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PLUX Wireless Biosignals, SA, Portugal

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25 Papers

Automated Detection of Mind Wandering: A Mobile Application

Topics: Medical Signal Acquisition, Analysis and Processing; Wearable Sensors and Systems; Real-Time Systems

Authors: Marcus Cheetham ¹ , Cátia Cepeda ² and Hugo Gamboa ³

Affiliations: ¹ University of Zurich and Nungin University, Switzerland , ² FCT-UNL, Portugal , ³ FCT-UNL and PLUX Wireless Biosignals S.A, Portugal

Digital Object Identifier: 10.5220/0005702401980205

Proceedings of BIOSIGNALS 2016/BIOSTEC, ISBN: 978-989-758-170-0

Quick Abstract

There is growing interest in mindfulness-based training of attention. A particular challenge for novices is learning to sustain focused attention while ensuring that the mind does not wander. This paper presents the development of a tool for the automated detection of episodes of mind wandering (MW), on the basis of biosignals, while normal healthy participants engaged in brief mindfulness-based training (BMT) of attention. BMT required five 20-minute training sessions on consecutive days and entailed practice of breath-focused attention, a typical exercise in mindfulness-based techniques of stress-reduction. Heart rate, respiratory rate, electrodermal and electromyographic activity were measured, and participants pressed a button to indicate the subjective detection of MW during training. The data showed that BMT did not influence our measures of stress but BMT was effective in reducing the frequency of subjectively detected MW events. The algorithm for offline detection of MW achieved an accuracy of 85%. Based on this algorithm, a mobile application was developed for automated MW detection in real-time. The application requires the use of easily placeable sensors, provides a new approach to the real-time MW detection, and could be developed further for use in MW-related investigations and interventions (such as mindfulness-based training of focused attention).

Related Ontology Subjects/Areas/Topics (11)

Applications and Services	Devices	Physiological Computing Systems
Biomedical Engineering	Health Information Systems	Real-Time Systems
Biomedical Signal Processing	Human-Computer Interaction	Wearable Sensors and Systems
Computer Vision, Visualization and Computer Graphics	Medical Image Detection, Acquisition, Analysis and Processing

Vertebral Metrics - Application of a Non-invasive System to Analyse Vertebrae Position using Two Seating Platforms

Topics: Emerging Technologies; Biomedical Instrumentation; Biomedical Equipment; Biomedical Metrology

Authors: Ana Teresa Gabriel ¹ , Cláudia Quaresma ¹ , Mário Forjaz Secca ² and Pedro Vieira ¹

Affiliations: ¹ Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa, Portugal , ² Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa and Ressonância Magnética - Caselas, Portugal

Digital Object Identifier: 10.5220/0005790202350240

Proceedings of BIODEVICES 2016/BIOSTEC, ISBN: 978-989-758-170-0

Quick Abstract

The study of the biomechanical changes in the spinal column is particularly important in modern society since they are considered the main responsible for back pain. Vertebral Metrics is an instrument that aims the global evaluation of the spinal column. Noninvasively and semi-automatically, this image processing based system allows the identification of X, Y and Z position of each spinal process on standing position. The analysis of vertebraes position using two different seating platforms through the application of Vertebral Metrics is the aim of this work. Along the paper the main stages concerning to the study will be described. Nine volunteers were recruited and an ergonomic chair and a bench were used to perform the study. Results show that differences in vertebrae position are not relevant when sitting in the ergonomic sit or in the lab. Also, spinal curvatures as well as lateral deviations of the spine were properly represented from data collected with Vertebral Metrics. The study proved that Vertebral Metrics has a huge potential to perform the analysis of the spinal curvatures.

Related Ontology Subjects/Areas/Topics (9)

Biomedical Engineering	Biomedical Instruments and Devices	Telecommunications
Biomedical Equipment	Biomedical Metrology	Wireless and Mobile Technologies
Biomedical Instrumentation	Emerging Technologies	Wireless Information Networks and Systems

From ESPRIT to H2020: The Evolution of ICT in the European Research Framework Programmes

Author: Filipa Duarte

Affiliation: FCT-UNL, Portugal

Digital Object Identifier: 10.5220/0006164000030022

Proceedings of EPS Berlin 2015, ISBN: 978-989-758-156-4

Quick Abstract

The European Research Framework Programmes have been around since 1984. The Framework Programmes have suffered many changes through the years and saw several increases in budget and impact. The area of information and communications technologies was triggered with ESPRIT in 1982 and has been financed up until Horizon 2020. This paper presents that evolution focusing in the Information and Communication Technologies area.

