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  • Preface

     Moreno Arostegui, Juan Manuel; Cabestany Moncusi, Joan; Rojas Ruiz, Ignacio
    Neural processing letters
    Date of publication: 2013-02-01
    Journal article

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  • A self-adaptive hardware architecture with fault tolerance capabilities

     Soto, Javier; Moreno Arostegui, Juan Manuel; Cabestany Moncusi, Joan
    Neurocomputing
    Date of publication: 2013-12-09
    Journal article

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    This paper describes a Fault Tolerance System (FTS) implemented in a new self-adaptive hardware architecture. This architecture is based on an array of cells that implements in a distributed way self-adaptive capabilities. The cell includes a configurable multiprocessor, so it can have between one and four processors working in parallel, with a programmable configuration mode that allows selecting the size of program and data memories. The self-elimination and self-replication capabilities of cell(s) are performed when the FTS detects a failure in any of the processors that include it, so that this cell(s) will be self-discarded for future implementations. Other adaptive capabilities of the system are self-routing, self-placement and runtime self-configuration. Additionally, it is described as an example application and a software tool that has been implemented to facilitate the development of applications to test the system.

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    A wearable inertial measurement unit for long-term monitoring in the dependency care area  Open access

     Rodriguez Martin, Daniel Manuel; Perez Lopez, Carlos; Sama Monsonis, Albert; Cabestany Moncusi, Joan; Català Mallofré, Andreu
    Sensors
    Date of publication: 2013-10-18
    Journal article

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    Human movement analysis is a field of wide interest since it enables the assessment of a large variety of variables related to quality of life. Human movement can be accurately evaluated through Inertial Measurement Units (IMU), which are wearable and comfortable devices with long battery life. The IMU's movement signals might be, on the one hand, stored in a digital support, in which an analysis is performed a posteriori. On the other hand, the signal analysis might take place in the same IMU at the same time as the signal acquisition through online classifiers. The new sensor system presented in this paper is designed for both collecting movement signals and analyzing them in real-time. This system is a flexible platform useful for collecting data via a triaxial accelerometer, a gyroscope and a magnetometer, with the possibility to incorporate other information sources in real-time. A SD card can store all inertial data and a Bluetooth module is able to send information to other external devices and receive data from other sources. The system presented is being used in the real-time detection and analysis of Parkinson's disease symptoms, in gait analysis, and in a fall detection system.

    Human movement analysis is a field of wide interest since it enables the assessment of a large variety of variables related to quality of life. Human movement can be accurately evaluated through Inertial Measurement Units (IMU), which are wearable and comfortable devices with long battery life. The IMU’s movement signals might be, on the one hand, stored in a digital support, in which an analysis is performed a posteriori. On the other hand, the signal analysis might take place in the same IMU at the same time as the signal acquisition through online classifiers. The new sensor system presented in this paper is designed for both collecting movement signals and analyzing them in real-time. This system is a flexible platform useful for collecting data via a triaxial accelerometer, a gyroscope and a magnetometer, with the possibility to incorporate other information sources in real-time. A μSD card can store all inertial data and a Bluetooth module is able to send information to other external devices and receive data from other sources. The system presented is being used in the real-time detection and analysis of Parkinson’s disease symptoms, in gait analysis, and in a fall detection system

  • Gait identification by means of box approximation geometry of reconstructed attractors in latent space

     Sama Monsonis, Albert; Ruiz Vegas, Francisco Javier; Agell Jané, Núria; Perez Lopez, Carlos; Català Mallofré, Andreu; Cabestany Moncusi, Joan
    Neurocomputing
    Date of publication: 2013-02
    Journal article

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    This paper presents a novel gait recognition method which uses the signals measured by a single inertial sensor located on the waist. This method considers human gait as a dynamical system and employs a few singular values obtained by means of Singular Spectrum Analysis applied to scalar measurements from the inertial sensor. Singular values can be interpreted as the approximate edge length of the bounding box wrapping the attractor in the latent space. Effects of different parameters on the gait recognition performance using patterns from 20 different subjects are analysed.

