Development of a novel scheme for long-term body temperature monitoring: a review of benefits and applications

Body temperature is a health or disease marker that has been in clinical use for centuries. The threshold currently applied to define fever, with small variations, is 38 °C. However, current approaches do not provide a full picture of the thermoregulation process and its correlation with disease. This paper describes a new non-invasive body temperature device that improves the understanding of the pathophysiology of diseases by integrating a variety of temperature data from different body locations. This device enables to gain a deeper insight into fever, endogenous rhythms, subject activity and ambient temperature to provide anticipatory and more efficient treatments. Its clinical use would be a big step in the overcoming of the anachronistic febrile/afebrile dichotomy and walking towards a system medicine approach to certain diseases. This device has already been used in some clinical applications successfully. Other possible applications based on the device features and clinical requirements are also described in this paper.Cuesta Frau, D.; Varela Entrecanales, M.; Valor Pérez, R.; Vargas, B. (2015). Development of a novel scheme for long-term body temperature monitoring: a review of benefits and applications. Journal of Medical Systems. 39(4):1-7. doi:10.1007/s10916-015-0209-3S17394Gai, M., Merlo, I., Dellepiane, S., Cantaluppi, V., Leonardi, G., Fop, F., Guarena, C., Grassi, G., and Biancore, L., Glycemic pattern in diabetic patients on hemodialysis: Continuous Glucose Monitoring (CGM) analysis. Blood Purif. 38(1):68–73 , 2014.Kondziella, D., Friberg, C.K., Wellwood, I., Reiffurth, C., Fabricius, M., and Dreier, J.P.: Continuous EEG monitoring in aneurysmal subarachnoid hemorrhage: A systematic review. Neurocrit. Care (2014)Ciccone, A., Celani, M.G., Chiaramonte, R., Rossi, C., and Righetti, E., Continuous versus intermittent physiological monitoring for acute stroke. Cochrane Database Syst. Rev. 31, 2013.Kushimoto, S., Yamanouchi, S., Endo, T., Sato, T., Nomura, R., Fujita, M., Kudo, D., Omura, T., Miyagawa, N., and Sato, T., Body temperature abnormalities in non-neurological critically ill patients: A review of the literature. J. Intensive Care 2, 2014.Mc Callum, L., and Higgings, D., Measuring body temperature. Nursing Times 108:20–22, 2012.Varela, M., Ruiz-Esteban, R., Martinez-Nicolas, A., Cuervo-Arango, A., Barros, C., and Delgado, E.G., Catching the spike and tracking the flow: Holter-temperature monitoring in patients admitted in a general internal medicine ward. Int. J. Clin. Pract. 65(12):1283–1288, 2011.Lopes, F., Peres, D., Bross, A., Melot, C., and Vincent, J.L., Serial evaluation of the SOFA score to predict outcome in critically ill patients. J. Am. Med. Assoc. 286:1754–1758, 2001.Vincent, J.L., and Moreno, R., Clinical review: Scoring systems in the critically ill. Crit. Care, 14, 2010.Sund-Levander, M., and Grodzinsky, E., Time for a change to assess and evaluate body temperature in clinical practice. Int. J. Nurs. Pract. 15:241–249, 2009.Cuesta-Frau, D., Varela, M., Aboy, M., and Miro, P., Description of a portable wireless device for body temperature acquisition and analysis. Sensors 9(10):7648–7663, 2009.Varela, M., Cuesta-Frau, D., Madrid, J.A., Churruca, J., Miro-Matinez, P., Ruiz, R., and Marinez, C., Holter monitoring of central peripheral temperature: Possible uses and feasibility study in outpatient settings. J. Clin. Monit. Comput. 4(23):209–216, 2009.Jordan, J., Miro, P., Cuesta-Frau, D., Varela, M., and Vargas B.: Aplicacion de analisis multivariante para la deteccion de estados prefebriles en pacientes ingresados (in Spanish), XXXIV Congreso Nacional de Estadistica e Investigacion Operativa, Castellon (Spain) (2013)Richman, J., and Moorman, J.R., Physiological time-series analysis using approximate entropy and sample entropy. Am. J. Physiol. Heart Circ. Physiol. 278(6):H2039–2049, 2000.Young, P., Saxena, M., Eastwood, G.M., Bellomo, R., and Beasley, R., Fever and fever management among intensive care patients with known or suspected infection: A multicentre prospective cohort study. Crit. Care Resusc. 13:97–102 , 2011.Drewry, A.M., Fuller, B.M., Bailey, T.C., and Hotchkiss, R.S., Body temperature patterns as a predictor of hospital-acquired sepsis in afebrile adult intensive care unit patients: A case-control study. Crit. Care,17, 2013.Musher, D., Fainstein, V., Young, E., and Pruett, T., Fever patterns. Their lack of significance. Arch. Intern. Med. 139(11):1225–8, 1979.Varela, M., Calvo, M., Chana, M., Gomez-Mestre, I., Asensio, R., and Galdos, P., Clinical implications of temperature curve complexity in critically ill patients. Crit. Care Med. 33(12):2764–2771, 2005.Varela, M., Churruca, J., Gonzalez, A., Martin, A., Ode, J., and Galdos, P., Temperature curve complexity predicts survival in critically ill patients. Am. J. Respir. Crit. Care Med. 174(3):290–298, 2006.Cuesta-Frau, D., Varela, M., Miro, P., Galdos, P., Abasolo, D., Hornero, R., and Aboy, M., Predicting survival in critical patients by use of body temperature regularity measurement based on Approximate Entropy. Med. Biol. Eng. Computing 45:671–678, 2007.Mackiowak, P. Temperature regulation and the pathogenesis of fever, Principles and Practice of Infectious Diseases, pp. 765–778. New York: Churchill Livingston Elsevier, 2010.Cherbuin N., and Brinkman C., Cognition is cool: Can hemispheric activation be assessed by tympanic membrane thermometry? Brain Cogn. 54:228–231, 2004