Multi-biosignals Analysis - The Effect of Peripheral Nerve Stimulation on Skin Conductance and Heart Rate Variability

Topics: Medical Signal Acquisition, Analysis and Processing; Time and Frequency Response

Authors: Tiago Araújo ¹ , Pedro Dias ¹ , Neuza Nunes ² and Hugo Gamboa ¹

Affiliations: ¹ New University of Lisbon, Portugal , ² PLUX - Wireless Biosignals S.A., Portugal

Digital Object Identifier: 10.5220/0005217902350239

Proceedings of BIOSIGNALS 2015/BIOSTEC, ISBN: 978-989-758-069-7

Quick Abstract

Objectives: This study aims to evaluate the influence of standard electrical stimulation on human electrophysiology. Methods: A total of 10 healthy subjects were submitted to the same protocol. The electrical stimuli were applied on the median nerve of the left wrist. Blood Volume Pulse (BVP) and Electrodermal Activity (EDA) signals were acquired from the index finger through an oximeter and from both the abductor pollicis muscle and the 3rd palmar interosseous muscle of the right hand, respectively. Nerve stimulation was performed using increasing intensities current: range from 5 to 30 mA, with 1mA step and applying 20 stimuli per step. Heart Rate (HR) and Heart Rate Variability (HRV) were computed, from the analysis of the latency between BVP pulses, in basal state and during stimulation. EDA parameters response latency, response rise time and readaptation slope were computed for each burst. Discussion: Electrical stimulation reveals to influence several parameters of the Autonomic Nervous System (ANS). It was easily detected an EDA rise response for each of the applied bursts and also an increase of the HRV during stimulation.

Related Ontology Subjects/Areas/Topics (9)

Applications and Services	Computer Vision, Visualization and Computer Graphics	Signal Processing, Sensors, Systems Modeling and Control
Biomedical Engineering	Informatics in Control, Automation and Robotics	Time and Frequency Response
Biomedical Signal Processing	Medical Image Detection, Acquisition, Analysis and Processing	Time-Frequency Analysis

New Visualization Model for Large Scale Biosignals Analysis

Topics: Medical Signal Acquisition, Analysis and Processing; Cybernetics and User Interface Technologies; Monitoring and Telemetry

Authors: Catarina Cavaco ¹ , Ricardo Gomes ¹ , Hugo Gamboa ² and Ricardo Matias ³

Affiliations: ¹ Faculdade de Ciências e Tecnologias - Universidade Nova de Lisboa, Portugal , ² Faculdade de Ciências e Tecnologias - Universidade Nova de Lisboa and PLUX Wireless Biosignals, Portugal , ³ Escola Superior de Saúde - Instituto Politécnico de Setúbal and Faculdade de Motricidade Humana - Universidade de Lisboa, Portugal

Digital Object Identifier: 10.5220/0005207201900197

Proceedings of BIOSIGNALS 2015/BIOSTEC, ISBN: 978-989-758-069-7

Quick Abstract

The development of new resources in the medical field, such as wearable sensors, allowed the improvement of biosignals monitoring. Acquired data is then an important source of information to clinicians and researchers. Thus, extracting useful information from data is a task of the greatest importance that involves a variety of concepts and methods, from which stands out data visualization. However, these methods present several limitations mainly when dealing with big data. In this paper we present an innovative web-based application for biosignals visualization and exploration in a fast and user friendly way overcoming the detected limitations. Three case studies are presented and a usability study supports the reliability of the implemented work.

Related Ontology Subjects/Areas/Topics (11)

Applications and Services	Cybernetics and User Interface Technologies	Medical Image Detection, Acquisition, Analysis and Processing
Biomedical Engineering	Devices	Monitoring and Telemetry
Biomedical Signal Processing	Human-Computer Interaction	Physiological Computing Systems
Computer Vision, Visualization and Computer Graphics	Information and Systems Security

Quadriceps Muscle Fatigue and Comfort Generated by Neuromuscular Electrical Stimulation with Current Modulated Waveforms

Topics: Medical Signal Acquisition, Analysis and Processing; Motion Control

Authors: Tiago Araújo ¹ , Ana Anjos ² , Neuza Nunes ³ , Pedro Rebelo ² and Hugo Gamboa ¹

