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Article ; Online: Detecting Bulbar Involvement in Patients with Amyotrophic Lateral Sclerosis Based on Phonatory and Time-Frequency Features.

Tena, Alberto / Clarià, Francesc / Solsona, Francesc / Povedano, Mònica

2022 Volume 22, Issue 3

Abstract: The term "bulbar involvement" is employed in ALS to refer to deterioration of motor neurons within the corticobulbar area of the brainstem, which results in speech and swallowing dysfunctions. One of the primary symptoms is a deterioration of the voice. ... ...

Abstract	The term "bulbar involvement" is employed in ALS to refer to deterioration of motor neurons within the corticobulbar area of the brainstem, which results in speech and swallowing dysfunctions. One of the primary symptoms is a deterioration of the voice. Early detection is crucial for improving the quality of life and lifespan of ALS patients suffering from bulbar involvement. The main objective, and the principal contribution, of this research, was to design a new methodology, based on the phonatory-subsystem and time-frequency characteristics for detecting bulbar involvement automatically. This study focused on providing a set of 50 phonatory-subsystem and time-frequency features to detect this deficiency in males and females through the utterance of the five Spanish vowels. Multivariant Analysis of Variance was then used to select the statistically significant features, and the most common supervised classifications models were analyzed. A set of statistically significant features was obtained for males and females to capture this dysfunction. To date, the accuracy obtained (98.01% for females and 96.10% for males employing a random forest) outperformed the models in the literature. Adding time-frequency features to more classical phonatory-subsystem features increases the prediction capabilities of the machine-learning models for detecting bulbar involvement. Studying men and women separately gives greater success. The proposed method can be deployed in any kind of recording device (i.e., smartphone).
MeSH term(s)	Amyotrophic Lateral Sclerosis/diagnosis ; Deglutition ; Female ; Humans ; Male ; Phonation ; Quality of Life ; Speech
Language	English
Publishing date	2022-02-02
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2052857-7
ISSN	1424-8220 ; 1424-8220
ISSN (online)	1424-8220
ISSN	1424-8220
DOI	10.3390/s22031137
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Voiceprint and machine learning models for early detection of bulbar dysfunction in ALS.

Tena, Alberto / Clarià, Francesc / Solsona, Francesc / Povedano, Mónica

Computer methods and programs in biomedicine

2022 Volume 229, Page(s) 107309

Abstract: Background and objective: Bulbar dysfunction is a term used in amyotrophic lateral sclerosis (ALS). It refers to motor neuron disability in the corticobulbar area of the brainstem which leads to a dysfunction of speech and swallowing. One of the ... ...

Abstract	Background and objective: Bulbar dysfunction is a term used in amyotrophic lateral sclerosis (ALS). It refers to motor neuron disability in the corticobulbar area of the brainstem which leads to a dysfunction of speech and swallowing. One of the earliest symptoms of bulbar dysfunction is voice deterioration characterized by grossly defective articulation, extremely slow laborious speech, marked hypernasality and severe harshness. Recently, research efforts have focused on voice analysis to capture this dysfunction. The main aim of this paper is to provide a new methodology to diagnose this dysfunction automatically at early stages of the disease, earlier than clinicians can do. Methods: The study focused on the creation of a voiceprint consisting of a pattern generated from the quasi-periodic components of a steady portion of the five Spanish vowels and the computation of the five principal and independent components of this pattern. Then, a set of statistically significant features was obtained using multivariate analysis of variance and the outcomes of the most common supervised classification models were obtained. Results: The best model (random forest) obtained an accuracy, sensitivity and specificity of 88.3%, 85.0% and 95.0% respectively when classifying bulbar vs. control participants but the results worsened when classifying bulbar vs. no-bulbar patients (accuracy, sensitivity and specificity of 78.7%, 80.0% and 77.5% respectively for support vector machines). Due to the great uncertainty found in the annotated corpus of the ALS patients without bulbar involvement, we used a safe semi-supervised support vector machine to relabel the ALS participants diagnosed without bulbar involvement as bulbar and no-bulbar. The performance of the results obtained increased, especially when classifying bulbar and no-bulbar patients obtaining an accuracy, sensitivity and specificity of 91.0%, 83.3% and 100.0% respectively for support vector machines. This demonstrates that our model can improve the diagnosis of bulbar dysfunction compared not only with clinicians, but also the methods published to date. Conclusions: The results obtained demonstrate the efficiency and applicability of the methodology presented in this paper. It may lead to the development of a cheap and easy-to-use tool to identify this dysfunction in early stages of the disease and monitor progress.
MeSH term(s)	Humans ; Amyotrophic Lateral Sclerosis/diagnosis ; Speech/physiology ; Voice ; Early Diagnosis
Language	English
Publishing date	2022-12-13
Publishing country	Ireland
Document type	Journal Article
ZDB-ID	632564-6
ISSN	1872-7565 ; 0169-2607
ISSN (online)	1872-7565
ISSN	0169-2607
DOI	10.1016/j.cmpb.2022.107309
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Article ; Online: Nonaqueous Interfacial Polymerization-Derived Polyphosphazene Films for Sieving or Blocking Hydrogen Gas.