  • SVM-based posture identification with a single waist-located triaxial accelerometer

     Rodriguez Martin, Daniel Manuel; Sama Monsonis, Albert; Perez Lopez, Carlos; Català Mallofré, Andreu; Cabestany Moncusi, Joan; Rodríguez Molinero, Alejandro
    Expert systems with applications
    Date of publication: 2013-12
    Journal article

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    Analysis of human body movement is an important research area, specially for health applications. In order to assess the quality of life of people with mobility problems like Parkinson¿s disease o stroke patients, it is crucial to monitor and assess their daily life activities. The main goal of this work is the characterization of basic activities using a single triaxial accelerometer located at the waist. This paper presents a novel postural detection algorithm based in SVM methods which is able to detect and identify Walking, Stand, Sit, Lying, Sit to Stand, Stand to sit, Bending up/down, Lying from Sit and Sit from Lying transitions with a sensitivity of 97% and specificity of 84% with 2884 postures analyzed from 31 healthy volunteers. Parameters and models found have been tested in another dataset from Parkinson¿s disease patients, achieving results of 98% of sensitivity and 78% of specificity in postural transitions. The proposed algorithm has been optimized to be easily implemented in real-time system for on-line monitoring applications.

    Analysis of human body movement is an important research area, specially for health applications. In order to assess the quality of life of people with mobility problems like Parkinson’s disease o stroke patients, it is crucial to monitor and assess their daily life activities. The main goal of this work is the characterization of basic activities using a single triaxial accelerometer located at the waist. This paper presents a novel postural detection algorithm based in SVM methods which is able to detect and identify Walking, Stand, Sit, Lying, Sit to Stand, Stand to sit, Bending up/down, Lying from Sit and Sit from Lying transitions with a sensitivity of 97% and specificity of 84% with 2884 postures analyzed from 31 healthy volunteers. Parameters and models found have been tested in another dataset from Parkinson’s disease patients, achieving results of 98% of sensitivity and 78% of specificity in postural transitions. The proposed algorithm has been optimized to be easily implemented in real-time system for on-line monitoring applications.

  • Advances in computational intelligence

     Rojas, Ignacio; Cabestany Moncusi, Joan; Joya, Gonzalo
    Softcomputing
    Date of publication: 2013-02
    Journal article

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  • Millor projecte europeu de recerca

     Cabestany Moncusi, Joan; Rovira, Jordi; Rodríguez, Alejandro
    Award or recognition

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  • CIP-297178-FATE - Fall Detector for the Elder

     Esposito, Gennaro; Cabestany Moncusi, Joan; Cortes Garcia, Claudio Ulises
    Participation in a competitive project

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  • Comparative and adaptation of step detection and step length estimators to a lateral belt worn accelerometer

     Sayeed, Taufique; Sama Monsonis, Albert; Català Mallofré, Andreu; Cabestany Moncusi, Joan
    IEEE International Conference on e-Health Networking, Applications and Services
    Presentation's date: 2013-10-10
    Presentation of work at congresses

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    Parkinson¿s Disease (PD) is a neurodegenerative disease that predominantly alter patients¿ motor performance and compromises the speed, the automaticity and fluidity of natural movements. The patients fluctuate between periods in which they can move almost normally for some hours (ON state) and periods with motor disorders (OFF state). Gait properties are affected by the motor state of a patient: reduced stride length, reduced gait speed, increased stride width etc. The ability to assess the motor states (ON/OFF) on a continuous basis for long time without disturbing the patients¿ daily life activities is an important component of PD management. An accurate report of motor states could allow clinics to adjust the medication regimen to avoid OFF periods. The real-time monitoring will also allow an online treatment by combining, for instance, with automatic drug-administration pump doses. Many studies have attempted to extract gait properties through a belt-worn single tri-axial accelerometer. In this paper, a user friendly position is proposed to place the accelerometer and three step detection methods and three step length estimators are compared considering the proposed sensor placement in signals obtained from healthy volunteers and PD patients. Adaptation methods to these step length estimators are also proposed and compared. The comparison shows that the adapted estimators improve the performance with the new proposed step detection method and reduce errors in respect of the original methods.

