Dissertations / Theses on the topic 'Thermoregulation of the human body'

A human thermoregulation model has been adapted for predicting the thermal response of Typical Older Persons. The model known as the Older Persons Model predicts the core body temperature and regulatory responses of the older people in environmental exposures of cold, warm and hot. The model was developed by modifying an existing dynamic human thermoregulation model using anthropometric and thermo-physical properties of older people. The Model defines the body as two interrelating systems of the body structure (passive system) and the control system of the central nervous system (active system). The Older person's passive system of the model was developed by meticulously extracting relevant experimental data from selected published research works relating to anthropometric and thermo-physical properties of older people. The resultant body structure (passive system) is a multi-segmented representation of a Typical Older Person. The active system (central nervous system) was developed by the application of a novel optimization method based on the working principles of Genetic Algorithms. The use of Genetic Algorithm enables the complex characteristics of the central nervous system of the older persons to be well represented and evaluated based on available data. Active system control signal coefficients for sweating, shivering, vasodilation and vasoconstriction were explicitly derived based on experimental data sourced from literature. The Older Persons Model has been validated using independent experimental data and its results show good agreement with measured data. Furthermore, the Older Persons Model has been applied to several test cases extracted from published literature and its results show good agreement with published findings on the thermal behaviour of older persons. An interview study conducted as part of this research revealed that, professionals (built environment specialists) found the Older Persons Model useful in assisting to further understand the thermal response of the older persons. In conclusion, the adaptation of an existing human thermoregulation model has resulted in a new model, which allows improved prediction of heat and cold strain of the older person although there exist limitations.

xvii, 174 p. : ill. A print copy of this thesis is available through the UO Libraries. Search the library catalog for the location and call number.
During acute altitude exposure, humans maintain higher skin temperature and lower core body temperature. However, the role of cutaneous vascular regulation in these thermoregulatory differences is unclear. Therefore, the purpose of these studies was to investigate the impact of altitude exposure on reflex control of skin blood flow and core temperature during cold exposure. In Chapter IV, the effects of hypoxia and hypocapnia on cutaneous vasoconstriction during mild cold exposure were investigated. We found that hypoxia stimulates cutaneous vasodilation in men whereas skin blood flow is unaltered in women. However, during whole body cooling skin blood flow is upward shifted in both sexes. The development of hypocapnia does not affect the vascular response to hypoxia in either sex, but reduces the magnitude of cutaneous vasoconstriction during cold exposure by 50% in women. In Chapter V, we studied the timecourse of α-adrenergic blockade by yohimbine in the cutaneous circulation and how the duration of cold exposure modulates cotransmitter-mediated vasoconstriction during cold stress. We found that yohimbine produces functional α-adrenergic blockade within 30 minutes of initial delivery and completely abolishes reflex cutaneous vasoconstriction during mild cold stress. This latter finding was surprising, and an additional protocol demonstrated that cotransmitter-mediated vasoconstriction only participates in the vascular response to cold stress when the exposure is more prolonged. In Chapter VI, the effects of hypoxia on cutaneous vasoconstrictor mechanisms and core cooling rate were tested during more prolonged and severe cold stress. In contrast to our findings during brief cold exposure, we showed that cutaneous vasoconstriction during prolonged cold stress is potentiated by hypoxia and abolishes hypoxic vasodilation. Moreover, increased cotransmitter-mediated vasoconstriction appears to account for this response. Hypoxia had no effect on core cooling rate during severe cold exposure. The selective potentiation of cotransmitter-mediated vasoconstriction observed during hypoxia in Chapter VI provided the basis for Chapter VII. This study was designed to test the effect of hypoxia on cutaneous vascular responsiveness to peripherally stimulated sympathetic vasoconstriction. The results demonstrated that α-adrenergic vasoconstrictor transduction is not affected by hypoxia, and that stimulation of adrenergic nerves with tyramine does not elicit cotransmitter-mediated vasoconstriction in skin.
Adviser: John R. Halliwill

Exercise and/or heat-induced dehydration is associated with decreases in plasma volume (hypovolemia) and increases in plasma osmolality (hyperosmolality), which are thought to stimulate peripheral baroreceptors and central osmoreceptors respectively. Independently, plasma hyperosmolality and baroreceptor unloading have been shown to attenuate sweating and cutaneous vasodilation during heat stress, and therefore, negatively impact body temperature regulation. However, to date little is known regarding the combined influence of plasma hyperosmolality and baroreceptor unloading on thermoefferent activity. Therefore, we evaluated the separate and combined effects of baroreceptor unloading (via lower body negative pressure, LBNP) and plasma hyperosmolality (via infusion of 3% NaCl saline) on heat loss responses of sweating and cutaneous vascular conductance (CVC) during progressive whole-body heating. We show that the combined nonthermal influences of plasma hyperosmolality and baroreceptor unloading additively delay the onset threshold for CVC, relative to their independent effects. In contrast, baroreceptor unloading has no influence on the sweating response regardless of osmotic state. These divergent roles of plasma hyperosmolality and the baroreflex on heat loss responses might serve to enhance blood pressure and body core temperature regulation during dehydration and heat stress.