Radmanesh, Farzaneh / Tena, Alberto / Sudhölter, Ernst J R / Hempenius, Mark A / Benes, Nieck E

ACS applied polymer materials

2023 Volume 5, Issue 3, Page(s) 1955–1964

Abstract: A series of cyclomatrix polyphosphazene films have been prepared by nonaqueous interfacial polymerization (IP) of small aromatic hydroxyl compounds in a potassium hydroxide dimethylsulfoxide solution and hexachlorocyclotriphosphazene in cyclohexane on ... ...

Abstract	A series of cyclomatrix polyphosphazene films have been prepared by nonaqueous interfacial polymerization (IP) of small aromatic hydroxyl compounds in a potassium hydroxide dimethylsulfoxide solution and hexachlorocyclotriphosphazene in cyclohexane on top of ceramic supports. Via the amount of dissolved potassium hydroxide, the extent of deprotonation of the aromatic hydroxyl compounds can be changed, in turn affecting the molecular structure and permselective properties of the thin polymer networks ranging from hydrogen/oxygen barriers to membranes with persisting hydrogen permselectivities at high temperatures. Barrier films are obtained with a high potassium hydroxide concentration, revealing permeabilities as low as 9.4 × 10
Language	English
Publishing date	2023-02-09
Publishing country	United States
Document type	Journal Article
ISSN	2637-6105
ISSN (online)	2637-6105
DOI	10.1021/acsapm.2c02022
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Automated detection of COVID-19 cough.

Tena, Alberto / Clarià, Francesc / Solsona, Francesc

Biomedical signal processing and control

2021 Volume 71, Page(s) 103175

Abstract: Easy detection of COVID-19 is a challenge. Quick biological tests do not give enough accuracy. Success in the fight against new outbreaks depends not only on the efficiency of the tests used, but also on the cost, time elapsed and the number of tests ... ...

Abstract	Easy detection of COVID-19 is a challenge. Quick biological tests do not give enough accuracy. Success in the fight against new outbreaks depends not only on the efficiency of the tests used, but also on the cost, time elapsed and the number of tests that can be done massively. Our proposal provides a solution to this challenge. The main objective is to design a freely available, quick and efficient methodology for the automatic detection of COVID-19 in raw audio files. Our proposal is based on automated extraction of time-frequency cough features and selection of the more significant ones to be used to diagnose COVID-19 using a supervised machine-learning algorithm. Random Forest has performed better than the other models analysed in this study. An accuracy close to 90% was obtained. This study demonstrates the feasibility of the automatic diagnose of COVID-19 from coughs, and its applicability to detecting new outbreaks.
Language	English
Publishing date	2021-09-13
Publishing country	England
Document type	Journal Article
ZDB-ID	2241886-6
ISSN	1746-8108 ; 1746-8094
ISSN (online)	1746-8108
ISSN	1746-8094
DOI	10.1016/j.bspc.2021.103175
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Article: Detection of Bulbar Involvement in Patients With Amyotrophic Lateral Sclerosis by Machine Learning Voice Analysis: Diagnostic Decision Support Development Study.

