Entropy analysis of acoustic signals recorded with a smartphone for detecting apneas and hypopneas: A comparison with a commercial system for home sleep apnea diagnosis

Obstructive sleep apnea (OSA) is a prevalent disease, but most patients remain undiagnosed and untreated. Here we propose analyzing smartphone audio signals for screening OSA patients at home. Our objectives were to: (1) develop an algorithm for detecting silence events and classifying them into apneas or hypopneas; (2) evaluate the performance of this system; and (3) compare the information provided with a type 3 portable sleep monitor, based mainly on nasal airflow. Overnight signals were acquired simultaneously by both systems in 13 subjects (3 healthy subjects and 10 OSA patients). The sample entropy of audio signals was used to identify apnea/hypopnea events. The apnea-hypopnea indices predicted by the two systems presented a very high degree of concordance and the smartphone correctly detected and stratified all the OSA patients. An event-by-event comparison demonstrated good agreement between silence events and apnea/hypopnea events in the reference system (Sensitivity = 76%, Positive Predictive Value = 82%). Most apneas were detected (89%), but not so many hypopneas (61%). We observed that many hypopneas were accompanied by snoring, so there was no sound reduction. The apnea/hypopnea classification accuracy was 70%, but most discrepancies resulted from the inability of the nasal cannula of the reference device to record oral breathing. We provided a spectral characterization of oral and nasal breathing to correct this effect, and the classification accuracy increased to 82%. This novel knowledge from acoustic signals may be of great interest for clinical practice to develop new non-invasive techniques for screening and monitoring OSA patients at homePeer ReviewedPostprint (published version

Oximetry use in obstructive sleep apnea

Producción CientíficaIntroduction. Overnight oximetry has been proposed as an accessible, simple, and reliable technique for obstructive sleep apnea syndrome (OSAS) diagnosis. From visual inspection to advanced signal processing, several studies have demonstrated the usefulness of oximetry as a screening tool. However, there is still controversy regarding the general application of oximetry as a single screening methodology for OSAS. Areas covered. Currently, high-resolution portable devices combined with pattern recognition-based applications are able to achieve high performance in the detection this disease. In this review, recent studies involving automated analysis of oximetry by means of advanced signal processing and machine learning algorithms are analyzed. Advantages and limitations are highlighted and novel research lines aimed at improving the screening ability of oximetry are proposed. Expert commentary. Oximetry is a cost-effective tool for OSAS screening in patients showing high pretest probability for the disease. Nevertheless, exhaustive analyses are still needed to further assess unattended oximetry monitoring as a single diagnostic test for sleep apnea, particularly in the pediatric population and in especial groups with significant comorbidities. In the following years, communication technologies and big data analysis will overcome current limitations of simplified sleep testing approaches, changing the detection and management of OSAS.This research has been partially supported by the projects DPI2017-84280-R and RTC-2015-3446-1 from Ministerio de Economía, Industria y Competitividad and European Regional Development Fund (FEDER), the project 66/2016 of the Sociedad Española de Neumología y Cirugía Torácica (SEPAR), and the project VA037U16 from the Consejería de Educación de la Junta de Castilla y León and FEDER. D. Álvarez was in receipt of a Juan de la Cierva grant IJCI-2014-22664 from the Ministerio de Economía y Competitividad

An exploration of the rhythm of Malay

In recent years there has been a surge of interest in speech rhythm. However we still lack a clear understanding of the nature of rhythm and rhythmic differences across languages. Various metrics have been proposed as means for measuring rhythm on the phonetic level and making typological comparisons between languages (Ramus et al, 1999; Grabe & Low, 2002; Dellwo, 2006) but the debate is ongoing on the extent to which these metrics capture the rhythmic basis of speech (Arvaniti, 2009; Fletcher, in press). Furthermore, cross linguistic studies of rhythm have covered a relatively small number of languages and research on previously unclassified languages is necessary to fully develop the typology of rhythm. This study examines the rhythmic features of Malay, for which, to date, relatively little work has been carried out on aspects rhythm and timing. The material for the analysis comprised 10 sentences produced by 20 speakers of standard Malay (10 males and 10 females). The recordings were first analysed using rhythm metrics proposed by Ramus et. al (1999) and Grabe & Low (2002). These metrics (∆C, %V, rPVI, nPVI) are based on durational measurements of vocalic and consonantal intervals. The results indicated that Malay clustered with other so-called syllable-timed languages like French and Spanish on the basis of all metrics. However, underlying the overall findings for these metrics there was a large degree of variability in values across speakers and sentences, with some speakers having values in the range typical of stressed-timed languages like English. Further analysis has been carried out in light of Fletcher’s (in press) argument that measurements based on duration do not wholly reflect speech rhythm as there are many other factors that can influence values of consonantal and vocalic intervals, and Arvaniti’s (2009) suggestion that other features of speech should also be considered in description of rhythm to discover what contributes to listeners’ perception of regularity. Spectrographic analysis of the Malay recordings brought to light two parameters that displayed consistency and regularity for all speakers and sentences: the duration of individual vowels and the duration of intervals between intensity minima. This poster presents the results of these investigations and points to connections between the features which seem to be consistently regulated in the timing of Malay connected speech and aspects of Malay phonology. The results are discussed in light of current debate on the descriptions of rhythm

Thought on Food: A Systematic Review of Current Approaches and Challenges for Food Intake Detection

Nowadays, individuals have very stressful lifestyles, affecting their nutritional habits. In the early stages of life, teenagers begin to exhibit bad habits and inadequate nutrition. Likewise, other people with dementia, Alzheimer’s disease, or other conditions may not take food or medicine regularly. Therefore, the ability to monitor could be beneficial for them and for the doctors that can analyze the patterns of eating habits and their correlation with overall health. Many sensors help accurately detect food intake episodes, including electrogastrography, cameras, microphones, and inertial sensors. Accurate detection may provide better control to enable healthy nutrition habits. This paper presents a systematic review of the use of technology for food intake detection, focusing on the different sensors and methodologies used. The search was performed with a Natural Language Processing (NLP) framework that helps screen irrelevant studies while following the PRISMA methodology. It automatically searched and filtered the research studies in different databases, including PubMed, Springer, ACM, IEEE Xplore, MDPI, and Elsevier. Then, the manual analysis selected 30 papers based on the results of the framework for further analysis, which support the interest in using sensors for food intake detection and nutrition assessment. The mainly used sensors are cameras, inertial, and acoustic sensors that handle the recognition of food intake episodes with artificial intelligence techniques. This research identifies the most used sensors and data processing methodologies to detect food intake.info:eu-repo/semantics/publishedVersio