Non-invasive monitoring of diaphragmatic timing by means of surface contact sensors: an experimental study in dogs

Background: Non-invasive monitoring of respiratory muscle function is an area of increasing research interest, resulting in the appearance of new monitoring devices, one of these being piezoelectric contact sensors. The present study was designed to test whether the use of piezoelectric contact (non-invasive) sensors could be useful in respiratory monitoring, in particular in measuring the timing of diaphragmatic contraction.Methods: Experiments were performed in an animal model: three pentobarbital anesthetized mongrel dogs. The motion of the thoracic cage was acquired by means of a piezoelectric contact sensor placed on the costal wall. This signal is compared with direct measurements of the diaphragmatic muscle length, made by sonomicrometry. Furthermore, to assess the diaphragmatic function other respiratory signals were acquired: respiratory airflow and transdiaphragmatic pressure. Diaphragm contraction time was estimated with these four signals. Using diaphragm length signal as reference, contraction times estimated with the other three signals were compared with the contraction time estimated with diaphragm length signal.Results: The contraction time estimated with the TM signal tends to give a reading 0.06 seconds lower than the measure made with the DL signal (-0.21 and 0.00 for FL and DP signals, respectively), with a standard deviation of 0.05 seconds (0.08 and 0.06 for FL and DP signals, respectively). Correlation coefficients indicated a close link between time contraction estimated with TM signal and contraction time estimated with DL signal (a Pearson correlation coefficient of 0.98, a reliability coefficient of 0.95, a slope of 1.01 and a Spearman's rank-order coefficient of 0.98). In general, correlation coefficients and mean and standard deviation of the difference were better in the inspiratory load respiratory test than in spontaneous ventilation tests.Conclusion: The technique presented in this work provides a non-invasive method to assess the timing of diaphragmatic contraction in canines, using a piezoelectric contact sensor placed on the costal wall.

Non-invasive RF built-in testing using on-chip temperature sensors

This poster shows how to efficiently observe high-frequency figures of merit in RF circuits by measuring DC temperature with CMOS-compatible built-in sensors.

On the Selection of Non-Invasive Methods Based on Speech Analysis Oriented to Automatic Alzheimer Disease Diagnosis

The work presented here is part of a larger study to identify novel technologies and biomarkers for early Alzheimer disease (AD) detection and it focuses on evaluating the suitability of a new approach for early AD diagnosis by non-invasive methods. The purpose is to examine in a pilot study the potential of applying intelligent algorithms to speech features obtained from suspected patients in order to contribute to the improvement of diagnosis of AD and its degree of severity. In this sense, Artificial Neural Networks (ANN) have been used for the automatic classification of the two classes (AD and control subjects). Two human issues have been analyzed for feature selection: Spontaneous Speech and Emotional Response. Not only linear features but also non-linear ones, such as Fractal Dimension, have been explored. The approach is non invasive, low cost and without any side effects. Obtained experimental results were very satisfactory and promising for early diagnosis and classification of AD patients.

Non-invasive diagnostic and prognostic evaluation of liver cirrhosis and portal hypertension.

Cirrhosis is the final stage of most of chronic liver diseases, and is almost invariably complicated by portal hypertension, which is the most important cause of morbidity and mortality in these patients. This review will focus on the non-invasive methods currently used in clinical practice for diagnosing liver cirrhosis and portal hypertension. The first-line techniques include physical examination, laboratory parameters, transient elastography and Doppler-US. More sophisticated imaging methods which are less commonly employed are CT scan and MRI, and new technologies which are currently under evaluation are MR elastography and acoustic radiation force imaging (ARFI). Even if none of them can replace the invasive measurement of hepatic venous pressure gradient and the endoscopic screening of gastroesophageal varices, they notably facilitate the clinical management of patients with cirrhosis and portal hypertension, and provide valuable prognostic information.

Tissue distribution of retinoids in common dolphins (Delphinus delphis).

