Technological Innovation for Life Improvement
11th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2020, Costa de Caparica, Portugal, July 1–3, 2020, Proceedings
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Article
Open AccessAddressing data limitations in seizure prediction through transfer learning
According to the literature, seizure prediction models should be developed following a patient-specific approach. However, seizures are usually very rare events, meaning the number of events that may be used t...
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Open AccessConcept-drifts adaptation for machine learning EEG epilepsy seizure prediction
Seizure prediction remains a challenge, with approximately 30% of patients unresponsive to conventional treatments. Addressing this issue is crucial for improving patients’ quality of life, as timely intervent...
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Open AccessEEG epilepsy seizure prediction: the post-processing stage as a chronology
Almost one-third of epileptic patients fail to achieve seizure control through anti-epileptic drug administration. In the scarcity of completely controlling a patient’s epilepsy, seizure prediction plays a sig...
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Open AccessRemoving artefacts and periodically retraining improve performance of neural network-based seizure prediction models
The development of seizure prediction models is often based on long-term scalp electroencephalograms (EEGs) since they capture brain electrical activity, are non-invasive, and come at a relatively low-cost. Ho...
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Open AccessUnsupervised EEG preictal interval identification in patients with drug-resistant epilepsy
Typical seizure prediction models aim at discriminating interictal brain activity from pre-seizure electrographic patterns. Given the lack of a preictal clinical definition, a fixed interval is widely used to ...
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Article
Open AccessEPIC: Annotated epileptic EEG independent components for artifact reduction
Scalp electroencephalogram is a non-invasive multi-channel biosignal that records the brain’s electrical activity. It is highly susceptible to noise that might overshadow important data. Independent component ...
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Open AccessInterpretable EEG seizure prediction using a multiobjective evolutionary algorithm
Seizure prediction might be the solution to tackle the apparent unpredictability of seizures in patients with drug-resistant epilepsy, which comprise about a third of all patients with epilepsy. Designing seiz...
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Article
Open AccessHeart rate variability analysis for the identification of the preictal interval in patients with drug-resistant epilepsy
Electrocardiogram (ECG) recordings, lasting hours before epileptic seizures, have been studied in the search for evidence of the existence of a preictal interval that follows a normal ECG trace and precedes th...
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Article
Open AccessA personalized and evolutionary algorithm for interpretable EEG epilepsy seizure prediction
Seizure prediction may improve the quality of life of patients suffering from drug-resistant epilepsy, which accounts for about 30% of the total epileptic patients. The pre-ictal period determination, characte...
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Comparing Different Methods for Named Entity Recognition in Portuguese Neurology Text
Electronic Medical Records (EMRs) are written in an unstructured way, often using natural language. Information Extraction (IE) may be used for acquiring knowledge from such texts, including the automatic reco...
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Book and Conference Proceedings
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Chapter
Empowering SMEs with Cyber-Physical Production Systems: From Modelling a Polishing Process of Cutlery Production to CPPS Experimentation
As technology evolves, the contemporary technological paradigm of manufacturing Small and Medium Enterprises (SME’s) has been changing and gaining traction to accommodate its ever-growing needs for adaptation ...
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Chapter and Conference Paper
Named Entity Recognition in Portuguese Neurology Text Using CRF
Automatic recognition of named entities from clinical text lighte...
