Respiration rate is an important indicator of a person's health, and thus it is monitored when performing clinical evaluations. There are different approaches for respiration monitoring, but generally they can be classed as contact or noncontact. For contact methods, the sensing device (or part of the instrument containing it) is attached to the subject's body. For noncontact approaches the monitoring is performed by an instrument that does not make any contact with the subject. In this article a review of respiration monitoring approaches (both contact and noncontact) is provided. Concerns related to the patient's recording comfort, recording hygiene, and the accuracy of respiration rate monitoring have resulted in the development of a number of noncontact respiration monitoring approaches. A description of thermal imaging based and vision based noncontact respiration monitoring approaches we are currently developing is provided. Pediatr. Pulmonol. 2011; 46:523–529. © 2011 Wiley‐Liss, Inc.

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Nocturnal hypoglycaemia has been implicated in the sudden deaths of young people with diabetes. Experimental hypoglycaemia has been found to prolong the ventricular repolarisotion and to affect the T wave morphology. It is postulated that abnormally low blood glucose could in certain circumstances, be responsible for the development of a fatal cardiac arrhythmia. We have used automatic extraction of both timeinterval and morphological features, from the Electrocardiogram (ECG) to classify ECGs into normal and arrhythmic. Classificntion was implemented by artificial neural networks (ANN) and LinearDiscriminant Analysis (LDA). The ANN gave more accurate results. Average training accuracy of the Ah" was 85.07% compared with 70.15% on unseen data.This study may lead towards the demonstration of the possible relationship between cardiac function and abnormally low blood glucose.

Abstract-A method has been developed to track a region related to respiration process in thermal images. The respiration region of interest (ROI) consisted of the skin area around the tip of the nose. The method was then used as part of a non-contact respiration rate monitoring that determined the skin temperature changes caused by respiration. The ROI was located by the first determining the relevant salient features of the human face physiology. These features were the warmest and coldest facial points. The tracking method was tested on thermal video images containing no head movements, small random and regular head movements. The method proved valuable for tracking the ROI in all these head movement types. It was also possible to use this tracking method to monitor respiration rate involving a number of head movement types. Currently, more investigations are underway to improve the tracking method so that it can track the ROI in cases larger head movements.