La articulación entre lo cuantitativo y lo cualitativo: de las grandes encuestas a la recogida de datos intensiva

Son casi innumerables las reflexiones que se han hecho en el campo de la metodología de las ciencias sociales, sobre la dicotomía, real o inexistente, entre las perspectivas de análisis cuantitativo y cualitativo, mientras que han sido menos abundantes los trabajos teóricos, aunque van siendo más abundantes los empíricos, que han tratado de compatibilizar y/o complementar ambas perspectivas. En muchos casos los trabajos cualitativos cubren solamente los primeros pasos de la investigación social, como fases previas o exploratorias de la misma, para prolongarla después con una metodología más cuantitativa y extensiva como la inherente a las encuestas, al análisis de datos, multivariados, causales u otros. Este artículo presenta un ejemplo concreto del planteamiento inverso. Se parte de una gran encuesta con el objetivo de estructurar la realidad objeto de estudio, para posteriormente aplicar técnicas cualitativas, concretamente grupos de discusión

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

Contact characterization between a cam and a crowned roller follower

In the higher pairs of a mechanism, like the one existing between a cam and roller follower, it is common to localize the maximum deformations, the maximum contact pressures and that appears the surface fatigue failure due to the relative motion between the cam and the roller. The formulations that characterized the contact are based in Hertz elastic contact theory. In this paper the contact between a cam and a crowned roller is studied applying the formulation for elliptical point contact proposed by Johnson. The contact ellipse obtained experimentally is presented to validate the elliptical point contact. The comparison of the width of the axes of the contact ellipse obtained experimentally and by the formulation presents the same level of errors than more sophisticated experimental methods.Postprint (published version

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

Postprint (published version

Aprenentatge basat en projectes en l’àrea d’electrònica per a Enginyers Biomèdics

Projecte: 2014PID-UB/076Actualment els estudiants d’Enginyeria Biomèdica realitzen pràctiques típiques d’electrònica en els seus estudis, similars a les que es realitzen en altres ensenyaments. Segons l’opinió dels estudiants aquest tipus de pràctiques són molt poc motivadores doncs, no veuen l’aplicació directa als seus estudis. La proposta és aplicar la metodologia basada en projectes per a la realització de les pràctiques en el grau d’Enginyeria Biomèdica en les dues assignatures: Electrònica Aplicada i "Biomedical Instruments and Equipment". D’aquesta forma els alumnes hauran de realitzar un projecte d’electrònica aplicat a l’Enginyeria Biomèdica. Els alumnes a més d’estar més motivats adquiriran competències en la realització d’un projecte, és a dir, mitjançant l’aprenentatge basat en projectes els estudiants podran adquirir competències professionals que són difícils de treballar amb metodologies convencionals. Algunes d’aquestes competències són les propostes per la UB com a competències transversals i els seran molt útils en el seu Treball Fi de Grau i en el seu futur desenvolupament professional

Caveolin-1 Modulates Mechanotransduction Responses to Substrate Stiffness through Actin-Dependent Control of YAP

The transcriptional regulator YAP orchestrates many cellular functions, including tissue homeostasis, organ growth control, and tumorigenesis. Mechanical stimuli are a key input to YAP activity, but the mechanisms controlling this regulation remain largely uncharacterized. We show that CAV1 positively modulates the YAP mechanoresponse to substrate stiffness through actin-cytoskeleton-dependent and Hippo-kinase-independent mechanisms. RHO activity is necessary, but not sufficient, for CAV1-dependent mechanoregulation of YAP activity. Systematic quantitative interactomic studies and image-based small interfering RNA (siRNA) screens provide evidence that this actin-dependent regulation is determined by YAP interaction with the 14-3-3 protein YWHAH. Constitutive YAP activation rescued phenotypes associated with CAV1 loss, including defective extracellular matrix (ECM) remodeling. CAV1-mediated control of YAP activity was validated in vivo in a model of pancreatitis-driven acinar-to-ductal metaplasia. We propose that this CAV1-YAP mechanotransduction system controls a significant share of cell programs linked to these two pivotal regulators, with potentially broad physiological and pathological implications. Moreno-Vicente et al. report that CAV1, a key component of PM mechanosensing caveolae, mediates adaptation to ECM rigidity by modulating YAP activity through the control of actin dynamics and phosphorylation-dependent interaction of YAP with the 14-3-3-domain protein YWHAH. Cav1-dependent YAP regulation drives two pathophysiological processes: ECM remodeling and pancreatic ADM. © 2018 The Author