Enhancing FoG detection by means of postural context using a waist accelerometer

Postprint (published version

Home detection of freezing of gait using Support Vector Machines through a single waist-worn triaxial accelerometer

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 living (ADL) and the PD symptoms experienced by patients throughout the day could provide a more accurate and objective evaluation of FoG in order to better understand the evolution of the disease and allow for a more informed decision-making process in making adjustments to the patient’s treatment plan. This paper presents a new algorithm to detect FoG with a machine learning approach based on Support Vector Machines (SVM) and a single tri-axial accelerometer worn at the waist. The method is evaluated through the acceleration signals in an outpatient setting gathered from 21 PD patients at their home and evaluated under two different conditions: first, a generic model is tested by using a leave-one-out approach and, second, a personalised model that also uses part of the dataset from each patient. Results show a significant improvement in the accuracy of the personalised model compared to the generic model, showing enhancement in the specificity and sensitivity geometric mean (GM) of 7.2%. Furthermore, the SVM approach adopted has been compared to the most comprehensive FoG detection method currently in use (referred to as MBFA in this paper). Results of our novel generic method provide an enhancement of 11.2% in the GM compared to the MBFA generic model and, in the case of the personalised model, a 10% of improvement with respect to the MBFA personalised model. Thus, our results show that a machine learning approach can be used to monitor FoG during the daily life of PD patients and, furthermore, personalised models for FoG detection can be used to improve monitoring accuracy.Peer ReviewedPostprint (published version

A kinematic sensor and algorithm to detect motor fluctuations in Parkinson disease: Validation study under real conditions of use

Postprint (published version

Posture transition identification on PD patients through a SVM-based technique and a single waist-worn accelerometer

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 recognition in Parkinson’s Disease (PD) patients by means of a triaxial accelerometer situated between the anterior and the left lateral part of the waist. Since sensor’s orientation is susceptible to change during long monitoring periods, a hierarchical structure of classifiers is proposed in order to identify PT while allowing such orientation changes. Results are presented based on signals obtained from 20 PD patients and 67 healthy people who wore an inertial sensor on different positions among the anterior and the left lateral part of the waist. The algorithm has been compared to a previous approach in which only the anterior-lateral location was analyzed improving the sensitivity while preserving specificity. Moreover, different supervised machine l earning techniques have been evaluated in distinguishing PT. Results show that the location of the sensor slightly affects method’s performance and, furthermore, PD motor state does not alter its accuracy.Peer ReviewedPostprint (author’s final draft

Determining the optimal features in freezing of gait detection through a single waist accelerometer in home environments

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 dependence on patients’ and caregivers’ judgment. Several authors have analyzed the usage of MEMS inertial systems to detect FoG with the aim of objectively evaluating it. So far, specific methods based on accelerometer's frequency response has been employed in many works; nonetheless, since they have been developed and tested in laboratory conditions, their performance is commonly poor when being used at patients’ home. Therefore, this work proposes a new set of features that aims to detect FoG in real environments by using accelerometers. This set of features is compared with three previously reported approaches to detect FoG. The different feature sets are trained by means of several machine learning classifiers; furthermore, different window sizes are also evaluated. In addition, a greedy subset selection process is performed to reduce the computational load of the method and to enable a real-time implementation. Results show that the proposed method detects FoG at patients’ home with 91.7% and 87.4% of sensitivity and specificity, respectively, enhancing the results of former methods between a 5% and 11% and providing a more balanced rate of true positives and true negatives.Peer ReviewedPostprint (published version

Basketball activity recognition using wearable inertial measurement units

The analysis and evaluation of human movement is a growing research area within the field of sports monitoring. This analysis can help support the enhancement of an athlete's performance, the prediction of injuries or the optimization of training programs. Although camera-based techniques are often used to evaluate human movements, not all movements of interest can be analyzed or distinguished effectively with computer vision only. Wearable inertial systems are a promising technology to address this limitation. This paper presents a new wearable sensing system to record human movements for sports monitoring. A new paradigm is presented with the purpose of monitoring basketball players with multiple inertial measurement units. A data collection plan has been designed and implemented, and experimental results show the potential of the system in basketball activity recognition.Peer ReviewedPostprint (author's final draft

El Pino Canario: Un superviviente entre volcanes

El pino canario constituye una singularidad dentro del conjunto de pinos, ya que presenta una amplia gama de estrategias que permiten su persistencia y que han sido adquiridas a lo largo de su evolución en un ambiente volcánico. Todos los pinos son especies que presentan adaptaciones frente al fuego y de centran en dos estrategias: 1) una eficiente dispersión posincendio basada en una gran capacidad dispersiva y en la presencia de piñas serótinas; y 2) la resistencia individual, con cortezas gruesas que les permiten alcanzar gran longevidad

New interfacial microtubule inhibitors of marine origin, PM050489/PM060184, with potent antitumor activity and a distinct mechanism