    Parkinson’s Disease (PD) is a neurodegenerative disease that predominantly alter patients’ motor performance and compromises the speed, the automaticity and fluidity of natural movements. The patients fluctuate between periods in which they can move almost normally for some hours (ON state) and periods with motor disorders (OFF state). Gait properties are affected by the motor state of a patient: reduced stride length, reduced gait speed, increased stride width etc. The ability to assess the motor states (ON/OFF) on a continuous basis for long time without disturbing the patients’ daily life activities is an important component of PD management. An accurate report of motor states could allow clinics to adjust the medication regimen to avoid OFF periods. The real-time monitoring will also allow an online treatment by combining, for instance, with automatic drug-administration pump doses. Many studies have attempted to extract gait properties through a belt-worn single tri-axial accelerometer. In this paper, a user friendly position is proposed to place the accelerometer and three step detection methods and three step length estimators are compared considering the proposed sensor placement in signals obtained from healthy volunteers and PD patients. Adaptation methods to these step length estimators are also proposed and compared. The comparison shows that the adapted estimators improve the performance with the new proposed step detection method and reduce errors in respect of the original methods.

  • Human activity and motion disorder recognition: towards smarter interactive cognitive environments

     Reyes Ortiz, Jorge Luis; Ghio, Alessandro; Anguita, Davide; Parra Perez, Xavier; Cabestany Moncusi, Joan; Català Mallofré, Andreu
    European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning
    Presentation's date: 2013-04-24
    Presentation of work at congresses

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    The rise of ubiquitous computing systems in our environment is engendering a strong need for novel approaches of human-computer interaction. Either for extending the existing range of possibilities and services available to people or for providing assistance the ones with limited conditions. Human Activity Recognition (HAR) is playing a central role in this task by offering the input for the development of more interactive and cognitive environments. This has motivated the organization of the ESANN 2013 Special Session in Human Activity and Motion Disorder Recognition and the execution of a competition in HAR. Here, a compilation of the most recent proposals in the area are exposed accompanied by the results of the contest calling for innovative approaches to recognize activities of daily living (ADL) from a recently published data set.

    The rise of ubiquitous computing systems in our environment is engendering a strong need for novel approaches of human-computer interaction. Either for extending the existing range of possibilities and services available to people or for providing assistance the ones with limited conditions. Human Activity Recognition (HAR) is playing a central role in this task by offering the input for the development of more interactive and cognitive environments. This has motivated the organization of the ESANN 2013 Special Session in Human Activity and Motion Disorder Recognition and the execution of a competition in HAR. Here, a compilation of the most recent proposals in the area are exposed accompanied by the results of the contest calling for innovative approaches to recognize activities of daily living (ADL) from a recently published data set.

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    A heterogeneous database for movement knowledge extraction in Parkinson's disease  Open access

     Sama Monsonis, Albert; Perez Lopez, Carlos; Rodriguez Martin, Daniel Manuel; Cabestany Moncusi, Joan; Moreno Arostegui, Juan Manuel; Rodríguez Molinero, Alejandro
    European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning
    Presentation's date: 2013-04-26
    Presentation of work at congresses

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    This paper presents the design and methodology used to create a heterogeneous database for knowledge movement extraction in Parkinson's Disease. This database is being constructed as part of REM- PARK project and is composed of movement measurements acquired from inertial sensors, standard medical scales as Unied Parkinson's Disease Rating Scale, and other information obtained from 90 Parkinson's Disease patients. The signals obtained will be used to create movement disorder detection algorithms using supervised learning techniques. The different sources of information and the need of labelled data pose many challenges which the methodology described in this paper addresses. Some preliminary data obtained are presented.

    This paper presents the design and methodology used to create a heterogeneous database for knowledge movement extraction in Parkinson's Disease. This database is being constructed as part of REM- PARK project and is composed of movement measurements acquired from inertial sensors, standard medical scales as Uni ed Parkinson's Disease Rating Scale, and other information obtained from 90 Parkinson's Disease patients. The signals obtained will be used to create movement disorder detection algorithms using supervised learning techniques. The different sources of information and the need of labelled data pose many challenges which the methodology described in this paper addresses. Some preliminary data obtained are presented.

