots and scored more runs, underpinned by superior bat-ball contact and technical efficiency. Furthermore, the state player’s cognitive evaluations of their own performance differed from junior batters, with more reported strategies based on an external outcome focus, such as where to score runs, rather than a focus on internal processes, such as making technical changes. State level batsmen also reported lower levels of nervousness compared with junior level batsmen. These results highlight the importance of viewing the emergence of skilled behaviour as multi-faceted, rather than simply the acquisition of superior execution and technical proficiency. (shrink)

Background: Parkinson’s disease is a neurodegenerative disease in which the progressive loss of dopaminergic neurons leads to initially sporadic and eventually widespread damage of the nervous system resulting in significant musculoskeletal and cognitive deterioration. Loss of motor function alongside increasing cognitive impairment is part of the natural disease progression. Gait is often considered an automatic activity; however, walking is the result of a delicate balance of multiple systems which maintain the body’s center of mass over an ever-changing base of support. (...) It is a complex motor behavior that requires components of attention and memory to prevent falls and injury. In addition, evidence points to the critical role of salient visual information to gait adaptability. There is a growing understanding that treatment for PD needs to address movement as it occurs naturally and walking needs to be practiced in more complex environments than traditional therapy has provided.MethodsIn this single-blinded randomized-controlled pilot study, an immersive treadmill training was piloted to determine feasibility and preliminary efficacy on gait and cognition in people with PD. Eighteen participants with Hoehn and Yahr stages I-III PD were randomized to either an intervention or a waitlist control group. Following baseline data collection, the intervention group trained for 30 min, three times/week for 4 weeks on a split belt treadmill combined with a first-person immersive video game targeting visuospatial skills and working memory. Assessment was repeated after 4 weeks of training for the experimental group and 1-month after baseline for the control group. Primary motor outcomes were captured with the APDM Opal sensors during 6 MWT, TUG, and TUG Cognitive. Secondary outcomes of cognition were measured with the Montreal Cognitive Assessment, Verbal Fluency and the Symbol Digit Modality Test. Within subject differences were calculated using the Wilcoxon Signed Ranked Test and between subject comparisons were analyzed using the Mann Whitney U-test.ResultsThis novel treadmill training program was well-tolerated with all participants in the intervention group completing 4 weeks of training three times a week without any adverse effects. After immersive cognitive motor training, the experimental group made clinically relevant improvements in gait speed and walking distance during the 6 MWT while members of the control group showed no change or decreased gait speed and walking distance over the 1-month trial. In addition, the experimental group demonstrated significant improvement for the TUG Cognitive and those changes were greater than the control group. The experimental group also improved scores on MoCA and SDMT cognitive outcome measures while the control group did not.ConclusionThe use of immersive gaming technology to engage specific areas of cognition related to gait is feasible in PD. The treadmill training program paired with a customized interactive video game improved walking velocity in addition to non-significant but consistent improvements in other gait measures and cognitive performance in participants with early to mid-stage PD. (shrink)

Background The COVID-19 pandemic posed many unprecedented challenges to health care systems and public health efforts worldwide. Policy making and science were deeply intertwined, in particular with regard to the justification of health policy measures. In this context, ethical considerations were often at the core of decision-making trade-offs. However, not much is known about the actual ethical challenges encountered by policy makers and scientists involved in policy advice. With this study, we therefore aim to explore the ethical challenges during COVID-19-related (...) political decision-making in Switzerland as perceived by policy makers and scientists involved in policy making. We also explore the role ethics advice had during the pandemic response and what can be learned for future public health crises. Methods We conducted thirteen qualitative expert interviews with policy makers and scientists involved in decision-making on COVID-19 policy responses in Switzerland on the regional and national level. We used inductive content analysis to analyse the interviews. Results Among the multitude of ethical challenges highlighted, interviewees perceived making trade-offs between the common good vs. the individual good and between economic welfare vs. health of the population, as well as proportionality of the policy measures, and the capacity of the public to accept uncertainty as central. Interviewees had diverging opinions on whether ethical considerations were sufficiently raised and discussed on the Swiss policy level during the COVID-19 pandemic. Among the reasons why ethics was not sufficiently discussed, they mentioned a lack of time in the fast-paced dynamic of the pandemic, ethics as a complex subject area, the interconnectedness between ethics and law, too much focus on few topics (mostly on vaccination-related ethical questions), and power relationships, such as dominance of medical professionals over ethicists. They evaluated ethics support to have been adequately present in the decision-making process, but wished for ethics training, involvement of the public in the discourse and for accompanying communication to build trust among the population for the future. Conclusions The study provides empirical insights into the ethical considerations of COVID-19 policy making in practice in Switzerland. It can help to develop ethics assistance for future crises and inform ethical health policy and decision-making not only in Switzerland, but also in other countries. (shrink)