Ingestion of cold (<10°C) compared to warm (>37°C) fluid has been suggested to attenuate heat storage levels during exercise. However, modulations in sweat output may yield differences in evaporative heat loss that are greater than differences in heat transfer with the ingested fluid. The purpose of the thesis was to evaluate thermoregulatory control and human heat balance, and compare thermometrically derived values of heat storage with those derived from partitional calorimetry following water ingestion of varying temperature during exercise. We found that water ingestion of 50°C compared to 1.5°C decreases heat storage in thermoneutral environments, and further exacerbates the error of thermometric heat storage estimations. Differences in heat storage were attributed exclusively to disproportionate reductions in whole-body and local sweat output and thus evaporative heat loss potential. Ingested fluid temperature only minimally altered skin blood flow and did not influence dry heat exchange with the ambient environment.

The current thesis examined whether sex-differences in local and whole-body heat loss are evident after accounting for confounding differences in physical characteristics and rate of metabolic heat production. Three experimental studies were performed: the first examined whole-body heat loss in males and females matched for body mass and surface area during exercise at a fixed rate of metabolic heat production; the second examined local and whole-body heat loss responses between sexes during exercise at increasing requirements for heat loss; the third examined sex-differences in local sweating and cutaneous vasodilation to given doses of pharmacological agonists, as well as during passive heating. The first study demonstrates that females exhibit a lower whole-body sudomotor thermosensitivity (553 ± 77 vs. 795 ± 85 W•°C-1, p=0.05) during exercise performed at a fixed rate of metabolic heat production. The second study shows that whole-body sudomotor thermosensitivity is similar between sexes at a requirement for heat loss of 250 W•m-2 (496 ± 139 vs. 483 ± 185 W•m-2•°C-1, p=0.91) and 300 W•m-2 (283 ± 70 vs. 211 ± 66 W•m-2•°C-1, p=0.17), only becoming greater in males at a requirement for heat loss of 350 W•m-2 (197 ± 61 vs. 82 ± 27 W•m-2•°C-1, p=0.007). In the third study, a lower sweat rate to the highest concentration of acetylcholine (0.27 ± 0.08 vs. 0.48 ± 0.13 mg•min-1•cm-2, p=0.02) and methylcholine (0.41 ± 0.09 vs. 0.57 ± 0.11 mg•min-1•cm-2, p=0.04) employed was evidenced in females, with no differences in cholinergic sensitivity. Taken together, the results of the current thesis show that sex itself can modulate sudomotor activity, specifically the thermosensitivity of the response, during both exercise and passive heat stress. Furthermore, the results of the third study point towards a peripheral modulation of the sweat gland as a mechanism responsible for the lower sudomotor thermosensitivity in females.

This thesis presents an efficient and biologically informed 3D human body morphing technique through data-driven alteration of standardized 3D models. The anthropometric data is derived from a large empirical database and processed using principal component analysis (PCA). Although techniques using PCA are relatively commonplace in computer graphics, they are mainly used for scientific visualizations and animation. Here we focus on uncovering the underlying mathematical structure of anthropometric data and using it to build an intuitive interface that allows the interactive manipulation of body shape within the normal range of human variation. We achieve weight/gender based body morphing by using PCA. First we calculate the principal vector space of the original data. The data then are transformed into a new orthogonal multidimensional space. Next, we reduce the dimension of the data by only keeping the components of the most significant principal vectors. We then fit a curve through the original data points and are able to generate a new human body shape by inversely transforming the data from principal vector space back to the original measuring data space. Finally, we sort the original data by the body weight, calculating males and females separately. This enables us to use weight and gender as two intuitive controls for body morphing. The Deformer program is implemented using the programming language C++ with OPENGL and FLTK API. 3D and human body models are created using Alias MayaTm.