Exposure to organochlorines induces retinoid deficiency in mammals; hence, retinoids are potential biomarkers of the impact of these pollutants. Appropriate target tissues to monitor retinoids in cetaceans have not been properly identified because of a lack of information on the contribution of each tissue to total body retinoids. Therefore, we have addressed this issue by studying the contribution of the main body tissues to retinoids in 21 common dolphins obtained from incidental catches and in apparent good health and nutritive condition. Although concentrations in the liver were highest, those in blubber were also high and accounted for 43% of the total retinoid load of the compartments examined. As blubber can be obtained using non-invasive biopsy techniques, this tissue is proposed as a reliable indicator of retinoid status in cetaceans. However, blubber topographical variation in structure and composition requires standardization of sampling sites. Retinoid concentrations did not differ significantly between sexes or with body size for any of the tissues, but the lipid content of blubber strongly influenced these concentrations. Biopsies from healthy, free-ranging individuals are preferred to samples from stranded animals. Further research on the influence of factors (age, sex, reproductive condition, diet) that potentially affect retinoid levels is required to implement the use of retinoids as biomarkers of pollutant exposure in cetaceans.

Estimulació beta-adrenèrgica en la síndrome del destret respiratori agut (SDRA)

Estudi elaborat a partir d’una estada al Royal Brompton Hospital, Londres, Regne Unit, durant octubre i novembre del 2006.Els beneficis de la estimulació beta-adrenèrgica en pacients amb lesió pulmonar aguda (LPA) són coneguts, però no es disposa de dades sobre el possible efecte antiinflamatori. El condensat d'aire exhalat (CAE) és una tècnica no-invasiva de recollida de mostres del tracte respiratori inferior, podent ser útil en la monitorització de patologies respiratòries. S’ha usat marcadors biològics en el CAE de pacients ventilats mecànicament amb LPA per estudiar el possible efecte antiinflamatori que el salbutamol hi podria exercir. El CAE va ser recollit abans i després de l'administració de salbutamol inahalat. Inmediatament després es va mesurar la conductivitat i el pH abans i després de la desgasificació amb heli. Es va mesurar la concentració de nitrits i nitrats. Les mostres varen ser liofilitzades i guardades a -80ºC. La concentració de leucotriè B4 es va mesurar després de la reconstitució de la mostra. Els resultats s'expressen com a mitjana (error estàndard de la mostra). No s'han detectat diferències entre els valors de CAE basals dels pacients amb LPA i els de referència de la població sana de Barcelona. Es conclou doncs que el CAE és una tècnica no invasiva que pot ser usada en la monitorització de paceints ventilats mecànicament. El salbutamol inhalat incrementa de manera significativa el pH del CAE dels paceints amb LPA, tot i que un efecte directe de la inhalació de slabutamol no pot ser desestimat.

Cortical mapping of the neuronal circuits modulating the muscle tone. Introduction to the electrophysiological treatment of the spastic hand.

L’objectiu d’aquest estudi es investigar l’organització cortical junt amb la connectivitat còrtico-subcortical en subjectes sans, com a estudi preliminar. Els mapes corticals s’han fet per TMS navegada, i els punts motors obtinguts s’han exportant per estudi tractogràfic i anàlisi de las seves connexions. El coneixement precís de la localització de l’àrea cortical motora primària i les seves connexions es la base per ser utilitzada en estudis posteriors de la reorganització cortical i sub-cortical en pacients amb infart cerebral. Aquesta reorganització es deguda a la neuroplasticitat i pot ser influenciada per els efectes neuromoduladors de la estimulació cerebral no invasiva.

Mejora diagnóstica de hepatopatías de afectación difusa mediante técnicas de inteligencia artificial

The automatic diagnostic discrimination is an application of artificial intelligence techniques that can solve clinical cases based on imaging. Diffuse liver diseases are diseases of wide prominence in the population and insidious course, yet early in its progression. Early and effective diagnosis is necessary because many of these diseases progress to cirrhosis and liver cancer. The usual technique of choice for accurate diagnosis is liver biopsy, an invasive and not without incompatibilities one. It is proposed in this project an alternative non-invasive and free of contraindications method based on liver ultrasonography. The images are digitized and then analyzed using statistical techniques and analysis of texture. The results are validated from the pathology report. Finally, we apply artificial intelligence techniques as Fuzzy k-Means or Support Vector Machines and compare its significance to the analysis Statistics and the report of the clinician. The results show that this technique is significantly valid and a promising alternative as a noninvasive diagnostic chronic liver disease from diffuse involvement. Artificial Intelligence classifying techniques significantly improve the diagnosing discrimination compared to other statistics.