Characterization of complex fractionated atrial electrograms by sample entropy: An international multi-center study

Atrial fibrillation (AF) is the most commonly clinically-encountered arrhythmia. Catheter ablation of AF is mainly based on trigger elimination and modification of the AF substrate. Substrate mapping ablation of complex fractionated atrial electrograms (CFAEs) has emerged to be a promising technique. To improve substrate mapping based on CFAE analysis, automatic detection algorithms need to be developed in order to simplify and accelerate the ablation procedures. According to the latest studies, the level of fractionation has been shown to be promisingly well estimated from CFAE measured during radio frequency (RF) ablation of AF. The nature of CFAE is generally nonlinear and nonstationary, so the use of complexity measures is considered to be the appropriate technique for the analysis of AF records. This work proposes the use of sample entropy (SampEn), not only as a way to discern between non-fractionated and fractionated atrial electrograms (A-EGM), but also as a tool for characterizing the degree of A-EGM regularity, which is linked to changes in the AF substrate and to heart tissue damage. The use of SampEn combined with a blind parameter estimation optimization process enables the classification between CFAE and non-CFAE with statistical significance (p < 0:001), 0.89 area under the ROC, 86% specificity and 77% sensitivity over a mixed database of A-EGM combined from two independent CFAE signal databases, recorded during RF ablation of AF in two EU countries (542 signals in total). On the basis of the results obtained in this study, it can be suggested that the use of SampEn is suitable for real-time support during navigation of RF ablation of AF, as only 1.5 seconds of signal segments need to be analyzed

The effect of electroporation pulses on functioning of the heart

Electrochemotherapy is an effective antitumor treatment currently applied to cutaneous and subcutaneous tumors. Electrochemotherapy of tumors located close to the heart could lead to adverse effects, especially if electroporation pulses were delivered within the vulnerable period of the heart or if they coincided with arrhythmias of some types. We examined the influence of electroporation pulses on functioning of the heart of human patients by analyzing the electrocardiogram. We found no pathological morphological changes in the electrocardiogram; however, we demonstrated a transient RR interval decrease after application of electroporation pulses. Although no adverse effects due to electroporation have been reported so far, the probability for complications could increase in treatment of internal tumors, in tumor ablation by irreversible electroporation, and when using pulses of longer durations. We evaluated the performance of our algorithm for synchronization of electroporation pulse delivery with electrocardiogram. The application of this algorithm in clinical electroporation would increase the level of safety for the patient and suitability of electroporation for use in anatomical locations presently not accessible to existing electroporation devices and electrodes

