Cross-dataset evaluation of wearable fall detection systems using data from real falls and long-term monitoring of daily life

The evaluation of fall detection systems based on wearables is controversial as most studies in the literature benchmark their proposals against falls that are simulated by experimental subjects under unrealistic laboratory conditions. In order to systematically investigate the suitability of this procedure, this paper evaluates a wide set of artificial intelligence algorithms used for fall detection, when trained with a large number of datasets containing acceleration samples captured during the emulation of falls and ordinary movements and then tested with the signals of both actual falls and long-term traces collected from the constant monitoring of users during their daily routines. The results, based on a large number of repositories, show a remarkable degradation in all performance metrics (sensitivity, specificity and false alarm hourly rate) with respect to the typical case in which the detectors are tested with the same types of laboratory movements for which they were trained.Funding for open access charge: Universidad de Málaga / CBU

UMATUG: A dataset of inertial signals of older and young adults using a gerontologic simulator collected during instrumented Timed Up and Go (iTUG) tests

Timed Up and Go (TUG) test is one of the most popular clinical tools aimed at the assessment of functional mobility and fall risk in older adults. The automation of the analysis of TUG movements is of great medical interest not only to speed up the test but also to maximize the information inferred from the subjects under study. In this context, this article describes a dataset collected from a cohort of 69 experimental subjects (including 30 adults over 60 years), during the execution of several repetitions of the TUG test. In particular, the dataset includes the measurements gath- ered with four wearables devices embedding four sensors (accelerometer, gyroscope magnetometer and barometer) located on four body locations (waist, wrist, ankle and chest). As a particularity, the dataset also includes the same measurements recorded when the young subjects repeat the test while wearing a commercial geriatric simulator, consisting of a set of weighted vests and other elements intended to replicate the limitations caused by aging. Thus, the generated dataset also enables the investigation into the potential of such tools to emulate the actual dynamics of older individuals.Funding for open access charge: Partial funding for open access charge: Universidad de Málaga / CBUA This research was funded by the Spanish Ministry of Science, Innovation, and Universities ( MCIN/AEI/10.13039/50110 0 011033 ) and NextGenerationEU/PRTR Funds under grant TED2021- 130456B-I00, by Universidad de Málaga, Campus de Excelencia Internacional Andalucia Tech (grant B4-2023-12) and DIANA PAIDI research group

Automatic recording and processing of saccadic electrooculograms.

Se reporta el desarrollo de un dispositivo de diseño propio para la captación de registros electrooculográficos, la identificación de sácadas inducidas y su procesado para la obtención de biomarcadores de interés médico.This work presents the development of a technology that processes human eye movement records in a fully automatic way. Since it is part of a collaboration with the Center for Rehabilitation and Research of Hereditary Ataxias (CIRAH) of Cuba, we focus on records of subjects suffering Spinocerebellar Ataxia type 2 (SCA2). Our research has two complementary objectives: (i) design a fully automatic method to extract the relevant medical data from saccadic eye movement recordings; (ii) design and testing a low-cost device to record eye movements for clinical purposes. To accomplish the first goal, we have defined a processing pipeline which comprises the following blocks: filtering, differentiation, segmentation and biomarkers extraction.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. Junta de Andalucía. Proyecto de Cooperación Universitaria 2020CU01

Non spontaneous saccadic movements identification in clinical electrooculography using machine learning

In this paper we evaluate the use of the machine learning algorithms Support Vector Machines, K-Nearest Neighbors, CART decision trees and Naive Bayes to identify non spontaneous saccades in clinical electrooculography tests. Our approach tries to solve problems like the use of manually established thresholds present in classical methods like identification by velocity threshold (I-VT) or identification by dispersion threshold (I-DT). We propose a modification to an adaptive threshold estimation algorithm for detecting signal impulses without the need of any user input. Also, a set of features were selected to take advantage of intrinsic characteristics of clinical electrooculography tests. The models were evaluated with signals recorded to subjects affected by Spinocerebellar Ataxia type 2 (SCA2). Results obtained by the algorithm shows accuracies over 97%, recalls over 97% and precisions over 91% for the four models evaluated.Universidad de Málaga, Campus de excelencia de Andalucía Tec

Architecture for Neurological Coordination Tests Implementation

DOI: 10.1007/978-3-319-59147-6_3This paper proposes a generic architecture for devising interactive neurological assessment tests, aimed at being implemented on a touchscreen device. The objective is both to provide a set of software primitives that allow the modular implementation of tests, and to contribute to the standardization of test protocols. Although our original goal was the application of machine learning methods to the analysis of test data, it turned out that the construction of such framework was a pre-requisite to collect enough data with the required levels of accuracy and reproducibility. In the proposed architecture, tests are defined by a set of stimuli, responses, feedback information, and execution control procedures. The presented definition has allowed for the implementation of a particular test, the Finger-Nose-Finger, that will allow the exploitation of data with intelligent techniques.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Cluster Analysis of Finger-to-nose Test for Spinocerebellar Ataxia Assessment

El test Finger-to-nose test (FNT) es una evaluación neurológica para estudiar la coordinación. Se presenta una metodología de análisis de datos de FNT, que permite evaluar la evolución del estado de enfermos de Ataxia Espinocerebral de tipo 2 (SCA2), mediante técnicas de aprendizaje computacional.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Diagnóstico de la cobertura de la red wifi en la Universidad de Holguín