This article highlights the tension of sustaining tradition versus the need for change within theological education. Within denominations, there is the challenge of maintaining tradition while at the same time wanting to embrace change. If this is not managed properly, the tradition can become out of date when there is a focus on controlling through enforcing tradition and through indoctrination in education. This article presents the Church of the Nazarene, as a case study, where their theological education is tested against (...) an organic and indigenous framework highlighting the need for a contextual driven curriculum. There are various aspects within the tradition that are slow to adapt, where aspects of Western church polity and practices linger on thereby negatively impact the curriculum. However, if a contextual learning programme does not materialise students’ knowledge from the classroom will not match what they need to know once they reach the ministerial setting. This article examines pastoral training in the Church of Nazarene’s southern African region to emphasise the dichotomy between preserving tradition and the need to innovate in order to ensure its long-term viability.Contribution: This article reflects on the important balance of sustainability in a global church tradition, and it serves as a case study of issues commonly found in many denominations. It is about holding on to the core teachings that has stood the test of time but having the ability to be adaptative to the contextual needs of a region. Reasons are provided for the slow pace in change and ways to overcome this. This article contributes to the literature on the Church of Nazarene. (shrink)

Mindfulness is intentional focus of one’s attention on emotions, thoughts, or sensations occurring in the present moment with a nonjudgmental attitude. Recently there has been increased interest in the effects of mindfulness practice on psychological processes such as concentration, focus, and attention. In the present study, a prepulse inhibition/facilitation paradigm was employed to investigate the effect of brief mindfulness practice on automatic attention regulation processes. PPI occurs when a relatively weak prepulse is presented 30–500 ms before a startle-inducing stimulus, and (...) reduces the magnitude of the startle response. Prepulse facilitation is the increase in startle magnitude when the prepulse is presented 500 ms or more before the startle-eliciting stimulus. In the present study, the effect of engaging in a 23-min mindfulness exercise on PPI and PPF was investigated. Participants listened to either a mindfulness instruction or relaxing music. In a PPI/PPF pretest and posttest, a startle-eliciting noise was presented at lead intervals of 60, 120, and 2,000 ms. Results showed that engaging in brief mindfulness practice increased prepulse facilitation at the 2,000 ms lead interval in the posttest compared to the pretest. The amount of PPI did not differ between tests. (shrink)

In this Introduction, I identify seven discrete aspects of attention brought to the fore by by considering the phenomenon of effortless attention: effort, decision-making, action syntax, agency, automaticity, expertise, and mental training. For each, I provide an overview of recent research, identify challenges to or gaps in current attention theory with respect to it, consider how attention theory can be advanced by including current research, and explain how relevant chapters of this volume offer such advances.

In this Introduction, I identify seven discrete aspects of attention brought to the fore by by considering the phenomenon of effortless attention: effort, decision-making, action syntax, agency, automaticity, expertise, and mental training. For each, I provide an overview of recent research, identify challenges to or gaps in current attention theory with respect to it, consider how attention theory can be advanced by including current research, and explain how relevant chapters of this volume offer such advances.