Tena, Alberto / Claria, Francec / Solsona, Francesc / Meister, Einar / Povedano, Monica

JMIR medical informatics

2021 Volume 9, Issue 3, Page(s) e21331

Abstract: Background: Bulbar involvement is a term used in amyotrophic lateral sclerosis (ALS) that refers to motor neuron impairment in the corticobulbar area of the brainstem, which produces a dysfunction of speech and swallowing. One of the earliest symptoms ... ...

Abstract	Background: Bulbar involvement is a term used in amyotrophic lateral sclerosis (ALS) that refers to motor neuron impairment in the corticobulbar area of the brainstem, which produces a dysfunction of speech and swallowing. One of the earliest symptoms of bulbar involvement is voice deterioration characterized by grossly defective articulation; extremely slow, laborious speech; marked hypernasality; and severe harshness. Bulbar involvement requires well-timed and carefully coordinated interventions. Therefore, early detection is crucial to improving the quality of life and lengthening the life expectancy of patients with ALS who present with this dysfunction. Recent research efforts have focused on voice analysis to capture bulbar involvement. Objective: The main objective of this paper was (1) to design a methodology for diagnosing bulbar involvement efficiently through the acoustic parameters of uttered vowels in Spanish, and (2) to demonstrate that the performance of the automated diagnosis of bulbar involvement is superior to human diagnosis. Methods: The study focused on the extraction of features from the phonatory subsystem-jitter, shimmer, harmonics-to-noise ratio, and pitch-from the utterance of the five Spanish vowels. Then, we used various supervised classification algorithms, preceded by principal component analysis of the features obtained. Results: To date, support vector machines have performed better (accuracy 95.8%) than the models analyzed in the related work. We also show how the model can improve human diagnosis, which can often misdiagnose bulbar involvement. Conclusions: The results obtained are very encouraging and demonstrate the efficiency and applicability of the automated model presented in this paper. It may be an appropriate tool to help in the diagnosis of ALS by multidisciplinary clinical teams, in particular to improve the diagnosis of bulbar involvement.
Language	English
Publishing date	2021-03-10
Publishing country	Canada
Document type	Journal Article
ZDB-ID	2798261-0
ISSN	2291-9694
ISSN	2291-9694
DOI	10.2196/21331
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Detection of Bulbar Involvement in Patients With Amyotrophic Lateral Sclerosis by Machine Learning Voice Analysis

Tena, Alberto / Claria, Francec / Solsona, Francesc / Meister, Einar / Povedano, Monica

JMIR Medical Informatics, Vol 9, Iss 3, p e

Diagnostic Decision Support Development Study

2021 Volume 21331

Abstract: BackgroundBulbar involvement is a term used in amyotrophic lateral sclerosis (ALS) that refers to motor neuron impairment in the corticobulbar area of the brainstem, which produces a dysfunction of speech and swallowing. One of the earliest symptoms of ... ...

