Non-contact life detection is a significant component of both civilian and military rescue applications. As a consequence, this interest has resulted in a very active area of research. The primary goal of this research is reliable detection of a human breathing signal. Additional goals of this research are to carry out detection under realistic conditions, to distinguish between two targets, to determine human breathing rate and estimate the posture. Range gating and Singular Value Decomposition (SVD) have been used to remove clutter in order to detect human breathing under realistic conditions. However, the information of the target range or what principal component contains target information may be unknown. DFT and Short Time Fourier Transform (STFT) algorithms have been used to detect the human breathing and discriminate between two targets. However, the algorithms result in many false alarms because they detect breathing when no target exists. The unsatisfactory performance of the DFT-based estimators in human breathing rate estimation is due to the fact that the second harmonic of the breathing signal has higher magnitude than the first harmonic. Human posture estimation has been performed by measuring the distance of the chest displacements from the ground. This requires multiple UWB receivers and a more complex system. In this thesis, monostatic UWB radar is used. Initially, the SVD method was combined with the skewness test to detect targets, discriminate between two targets, and reduce false alarms. Then, a novel human breathing rate estimation algorithm was proposed using zero-crossing method. Subsequently, a novel method was proposed to distinguish between human postures based on the ratios between different human breathing frequency harmonics magnitudes. It was noted that the ratios depend on the abdomen displacements and higher harmonic ratios were observed when the human target was sitting or standing. The theoretical analysis shows that the distribution of the skewness values of the correlator output of the target and the clutter signals in a single range-bin do not overlap. The experimental results on human breathing detection, breathing rate, and human posture estimation show that the proposed methods improve performance in human breathing detection and rate estimation.

The aim of this research was to investigate the breathing patterns of children aged 5-9 years with asthma as they read aloud stories of increasingly difficulty. Participants were 11 children diagnosed with moderate to severe asthma recruited from an out-patient clinic and 11 gender- and age-matched controls recruited from local schools. Non-contact respiratory monitoring methods were employed to yield acoustic recordings during three non-reading tasks and three reading aloud tasks which increased in difficulty. Measurements included breathing rate, pause time in speech, and time ratio between inspiration between inspiration and expiration (I/E ratio). Pauses that occurred during the reading tasks were classified as either occurring at grammatical junctions where pausing during oral reading would be expected, or at ungrammatical junctions, where pausing was associated with either needing to breath, a reading mistake and/or upon recognition of an unknown word. The acoustic measures were recorded using a free audio editor and recorder programme (Audacity version 2.0.3’) on a Notebook laptop with an inbuilt microphone. The main result indicated that 82% of children with asthma breathed more slowly when reading books that were difficult for them, and this was negatively associated with asthma severity (p=0.046). The findings demonstrated that children with asthma appear to cope when reading more difficult materials by breathing more slowly, pausing for longer ([F(1, 16) = 5.454, p = 0.033]) and increasing expiration time. The current research is the first of its kind and provides a base for future studies to investigate the relationship between breathing and the reading of children with asthma. Questions remain whether this relationship is related to low achievement in reading. Future research to confirm, disconfirm or otherwise is necessary to add to the sparse literature on the breathing of children with asthma while reading aloud.

abstract: Advances in miniaturized sensors and wireless technologies have enabled mobile health systems for efficient healthcare. A mobile health system assists the physician to monitor the patient's progress remotely and provide quick feedbacks and suggestions in case of emergencies, which reduces the cost of healthcare without the expense of hospitalization. This work involves development of an innovative mobile health system with adaptive biofeedback mechanism and demonstrates the importance of biofeedback in accurate measurements of physiological parameters to facilitate the diagnosis in mobile health systems. Resting Metabolic Rate (RMR) assessment, a key aspect in the treatment of diet related health problems is considered as a model to demonstrate the importance of adaptive biofeedback in mobile health. A breathing biofeedback mechanism has been implemented with digital signal processing techniques for real-time visual and musical guidance to accurately measure the RMR. The effects of adaptive biofeedback with musical and visual guidance were assessed on 22 healthy subjects (12 men, 10 women). Eight RMR measurements were taken for each subject on different days under same conditions. It was observed the subjects unconsciously followed breathing biofeedback, yielding consistent and accurate measurements for the diagnosis. The coefficient of variation of the measured metabolic parameters decreased significantly (p < 0.05) for 20 subjects out of 22 subjects. / Dissertation/Thesis / M.S. Electrical Engineering 2012

