Albert Samà Monsonís

Polytechnic University of Catalonia | UPC · Department of Automatic Control (ESAII)

In the past decade, the use of wearable medical devices has been a great breakthrough in clinical practice, trials, and research. In the Parkinson's disease field, clinical evaluation is time limited, and healthcare professionals need to rely on retrospective data collected through patients' self-filled diaries and administered questionnaires. As t...

Posture transitions are one of the most mechanically demanding tasks and are useful to evaluate the motor status of patients with motor impairments, frail individuals or the elderly, among others. So far, wearable inertial systems have been one of the most employed tools in the study of these movements due to their suitable size and weight, being n...

Objective: We present a wearable inertial system for the evaluation of motor symptoms in Parkinson's Disease. Background: PD is the second neurodegenerative disease affecting to around 10 million people around the world and some studies are claiming that this number will double by 2040. Parkinson’s Disease (PD) is characterized by a big number of...

Abstract Our research team previously developed an accelerometry-based device, which can be worn on the waist during daily life activities and detects the occurrence of dyskinesia in patients with Parkinson’s disease. The goal of this study was to analyze the magnitude of correlation between the numeric output of the device algorithm and the result...

In this article, the Kalman filter, Mahony filter and Madgwick filter are implemented to estimate the orientation from inertial data, using an IMU called 9 × 3 of the MoMoPa3 project which contain various sensors including a gyroscope, an accelerometer and a magnetometer, each one of them, equipped with three perpendicular axes, in the magnetometer...

A presentation of the eHealth related concepts and challenges is done, together with an analysis on how the use of the Artificial Intelligence (AI) techniques can improve the management of the data generated by the eHealth activity, permitting to take more advanced decisions on the treatment and supervision of the patients. A concrete example and d...

Background: A new algorithm has been developed, which combines information on gait bradykinesia and dyskinesia provided by a single kinematic sensor located on the waist of Parkinson disease (PD) patients to detect motor fluctuations (On- and Off-periods). Objective: The goal of this study was to analyze the accuracy of this algorithm under real...

[This corrects the article on p. 431 in vol. 8, PMID: 28919877.].

Among Parkinson's disease (PD) motor symptoms, freezing of gait (FOG) may be the most incapacitating. FOG episodes may result in falls and reduce patients' quality of life. Accurate assessment of FOG would provide objective information to neurologists about the patient's condition and the symptom's characteristics, while it could enable non-pharmac...

Objective: To analyze the ability of the REMPARK System to detect ON-OFF fluctuations. Methods: Forty-one patients with moderate to severe idiopathic PD were recruited according to the UK Parkinson's Disease Society Brain Bank criteria. Patients with motor fluctuations, freezing of gait and/or dyskinesia and who were able to walk unassisted in t...

Background Our group earlier developed a small monitoring device, which uses accelerometer measurements to accurately detect motor fluctuations in patients with Parkinson’s (On and Off state) based on an algorithm that characterizes gait through the frequency content of strides. To further validate the algorithm, we studied the correlation of its o...

Posture transitions (PT) are important movements among the activities performed in daily life of older adults. Their analysis provides information related to the amount of activity performed by a patient over a day and, furthermore, they are useful for assessing symptoms in some movement disorders such as Parkinson’s disease. Many research works ha...

Freezing of gait (FOG) is one of the most incapacitating symptoms among the motor alterations of Parkinson’s disease (PD). Manifesting FOG episodes reduce patients’ quality of life and their autonomy to perform daily living activities, while it may provoke falls. Accurate ambulatory FOG assessment would enable non-pharmacologic support based on cue...

Freezing of gait (FoG) is one of the most disturbing and incapacitating symptoms in Parkinson’s Disease. It is defined as a sudden block in effective stepping, provoking anxiety, stress and falls. FoG is usually evaluated by means of different questionnaires; however, this method has shown to be not reliable, since it is subjective due to its depen...