En el presente artículo se centra en el analisis, diagnóstico y posible optimización a la red de datos de las dos universidades en donde se realizaron las mediciones de la Wi-Fi, el cual tuvo dos fases: la localización de la red y trazado de los edificios a escala con el objetivo de plantear una mejora para la red. Estas mejoras deben realizarse para la solución de algunos problemas detectados en la mayoría de las zonas de la universidad como deficiencia en el alcance de la Wi-Fi en los edificios. Este problema se detectó en la investigación realizada utilizando un analizador de redes inalámbricas. Los resultados obtenidos fueron que en los dos últimos salones de cada edificio no alcanza la señal de ningún router así como en algunos otros puntos de la misma, la señal de la Wi-Fi es deficiente. Según los resultados obtenidos, una forma de solucionar estos problemas sería la implementación de puntos de acceso inalámbricos en las áreas donde la señal llega deficiente o de otra manera puede ser la reubicación de los dispositivos para que esta señal pueda ser más optima y llegue a las zonas donde su cobertura es muy deficiente y con esto obtendríamos la optimización de la Wi-Fi

Rich oleocanthal and oleacein extra virgin olive oil and inflammatory and antioxidant status in people with obesity and prediabetes. The APRIL study: A randomised, controlled crossover study

Background: Oleocanthal and oleacein are olive oil phenolic compounds with well known anti inflammatory and anti-oxidant properties. The main evidence, however, is provided by experimental studies. Few human studies have examined the health benefits of olive oils rich in these biophenols. Our aim was to assess the health properties of rich oleocanthal and oleacein extra virgin olive oil (EVOO), compared to those of common olive oil (OO), in people with prediabetes and obesity. Methods: Randomised, double-blind, crossover trial done in people aged 40e65 years with obesity (BMI 30e40 kg/m2 ) and prediabetes (HbA1c 5.7e6.4%). The intervention consisted in substituting for 1 month the oil used for food, both raw and cooked, by EVOO or OO. No changes in diet or physical activity were recommended. The primary outcome was the inflammatory status. Secondary outcomes were the oxidative status, body weight, glucose handling and lipid profile. An ANCOVA model adjusted for age, sex and treatment administration sequence was used for the statistical analysis. Results: A total of 91 patients were enrolled (33 men and 58 women) and finished the trial. A decrease in interferon-g was observed after EVOO treatment, reaching inter-treatment differences (P ¼ 0.041). Total antioxidant status increased and lipid and organic peroxides decreased after EVOO treatment, the changes reaching significance compared to OO treatment (P < 0.05). Decreases in weight, BMI and blood glucose (p < 0.05) were found after treatment with EVOO and not with OO. Conclusions: Treatment with EVOO rich in oleocanthal and oleacein differentially improved oxidative and inflammatory status in people with obesity and prediabetes.Funding for open access charge: Universidad de Málaga/CBU

Rich oleocanthal and oleacein extra virgin olive oil and inflammatory and antioxidant status in people with obesity and prediabetes. The APRIL study: A randomised, controlled crossover study

10 Páginas.-- 2 Figuras.-- 6 TablasOleocanthal and oleacein are olive oil phenolic compounds with well known anti-inflammatory and anti-oxidant properties. The main evidence, however, is provided by experimental studies. Few human studies have examined the health benefits of olive oils rich in these biophenols. Our aim was to assess the health properties of rich oleocanthal and oleacein extra virgin olive oil (EVOO), compared to those of common olive oil (OO), in people with prediabetes and obesity.his study was funded by Consejeria de Salud y Familias, Junta de Andalucia (PI-0247-2016) and Instituto de Salud Carlos III, Ministerio de Sanidad, Gobierno de España, (PI17/01004). FJBS, GRM and REB belong to the regional “Nicolás Monardes” research program from Consejería de Salud, Junta de Andalucía, Spain (C-0070-2012, C-0060-2012 and C-0030-2016). IRG holds a Río Hortega contract from Instituto de Salud Carlos III (CM20/00225) cofunded by European Social Fund 2014–2020, EU “The ESF invests in your future”. CIBERDEM is an initiative of the Instituto de Salud Carlos III, EU. Funding for Open Access charge: Universidad de Málaga/CBUA.Peer reviewe

Efficacy of naloxegol on symptoms and quality of life related to opioid-induced constipation in patients with cancer: a 3-month follow-up analysis

Objectives: Opioid-induced constipation (OIC) can affect up to 63% of all patients with cancer. The objectives of this study were to assess quality of life as well as efficacy and safety of naloxegol, in patients with cancer with OIC. Methods: An observational study was made of a cohort of patients with cancer and with OIC exhibiting an inadequate response to laxatives and treated with naloxegol. The sample consisted of adult outpatients with a Karnofsky performance status score ≥50. The Patient Assessment of Constipation Quality of Life Questionnaire (PAC-QOL) and the Patient Assessment of Constipation Symptoms (PAC-SYM) were applied for 3 months. Results: A total of 126 patients (58.2% males) with a mean age of 61.3 years (range 34-89) were included. Clinically relevant improvements (>0.5 points) were recorded in the PAC-QOL and PAC-SYM questionnaires (p<0.0001) from 15 days of treatment. The number of days a week with complete spontaneous bowel movements increased significantly (p<0.0001) from 2.4 to 4.6 on day 15, 4.7 after 1 month and 5 after 3 months. Pain control significantly improved (p<0.0001) during follow-up. A total of 13.5% of the patients (17/126) presented some gastrointestinal adverse reaction, mostly of mild (62.5%) or moderate intensity (25%). Conclusions: Clinically relevant improvements in OIC-related quality of life, number of bowel movements and constipation-related symptoms were recorded as early as after 15 days of treatment with naloxegol in patients with cancer and OIC, with a good safety profile