Contact-less human detection and monitoring using radar technology has been recently applied in many areas including search-and-rescue for earthquake victims, fall detection, gait analysis and detection of other human activities. Radars can also provide important information about a persons state of health by monitoring the level of activities, heart and breathing rate. Also it can be used to generate warnings if some of the monitored parameters are outside of predefined limits. The major application of this work is for monitoring in-mates and their activities. This thesis deals with characterizing the performance of the radar system used for monitoring a single person in a contained environment. This thesis is experimentally based and during the thesis a large number of experiments were performed in order to monitor subjects in realistic conditions. The thesis explores feasibility of using the radar with a single radio-frequency channel input and two algorithms for breathing and heart rate estimation when the subject is at different relative orientation towards the radar as well as in different postures. Algorithm one is using Fast Fourier Transformation (FFT) and algorithm two is using Empirical Mode Decomposition (EMD) with Minkowski distance. We also detect the zones where the subject is when the subject is moving. Since this exploratory analysis provides initial features for classifications and algorithms for breathing and heart beat estimation, it can represent a foundation for future works on designing systems that track subjects and their breathing in real-time.

This work explores the use of a commodity ultra-wideband (UWB) radar based device to detect breathing rate for health monitoring applications. Health monitoring devices observe physiological signals to detect medical conditions. We focus on capturing the small mechanical movements caused by breathing. This is traditionally done via a strain gauge worn around the chest or stomach, but these systems limit user movement. Contactless systems provide a unique design that allows free user movement by eliminating all direct contact with the user. Additionally, these systems have the potential to support full health monitoring in a Smart Built Environment (SBE). In this work, a comparative evaluation is performed on a commodity UWB radar based device, the Walabot, to determine the accuracy and possible health monitoring applications. Based on results from a systematic review, six research challenges were identified: (1) high cost, functional limitations based on the user's (2) location, (3) orientation, and (4) movement, (5) dependency on system hardware placement, and (6) vulnerabilities in signal processing methods. A comparative evaluation was designed to test the Walabot against a medical grade wearable system in the context of these research challenges. The data was processed using two breathing rate derivation techniques: Fast Fourier Transformation (FFT) and Peak Detection. Results suggest great potential for the Walabot coupled with the FFT technique. However, the system requires further testing to address all of the research challenges. Overall, this work provides important steps toward using the Walabot in health monitoring applications. / Master of Science / The goal of research in the field of health monitoring is to gather medical information about a user by constantly collecting physiological signals emitted by their body. Four physiological signals are deemed the "vital signs" because they provide information about the overall health of the patient. These vital signs are heart rate, breathing rate, temperature and blood pressure. Breathing rate is an important vital sign that, when monitored closely, can indicate the oncoming of dangerous health conditions and events. The act of breathing causes the chest to expand and contract. This movement can be captured by placing a strain gauge around a user's chest and analyzing fluctuation in strain readings. However, this is not practical for health monitoring applications because this system is uncomfortable to wear and the accuracy of the system is heavily dependent on the user's ability to wear the chest band constantly and correctly. Capturing this signal without any direct user contact would eliminate the user's discomfort and provide better reliability. This can be done by several methods, but the focus of this work is on systems that capture chest movements using ultra-wideband (UWB) radar. In this work, a specific UWB radar based device, called the Walabot, is tested against a standard strain gauge system to determine if it has health monitoring applications. Other radar based devices that aim to detect breathing rate are limited by their high cost and inaccuracies in signal processing techniques. The functionality of the devices are also dependent on the user's location and body orientation relative to the system, any user movement and the placement of the system itself. The study in this work was designed to determine the Walabot accuracy when the data is processed by two common breathing rate derivation methods. Results showed that the Walabot is cost effective and flexible in terms of user location and system placement. Overall, this work demonstrates the potential of the Walabot as a breathing rate monitor.