Inertial measurement units (IMUs) are devices used, among other fields, in health applications, since they are light, small and effective. More concretely, IMUs have been demonstrated to be useful in the monitoring of motor symptoms of Parkinson's disease (PD). In this sense, most of previous works have attempted to assess PD symptoms in controlled...

Bradykinesia is a cardinal symptom of Parkinson's disease (PD) and describes the slowness of movement revealed in patients. Current PD therapies are based on dopamine replacement, and given that bradykinesia is the symptom that best correlates with the dopaminergic deficiency, the knowledge of its fluctuations may be useful in the diagnosis, treatm...

Among Parkinson’s disease (PD) symptoms, freezing of gait (FoG) is one of the most debilitating. To assess FoG, current clinical practice mostly employs repeated evaluations over weeks and months based on questionnaires, which may not accurately map the severity of this symptom. The use of a non-invasive system to monitor the activities of daily li...

Altered movement control is typically the first noticeable symptom manifested by Parkinson's disease (PD) patients. Once under treatment, the effect of the medication is very patent and patients often recover correct movement control over several hours. Nonetheless, as the disease advances, patients present motor complications. Obtaining precise in...

Freezing of gait is one of the most disturbing and incapacitating symptoms in Parkinson's Disease. This is defined as a sudden block in effective stepping, provoking anxiety, stress and falls. FoG is usually evaluated by means of different questionnaires; however, this method has shown not to be reliable since it is subjective due to its dependence...

Freezing of gait (FOG) is a common motor symptom of Parkinson's disease (PD), which presents itself as an inability to initiate or continue gait. This paper presents a method to monitor FOG episodes based only on acceleration measurements obtained from a waist-worn device. Three approximations of this method are tested. Initially, FOG is directly d...

Analysis of human movement is a growing research area within the field of sport monitoring which aims to enhance the performance of athletes, predicting injuries or optimizing training programs. Camera-based techniques are the most spread method to evaluate although frequently this method can be cumbersome and, furthermore, specific movements where...

This work presents the Transition-Aware Human Activity Recognition (TAHAR) system architecture for the recognition of physical activities using smartphones. It targets real-time classification with a collection of inertial sensors while addressing issues regarding the occurrence of transitions between activities and unknown activities to the learni...

A new formulation of the central ideas of Boden's well-established theory on combinational, exploratory and transformational creativity is presented. This new formulation, based on the idea of conceptual space, redefines some terms and includes several types of concept properties (appropriateness and relevance), whose relationship facilitates the c...

Parkinson's disease (PD) is the second most common neuro‐ degenerative disorder. First appreciable symptoms in PD are those re‐ lated to an altered movement control. Current PD treatments temporally revert the symptoms, but they do not prevent disease's progression. At the beginning of the treatment, the antiparkinsonian effect of the medi‐ cation...

Identification of activities of daily living is essential in order to evaluate the quality of life both in the elderly and patients with mobility problems. Posture transitions (PT) are one of the most mechanically demanding activities in daily life and, thus, they can lead to falls in patients with mobility problems. This paper deals with PT recogn...

Patients with severe idiopathic Parkinson's disease experience motor fluctuations, which are often difficult to control. Accurate mapping of such motor fluctuations could help improve patients' treatment. The objective of the study was to focus on developing and validating an automatic detector of motor fluctuations. The device is small, wearable,...

Freezing of Gait (FoG) is one of the most disabling symptoms in Parkinson's disease (PD). Current algorithms to detect FoG are based on wearable inertial systems which relies on the frequency response given by the inertial signal. However, these algorithms have only been evaluated under laboratory conditions causing that, in real life, they present...

This paper presents REMPARK system, a novel approach to deal with Parkinson's Disease (PD). REMPARK system comprises two closed loops of actuation onto PD. The first loop consists in a wearable system that, based on a belt-worn movement sensor, detects movement alterations that activate an auditory cueing system controlled by a smartphone in order...