Compact matrix expressions for generalized Wald tests of equality of moment vectors

Asymptotic chi-squared test statistics for testing the equality ofmoment vectors are developed. The test statistics proposed aregeneralizedWald test statistics that specialize for different settings by inserting andappropriate asymptotic variance matrix of sample moments. Scaled teststatisticsare also considered for dealing with situations of non-iid sampling. Thespecializationwill be carried out for testing the equality of multinomial populations, andtheequality of variance and correlation matrices for both normal andnon-normaldata. When testing the equality of correlation matrices, a scaled versionofthe normal theory chi-squared statistic is proven to be an asymptoticallyexactchi-squared statistic in the case of elliptical data.

Rockfall induced seismic signals: case study in Montserrat, Catalonia

After a rockfall event, a usual post event survey includes qualitative volume estimation, trajectory mapping and determination of departing zones. However, quantitative measurements are not usually made. Additional relevant quantitative information could be useful in determining the spatial occurrence of rockfall events and help us in quantifying their size. Seismic measurements could be suitable for detection purposes since they are non invasive methods and are relatively inexpensive. Moreover, seismic techniques could provide important information on rockfall size and location of impacts. On 14 February 2007 the Avalanche Group of the University of Barcelona obtained the seismic data generated by an artificially triggered rockfall event at the Montserrat massif (near Barcelona, Spain) carried out in order to purge a slope. Two 3 component seismic stations were deployed in the area about 200 m from the explosion point that triggered the rockfall. Seismic signals and video images were simultaneously obtained. The initial volume of the rockfall was estimated to be 75 m3 by laser scanner data analysis. After the explosion, dozens of boulders ranging from 10¿4 to 5 m3 in volume impacted on the ground at different locations. The blocks fell down onto a terrace, 120 m below the release zone. The impact generated a small continuous mass movement composed of a mixture of rocks, sand and dust that ran down the slope and impacted on the road 60 m below. Time, time-frequency evolution and particle motion analysis of the seismic records and seismic energy estimation were performed. The results are as follows: 1 ¿ A rockfall event generates seismic signals with specific characteristics in the time domain; 2 ¿ the seismic signals generated by the mass movement show a time-frequency evolution different from that of other seismogenic sources (e.g. earthquakes, explosions or a single rock impact). This feature could be used for detection purposes; 3 ¿ particle motion plot analysis shows that the procedure to locate the rock impact using two stations is feasible; 4 ¿ The feasibility and validity of seismic methods for the detection of rockfall events, their localization and size determination are comfirmed.

Preparació física específica en l'esport col·lectiu del futbol. Estudi de la millora i el manteniment del valor del VO2màx

En el treball que es mostra a continuació podrem observar un estudi sobre la preparació física aplicada a l’esport del futbol. A més, farem un estudi dels nivells del volum màxim d’Oxigen (Vo2màx) a través d’un procés d’obtenció de resultats indirecte (Test de Course Navette) tenint present el nombre de sessions setmanals. Observarem les diferències en la definició del paràmetre segons Zintl (1991), Diéguez (1997), Gómez, Aranda i Ferrer (2010), entre d’altres. També observarem els nivells que s’han de tenir a partir d’autors com Zintl (1991), Rivera i Avella (1992), Sánchez i Salas (2008). Per dur-ho a terme, farem un estudi hipotètic-deductiu a través d’un mostreig no probabilístic. Observarem els valors del Vo2màx. assolits en el període preparatori, comparats amb el manteniment, la millora o la pèrdua d’aquest després d’un període d’entrenament diferenciat entre una i tres sessions. Un cop realitzat el procés, hem pogut veure que els nivells assolits després del període preparatori (60.87+ 8.81 ml/kg/min) són majors respecte l’inici del període (44.38 +8.92 ml/kg/min.). Posteriorment, al observar les diferències entre els dos grups de la mostra, podem afirmar que amb tres sessions realitzades no es poden mantenir els nivells anteriors (57.80 +10.16) respecte els (56.73 +9.24) de l’últim test. Per últim, el grup 2, amb una única sessió setmanal els valors baixen més, es passa dels (63.93 + 6.24 ml/kg/min.) als (56.50 + 7.52 ml/kg/min)