  • Comparison and adaptation of step length and gait speed estimators from single belt worn accelerometer positioned on lateral side of the body

     Sayeed, Taufique; Sama Monsonis, Albert; Català Mallofré, Andreu; Cabestany Moncusi, Joan
    IEEE International Symposium on Intelligent Signal Processing
    Presentation's date: 2013-09-17
    Presentation of work at congresses

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    Parkinson¿s Disease (PD) is a neurodegenerative disease that predominantly alter patients¿ motor performance and compromises the speed, the automaticity and fluidity of natural movements. The patients fluctuate between periods in which they can move almost normally for some hours (ON state) and periods with motor disorders (OFF state). Gait properties are affected by the motor state of a patient: reduced stride length, reduced gait speed, increased stride width etc. The ability to assess the motor states (ON/OFF) on a continuous basis for long time without disturbing the patients¿ daily life activities is an important component of PD management. An accurate report of motor states could allow clinics to adjust the medication regimen to avoid OFF periods. The real-time monitoring will also allow an online treatment by combining, for instance, with automatic drugadministration pump doses. Many studies have attempted to extract gait properties through a belt-worn single tri-axial accelerometer. In this paper, a user friendly position is proposed to place the accelerometer and six step length estimators are compared considering the proposed sensor placement in a preliminary database of healthy volunteers. Adaptation methods to some of these estimators are also proposed and compared. The comparison shows that the adapted estimators improve the performance and reduce errors in respect of the original methods applied in the new sensor location.

    Parkinson’s Disease (PD) is a neurodegenerative disease that predominantly alter patients’ motor performance and compromises the speed, the automaticity and fluidity of natural movements. The patients fluctuate between periods in which they can move almost normally for some hours (ON state) and periods with motor disorders (OFF state). Gait properties are affected by the motor state of a patient: reduced stride length, reduced gait speed, increased stride width etc. The ability to assess the motor states (ON/OFF) on a continuous basis for long time without disturbing the patients’ daily life activities is an important component of PD management. An accurate report of motor states could allow clinics to adjust the medication regimen to avoid OFF periods. The real-time monitoring will also allow an online treatment by combining, for instance, with automatic drugadministration pump doses. Many studies have attempted to extract gait properties through a belt-worn single tri-axial accelerometer. In this paper, a user friendly position is proposed to place the accelerometer and six step length estimators are compared considering the proposed sensor placement in a preliminary database of healthy volunteers. Adaptation methods to some of these estimators are also proposed and compared. The comparison shows that the adapted estimators improve the performance and reduce errors in respect of the original methods applied in the new sensor location.

  • Preface

     Rojas, Ignacio; Joya, Gonzalo; Cabestany Moncusi, Joan
    International Work-Conference on Artificial Neural Networks
    Presentation's date: 2013-06
    Presentation of work at congresses

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  • Identification of postural transitions using a waist-located inertial sensor

     Rodriguez Martin, Daniel Manuel; Sama Monsonis, Albert; Perez Lopez, Carlos; Català Mallofré, Andreu; Cabestany Moncusi, Joan; Rodríguez Molinero, Alejandro
    International Work-Conference on Artificial Neural Networks
    Presentation's date: 2013-06-13
    Presentation of work at congresses

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    Analysis of human movement is an important research area, specially for health applications. In order to assess the quality of life of people with mobility problems like Parkinson¿s disease (PD) or stroke patients, it is crucial to monitor their daily life activities. The main goal of this work is to characterize basic activities and their transitions using a single sensor located at the waist. This paper presents a novel postural detection algorithm which is able to detect and identify 6 different postural transitions, sit to stand, stand to sit, bending up/down and lying to sit and sit to lying transitions with a sensitivity of 86.5% and specificity of 95%. The algorithm has been tested on 31 healthy volunteers and 8 PD patients who performed a total of 545 and 176 transitions respectively. The proposed algorithm is suitable to be implemented in real-time systems for on-line monitoring applications.

    Analysis of human movement is an important research area, specially for health applications. In order to assess the quality of life of people with mobility problems like Parkinson’s disease (PD) or stroke patients, it is crucial to monitor their daily life activities. The main goal of this work is to characterize basic activities and their transitions using a single sensor located at the waist. This paper presents a novel postural detection algorithm which is able to detect and identify 6 different postural transitions, sit to stand, stand to sit, bending up/down and lying to sit and sit to lying transitions with a sensitivity of 86.5% and specificity of 95%. The algorithm has been tested on 31 healthy volunteers and 8 PD patients who performed a total of 545 and 176 transitions respectively. The proposed algorithm is suitable to be implemented in real-time systems for on-line monitoring applications.