Abstract	BackgroundBulbar involvement is a term used in amyotrophic lateral sclerosis (ALS) that refers to motor neuron impairment in the corticobulbar area of the brainstem, which produces a dysfunction of speech and swallowing. One of the earliest symptoms of bulbar involvement is voice deterioration characterized by grossly defective articulation; extremely slow, laborious speech; marked hypernasality; and severe harshness. Bulbar involvement requires well-timed and carefully coordinated interventions. Therefore, early detection is crucial to improving the quality of life and lengthening the life expectancy of patients with ALS who present with this dysfunction. Recent research efforts have focused on voice analysis to capture bulbar involvement. ObjectiveThe main objective of this paper was (1) to design a methodology for diagnosing bulbar involvement efficiently through the acoustic parameters of uttered vowels in Spanish, and (2) to demonstrate that the performance of the automated diagnosis of bulbar involvement is superior to human diagnosis. MethodsThe study focused on the extraction of features from the phonatory subsystem—jitter, shimmer, harmonics-to-noise ratio, and pitch—from the utterance of the five Spanish vowels. Then, we used various supervised classification algorithms, preceded by principal component analysis of the features obtained. ResultsTo date, support vector machines have performed better (accuracy 95.8%) than the models analyzed in the related work. We also show how the model can improve human diagnosis, which can often misdiagnose bulbar involvement. ConclusionsThe results obtained are very encouraging and demonstrate the efficiency and applicability of the automated model presented in this paper. It may be an appropriate tool to help in the diagnosis of ALS by multidisciplinary clinical teams, in particular to improve the diagnosis of bulbar involvement.
Keywords	Computer applications to medicine. Medical informatics ; R858-859.7
Subject code	006
Language	English
Publishing date	2021-03-01T00:00:00Z
Publisher	JMIR Publications
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: A Machine-Learning Model for Lung Age Forecasting by Analyzing Exhalations.

Pifarré, Marc / Tena, Alberto / Clarià, Francisco / Solsona, Francesc / Vilaplana, Jordi / Benavides, Arnau / Mas, Lluis / Abella, Francesc

Sensors (Basel, Switzerland)

2022 Volume 22, Issue 3

Abstract: Spirometers are important devices for following up patients with respiratory diseases. These are mainly located only at hospitals, with all the disadvantages that this can entail. This limits their use and consequently, the supervision of patients. ... ...

Abstract	Spirometers are important devices for following up patients with respiratory diseases. These are mainly located only at hospitals, with all the disadvantages that this can entail. This limits their use and consequently, the supervision of patients. Research efforts focus on providing digital alternatives to spirometers. Although less accurate, the authors claim they are cheaper and usable by many more people worldwide at any given time and place. In order to further popularize the use of spirometers even more, we are interested in also providing user-friendly lung-capacity metrics instead of the traditional-spirometry ones. The main objective, which is also the main contribution of this research, is to obtain a person's lung age by analyzing the properties of their exhalation by means of a machine-learning method. To perform this study, 188 samples of blowing sounds were used. These were taken from 91 males (48.4%) and 97 females (51.6%) aged between 17 and 67. A total of 42 spirometer and frequency-like features, including gender, were used. Traditional machine-learning algorithms used in voice recognition applied to the most significant features were used. We found that the best classification algorithm was the Quadratic Linear Discriminant algorithm when no distinction was made between gender. By splitting the corpus into age groups of 5 consecutive years, accuracy, sensitivity and specificity of, respectively, 94.69%, 94.45% and 99.45% were found. Features in the audio of users' expiration that allowed them to be classified by their corresponding lung age group of 5 years were successfully detected. Our methodology can become a reliable tool for use with mobile devices to detect lung abnormalities or diseases.
MeSH term(s)	Adolescent ; Adult ; Aged ; Algorithms ; Child, Preschool ; Exhalation ; Female ; Humans ; Lung ; Machine Learning ; Male ; Middle Aged ; Spirometry ; Young Adult
Language	English
Publishing date	2022-02-01
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2052857-7
ISSN	1424-8220 ; 1424-8220
ISSN (online)	1424-8220
ISSN	1424-8220
DOI	10.3390/s22031106
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Gas Permeability through Polyimides: Unraveling the Influence of Free Volume, Intersegmental Distance and Glass Transition Temperature.