IntroductionExercise at high intensity may cause lower affective responses toward exercise compared with moderate intensity exercise. We aimed to elucidate affective valence and enjoyment in high- and moderate-high interval exercise.MethodsTwenty recreationally active participants (9 females, 11 males, age range: 20–51 years) underwent three different treadmill running exercise sessions per week over a 3-week period, in randomized order; (1) CE70: 45 min continuous exercise at 70% of heart rate maximum (HRmax), (2) INT80: 4 × 4 min intervals at 80% of HRmax, (...) (3) INT90: 4 × 4 min intervals at 90% of HRmax. Pre-tests included graded submaximal steady state intensities and a test to exhaustion for determining peak oxygen uptake and HRmax. Affective valence (pleasure/displeasure) was measured before, during and after the sessions using the Feeling Scale (FS). Enjoyment was assessed before and after the sessions applying the Physical Activity Enjoyment Scale (PACES) and during the sessions using the Exercise Enjoyment Scale (EES).ResultsThe participants felt lower pleasure (between-sessions effect:p= 0.02,pη2: 0.13) during INT90 sessions (FS: 1.08, 95% CI: 0.35–1.92) compared with INT80 (FS: 2.35, 95% CI: 1.62–3.08,p= 0.052) and CE70 sessions (FS: 2.45, 95% CI: 1.72–3.18,p= 0.03), with no differences between INT80 and CE70 sessions (p= 1.00). There were higher enjoyment after INT80 sessions (PACES: 101.5, 95% CI: 95.7–107.3) versus CE70 sessions (PACES: 91.3 95% CI: 85.5–97.1,p= 0.046), and no differences between INT90 (PACES: 98.2, 95% CI: 92.4–103.4) and CE70 (p= 0.29) or INT80 (p= 1.00). For enjoyment during exercise, CE70 were perceived more enjoyable, and INT80 and INT90 less enjoyable in week 2 (EES: week x session:p= 0.01,pη2: 0.11; CE70: 4.3, 95% CI: 3.6–4.9, INT80: 4.6, 95% CI: 3.9–5.2, INT90: 4.0, 95% CI: 3.4–4.7) and 3 (EES: CE70: 4.2, 95% CI: 3.7–4.8, INT80: 4.8, 95% CI: 4.2–5.3, INT90: 4.3, 95% CI: 3.8–4.9) than in week 1 (EES: CE70: 3.5, 95% CI: 3.0–4.0, INT80: 5.0, 95% CI: 4.5–5.5, INT90: 4.5, 95% CI: 4.0–5.0).ConclusionThe negative affective consequences associated with high intensity interval exercise can be alleviated by keeping the intensity at or around 80% of HRmaxwhile preserving the beneficial enjoyment responses associated with interval exercise. (shrink)

Much research has explored the physiological, energetic, environmental, and psychological factors that influence pacing in endurance events. Although this research has generally neglected the role of psychological variation across individuals, recent studies have hinted at its importance. Here we conducted an online survey of over 1,300 marathon runners, testing whether any of five psychological constructs—competitiveness, goal achievement, risk taking in pace (RTP), domain-specific risk taking, and willingness to suffer in the marathon—predicted slowing in runners’ most recent marathons. Analyses revealed that (...) RTP—the extent to which runners agreed that they began the marathon at a pace that was so fast that it would jeopardize their capacity to maintain this pace throughout the event—was a robust predictor of marathon slowing. RTP proved a substantial predictor even in regression models controlling for the other psychological constructs, training, experience, and other known pacing correlates. This result suggests that marathoners consider trade-offs when making pacing decisions, and that individuals vary in their pacing decision making. (shrink)

An English double-embedded relative clause from which the middle verb is omitted can often be processed more easily than its grammatical counterpart, a phenomenon known as the grammaticality illusion. This effect has been found to be reversed in German, suggesting that the illusion is language specific rather than a consequence of universal working memory constraints. We present results from three self-paced reading experiments which show that Dutch native speakers also do not show the grammaticality illusion in Dutch, whereas both (...) German and Dutch native speakers do show the illusion when reading English sentences. These findings provide evidence against working memory constraints as an explanation for the observed effect in English. We propose an alternative account based on the statistical patterns of the languages involved. In support of this alternative, a single recurrent neural network model that is trained on both Dutch and English sentences is shown to predict the cross-linguistic difference in the grammaticality effect. (shrink)

From 19th January 2013 there have been changes in the operation of driver training centres due to the legislation regarding vehicle drivers coming into force. Changes related to the conduct of driving schools concern four major areas. The first one is a new form of enrolment on driving courses by candidates for drivers, which is done by using the so-called Profile of Candidate for Driver (PCD) generated by the county authorities. The second aspect is the new formula of the (...) theoretical state examination. The third issue is the introduction of cash registers for the operators conducting drivers’ education. The fourth feature is the introduction of new categories of the driving license, in particular a category including two-wheeled vehicles. The existing regulations, as well as the huge competition in the market, have contributed to the fact that the activity of training of candidates for drivers has been dominated by the principle according to which the service must be performed in a cheap and fast way. It automatically translates into the low quality of training and the disregard of procedural steps associated with it. In practice, the lack of adequate control on the part of the state is the reason for the fact that driving has become an arbitrary function based on ruthless marketing and low-cost services. In this situation, ethical dilemmas arise that, in the author’s opinion, will not necessarily be resolved by the new legal standards for drivers. (shrink)

