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Ruiz-Vega, G., Arias-Alpízar, K., de la Serna, E., Borgheti-Cardoso, L. N., Sulleiro, E., Molina, I., Fernàndez-Busquets, X., Sánchez-Montalvá, A., del Campo, F. J., Baldrich, E., (2020). Electrochemical POC device for fast malaria quantitative diagnosis in whole blood by using magnetic beads, Poly-HRP and microfluidic paper electrodes Biosensors and Bioelectronics 150, 111925

Malaria, a parasitic infection caused by Plasmodium parasites and transmitted through the bite of infected female Anopheles mosquitos, is one of the main causes of mortality in many developing countries. Over 200 million new infections and nearly half a million deaths are reported each year, and more than three billion people are at risk of acquiring malaria worldwide. Nevertheless, most malaria cases could be cured if detected early. Malaria eradication is a top priority of the World Health Organisation. However, achieving this goal will require mass population screening and treatment, which will be hard to accomplish with current diagnostic tools. We report an electrochemical point-of-care device for the fast, simple and quantitative detection of Plasmodium falciparum lactate dehydrogenase (PfLDH) in whole blood samples. Sample analysis includes 5-min lysis to release intracellular parasites, and stirring for 5 more min with immuno-modified magnetic beads (MB) along with an immuno-modified signal amplifier. The rest of the magneto-immunoassay, including sample filtration, MB washing and electrochemical detection, is performed at a disposable paper electrode microfluidic device. The sensor provides PfLDH quantitation down to 2.47 ng mL−1 in spiked samples and for 0.006–1.5% parasitemias in Plasmodium-infected cultured red blood cells, and discrimination between healthy individuals and malaria patients presenting parasitemias >0.3%. Quantitative malaria diagnosis is attained with little user intervention, which is not achieved by other diagnostic methods.

Keywords: Electrochemical magneto-immunosensor, Malaria quantitative diagnosis, Paper microfluidic electrode, Plasmodium LDH, Point-of-care (POC) testing

Blanco-Almazán, Dolores, Groenendaal, Willemijn, Catthoor, Francky, Jané, Raimon, (2019). Chest movement and respiratory volume both contribute to thoracic bioimpedance during loaded breathing Scientific Reports 9, (1), 20232

Bioimpedance has been widely studied as alternative to respiratory monitoring methods because of its linear relationship with respiratory volume during normal breathing. However, other body tissues and fluids contribute to the bioimpedance measurement. The objective of this study is to investigate the relevance of chest movement in thoracic bioimpedance contributions to evaluate the applicability of bioimpedance for respiratory monitoring. We measured airflow, bioimpedance at four electrode configurations and thoracic accelerometer data in 10 healthy subjects during inspiratory loading. This protocol permitted us to study the contributions during different levels of inspiratory muscle activity. We used chest movement and volume signals to characterize the bioimpedance signal using linear mixed-effect models and neural networks for each subject and level of muscle activity. The performance was evaluated using the Mean Average Percentage Errors for each respiratory cycle. The lowest errors corresponded to the combination of chest movement and volume for both linear models and neural networks. Particularly, neural networks presented lower errors (median below 4.29%). At high levels of muscle activity, the differences in model performance indicated an increased contribution of chest movement to the bioimpedance signal. Accordingly, chest movement contributed substantially to bioimpedance measurement and more notably at high muscle activity levels.

Keywords: Diagnosis, Health care

Urbán, P., Fernàndez-Busquets, X., (2014). Nanomedicine against malaria Current Medicinal Chemistry , 21, (5), 605-629

Malaria is arguably one of the main medical concerns worldwide because of the numbers of people affected, the severity of the disease and the complexity of the life cycle of its causative agent, the protist Plasmodium sp. The clinical, social and economic burden of malaria has led for the last 100 years to several waves of serious efforts to reach its control and eventual eradication, without success to this day. With the advent of nanoscience, renewed hopes have appeared of finally obtaining the long sought-after magic bullet against malaria in the form of a nanovector for the targeted delivery of antimalarial drugs exclusively to Plasmodium-infected cells. Different types of encapsulating structure, targeting molecule, and antimalarial compound will be discussed for the assembly of Trojan horse nanocapsules capable of targeting with complete specificity diseased cells and of delivering inside them their antimalarial cargo with the objective of eliminating the parasite with a single dose. Nanotechnology can also be applied to the discovery of new antimalarials through single-molecule manipulation approaches for the identification of novel drugs targeting essential molecular components of the parasite. Finally, methods for the diagnosis of malaria can benefit from nanotools applied to the design of microfluidic-based devices for the accurate identification of the parasite's strain, its precise infective load, and the relative content of the different stages of its life cycle, whose knowledge is essential for the administration of adequate therapies. The benefits and drawbacks of these nanosystems will be considered in different possible scenarios, including cost-related issues that might be hampering the development of nanotechnology-based medicines against malaria with the dubious argument that they are too expensive to be used in developing areas.