  • REMPARK: when AI and technology meet parkinson disease assessment

     Cabestany Moncusi, Joan; Perez Lopez, Carlos; Sama Monsonis, Albert; Moreno Arostegui, Juan Manuel; Bayes, Ángels; Rodríguez Molinero, Alejandro
    International Conference Mixed Design of Integrated Circuits and Systems
    Presentation's date: 2013-06
    Presentation of work at congresses

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    REMPARK project objective is to develop a personal health system with closed loop detection, response and action capabilities for the assessment and possible management of Parkinson's Disease (PD) patients. The project is developing a wearable monitoring system able to identify in real time the motor status of the PD patients and evaluating ON/OFF/Dyskinesia status with a very high sensitivity and specificity degree (>80%) in operation during ambulatory conditions. Identification of the motor status is based on the knowledge included in a large database obtained with the collaboration of a number of volunteer PD patients, according a specific defined protocol in ambulatory conditions. Artificial Intelligence (AI) methods are applied to the database information for the automatic detection of motor symptoms.

  • FATE: one step towards an automatic aging people fall detection service

     Cabestany Moncusi, Joan; Moreno Arostegui, Juan Manuel; Perez Lopez, Carlos; Sama Monsonis, Albert; Català Mallofré, Andreu; Rodríguez Molinero, Alejandro; Arnal, Marc
    International Conference Mixed Design of Integrated Circuits and Systems
    Presentation's date: 2013-06
    Presentation of work at congresses

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    FATE is a project funded by the European Union under the program CIP/ICT-PSP with the main objective of organizing a big pilot on the automatic falls detection in aging people living at home. Automatic detection of falls is done in indoors and outdoors conditions, and in both cases the detection generates an alarm sent to a call center. The detection system is designed around a sensor sub-system based on accelerometers and gyroscopes able to detect falls with a high reliability. The complete system is based on a communications layer based in ZigBee and Bluetooth protocols. The gateway for sending the alarm to the call center is a mobile phone. Pilots are organized in three different countries (Spain, Italy and Ireland) where different models of health service and implemented call centers are available. Pilots duration will be one year, involving 175 users and one of the main final objectives is to gain experience with the integration of an automatic fall detection service in an already care/health existing service.

    FATE is a project funded by the European Union under the program CIP/ICT-PSP with the main objective of organizing a big pilot on the automatic falls detection in aging people living at home. Automatic detection of falls is done in indoors and outdoors conditions, and in both cases the detection generates an alarm sent to a call center. The detection system is designed around a sensor sub-system based on accelerometers and gyroscopes able to detect falls with a high reliability. The complete system is based on a communications layer based in ZigBee and Bluetooth protocols. The gateway for sending the alarm to the call center is a mobile phone. Pilots are organized in three different countries (Spain, Italy and Ireland) where different models of health service and implemented call centers are available. Pilots duration will be one year, involving 175 users and one of the main final objectives is to gain experience with the integration of an automatic fall detection service in an already care/health existing service.

  • A system for inference of spatial context of Parkinson's disease patients

     Takac, Boris; Català Mallofré, Andreu; Cabestany Moncusi, Joan; Chen, Wei; Rauterberg, Mattias
    Studies in health technology and informatics
    Date of publication: 2012
    Journal article

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    This work proposes a concept for indoor ambulatory monitoring for Parkinson's disease patients. In the proposed concept, a wearable inertial sensor is kept as the main monitoring device through the day, and it is expanded by an ambient sensor system in the specific living areas with high estimated probability of occurrence of freezing of gait episode. The ambient sensor system supports decisions of the wearable sensor system by providing relevant spatial context information of the user, which is obtained through precise localization.

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    Fuzzy expert system for the detection of episodes of poor water quality through continuous measurement  Open access

     Angulo Bahón, Cecilio; Cabestany Moncusi, Joan; Rodríguez, Pablo; Batlle, Montserrat; González, Antonio; de Campos, Sergio
    Expert systems with applications
    Date of publication: 2012
    Journal article

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    In order to prevent and reduce water pollution, promote a sustainable use, protect the environment and enhance the status of aquatic ecosystems, this article deals with the application of advanced mathematical techniques designed to aid in the management of records of different water quality monitoring networks. These studies include the development of a software tool for decision support, based on the application of fuzzy logic techniques, which can indicate water quality episodes from the behaviour of variables measured at continuous automatic water control networks. Using a few physicalchemical variables recorded continuously, the expert system is able to obtain water quality phenomena indicators, which can be associated, with a high probability of cause-effect relationship, with human pressure on the water environment, such as urban discharges or diffuse agricultural pollution. In this sense, at the proposed expert system, automatic water quality control networks complement manual sampling of official administrative networks and laboratory analysis, providing information related to specific events (discharges) or continuous processes (eutrophication, fish risk) which can hardly be detected by discrete sampling.