Affiliations: ¹ New University of Lisbon, Portugal , ² Polytecnic Institute of Lisbon, Portugal , ³ PLUX - Wireless Biosignals S.A., Portugal

Digital Object Identifier: 10.5220/0005267400920098

Proceedings of BIOSIGNALS 2015/BIOSTEC, ISBN: 978-989-758-069-7

Quick Abstract

Introduction: Neuromuscular electrical stimulation (NMES) is used by physical therapists in the clinic. The efficacy of NMES is limited by the rapid onset muscle fatigue. The role of NMES parameters is muscle fatigue is not clear. Objective: To determine the effects of shape waveform on muscle fatigue, during NMES. Methods: Twelve healthy subjects participated in the study. Subjects were assigned to 1 of 3 groups, randomly. Group assignment determined the order in which they were tested using 3 different shape waveforms. Maximal voluntary isometric contraction (MVIC) was measured during the first session. Fatigue test was applied with amplitude required to elicit 50% of the MVIC. In each 3 testing sessions torque of contraction and level comfort were measured, and percent fatigue was calculated. Analysis of variance tests for dependent samples was used to determine the effect of shape waveform on muscle fatigue and comfort scores Results: The results showed no one shape waveform was most fatigable and that SQ wave induced more uncomfortable stimulus.

Related Ontology Subjects/Areas/Topics (7)

Animation and Simulation	Biomedical Signal Processing	Medical Image Detection, Acquisition, Analysis and Processing
Applications and Services	Computer Vision, Visualization and Computer Graphics	Motion Control
Biomedical Engineering

Human Activity Recognition from Triaxial Accelerometer Data - Feature Extraction and Selection Methods for Clustering of Physical Activities

Topics: Pattern Recognition; Medical Signal Acquisition, Analysis and Processing; Wearable Sensors and Systems; Real-Time Systems; Time and Frequency Response

Authors: Inês Machado ¹ , Ricardo Gomes ¹ , Hugo Gamboa ² and Vítor Paixão ³

Affiliations: ¹ FCT-UNL, Portugal , ² FCT-UNL and PLUX - Wireless Biosignals, Portugal , ³ Champalimaud Foundation, Portugal

Digital Object Identifier: 10.5220/0004749801550162

Proceedings of BIOSIGNALS 2014/BIOSTEC, ISBN: 978-989-758-011-6

Quick Abstract

The demand for objectivity in clinical diagnosis has been one of the greatest challenges in Biomedical Engineering. The study, development and implementation of solutions that may serve as ground truth in physical activity recognition and in medical diagnosis of chronic motor diseases is ever more imperative. This paper describes a human activity recognition framework based on feature extraction and feature selection techniques where a set of time, statistical and frequency domain features taken from 3-dimensional accelerometer sensors are extracted. In this paper, unsupervised learning is applied to the feature representation of accelerometer data to discover the activities performed by different subjects. A feature selection framework is developed in order to improve the clustering accuracy and reduce computational costs. The features which best distinguish a particular set of activities are selected from a 180th- dimensional feature vector through machine learning algorithms. The implemented framework achieved very encouraging results in human activity recognition: an average person-dependent Adjusted Rand Index (ARI) of 99:29%0:5% and a person-independent ARI of 88:57%4:0% were reached.

Related Ontology Subjects/Areas/Topics (24)

Applications and Services	Health Information Systems	Physiological Computing Systems
Artificial Intelligence	Human-Computer Interaction	Real-Time Systems
Biomedical Engineering	Informatics in Control, Automation and Robotics	Sensor Networks
Biomedical Signal Processing	Medical Image Detection, Acquisition, Analysis and Processing	Signal Processing, Sensors, Systems Modeling and Control
Computer Vision, Visualization and Computer Graphics	Methodologies and Methods	Soft Computing
Data Manipulation	Neurocomputing	Time and Frequency Response
Devices	Neurotechnology, Electronics and Informatics	Time-Frequency Analysis
Health Engineering and Technology Applications	Pattern Recognition	Wearable Sensors and Systems

