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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.

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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.

  • 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.

  • Identification of sit-to-stand and stand-to-sit transitions using a single inertial sensor

     Rodriguez Martin, Daniel Manuel; Sama Monsonis, Albert; Perez Lopez, Carlos; Català Mallofré, Andreu
    Studies in health technology and informatics
    Date of publication: 2012
    Journal article

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    In order to enhance the quality of life of people with mobility problems like Parkinson's disease or stroke patients, it is crucial to monitor and assess their daily life activities by characterizing basic movements like postural transitions, which is the main goal of this work. This paper presents a novel postural transition detection algorithm which is able to detect and identify Sit to Stand and Stand to Sit transitions with a Sensitivity of 88.2% and specificity of 98.6% by using a single sensor located at the user's waist. The algorithm has been tested with 31 healthy volunteers and an overall amount of 545 transitions. The proposed algorithm can be easily implemented in real-time system for on-line monitoring applications.

    In order to enhance the people’s quality of life with mobility problems like Parkinson’s disease or stroke patients is crucial to monitor and assess their daily life activities by characterizing basic movements like postural transitions, which is the main goal of this work. This paper presents a novel postural transition detection algorithm which is able to detect and identify Sit to Stand and Stand to Sit transitions with a Sensitivity of 88.2% and specificity of 98.6% by using a single sensor located at the user’s waist. The algorithm has been tested into 31 healthy volunteers and an overall amount of 545 transitions. The proposed algorithm can be implemented easily in real-time system for on-line monitoring applications.

    Postprint (author’s final draft)

  • 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.

  • 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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    Gait recognition by using spectrum analysis on state space reconstruction  Open access

     Sama Monsonis, Albert; Ruiz Vegas, Francisco Javier; Perez Lopez, Carlos; Català Mallofré, Andreu
    Congrés Internacional de l¿Associació Catalana d¿Intel·ligència Artificial
    Presentation's date: 2011-10-28
    Presentation of work at congresses

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    This paper describes a method for identifying a person while walking by means of a triaxial accelerometer attached to the waist. Human gait is considered as a dynamical system whose attractor is reconstructed by time delay vectors. A Spectral Analysis on the state space reconstruction is used to characterize the attractor. The method is compared to other common methods used in gait recognition tasks through a preliminary test.

  • Gait identification by using spectrum analysis on state space reconstruction

     Ruiz Vegas, Francisco Javier; Sama Monsonis, Albert; Perez Lopez, Carlos; Català Mallofré, Andreu
    International Work-Conference on Artificial Neural Networks
    Presentation's date: 2011-06-10
    Presentation of work at congresses

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    This paper describes a method for identifying a person while walking by means of a triaxial accelerometer attached to the waist. Human gait is considered as a dynamical system whose attractor is reconstructed by time delay vectors. A Spectral Analysis on the state space reconstruction is used to characterize the attractor. Parameters involved in the reconstruction and characterization process are evaluated to examine the effect in gait identification. The method is tested in five volunteers, obtaining an overall accuracy of 92%.

    Postprint (author’s final draft)

  • Detection of Gait Parameters, Bradykinesia, and Falls in Patients with Parkinson's Disease by Using a Unique Triaxial Accelerometer

     Rodríguez Molinero, A.; Sanz, P.; Sama, A.; Calopa, M.; Romagosa Cabús, Jaume; Galvez, A.; Pérez Martínez, David Andrés; Perez Lopez, Carlos; Català, C.
    Movement disorders
    Date of publication: 2010-09-15
    Journal article

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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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  • 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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  • User activity detection with machine learning methods using wireless inertial sensors

     Parera Giro, Jordi; Pardo Ayala, Diego Esteban; TORRENT, MARC; Perez Lopez, Carlos; López-Pérez, Carlos; Angulo Bahón, Cecilio; Rodríguez-Molinero, Antonio
    X Jornadas de ARCA. Sistemas Cualitativos y Diagnosis, Robótica, Sistemas Domóticos y Computación Ubicua
    Presentation of work at congresses

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  • Servicio de gestión de información remota para actividades de la vida diaria adaptable a usuario

     Perez Lopez, Carlos; Català Mallofré, Andreu; Diaz Boladeras, Marta; Celma, M; Solana, M; Cabestany Moncusi, Joan
    Congreso Internacional sobre Domótica, Robótica y Teleasistencia para Todos
    Presentation of work at congresses

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  • Participación de usuarios en el desarrollo de un sistema de etiquetado de objetos del hogar para personas con discapacidad visual

     Diaz Boladeras, Marta; Celma, M; Solana, M; Perez Lopez, Carlos; Català Mallofré, Andreu
    Congreso Internacional sobre Domótica, Robótica y Teleasistencia para Todos
    Presentation of work at congresses

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  • Participación de usuarios en el desarrollo de un sistema de etiquetaje inteligente de objetos del hogar para personas con discapacidad visual

     Perez Lopez, Carlos; Diaz Boladeras, Marta; Català Mallofré, Andreu; Solana, M
    VII Congreso Internacional de Interacción Persona-Ordenador
    Presentation of work at congresses

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  • Servicio de gestión de Información Remota para las Actividades de la vida diaria, adaptable a Usuario

     Català Mallofré, Andreu; Diaz Boladeras, Marta; Perez Lopez, Carlos; Angulo Bahón, Cecilio; Guasch Murillo, Daniel; Cabestany Moncusi, Joan
    Participation in a competitive project

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  • Sistema d'Agents Portables Incrustats per a Entorns Naturals Segurs. (SAPIENS) (10605 IMSERSO)

     Català Mallofré, Andreu; Angulo Bahón, Cecilio; Guasch Murillo, Daniel; Silvestre Berges, Santiago; Diaz Boladeras, Marta; Cabestany Moncusi, Joan; Perez Lopez, Carlos
    Participation in a competitive project

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  • Uncertainties of the gradient and the variance methods in retrieving the mixing layer height in three meteorological sscenarios

     Sicard, Michaël; Perez Lopez, Carlos; Rocadenbosch Burillo, Francisco; Baldasano Recio, Jose M.; Comeron Tejero, Adolfo
    International Laser Radar Conference
    Presentation of work at congresses

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  • Summertine re-circulations of air pollutants over the north-eastern Iberian coast observed from systematic EARLINET lidar measurements in Barcelona

     Perez Lopez, Carlos; Sicard, Michaël; Jorba Casellas, Oriol; Comeron Tejero, Adolfo; Baldasano Recio, Jose M.
    Atmospheric environment
    Date of publication: 2004-08
    Journal article

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  • Multiple layer aerosol structures observed within the Barcelona air basin from regular Lidar mesurements

     Perez Lopez, Carlos; Sicard, Michaël; Baldasano Recio, Jose M.; Jorba Casellas, Oriol; Comeron Tejero, Adolfo
    Journal of aerosol science
    Date of publication: 2003-09
    Journal article

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