Keywords: Dendrimers, Liposomes, Malaria diagnosis, Nanobiosensors, Nanoparticles, Plasmodium, Polymers, Targeted drug delivery

Giraldo, B. F., Tellez, J. P., Herrera, S., Benito, S., (2013). Analysis of heart rate variability in elderly patients with chronic heart failure during periodic breathing CinC 2013 Computing in Cardiology Conference (CinC) , IEEE (Zaragoza, Spain) , 991-994

Assessment of the dynamic interactions between cardiovascular signals can provide valuable information that improves the understanding of cardiovascular control. Heart rate variability (HRV) analysis is known to provide information about the autonomic heart rate modulation mechanism. Using the HRV signal, we aimed to obtain parameters for classifying patients with and without chronic heart failure (CHF), and with periodic breathing (PB), non-periodic breathing (nPB), and Cheyne-Stokes respiration (CSR) patterns. An electrocardiogram (ECG) and a respiratory flow signal were recorded in 36 elderly patients: 18 patients with CHF and 18 patients without CHF. According to the clinical criteria, the patients were classified into the follow groups: 19 patients with nPB pattern, 7 with PB pattern, 4 with Cheyne-Stokes respiration (CSR), and 6 non-classified patients (problems with respiratory signal). From the HRV signal, parameters in the time and frequency domain were calculated. Frequency domain parameters were the most discriminant in comparisons of patients with and without CHF: PTot (p = 0.02), PLF (p = 0.022) and fpHF (p = 0.021). For the comparison of the nPB vs. CSR patients groups, the best parameters were RMSSD (p = 0.028) and SDSD (p = 0.028). Therefore, the parameters appear to be suitable for enhanced diagnosis of decompensated CHF patients and the possibility of developed periodic breathing and a CSR pattern.

Keywords: cardiovascular system, diseases, electrocardiography, frequency-domain analysis, geriatrics, medical signal processing, patient diagnosis, pneumodynamics, signal classification, Cheyne-Stokes respiration patterns, ECG, autonomic heart rate modulation mechanism, cardiovascular control, cardiovascular signals, chronic heart failure, decompensated CHF patients, dynamic interaction assessment, elderly patients, electrocardiogram, enhanced diagnosis, frequency domain parameters, heart rate variability analysis, patient classification, periodic breathing, respiratory flow signal recording, Electrocardiography, Frequency modulation, Frequency-domain analysis, Heart rate variability, Senior citizens, Standards

Correa, R., Laciar, E., Arini, P., Jané, R., (2010). Analysis of QRS loop in the Vectorcardiogram of patients with Chagas' disease Engineering in Medicine and Biology Society (EMBC) 32nd Annual International Conference of the IEEE , IEEE (Buenos Aires, Argentina) , 2561-2564

In the present work, we have studied the QRS loop in the Vectorcardiogram (VCG) of 95 chronic chagasic patients classified in different groups (I, II and III) according to their degree of myocardial damage. For comparison, the VCGs of 11 healthy subjects used as control group (Group O) were also examined. The QRS loop was obtained for each patient from the XYZ orthogonal leads of their High-Resolution Electrocardiogram (HRECG) records. In order to analyze the variations of QRS loop in each detected beat, it has been proposed in this study the following vectorcardiographic parameters a) Maximum magnitude of the cardiac depolarization vector, b) Volume, c) Area of QRS loop, d) Ratio between the Area and Perimeter, e) Ratio between the major and minor axes of the QRS loop and f) QRS loop Energy. It has been found that one or more indexes exhibited statistical differences (p<0.05) between groups 0-II, O-III, I-II, I-III and II-III. We concluded that the proposed method could be use as complementary diagnosis technique to evaluate the degree of myocardial damage in chronic chagasic patients.

Keywords: Practical, Experimental/ bioelectric phenomena, Diseases, Electrocardiography, Medical signal, Processing/ QRS loop, Vectorcardiogram, Cardiac depolarization vector, Myocardial damage, Chagas disease, Complementary diagnosis technique, High-resolution electrocardiogram

Morgenstern, C., Schwaibold, M., Randerath, W., Bolz, A., Jané, R., (2010). Automatic non-invasive differentiation of obstructive and central hypopneas with nasal airflow compared to esophageal pressure Engineering in Medicine and Biology Society (EMBC) 32nd Annual International Conference of the IEEE , IEEE (Buenos Aires, Argentina) , 6142-6145

The differentiation of obstructive and central respiratory events is a major challenge in the diagnosis of sleep disordered breathing. Esophageal pressure (Pes) measurement is the gold-standard method to identify these events but its invasiveness deters its usage in clinical routine. Flattening patterns appear in the airflow signal during episodes of inspiratory flow limitation (IFL) and have been shown with invasive techniques to be useful to differentiate between central and obstructive hypopneas. In this study we present a new method for the automatic non-invasive differentiation of obstructive and central hypopneas solely with nasal airflow. An overall of 36 patients underwent full night polysomnography with systematic Pes recording and a total of 1069 hypopneas were manually scored by human experts to create a gold-standard annotation set. Features were automatically extracted from the nasal airflow signal to train and test our automatic classifier (Discriminant Analysis). Flattening patterns were non-invasively assessed in the airflow signal using spectral and time analysis. The automatic non-invasive classifier obtained a sensitivity of 0.71 and an accuracy of 0.69, similar to the results obtained with a manual non-invasive classification algorithm. Hence, flattening airflow patterns seem promising for the non-invasive differentiation of obstructive and central hypopneas.