We have investigated the target and mechanism of action of a new family of cytotoxic small molecules of marine origin. PM050489 and its dechlorinated analogue PM060184 inhibit the growth of relevant cancer cell lines at subnanomolar concentrations. We found that they are highly potent microtubule inhibitors that impair mitosis with a distinct molecular mechanism. They bind with nanomolar affinity to unassembled αβ-tubulin dimers, and PM050489 binding is inhibited by known Vinca domain ligands. NMR TR-NOESY data indicated that a hydroxyl-containing analogue, PM060327, binds in an extended conformation, and STD results define its binding epitopes. Distinctly from vinblastine, these ligands only weakly induce tubulin self-association, in a manner more reminiscent of isohomohalichondrin B than of eribulin. PM050489, possibly acting like a hinge at the association interface between tubulin heterodimers, reshapes Mg2+-induced 42 S tubulin double rings into smaller 19 S single rings made of 7 ± 1 αβ-tubulin dimers. PM060184-resistant mutants of Aspergillus nidulans map to β-tubulin Asn100, suggesting a new binding site different from that of vinblastine at the associating β-tubulin end. Inhibition of assembly dynamics by a few ligand molecules at the microtubule plus end would explain the antitumor activity of these compounds, of which PM060184 is undergoing clinical trials.We wish to thank J. M. Fernandez Sousa (PharmaMar) for useful discussions and support, E. Hamel (NCI) for providing eribulin, C. Scazzocchio and G. Diallinas for useful advice on mutant screening, H. N. Arst for advice on mutant screening and mapping and for kindly providing strains MAD3688 and MAD4655, T. J. Fitzgerald (A&M University) for MTC and C. Alfonso (CIB) for AUC analysis. We also thank Rhône Poulenc Rorer Aventis for supplying docetaxel and Matadero Municipal Vicente de Lucas de Segovia for providing the calf brains for tubulin purification. B.P. had a contract from Comunidad de Madrid, and A.C. had a Ramon y Cajal contract, J.R.-S. had a fellowship from “Programa de Cooperación Científica entre el Ministerio de Ciencia, Tecnologías y Medio Ambiente de la República de Cuba (CITMA) y el CSIC”. This work was supported by grants BIO2010-16351 (J.F.D.), BQU2009-08536 (J.J.-B.), CAM S2010/BMD-2457 (J.F.D.), CAM S2010/BMD-2353 (J.J.-B., J.M.A.), IPT-2011-0752-900000 and BIO2012-30965 (M.A.P.), BFU2011-23416 (J.M.A.) and PharmaMar-CSIC contracts

Recensiones [Revista de Historia Económica Año XIV Primavera-Verano 1996 n. 2 pp. 477-528]

Editada en la Fundación Empresa PúblicaBeatriz Cárceles de Gea. Fraude y administración fiscal en Castilla La Comisión de Millones (1632-1658): Poder fiscal y privilegio jurídico-político (Por Juan Zafra Oteyza).-- Enric Tello. Cervera i la Segarra al segle XVIII. En els origens d`una Catalunya pobra, 1700-1860 (Por Tomás Peris Albentosa).-- Ángela Atienza. Propiedad y Señorío en Aragón. El clero regular entre la expansión y la crisis (1700-1835) (Por José Manuel Latorre Ciria).-- Michel Zylberberg. Une si duouce domination. Les milieux d'affaires français et l`Espagne vers 1780-1808 (Por Joan Caries Maixé Altes).-- Paloma Pastor Rey de Viñas. Historia de la Fábrica de Cristales de San Ildefonso durante la época de la Ilustración (1727-1810) (Por Juan Helguera Quijada).-- Ricardo Robledo Hernández. Economistas y reformadores españoles: La cuestión agraria (1760-1935) (Por Juan Antonio Carmona Pidal).-- Juan Pan Montojo. La bodega del mundo (1800-1936) (Por José Pujol Andréu).-- Moisés Llordén Miñambres. Desarrollo económico y urbano de Gijón en los siglos XIX y XX (Por Carlos Larrinaga Rodríguez).-- Manuel Montero. La California del hierro. Las minas y la modernización económica y social de Vizcaya (Por Antonio Escudero).-- Salvador Cruz Artacho. Caciques y campesinos. Poder político, modernización agraria y conflictividad rural en Granada. 1890-1923 (Por Luis Garrido González).-- Miguel Muñoz Rubio. Renfe (1941-1991). Medio siglo de ferrocarril público (Por Francisco Javier Vidal Olivares).-- Eric Hobsbawn. Historia del siglo XX. 1914-1991 (Por Gabriel Tortella).-- Marjorie Grice-Hutchinson. Ensayos sobre el pensamiento económico en España (Por José Luis García Ruiz).-- Richard N. Langlois y Paul L. Robertson. Firms, Markets and Economic Change. A Dynamic Theory of Business Institutions (Por Jesús M. Valdaliso).-- John Komlos (ed.). Stature, Living Standards, and Economic Development: Essays in Anthropometric History, y John Komlos (ed.). The Biological Standard of Living on Three Continents: Further Explorations in Anthropometric History (Por James Simpson)Publicad

Deep learning for detecting freezing of gait episodes in Parkinson’s disease based on accelerometers

The final publication is available at Springer via https://doi.org/10.1007/978-3-319-59147-6_30Freezing 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 cues and would provide relevant information to neurologists on the disease evolution. This paper presents a method for FOG detection based on deep learning and signal processing techniques. This is, to the best of our knowledge, the first time that FOG detection is addressed with deep learning. The evaluation of the model has been done based on the data from 15 PD patients who manifested FOG. An inertial measurement unit placed at the left side of the waist recorded tri-axial accelerometer, gyroscope and magnetometer signals. Our approach achieved comparable results to the state-of-the-art, reaching validation performances of 88.6% and 78% for sensitivity and specificity respectively.Peer ReviewedPostprint (author's final draft