Accurate assessment of a child’s health is critical for appropriate allocation of medical resources and timely delivery of healthcare in both primary care (GP consultations) and secondary care (ED consultations). Serious illnesses such as meningitis and pneumonia account for 20% of deaths in childhood and require early recognition and treatment in order to maximize the chances of survival of affected children. Due to time constraints, poorly defined normal ranges, difficulty in achieving accurate readings and the difficulties faced by clinicians in interpreting combinations of vital signs, vital signs are rarely measured in primary care and their utility is limited in emergency departments. This thesis aims to develop a monitoring and data fusion system, to be used in both primary care and emergency department settings during the initial assessment of children suspected of having a serious infection. The proposed system relies on the photoplethysmogram (PPG) which is routinely recorded in different clinical settings with a pulse oximeter using a small finger probe. The most difficult vital sign to measure accurately is respiratory rate which has been found to be predictive of serious infection. An automated method is developed to estimate the respiratory rate from the PPG waveform using both the amplitude modulation caused by changes in thoracic pressure during the respiratory cycle and the phenomenon of respiratory sinus arrhythmia, the heart rate variability associated with respiration. The performance of such automated methods deteriorates when monitoring children as a result of frequent motion artefact. A method is developed that automatically identifies high-quality PPG segments mitigating the effects of motion on the estimation of respiratory rate. In the final part of the thesis, the four vital signs (heart rate, temperature, oxygen saturation and respiratory rate) are combined using a probabilistic framework to provide a novelty score for ranking various diagnostic groups, and predicting the severity of infection in two independent data sets from two different clinical settings.

De nos jours, la détection et la mesure de la distance avec les ondes électromagnétiques (Radar) sont utilisées dans de nombreux domaines tels que l’aéronautique, l’automobile ou bien la médecine. Dans cette thèse, nous nous intéressons plus particulièrement au Radar dans le domaine du bien-être pour le grand public : capteur sans contact pour le suivi du sommeil, et lunettes ou canne pour malvoyants pour la détection des obstacles sur la route. Le problème posé dans cette thèse est d’ajouter les fonctionnalités nécessaires suivantes à la solution Radar existante afin de répondre à ces applications : la mesure du rythme respiratoire issu du déplacement de la cage thoracique et de l'abdomen de quelques millimètres pendant la respiration et la mesure de la direction d'arrivée de l'onde électromagnétique rétro-diffusée des obstacles devant le malvoyant. Le contexte technologique de départ est celui de la technologie ultra large bande qui offre une résolution de l’ordre du centimètre pour la mesure de distance à une portée de quelques mètres et la discrimination des signaux rétro-diffusés des multiples obstacles. Suivant les besoins, les travaux décrits ici se sont concentrés sur le canal de propagation en rétro-diffusion sur corps humain. Ils se sont aussi portés sur les techniques de traitement du signal pour pouvoir estimer le rythme respiratoire dans le signal rétro-diffusé du corps humain, et sur l'estimation de la direction d'arrivée de l'onde à un réseau d'antennes avec une résolution au degré près. Enfin, cette thèse aborde l’architecture du système, et notamment du récepteur associé au réseau d'antennes, afin de pouvoir réaliser la mesure angulaire sans augmenter la complexité, le coût et la consommation du récepteur. / Detection and ranging with electromagnetic waves (Radar) are used in a number of domains such as aeronautics, automobile or even medecin. In this thesis, we are interested particularly on Radar in the wellness domain for widely use: sleep pattern tracking sensors, smart glasses or white cane with obstacles detection for visually impaired people. The problem, which so far has not been discussed, is to add necessary functionalities as follow to the exciting solution to resolve theses applications: the thoracic and abdominal displacement tracking with a millimetric resolution; and the measurements of arrival direction of backscattered signals from obstacles in front of visually impaired individuals. The technological starting point is the one of Ultra Wideband (UWB) technology, which offers a resolution of approximate one centimeter in the distance measurement within the range of few meters and in the discrimination of backscattered signals from multiple obstacles. To meet these criterias, the research focuses on the backscattering propagation channel in particularly from the human body. It also analyses the techniques in signal processing, aiming to estimate the breathing rate in the backscattered signal of human body, and to estimate the arrival direction to an antenna array to nearly one degree. Finally, it investigates the systematic architecture, especially in the receiver associated with the antenna array, in order to withstand the angular measurement without notably increasing the receiver complexity and consumption.