  • AAL Forum Award 2012

     Rovira Simón, Jordi; Cabestany Moncusi, Joan
    Award or recognition

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  • Fall Detector for the Elder

     Català Mallofré, Andreu; Moreno Arostegui, Juan Manuel; Sama Monsonis, Albert; Perez Lopez, Carlos; Cortes Garcia, Claudio Ulises; Martinez Velasco, Antonio Benito; Romagosa Cabús, Jaume; Cabestany Moncusi, Joan
    Participation in a competitive project

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  • Dyskinesia and motor state detection in Parkinson's disease patients with a single movement sensor

     Sama Monsonis, Albert; Perez Lopez, Carlos; Rodriguez Martin, Daniel Manuel; Romagosa Cabús, Jaume; Català Mallofré, Andreu; Cabestany Moncusi, Joan; Pérez Martínez, David Andrés; Rodríguez Molinero, A.
    IEEE Engineering in Medicine and Biology Society
    Presentation's date: 2012-08
    Presentation of work at congresses

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    Parkinson's Disease (PD) is a neurodegenerative disease that alters the patients' motor performance. Patients suffer many motor symptoms: bradykinesia, dyskinesia and freezing of gait, among others. Furthermore, patients alternate between periods in which they are able to move smoothly for some hours (ON state), and periods with motor complications (OFF state). An accurate report of PD motor states and symptoms will enable doctors to personalize medication intake and, therefore, improve response to treatment. Additionally, real-time reporting could allow an automatic management of PD by means of an automatic control of drug-administration pump doses. Such a system must be able to provide accurate information without disturbing the patients' daily life activities.

  • Bio-inspired systems. Computational and ambient intelligence

     Sandoval, Francisco; Cabestany Moncusi, Joan; Prieto, Alberto
    Neurocomputing
    Date of publication: 2011-09
    Journal article

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    In the present issue of Neurocomputing, it is apleasure to present you a collection of 12 extended versions of selected papers from the 10 the dition of the International Work Conference on Artificial Neural Networks (IWANN2009). This is a conference held every two year in Spain, and focus in gon the foundations, theory, models and applications of systems, which are inspired by nature (e.g.neural networks, fuzzy logic and evolutionary systems).

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    Analyzing human gait and posture by combining feature selection and kernel methods  Open access

     Sama Monsonis, Albert; Angulo Bahón, Cecilio; Pardo Ayala, Diego Esteban; Català Mallofré, Andreu; Cabestany Moncusi, Joan
    Neurocomputing
    Date of publication: 2011-09
    Journal article

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    This paper evaluates a set of computational algorithms for the automatic estimation of human postures and gait properties from signals provided by an inertial body sensor. The use of a single sensor device imposes limitations for the automatic estimation of relevant properties, like step length and gait velocity, as well as for the detection of standard postures like sitting or standing. Moreover, the exact location and orientation of the sensor is also a common restriction that is relaxed in this study. Based on accelerations provided by a sensor, known as the `9 2', three approaches are presented extracting kinematic information from the user motion and posture. Firstly, a two-phases procedure implementing feature extraction and Support Vector Machine based classi cation for daily living activity monitoring is presented. Secondly, Support Vector Regression is applied on heuristically extracted features for the automatic computation of spatiotemporal properties during gait. Finally, sensor information is interpreted as an observation of a particular trajectory of the human gait dynamical system, from which a reconstruction space is obtained, and then transformed using standard principal components analysis, nally Support Vector Regression is used for prediction. Daily living Activities are detected and spatiotemporal parameters of human gait are estimated using methods sharing a common structure based on feature extraction and kernel methods. The approaches presented are susceptible to be used for medical purposes.