Semantic and Syntactic Matching of e-Catalogues - Using Vector Space Model

Topics: Semantic Web; Integration/Interoperability

Authors: Ahmad Mehrbod ¹ , Aneesh Zutshi ¹ and António Grilo ²

Affiliations: ¹ FCT/UNL, Portugal , ² Universidade Nova De Lisboa, Portugal

Digital Object Identifier: 10.5220/0005115302240229

Proceedings of ICE-B 2014/ICETE, ISBN: 978-989-758-043-7

Quick Abstract

E-catalogues play a key role in e-procurement. Matching a product request from a buyer with products e-catalogues, helps companies to find business partners in e-marketplaces. Plethora of e-catalogue standards and enterprise specific formats is one of the major challenges in the matching process. In addition to this syntactic heterogeneity, the same product concept can be expressed using different words that causes semantic diversity in e-catalogues. In this paper, we propose a flexible approach to e-catalogue matching using Vector Space Model. Each e-catalogue is interpreted syntactically in its schema and semantically in an ontology that is developed based on its product classification system. Schemas and ontologies are added to the VSM by adding the syntax of the structure and semantic of the ontology to the indexing and searching mechanisms. The matching process uses the syntactic and semantic metadata for interpreting each e-catalogue as much as the information is available for the system, but is not dependent on this information.

Related Ontology Subjects/Areas/Topics (10)

Artificial Intelligence	Integration/Interoperability	Semantic Web
Collaboration and e-Services	Knowledge Engineering and Ontology Development	Soft Computing
e-Business	Knowledge-Based Systems	Symbolic Systems
Enterprise Information Systems

Simulating Digital Businesses using an Agent Based Modeling Approach

Topics: Business Performance; Business Models; Enterprise Ontologies; Modeling and Frameworks

Authors: Aneesh Zutshi ¹ , Antonio Grilo ¹ and Ricardo Jardim-Gonçalves ²

Affiliations: ¹ UNIDEMI, Portugal , ² UNINOVA, Portugal

Digital Object Identifier: 10.5220/0005121301650171

Proceedings of ICE-B 2014/ICETE, ISBN: 978-989-758-043-7

Quick Abstract

This paper proposes a complex systems approach to understand the growth and decline of Digital Businesses. Digital Businesses are characterised by unique factors such as a highly networked online customer base, where word of mouth spreads very fast, and minimal cost of incremental users due to economies of scale. Thus online businesses peak and plummet rapidly making it difficult to fathom their success. Through an Agent Based Modeling approach we propose that online businesses can be represented as simulation models which can enable forecasting, what-if analysis and optimization of business parameters.

Related Ontology Subjects/Areas/Topics (8)

Business Models	Enterprise Engineering	Logistics
Business Performance	Enterprise Information Systems	Modeling and Frameworks
e-Business	Enterprise Ontologies

Algorithm for Testing Behavioural Phenotypes in a Zebrafish Model of Parkinson’s Disease

Topics: Medical Signal Acquisition, Analysis and Processing; Wearable Sensors and Systems; Detection and Identification

Authors: Angela Pimentel ¹ , Hugo Gamboa ² , Sérgio Reis Cunha ³ and Ana Dulce Correia ⁴

Affiliations: ¹ FCT-UNL, Portugal , ² FCT-UNL and PLUX - Wireless Biosignals, Portugal , ³ Porto University, Portugal , ⁴ University of Lisbon, Portugal

Digital Object Identifier: 10.5220/0004238101960202

Proceedings of BIOSIGNALS 2013/BIOSTEC, ISBN: 978-989-8565-36-5

Quick Abstract

Parkinson’s disease (PD) is one of the neurodegenerative diseases with an increased prevalence widely studied by the scientific community. Understanding the behaviour related to the disease is an added value for diagnosis and treatment. Thus the use of an animal model for PD that develops similar symptoms to the human being allows to the clinic a larger vision over the health of a patient. Zebrafish can be used to study some human diseases including PD. This work describes the development of an algorithm for the characterization of behaviour in this specie. The biosensor called Marine On-line Biomonitor System (MOBS) is connected electrically to chambers where the specimen of zebrafish moves freely providing a signal that is related with the fish activity. Using the developed algorithm based on signal processing, statistic analysis and machine learning techniques we present classification of a fish as normal or ill and characterize its behaviour.

Related Ontology Subjects/Areas/Topics (11)

Applications and Services	Detection and Identification	Medical Image Detection, Acquisition, Analysis and Processing
Biomedical Engineering	Devices	Physiological Computing Systems
Biomedical Signal Processing	Health Information Systems	Wearable Sensors and Systems
Computer Vision, Visualization and Computer Graphics	Human-Computer Interaction