Alzheimer Disease Diagnosis based on Automatic Spontaneous Speech Analysis

Alzheimer’s disease (AD) is the most prevalent form of progressive degenerative dementia and it has a high socio-economic impact in Western countries, therefore is one of the most active research areas today. Its diagnosis is sometimes made by excluding other dementias, and definitive confirmation must be done trough a post-mortem study of the brain tissue of the patient. The purpose of this paper is to contribute to improvement of early diagnosis of AD and its degree of severity, from an automatic analysis performed by non-invasive intelligent methods. The methods selected in this case are Automatic Spontaneous Speech Analysis (ASSA) and Emotional Temperature (ET), that have the great advantage of being non invasive, low cost and without any side effects

Feature selection for automatic analysis of emotional response based on nonlinear speech modeling suitable for diagnosis of Alzheimer׳s disease

Alzheimer׳s disease (AD) is the most common type of dementia among the elderly. This work is part of a larger study that aims to identify novel technologies and biomarkers or features for the early detection of AD and its degree of severity. The diagnosis is made by analyzing several biomarkers and conducting a variety of tests (although only a post-mortem examination of the patients’ brain tissue is considered to provide definitive confirmation). Non-invasive intelligent diagnosis techniques would be a very valuable diagnostic aid. This paper concerns the Automatic Analysis of Emotional Response (AAER) in spontaneous speech based on classical and new emotional speech features: Emotional Temperature (ET) and fractal dimension (FD). This is a pre-clinical study aiming to validate tests and biomarkers for future diagnostic use. The method has the great advantage of being non-invasive, low cost, and without any side effects. The AAER shows very promising results for the definition of features useful in the early diagnosis of AD

Hydration and cooling in elite athletes: relationship with performance, body mass loss and body temperatures during the Doha 2019 IAAF World Athletics Championships

Purpose: To characterise hydration, cooling, body mass loss, and core (Tcore) and skin (Tsk) temperatures during World Athletics Championships in hot-humid conditions. Methods: Marathon and race-walk (20 km and 50 km) athletes (n=83, 36 women) completed a pre-race questionnaire. Pre-race and post-race body weight (n=74), Tcore (n=56) and Tsk (n=49; thermography) were measured. Results: Most athletes (93%) had a pre-planned drinking strategy (electrolytes (83%), carbohydrates (81%)) while ice slurry was less common (11%; p<0.001). More men than women relied on electrolytes and carbohydrates (91%–93% vs 67%–72%, p≤0.029). Drinking strategies were based on personal experience (91%) rather than external sources (p<0.001). Most athletes (80%) planned pre-cooling (ice vests (53%), cold towels (45%), neck collars (21%) and ice slurry (21%)) and/or midcooling (93%; head/face dousing (65%) and cold water ingestion (52%)). Menthol usage was negligible (1%–2%). Pre-race Tcore was lower in athletes using ice vests (37.5°C±0.4°C vs 37.8°C±0.3°C, p=0.024). Tcore (pre-race 37.7°C±0.3°C, post-race 39.6°C±0.6°C) was independent of event, ranking or performance (p≥0.225). Pre-race Tsk was correlated with faster race completion (r=0.32, p=0.046) and was higher in non-finishers (did not finish (DNF); 33.8°C±0.9°C vs 32.6°C±1.4°C, p=0.017). Body mass loss was higher in men than women (−2.8±1.5% vs −1.3±1.6%, p<0.001), although not associated with performance. Conclusion: Most athletes’ hydration strategies were pre-planned based on personal experience. Ice vests were the most adopted pre-cooling strategy and the only one minimising Tcore, suggesting that event organisers should be cognisant of logistics (ie, freezers). Dehydration was moderate and unrelated to performance. Pre-race Tsk was related to performance and DNF, suggesting that Tsk modulation should be incorporated into pre-race strategies

Hydration and cooling in elite athletes: relationship with performance, body mass loss and body temperatures during the Doha 2019 IAAF World Athletics Championships.