  • Personal Health Device for the Remote and Autonomous Management of

     Català Mallofré, Andreu; Moreno Arostegui, Juan Manuel; Perez Lopez, Carlos; Sama Monsonis, Albert; Cabestany Moncusi, Joan
    Participation in a competitive project

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  • SISTEMA ON-LINE PARA COMPENSACIÓN DE ALTERACIONES DE LA MARCHA EN PERSONAS AFECTADAS DE PARKINSON

     Llanas Parra, Francesc Xavier; Raya Giner, Cristobal; Cabestany Moncusi, Joan; Perez Lopez, Carlos; Ferrer Arnau, Luis Jorge; Català Mallofré, Andreu
    Participation in a competitive project

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  • CIP-ICT-PSP-2010-4, 250577 CAALIX-MW

     Angulo Bahón, Cecilio; Cabestany Moncusi, Joan; Llanas Parra, Francesc Xavier; Sama Monsonis, Albert; Perez Lopez, Carlos; Diaz Boladeras, Marta; Català Mallofré, Andreu
    Participation in a competitive project

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  • Complete Ambient Assisted Living Experiment-Market Validation (CAALYX-MV)

     Cabestany Moncusi, Joan; Català Mallofré, Andreu; Sama Monsonis, Albert; Llanas Parra, Francesc Xavier; Diaz Boladeras, Marta
    Participation in a competitive project

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  • Description of a fault tolerance system implemented in a hardware architecture with self-adaptive capabilities

     Soto, Javier; Moreno Arostegui, Juan Manuel; Cabestany Moncusi, Joan
    International Work-Conference on Artificial Neural Networks
    Presentation's date: 2011-06-09
    Presentation of work at congresses

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    This paper describes a Fault Tolerance System (FTS) implemented in a new self-adaptive hardware architecture. This architecture is based on an array of cells that implements in a distributed way self-adaptive capabilities. The cell includes a configurable multiprocessor, so it can have between one and four processors working in parallel, with a programmable configuration mode that allows selecting the size of program and data memories. The self-elimination and self-replication capabilities of cell(s) are performed when the FTS detects a failure in any of the processors that include it, so that this cell(s) will be self-discarded for future implementations. Other self-adaptive capabilities of the system are self-routing, self-placement and runtime self-configuration.

  • Prefaci edició del llibre d'actes del congrés IWANN 2011. LNCS 6691 i 6692

     Cabestany Moncusi, Joan; Rojas, Ignacio; Joya, Gonzalo
    International Work-Conference on Artificial Neural Networks
    Presentation of work at congresses

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  • Personal Health System for Remote Management of Parkinson Disease (REMPARK)

     Cabestany Moncusi, Joan
    Participation in a competitive project

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  • DESARROLLO EN ROBÓTICA SOCIAL PARA LA SALUD Y CALIDAD DE VIDA EN PERSONAS DEPENDIENTES

     Diaz Boladeras, Marta; Cabestany Moncusi, Joan; Pardo Ayala, Diego Esteban; Angulo Bahón, Cecilio
    Participation in a competitive project

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  • Time series analysis of inertial-body signals for the extraction of dynamic properties from human gait

     Sama Monsonis, Albert; Pardo Ayala, Diego Esteban; Cabestany Moncusi, Joan; Rodríguez Molinero, A.
    IEEE World Congress on Computational Intelligence
    Presentation's date: 2010-07-19
    Presentation of work at congresses

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  • Method and device for detecting the On and Off states of a Parkinson patient

     Rodríguez Molinero, A.; Cabestany Moncusi, Joan; Català Mallofré, Andreu; Sama Monsonis, Albert; Gálvez Barrón, Cesar Pavel; Romagosa Cabús, Jaume; Pérez Martínez, David Andrés; Angulo Bahón, Cecilio; Perez Lopez, Carlos
    Date of request: 2010-08-01
    Invention patent

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  • User Daily Activity Classification from Accelerometry Using Feature Selection and SVM

     Parera Giro, Jordi; Angulo Bahón, Cecilio; Rodríguez Molinero, A.; Cabestany Moncusi, Joan
    Lecture notes in computer science
    Date of publication: 2009
    Journal article

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  • Computational and ambient intelligence

     Cabestany Moncusi, Joan; Sandoval, Francisco; Prieto, Alberto
    Neurocomputing
    Date of publication: 2009-10
    Journal article

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  • Preparació de propOsta CAALYX-MV (7PM-CIP)

     Llanas Parra, Francesc Xavier; Cabestany Moncusi, Joan; Angulo Bahón, Cecilio; Diaz Boladeras, Marta; Català Mallofré, Andreu
    Participation in a competitive project