Action perception and recognition are core abilities fundamental for human social interaction. A parieto-frontal network (the mirror neuron system) matches visually presented biological motion information onto observers' motor representations. This process of matching the actions of others onto our own sensorimotor repertoire is thought to be important for action recognition, providing a non-mediated “motor perception” based on a bidirectional flow of information along the mirror parieto-frontal circuits. State-of-the-art machine learning strategies for hand action identification have shown better performances when sensorimotor (...) data, as opposed to visual information only, are available during learning. As speech is a particular type of action (with acoustic targets), it is expected to activate a mirror neuron mechanism. Indeed, in speech perception, motor centers have been shown to be causally involved in the discrimination of speech sounds. In this paper, we review recent neurophysiological and machine learning-based studies showing (a) the specific contribution of the motor system to speech perception and (b) that automatic phone recognition is significantly improved when motor data are used during training of classifiers (as opposed to learning from purely auditory data). (shrink)

Automatic synonym extraction plays an important role in many natural language processing systems, such as those involving information retrieval and question answering. Recently, research has focused on extracting semantic relations from word embeddings since they capture relatedness and similarity between words. However, using word embeddings alone poses problems for synonym extraction because it cannot determine whether the relation between words is synonymy or some other semantic relation. In this paper, we present a novel solution for this problem by proposing the (...) SynoExtractor pipeline, which can be used to filter similar word embeddings to retain synonyms based on specified linguistic rules. Our experiments were conducted using KSUCCA and Gigaword embeddings and trained with CBOW and SG models. We evaluated automatically extracted synonyms by comparing them with Alma’any Arabic synonym thesauri. We also arranged for a manual evaluation by two Arabic linguists. The results of experiments we conducted show that using the SynoExtractor pipeline enhances the precision of synonym extraction compared to using the cosine similarity measure alone. SynoExtractor obtained a 0.605 mean average precision for the King Saud University Corpus of Classical Arabic with 21% improvement over the baseline and a 0.748 MAP for the Gigaword corpus with 25% improvement. SynoExtractor outperformed the Sketch Engine thesaurus for synonym extraction by 32% in terms of MAP. Our work shows promising results for synonym extraction suggesting that our method can also be used with other languages. (shrink)

The race among global firms to launch its respective products and services into the market sooner than the competitors puts pressure to equip its employees with job-related skills at the pace of business. Today’s global and dynamic business requires employees to develop highly complex cognitive skills such as decision-making, problem-solving, troubleshooting to perform their jobs proficiently. Traditional training models used by some organizations lead to a very slow speed at which employees gain an acceptable level of proficiency in the (...) targeted job skills. Also, these models have long and regimented instructional development cycle. Thus, traditional models are inherently counter-productive to the business and do not enable employees and organizations for today’s business needs. Therefore, business organizations need to explore new training models and strategies that could reduce the time an employee takes to reach target proficiency in complex skills without compromising the effectiveness or outcome. A comprehensive review of the literature shows a very limited amount of academic or practitioner research on this topic. This doctorate research study aims to find various training strategies that have proven successful in organizations for accelerating proficiency of employees in complex job skills. The researcher collected data primarily through 74 in-depth interviews with 86 training experts with known work experience of reducing time-to-proficiency in various settings. A total of 105 project cases have been collected across 42 industries to date. A grounded theory approach with constant comparison method is used to guide the theoretical saturation, analyze the data and to develop a theoretical model of training strategies. This unique study revealed a range of training strategies from non-training solutions to classroom instructions to workplace training to accelerate proficiency of employees in acquiring complex skills. This paper will specifically report the preliminary findings and conceptual model of major classroom-based instructional strategies only that has been found to hold the potential to shorten time-to-proficiency of employees at the workplace. This paper will also discuss the implications of the findings for the practitioners. Results in this study confirmed that classroom-based instructional strategies need to be designed and delivered the way the work is being performed in reality by the learners. Research findings suggest a pattern of five classroom-based instructional strategies that are more successful in reducing time-to-proficiency - 1) Contextualized learning 2) Performance analysis of star performer 3) Active processing and emotional involvement 4) Access to self-guided learning resources 5) Social interconnectivity and informal learning. (shrink)

Automatic control of physiological variables is one of the most active areas in biomedical engineering. This paper is centered in the prediction of the analgesic variables evolution in patients undergoing surgery. The proposal is based on the use of hybrid intelligent modelling methods. The study considers the Analgesia Nociception Index to assess the pain in the patient and remifentanil as intravenous analgesic. The model proposed is able to make a one-step-ahead prediction of the remifentanil dose corresponding to the current state (...) of the patient. The input information is the previous remifentanil dose, the ANI variable and the electromyogram signal. Modelling techniques used are Artificial Neural Networks and Support Vector machines for Regression combined with clustering methods. Both training and validation were done with a real dataset from different patients. Results obtained show the potential of this methodology to calculate the drug dose corresponding to a given analgesic state of the patient. (shrink)