Parkinson's disease (PD) is a neurodegenerative disease that predominantly alters patients' motor performance. Reduced step length and inability of step are important symptoms associated with PD. Assessing patients' motor state monitoring step length helps to detect periods in which patients suffer lack of medication effect. Evaluate the adaption o...

Freezing of Gait (FoG) is one of the most disturbing symptoms in Parkinson’s disease (PD). Current algorithms that detect this symptom depend on frequency features extracted from wearable systems. These algorithms have only been eval-uated under laboratory conditions and, in real life, they might present false posi-tives, reducing the reliability o...

Postural Transitions (PTs) are transitory movements that describe the change of state from one static posture to another. In several Human Activity Recognition (HAR) systems, these transitions cannot be disregarded due to their noticeable incidence with respect to the duration of other Basic Activities (BAs). In this work, we propose an online smar...

This paper presents two approaches on detecting tremor in patients with Parkinson's Disease by means of a wrist-worn accelerometer. Both approaches are evaluated in terms of specificity and sensitivity as well as their applicability for a real-time implementation. One approach is solely based on the frequency distribution of a windowed time series,...

Objectives Current FoG detection algorithms depend on movement frequencies and, thus, false positives could appear during daily life of patients. The aim of this study is to analyse the contextualization of FoG detection based on a waist inertial sensor by including a posture detection algorithm previously validated. Methods 20 PD patients (mea...

In this paper, a new formulation of the central ideas of the well-established theory of Boden about creativity is presented. This new formulation redefines some terms and reviews the formal mechanisms of exploratory and transformational creativity. The presented approach is based on the conceptual space proposed by Boden and formalized by other aut...

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...

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...

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 propert...

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,...

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 propert...

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 propert...

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 transiti...

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,...

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 detecti...

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/...

Gait Recognition is a biometric application that aims to identify a person by analyzing his/her gait. Common methods for gait recognition rely on supervised machine learning techniques and step detection methods. However, the latter has been showed to provide poor performances in ambulatory conditions [4]. In this paper, a Granular Computing approa...

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 wh...

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...

Gait Recognition is a biometric application that aims to identify a person by analyzing his/her gait. It is based on the fact that people often feel that they can identify a familiar person from afar simply by recognizing the way the person walks. In this work, a qualitative approach based on Granular computing paradigm is proposed. This paradigm i...

This paper presents a novel health monitoring system for Parkinson’s disease (pd ) patients called help (Home-based Empowered Living for Parkinson’s disease patients). The help system has been specifically designed and implemented as a health monitoring system in order to optimize treatment and improve quality of life of people with Parkinson’s. Th...

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 sta...

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 t...

In this work we compare the performance of some standard technical indicators with an interval technical indicator, the moving interval (MI), for time series forecasting. MI has the advantage of taking into account the variability of data in the range considered and not only the average, like standard indicators do. However, the use of intervals as...

In this paper we introduce the use of interval variables in classification problems of time series signals. By introducing the concept of interval kernel as a similarity measure among intervals, modifications for some well-known feature selection methods are developed in order to apply these methods to select the most relevant interval variables. A...

This paper presents an algorithm for the automatic estimation of spatio temporal gait properties from signals provided by inertial body sensors. The approach is based on time series analysis. Here, a minimum number of body sensor devices is used, which imposes limitations for the automatic extraction of relevant properties of the gait like step len...

In this paper a new forecasting methodology to be used on time series prediction is introduced. The considered nonlinear method is based on support vector machines (SVM) using an interval kernel. An extended intersection kernel is introduced to discriminate between disjoint intervals in reference to the existing distance among them. The model prese...

This paper introduces a new approach to enhance learning in adjustment processes by using a support vector machine (SVM) algorithm as discriminant function jointly with an action generator module. The method trains a SVM with state-action patterns and uses trained SVM to select an appropriate action given a certain state in order to reach the targe...