Morphology Analysis of Intracranial Pressure Using Pattern Matching Techniques

We present a clustering algorithm based on Dynamic Time Warping (DTW) to automatically classify intracranial pressure (ICP) beats based on their morphology. The algorithm detects, classifies and labels each beat as a low--pressure or high--pressure beat based on morphology. The trend is removed during prepocessing to ensure the classifications are independent of the mean ICP. An ICP beat detection algorithm is used to automatically detect each beat. We measured the performance of the algorithm compared to expert classification of ICP beats acquired from intensive care unit patients using linear and non-- linear temporal alignment techniques. The algorithm achieved a superior performance using non--linear temporal alignment

Unsupervised feature relevance analysis applied to improve ecg heartbeat clustering

c o m p u t e r m e t h o d s a n d p r o g r a m s i n b i o m e d i c i n e 1 0 8 ( 2 0 1 2 ) j o u r n a l h o m e p a g e : w w w . i n t l . e l s e v i e r h e a l t h . c o m / j o u r n a l s / c m p b t r a c t The computer-assisted analysis of biomedical records has become an essential tool in clinical settings. However, current devices provide a growing amount of data that often exceeds the processing capacity of normal computers. As this amount of information rises, new demands for more efficient data extracting methods appear. This paper addresses the task of data mining in physiological records using a feature selection scheme. An unsupervised method based on relevance analysis is described. This scheme uses a least-squares optimization of the input feature matrix in a single iteration. The output of the algorithm is a feature weighting vector. The performance of the method was assessed using a heartbeat clustering test on real ECG records. The quantitative cluster validity measures yielded a correctly classified heartbeat rate of 98.69% (specificity), 85.88% (sensitivity) and 95.04% (general clustering performance), which is even higher than the performance achieved by other similar ECG clustering studies. The number of features was reduced on average from 100 to 18, and the temporal cost was a 43% lower than in previous ECG clustering schemes. © 2012 Elsevier Ireland Ltd. All rights reserved. Introduction The computer-assisted analysis of biomedical records has become an essential tool in clinical settings. The widespread access to portable medical devices or new personal devices such as cell phones, smartphones, pdas, tablets, and wearable devices, is boosting the amount of biomedical data available. These devices provide a growing amount of data that often exceeds the processing capacity of affordable computers. As this amount of biosignal data rises, new demands for more efficient information extracting methods appear E-mail addresses: [email protected] (J.L. Rodríguez-Sotelo), [email protected] (D. Cuesta-Frau), [email protected] (G. Castellanos-Domínguez). A number of algorithms have been proposed for knowledge discovery and management in medical databases Feature selection algorithms are dimensionality reduction methods often associated to data mining tasks of classificationor clusterin

A novel acquisition platform for long-term breathing frequency monitoring based on inertial measurement units

Continuous monitoring of breathing frequency (fB) could foster early prediction of adverse clinical effects and exacerbation of medical conditions. Current solutions are invasive or obtrusive and thus not suitable for prolonged monitoring outside the clinical setting. Previous studies demonstrated the feasibility of deriving fB by measuring inclination changes due to breathing using accelerometers or inertial measurement units (IMU). Nevertheless, few studies faced the problem of motion artifacts that limit the use of IMU-based systems for continuous monitoring. Moreover, few attempts have been made to move towards real portability and wearability of such devices. This paper proposes a wearable IMU-based device that communicates via Bluetooth with a smartphone, uploading data on a web server to allow remote monitoring. Two IMU units are placed on thorax and abdomen to record breathing-related movements, while a third IMU unit records body/trunk motion and is used as reference. The performance of the proposed system was evaluated in terms of long-acquisition-platform reliability showing good performances in terms of duration and data loss amount. The device was preliminarily tested in terms of accuracy in breathing temporal parameter measurement, in static condition, during postural changes, and during slight indoor activities showing favorable comparison against the reference methods (mean error breathing frequency &lt; 5%). [Figure not available: see fulltext.]

2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC'10

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