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  • BLOCKSAT-2: GUIADO Y POSICIONAMIENTO DE TRÁFICO FERROVIARIO CON SEGURIDAD INTRÍNSECA: SISTEMA DE BLOQUEO BASADO EN NAVEGACIÓN X SATÉ

     Comeron Tejero, Adolfo; Gelonch Bosch, Antoni; Jofre Roca, Luis; Romeu Robert, Jordi; Fuertes Armengol, José Mª; Cabestany Moncusi, Joan; Broquetas Ibars, Antoni
    Participation in a competitive project

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  • HOME-BASED EMPOWERED LIVING FOR PARKINSON'S DISEASENS PATIENTS

     Català Mallofré, Andreu; Pardo Ayala, Diego Esteban; Sama Monsonis, Albert; Angulo Bahón, Cecilio; Raya Giner, Cristobal; Cabestany Moncusi, Joan
    Participation in a competitive project

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  • Monitorització de la movilitat de Malalts de PArkinson amb fins terapèutics

     Perez Lopez, Carlos; Cabestany Moncusi, Joan
    Participation in a competitive project

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  • Home Empowered Living for Parkinson's disease Patiens (HELP)

     Cabestany Moncusi, Joan; Angulo Bahón, Cecilio; Català Mallofré, Andreu; Perez Lopez, Carlos; Bermejo Sanchez, Sergio
    Participation in a competitive project

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  • Implementation of a dynamic fault-tolerance scaling technique on a self-adaptative hardware architecture

     Soto Vargas, J.; Moreno Arostegui, Juan Manuel; Madrenas Boadas, Jordi; Cabestany Moncusi, Joan
    2009 International Conference on ReConFigurable Computing and FPGAs
    Presentation of work at congresses

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  • User Daily Activity Classification from Accelerometry Using Feature Selection and SVM

     Parera Giro, Jordi; Angulo Bahón, Cecilio; Cabestany Moncusi, Joan; Rodríguez-Molinero, A
    10th International Work-Conference on Artificial Neural Nerworks, IWANN 2009
    Presentation of work at congresses

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  • Implementation of a dynamic fault-tolerance scaling technique on a self-adaptive hardware architecture

     Soto Vargas, J.; Moreno Arostegui, Juan Manuel; Madrenas Boadas, Jordi; Cabestany Moncusi, Joan
    International Conference on ReConFigurable Computing and FPGAs
    Presentation of work at congresses

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  • Treatment of Parkinson's disease could be regulated by movement sensors: Subcutaneous infusion of varying apomorphine doses according to the intensity of motor activity

     Rodriguez-Molinero, Alejandro; Pérez Martínez, David Andrés; Català Mallofré, Andreu; Yuste, Antonio; Cabestany Moncusi, Joan
    Medical hypotheses
    Date of publication: 2008-12
    Journal article

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  • Diseño de un Multiprocesador Configurable y de la Interfaz de Comunicaciones para una Arquitectura de Hardware Auto-Adaptable

     Vargas, Soto J; Moreno Arostegui, Juan Manuel; Madrenas Boadas, Jordi; Cabestany Moncusi, Joan
    JCRA 08 - VIII Jornadas de Computación Reconfigurable y Aplicaciones
    Presentation of work at congresses

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  • Communication Infrastructure for a Self-Adaptive Hardware Architecture

     Soto, J; Moreno Arostegui, Juan Manuel; Madrenas Boadas, Jordi; Cabestany Moncusi, Joan
    Reconfigurable Communication-centric Systems-on-Chip workshop 2008 - ReCoSoC'08
    Presentation of work at congresses

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  • Accelerometer signals analysis using SVM and decision tree in daily activity identification

     Parera Giro, Jordi; Angulo Bahón, Cecilio; Cabestany Moncusi, Joan
    6th Conference of the International Society for Gerontechnology
    Presentation of work at congresses

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  • Design of a Configurable Multiprocessor for a Self-Adaptive Hardware Architecture

     Vargas, Soto J; Moreno Arostegui, Juan Manuel; Madrenas Boadas, Jordi; Cabestany Moncusi, Joan
    Conference on Design of Circuits and Integrated Systems
    Presentation of work at congresses

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  • ZigBee communication when building a body sensor network for elderly people

     Parera Giro, Jordi; Angulo Bahón, Cecilio; Cabestany Moncusi, Joan
    6th Conference of the International Society for Gerontechnology
    Presentation of work at congresses

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