Torres, Alba / Soto, Cenit / Carmona, Javier / Comesaña-Gandara, Bibiana / de la Viuda, Mónica / Palacio, Laura / Prádanos, Pedro / Simorte, María Teresa / Sanz, Inmaculada / Muñoz, Raúl / Tena, Alberto / Hernández, Antonio

Polymers

2023 Volume 16, Issue 1

Abstract: The relationships between gas permeability and free volume fraction, intersegmental distance, and glass transition temperature, are investigated. They are analyzed for He, ... ...

Abstract	The relationships between gas permeability and free volume fraction, intersegmental distance, and glass transition temperature, are investigated. They are analyzed for He, CO
Language	English
Publishing date	2023-12-19
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2527146-5
ISSN	2073-4360 ; 2073-4360
ISSN (online)	2073-4360
ISSN	2073-4360
DOI	10.3390/polym16010013
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Simple iodoalkyne-based organocatalysts for the activation of carbonyl compounds.

Alegre-Requena, Juan V / Valero-Tena, Alberto / Sonsona, Isaac G / Uriel, Santiago / Herrera, Raquel P

Organic & biomolecular chemistry

2020 Volume 18, Issue 8, Page(s) 1594–1601

Abstract: A novel approach for the formation of bisindolylmethane derivatives (BIMs) is described as a proof of concept to evaluate the catalytic capacity of iodoalkynes. The use of these derivatives is reported as an example of simple halogen bond-based ... ...

Abstract	A novel approach for the formation of bisindolylmethane derivatives (BIMs) is described as a proof of concept to evaluate the catalytic capacity of iodoalkynes. The use of these derivatives is reported as an example of simple halogen bond-based organocatalyst. This kind of activation has not been used before for the synthesis of bisindolylmethane derivatives 3. Interestingly, the preparation of 3-(1H-indol-3-yl)-1-phenylbutan-1-one (8) has been also achieved for the first time with an iodoalkyne derivative. We prove the efficiency of this family of new catalysts by developing a simple and easy operational methodology, opening the door to the development of alternative catalysts in the area of halogen bond-based organocatalysts.
Language	English
Publishing date	2020-01-14
Publishing country	England
Document type	Journal Article
ZDB-ID	2097583-1
ISSN	1477-0539 ; 1477-0520
ISSN (online)	1477-0539
ISSN	1477-0520
DOI	10.1039/c9ob02688f
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Poly(ether–amide) vs. poly(ether–imide) copolymers for post-combustion membrane separation processes

Tena, Alberto / Filiz, Volkan / Shishatskiy, Sergey

RSC advances. 2015 Feb. 27, v. 5, no. 29

2015

Abstract: This work is focused on the comparison between the commercial polyamide PEBAX® MH 1657 and a new set of synthetized polyimides with different polyethylene glycol lengths. The samples were synthesized with the same poly(ethylene oxide) (PEO) content (57 ... ...

Abstract	This work is focused on the comparison between the commercial polyamide PEBAX® MH 1657 and a new set of synthetized polyimides with different polyethylene glycol lengths. The samples were synthesized with the same poly(ethylene oxide) (PEO) content (57 wt%) for comparison with the commercial polymer. All polymers have been characterized by several techniques revealing a direct relationship between crystallinity, PEO length and permeability properties. Results at temperatures lower than the Tm of the polyether blocks confirm that lower PEO crystallinity corresponds to higher permeability. At temperatures higher than the Tm of the PEO block, no significant differences were found between the commercial polyamides and the synthesized polyimides. This confirms that the aliphatic phase controls the separation while the hard block provides mechanical strength. Remarkable are the results for the CO2/N2 separation. These new copolyimides are promising materials for post-combustion processes.
Keywords	carbon dioxide ; composite polymers ; crystal structure ; nitrogen ; permeability ; polyamides ; polyethylene glycol ; strength (mechanics) ; temperature
Language	English
Dates of publication	2015-0227
Size	p. 22310-22318.
Publishing place	The Royal Society of Chemistry
Document type	Article
ISSN	2046-2069
DOI	10.1039/c5ra01328c
Database	NAL-Catalogue (AGRICOLA)

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