This thesis describes a novel method to reversibly and safely block nerve conduction using a low frequency alternating current (LFAC) waveform at 1 Hz applied through a bipolar extrafascicular electrode. This work follows up on observations made on excised mammalian peripheral nerves and earthworm nerve cords. An<i> in-situ</i> electrophysiology setup was used to assess the LFAC<br>waveform on propagating action potentials (APs) within the cervical vagus nerve in anaesthetized Sprague-Dawley rats (n = 12). Two sets of bipolar cuff or hook electrodes were applied unilaterally to the cervical vagus nerve, which was crushed rostral to the electrodes to exclude reflex effects<br>on the animal. Pulse stimulation was applied to the rostral electrode, while the LFAC conditioning waveform was applied to the caudal electrode. The efferent volley, if unblocked, elicits acute bradycardia and hypotension. The degree of block of the vagal stimulation induced bradycardia<br>was used as a biomarker. Block was assessed by the ability to reduce the bradycardic drive by monitoring the heart rate (HR) and blood pressure (BP) during LFAC alone, LFAC with vagal stimulation, and vagal stimulation alone. LFAC applied via a hook electrode (n = 7) achieved 86.6 +/- 11% block at current levels 95 +/- 38 uAp (current to peak). When applied via a cuff electrode (n = 5) 85.3 +/- 4.60% block was achieved using current levels of 110 +/- 65 uAp. Furthermore, LFAC was explored on larger vagal afferent fibers in larger human sized nerve bundles projecting to effects mediated by a reflex. The effectiveness of LFAC was assessed in an <i>in-situ</i> electrophysiological setup on the left cervical vagus in anaesthetized domestic swine (n = 5). Two bipolar cuff electrodes were applied unilaterally to the cervical vagus nerve, which was crushed caudal to the electrodes to eliminate cardiac effects. A tripolar extrafascicular cuff electrode was placed most rostral on the nerve for recording of propagating APs induced by<br>electrical stimulation and blocked via the LFAC waveform.<br>Standard pulse stimulation was applied to the left cervical vagus to induce the Hering-Breuer reflex. If unblocked, the activation of the Hering-Breuer reflex would cause breathing to slow down and potentially cease. Block was quantified by the ability to reduce the effect of the Hering-Breuer<br>reflex by monitoring the breathing rate during LFAC alone, LFAC and vagal stimulation, and vagal stimulation alone. LFAC achieved 87.2 +/- 8.8% (n = 5) block at current levels of 0.8 +/- 0.3 mAp. Compound nerve action potentials (CNAP) were monitored directly. They show changes<br>in nerve activity during LFAC, which manifests itself as the slowing and amplitude reduction of components of the CNAPs. Since the waveform is balanced, all forward reactions are reversed, leading to a blocking method that is similar in nature to DC block without the potential issues of<br>toxic byproduct production. These results suggest that LFAC can achieve a high degree of nerve block in both small and large nerve bundles, resulting in the change in behavior of a biomarker, <i>in-vivo </i>in the mammalian nervous system at low amplitudes of electrical stimulation that are within the water window of the electrode.<br>