Multiway Array Decomposition Analysis of EEGs in Alzheimer’s Disease

Methods for the extraction of features from physiological datasets are growing needs as clinical investigations of Alzheimer’s disease (AD) in large and heterogeneous population increase. General tools allowing diagnostic regardless of recording sites, such as different hospitals, are essential and if combined to inexpensive non-invasive methods could critically improve mass screening of subjects with AD. In this study, we applied three state of the art multiway array decomposition (MAD) methods to extract features from electroencephalograms (EEGs) of AD patients obtained from multiple sites. In comparison to MAD, spectral-spatial average filter (SSFs) of control and AD subjects were used as well as a common blind source separation method, algorithm for multiple unknown signal extraction (AMUSE). We trained a feed-forward multilayer perceptron (MLP) to validate and optimize AD classification from two independent databases. Using a third EEG dataset, we demonstrated that features extracted from MAD outperformed features obtained from SSFs AMUSE in terms of root mean squared error (RMSE) and reaching up to 100% of accuracy in test condition. We propose that MAD maybe a useful tool to extract features for AD diagnosis offering great generalization across multi-site databases and opening doors to the discovery of new characterization of the disease.

On Automatic Diagnosis of Alzheimer's Disease based on Spontaneous Speech Analysis and Emotional Temperature

Alzheimer's disease is the most prevalent form of progressive degenerative dementia; it has a high socio-economic impact in Western countries. Therefore it is one of the most active research areas today. Alzheimer's is sometimes diagnosed by excluding other dementias, and definitive confirmation is only obtained through a post-mortem study of the brain tissue of the patient. The work presented here is part of a larger study that aims to identify novel technologies and biomarkers for early Alzheimer's disease detection, and it focuses on evaluating the suitability of a new approach for early diagnosis of Alzheimer’s disease by non-invasive methods. The purpose is to examine, in a pilot study, the potential of applying Machine Learning algorithms to speech features obtained from suspected Alzheimer sufferers in order help diagnose this disease and determine its degree of severity. Two human capabilities relevant in communication have been analyzed for feature selection: Spontaneous Speech and Emotional Response. The experimental results obtained were very satisfactory and promising for the early diagnosis and classification of Alzheimer’s disease patients.

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 im-provement 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.

Comparison of quality of life after stereotactic body radiotherapy and surgery for early-stage prostate cancer

Background: As the long-term efficacy of stereotactic body radiation therapy (SBRT) becomes established and other prostate cancer treatment approaches are refined and improved, examination of quality of life (QOL) following prostate cancer treatment is critical in driving both patient and clinical treatment decisions. We present the first study to compare QOL after SBRT and radical prostatectomy, with QOL assessed at approximately the same times pre- and post-treatment and using the same validated QOL instrument. Methods: Patients with clinically localized prostate cancer were treated with either radical prostatectomy (n = 123 Spanish patients) or SBRT (n = 216 American patients). QOL was assessed using the Expanded Prostate Cancer Index Composite (EPIC) grouped into urinary, sexual, and bowel domains. For comparison purposes, SBRT EPIC data at baseline, 3 weeks, 5, 11, 24, and 36 months were compared to surgery data at baseline, 1, 6, 12, 24,and 36 months. Differences in patient characteristics between the two groups were assessed using Chi-squared tests for categorical variables and t-tests for continuous variables. Generalized estimating equation (GEE) models were constructed for each EPIC scale to account for correlation among repeated measures and used to assess the effect of treatment on QOL. Results: The largest differences in QOL occurred in the first 16 months after treatment, with larger declines following surgery in urinary and sexual QOL as compared to SBRT, and a larger decline in bowel QOL following SBRT as compared to surgery. Long-term urinary and sexual QOL declines remained clinically significantly lower for surgery patients but not for SBRT patients. Conclusions: Overall, these results may have implications for patient and physician clinical decision making which are often influenced by QOL. These differences in sexual, urinary and bowel QOL should be closely considered in selecting the right treatment, especially in evaluating the value of non-invasive treatments, such as SBRT.