PURPOSE: To characterise hydration, cooling, body mass loss, and core (Tcore) and skin (Tsk) temperatures during World Athletics Championships in hot-humid conditions. METHODS: Marathon and race-walk (20 km and 50 km) athletes (n=83, 36 women) completed a pre-race questionnaire. Pre-race and post-race body weight (n=74), Tcore (n=56) and Tsk (n=49; thermography) were measured. RESULTS: Most athletes (93%) had a pre-planned drinking strategy (electrolytes (83%), carbohydrates (81%)) while ice slurry was less common (11%; p<0.001). More men than women relied on electrolytes and carbohydrates (91%-93% vs 67%-72%, p≤0.029). Drinking strategies were based on personal experience (91%) rather than external sources (p<0.001). Most athletes (80%) planned pre-cooling (ice vests (53%), cold towels (45%), neck collars (21%) and ice slurry (21%)) and/or mid-cooling (93%; head/face dousing (65%) and cold water ingestion (52%)). Menthol usage was negligible (1%-2%). Pre-race Tcore was lower in athletes using ice vests (37.5°C±0.4°C vs 37.8°C±0.3°C, p=0.024). Tcore (pre-race 37.7°C±0.3°C, post-race 39.6°C±0.6°C) was independent of event, ranking or performance (p≥0.225). Pre-race Tsk was correlated with faster race completion (r=0.32, p=0.046) and was higher in non-finishers (did not finish (DNF); 33.8°C±0.9°C vs 32.6°C±1.4°C, p=0.017). Body mass loss was higher in men than women (-2.8±1.5% vs -1.3±1.6%, p<0.001), although not associated with performance. CONCLUSION: Most athletes' hydration strategies were pre-planned based on personal experience. Ice vests were the most adopted pre-cooling strategy and the only one minimising Tcore, suggesting that event organisers should be cognisant of logistics (ie, freezers). Dehydration was moderate and unrelated to performance. Pre-race Tsk was related to performance and DNF, suggesting that Tsk modulation should be incorporated into pre-race strategies

TweetLID : a benchmark for tweet language identification

Language identification, as the task of determining the language a given text is written in, has progressed substantially in recent decades. However, three main issues remain still unresolved: (1) distinction of similar languages, (2) detection of multilingualism in a single document, and (3) identifying the language of short texts. In this paper, we describe our work on the development of a benchmark to encourage further research in these three directions, set forth an evaluation framework suitable for the task, and make a dataset of annotated tweets publicly available for research purposes. We also describe the shared task we organized to validate and assess the evaluation framework and dataset with systems submitted by seven different participants, and analyze the performance of these systems. The evaluation of the results submitted by the participants of the shared task helped us shed some light on the shortcomings of state-of-the-art language identification systems, and gives insight into the extent to which the brevity, multilingualism, and language similarity found in texts exacerbate the performance of language identifiers. Our dataset with nearly 35,000 tweets and the evaluation framework provide researchers and practitioners with suitable resources to further study the aforementioned issues on language identification within a common setting that enables to compare results with one another

DECISION TREE-BASED CONTEXT DEPENDENT SUBLEXICAL UNITS FOR CONTINUOUS SPEECH RECOGNITION OF BASQUE

This paper presents a new methodology, based on the classical decision trees, to get a suitable set of context dependent sublexical units for Basque Continuous Speech Recognition (CSR). The original method proposed by Bahl [1] was applied as the benchmark. Then two new features were added: a data massaging to emphasise the data and a fast and efficient Growing and Pruning algorithm for DT construction. In addition, the use of the new context dependent units to build word models was addressed. The benchmark Bahl approach gave recognition rates clearly outperforming those of context independent phone-like units. Finally the new methodology improves over the benchmark DT approach

Effects of amine molecular structure on carbon nanotubes functionalization

Three amines with different molecular structure, triethylenetetramine (TETA) and two polyetheramines (Jeffamine D-230 and Jeffamine T-403) were employed to functionalize multi-walled carbon nanotubes (MWCNT) previously oxidized by acid treatment. The functionalized MWCNT were characterized by Fourier transform infrared spectroscopy (FT-IR), Raman spectroscopy, UV-vis spectroscopy and the surface modification was investigated by field emission scanning electron microscopy (FE-SEM). Thermogravimetric analysis (TGA) was employed to quantify the amount of amine groups anchored to MWCNTs. The results have shown that the efficiency of amine functionalization is in the order TETA > D-230 > T-403, thus showing that amine chemical structure and molecular weight are important parameters on functionalization of carbon nanotubes. Copyright © 2009 American Scientific Publishers.Fil: Jimeno, A. Universidad del País Vasco; EspañaFil: Goyanes, Silvia Nair. Universidad de Buenos Aires; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Física de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Física de Buenos Aires; ArgentinaFil: Ezeiza, A. Universidad del País Vasco; EspañaFil: Kortaberria, G. Universidad del País Vasco; EspañaFil: Mondragon Iñaki,. Universidad del País Vasco; EspañaFil: Corcuera, M A,. Universidad del País Vasco; Españ