Introduction. Editorial on ‘Signal processing in vital rhythms and signs’

Laguna, Pablo; Sörnmo, Leif

doi:10.1098/rsta.2008.0239

Cited by 4 publications

(2 citation statements)

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“…In the last twenty years the field of the biomedical signal processing has known an upsurge, as witnessed by the progressively increasing number of peer-review international journals and sessions in biomedical meetings. Topics that twenty years ago were confined to restricted communities of theoretic researchers and primarily addressed in specific fields of the science such as causal inference, information coding, graph theory, symbolic dynamics and complexity analysis, are now becoming the hot matter of special issues of international biomedical journals and invited sessions in biomedical conferences around the world (Merletti and Farina 2008, Laguna and Sornmo 2009, Olbrich et al 2011, Fang et al 2011, Wessel et al 2011, Faes et al 2012, Porta and Faes 2013, Micera and Akay 2013, Clifford et al 2014, Gruzelier et al 2014. The rapid dissemination of results, tools and datasets, enabled by web-based facilities, journals with flexible copyright policies, open access repositories and free-downloadable computer programs, has been enlarging the possibility of applications of advanced signal processing techniques to the biomedical field at a faster than ever rate.…”

Section: Bridging the Gap Between The Development Of Advanced Biomedi...mentioning

confidence: 99%

Bridging the gap between the development of advanced biomedical signal processing tools and clinical practice

2015

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Section: Bridging the Gap Between The Development Of Advanced Biomedi...mentioning

confidence: 99%

Bridging the gap between the development of advanced biomedical signal processing tools and clinical practice

2015

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“…It is also really useful for uncovering components with low amplitude and/or subtle variations in frequency that are very difficult to observe visually. In addition, it enables to remove undesired components in order to enhance the signal-to-noise ratio and to facilitate the analysis (Laguna and Sörnmo 2009).…”

Section: Context: Biomedical Engineeringmentioning

confidence: 99%

Decoding P300 evoked potentials for Brain Computer Interfaces (BCI) aimed at assisting potential end-users at home

Palacios¹

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A Brain Computer Interface (BCI) is a communication system that provides an alternative channel to natural communication and control processes since it bypasses the body's normal efferent pathways, which are the neuromuscular output channels. Hence, a BCI system monitors brain activity and translates specific signal features, which reflect the user's intent, into commands that operate a device. BCIs are especially interesting for severely impaired individuals that cannot perform physical movements. Conventional augmentative and alternative communication technologies require some form of muscle control and thus may not be useful for those with the most severe motor disabilities, such as late-stage amyotrophic lateral sclerosis (ALS), brainstem stroke or severe cerebral palsy. This Thesis proposes the use of P300 evoked potentials as signal control in BCI systems for end-users, i.e. severely impaired people. Selective attention to a specific and infrequent flashing symbol evokes a brain pattern called P300, which appears around the central and parietal brain cortex, about 300 ms after the stimulus presentation. A novel assistive BCI tool for environment control at home is researched. The proposed application is based on P300 evoked responses to infrequent stimuli, known as the 'oddball' paradigm. P300-based BCIs could be the most proper type of BCIs for severely disabled populations since it does not require training period. Furthermore, its typical paradigm allows to select in a fast manner the desired symbol among a large number of choices only by focusing on it. The methodology proposed in this work is focused on the real end-users. Thus, the design, the experiments and the assessment are centred on the potential end-users' needs. A population of 30 potential BCI end-users, people with severe impairments due to different pathologies and degree of both motor and cognitive disabilities, took part in the study. Participants were recruited through the Spanish National Reference Centre on Disability and Dependence (León, Spain). The main needs identified for the population under study were related to three main categories: comfort, communication and security. Hence, the proposed assistive BCI tool was designed to cover them. Specifically, it enables to manage 8 devices, usually present at home, by means of 115

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An Introduction to the Use of Evolutionary Computation Techniques for Dealing with ECG Signals

Leguizamón

Coello

2011

ECG Signal Processing, Classification and Interpretation

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Introduction. Editorial on ‘Signal processing in vital rhythms and signs’

Cited by 4 publications

References 12 publications

Bridging the gap between the development of advanced biomedical signal processing tools and clinical practice

Bridging the gap between the development of advanced biomedical signal processing tools and clinical practice

Decoding P300 evoked potentials for Brain Computer Interfaces (BCI) aimed at assisting potential end-users at home

An Introduction to the Use of Evolutionary Computation Techniques for Dealing with ECG Signals

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