Keywords: Practical, Experimental/ biomedical measurement, Feature extraction, Flow measurement, Medical disorders, Medical signal processing, Patient diagnosis, Pneumodynamics, Pressure measurement, Signal classification, Sleep, Spectral analysis/ automatic noninvasive differentiation, Obstructive hypopnea, Central hypopnea, Inspiratory flow limitation, Nasal airflow, Esophageal pressure, Polysomnography, Feature extraction, Discriminant analysis, Spectral analysis

Padilla, M., Perera, A., Montoliu, I., Chaudry, A., Persaud, K., Marco, S., (2010). Fault detection, identification, and reconstruction of faulty chemical gas sensors under drift conditions, using Principal Component Analysis and Multiscale-PCA Theoretical or Mathematical; Experimental The 2010 International Joint Conference on Neural Networks (IJCNN 2010) , IEEE, Piscataway, NJ, USA (Barcelona, Spain) , 7 pp.

Statistical methods like Principal Components Analysis (PCA) or Partial Least Squares (PLS) and multiscale approaches, have been reported to be very useful in the task of fault diagnosis of malfunctioning sensors for several types of faults. In this work, we compare the performance of PCA and Multiscale-PCA on a fault based on a change of sensor sensitivity. This type of fault affects chemical gas sensors and it is one of the effects of the sensor poisoning. These two methods will be applied on a dataset composed by the signals of 17 conductive polymer gas sensors, measuring three analytes at several concentration levels during 10 months. Therefore, additionally to performance's comparison, both method's stability along the time will be tested. The comparison between both techniques will be made regarding three aspects; detection, identification of the faulty sensors and correction of faulty sensors response.

Keywords: Fault diagnosis, Gas sensors, Principal component analysis

Leder, R. S., Schlotthauer, G., Penzel, T., Jané, R., (2010). The natural history of the sleep and respiratory engineering track at EMBC 1988 to 2010 Engineering in Medicine and Biology Society (EMBC) 32nd Annual International Conference of the IEEE , IEEE (Buenos Aires, Argentina) , 288-291

Sleep science and respiratory engineering as medical subspecialties and research areas grew up side-by-side with biomedical engineering. The formation of EMBS in the 1950's and the discovery of REM sleep in the 1950's led to parallel development and interaction of sleep and biomedical engineering in diagnostics and therapeutics.

Keywords: Practical/ biomedical equipment, Biomedical measurement, Patient diagnosis, Patient monitoring, Patient treatment, Pneumodynamics, Sleep/ sleep engineering, Respiratory engineering, Automatic sleep analysis, Automatic sleep interpretation systems, Breathing, Biomedical, Engineering, Diagnostics, Therapeutics, REM sleep, Portable, Measurement, Ambulatory measurement, Monitoring

Mesquita, J., Fiz, J. A., Solà, J., Morera, J., Jané, R., (2010). Regular and non regular snore features as markers of SAHS Engineering in Medicine and Biology Society (EMBC) 32nd Annual International Conference of the IEEE , IEEE (Buenos Aires, Argentina) , 6138-6141

Sleep Apnea-Hypopnea Syndrome (SAHS) diagnosis is still done with an overnight multi-channel polysomnography. Several efforts are being made to study profoundly the snore mechanism and discover how it can provide an opportunity to diagnose the disease. This work introduces the concept of regular snores, defined as the ones produced in consecutive respiratory cycles, since they are produced in a regular way, without interruptions. We applied 2 thresholds (TH/sub adaptive/ and TH/sub median/) to the time interval between successive snores of 34 subjects in order to select regular snores from the whole all-night snore sequence. Afterwards, we studied the effectiveness that parameters, such as time interval between successive snores and the mean intensity of snores, have on distinguishing between different levels of SAHS severity (AHI (Apnea-Hypopnea Index)<5h/sup -1/, AHI<10 h/sup -1/, AHI<15h/sup -1/, AHI<30h/sup -1/). Results showed that TH/sub adaptive/ outperformed TH/sub median/ on selecting regular snores. Moreover, the outcome achieved with non-regular snores intensity features suggests that these carry key information on SAHS severity.

Keywords: Practical, Experimental/ acoustic signal processing, Bioacoustics, Biomedical measurement, Diseases, Feature extraction, Medical signal processing, Patient diagnosis, Pneumodynamics, Sleep/ nonregular snore features, SAHS markers, Sleep apnea hypopnea syndrome, Overnight multichannel polysomnography, Snore mechanism