Thesis (MSc) -- University of Stellenbosch, 2003.
ENGLISH ABSTRACT: A need for intelligent robotic machines is identified. Research and experiments have focussed on stable, or relatively stable, dynamic simulated systems to demonstrate the feasibility of embedding advanced AI into dynamic physical systems. This thesis presents an attempt to scale the techniques to a dynamically highly unstable system - the coordination of movements in a humanoid model. Environmental simulation, articulated systems and artificial intelligence methods are identified as three essential layers for a complete and unified approach to embedding AI into robotic machinery. The history of the physics subsystem for this project is discussed, leading to the adoption of the Open Dynamics Engine as the physics simulator of choice. An approach to articulated systems is presented along with the EBNF of a hierarchical articulated system that was used to describe the model. A revised form of evolution is presented and justified. An AI model that makes use of this new evolutionary paradigm is introduced. A variety of AI variants are defined and simulated. The results of these simulations are presented and analysed. Based on these results recommendations for future work are made.
AFRIKAANSE OPSOMMING: Die beheer van dinamiese masjiene, soos intelligente robotte, is tans beperk tot fisies stabilie - of relatief stabiele - sisteme. In hierdie tesis word die tegnieke van kunsmatige intelligensie (KI) toegepas op die kontrole en beheer van 'n dinamies hoogs onstabiele sisteem: 'n Humanoïede model. Fisiese simulasie, geartikuleerde sisteme en kunmatige intelligensie metodes word geïdentifiseer as drie noodsaaklike vereistes vir 'n volledige en eenvormige benadering tot KI beheer in robotte. Die implementasie van 'n fisiese simulator word beskryf, en 'n motivering vir die gebruik van die sogenaamde "Open Dynamics Engine" as fisiese simulator word gegee. 'n Benadering tot geartikuleerde sisteme word beskryf, tesame met die EBNF van 'n hierargiese geartikuleerde sisteem wat gebruik is om die model te beskryf. 'n Nuwe interpretasie vir evolusie word voorgestel, wat die basis vorm van 'n KI model wat in die tesis gebruik word. 'n Verskeidenheid van KI variasies word gedefineer en gesimuleer, en die resultate word beskryf en ontleed. Voorstelle vir verdere navorsing word gemaak.

Human Body Communication (HBC) is a novel communication method between devices which use human body as a transmission medium. This idea is mostly based on the concept of wireless biomedical monitoring system. The on-body sensor nodes can monitor vital signs of a human body and use the body as a transmission medium. This technology is convenient for long durations of clinical monitoring with the option of more mobility and freedom for the user. In this thesis, IEEE 802.15.6-2012 physical (PHY) layer for the HBC was simulated. Simulation model is following the standard’s requirements and processes. The human body was taken as a transmission medium and simulations, which follow the HBC standard, have been carried out. For the purpose of simulations, MATLAB is used as a platform to test and run the simulations. The constants and variables used in the simulations are taken from the IEEE 802.15 working group for wireless personal area networks (WPANs). The transmitter model and the receiver model have been taken from the standard, with changes done in it for performing the simulations on the PHY layer only. The simulations were done keeping in mind the dielectric properties of the outer layer of a human body, i.e., the dielectric values for human skin are noted and their corresponding values were used in the mathematical calculations. The work done here presents a transmitter and receiver architecture for the human body communication. The minimum data rate being 164 kbps and the transmitter being designed around the 21 MHz center frequency has achieved some outputs which are worth looking. The channel models used in this simulator are HBC channel and AWGN (additive white Gaussian noise) channel. It was observed that when signal was passed through AWGN channel, noise was added uniformly over the signal, while in the HBC channel signal strength is directly proportional to the transceiver ground sizes. In conclusion, the size of the ground terminals plays a critical role for the signal quality in the HBC simulator. The results in this thesis show that pathloss has certain linearity with the distance. The pathloss is calculated for different parts of the body with higher loss for structure with higher amount of bone, and vice versa. It is observed that in the HBC channel there are four factors with high impact on the system. These are the distances between the transceiver in air and on body while the other two are the sizes of the transceiver grounds. The size of the transmitter ground has been deemed very significant for the HBC from the simulations results. The four factors show high impact on the HBC channel. The signal strength is highly effected with the change in these four characteristics. From the simulation results it is evident that the HBC channel show a 15 to 20 dB deviation when compared to AWGN channel. The Eb⁄N0 for BER level at 10^(-3) for AWGN channel is 10 to 11 dB while for HBC it is around 27 dB showing a significant difference in the results.

Previous research has demonstrated that ingesting fluid of different temperatures results in different whole-body sweat losses (WBSL) and transient changes in local sweat rate (LSR) without any parallel differences in core or skin temperatures. The purpose of this thesis was to determine the potential location and relative contribution of gastrointestinal thermoreceptors that modify sudomotor activity. Eight participants cycled for 75 min while cold (1.5°C) and warm (50°C) water was either swilled in the mouth, or delivered directly to the stomach bypassing the mouth using a nasogastric tube, after 15, 30 and 45-min of exercise. Mouth-swilling warm or cold water did not alter sudomotor output, however delivering warm or cold water directly into the stomach led to a temperature-dependent change in sudomotor output, despite similar core and skin temperatures. These data indicate that thermoreceptors independently modulating sudomotor output probably reside within the abdominal area, but not the mouth.

In the Inca Empire, the human body served as a symbol and mediator of cosmic structures and processes through its own structures and processes. The structures of the body with cosmological relevance included the duality of right and left and the integrated unity of the body as a whole, while the processes of the body included reproduction, illness and sensory perception. Inca myths and rituals both expressed and enacted this corporeal and cosmic order.
With the arrival of the Spanish, the Incas were confronted with a radically different image of the body and the cosmos. The clash between the Spanish and Inca orders was experienced by the Incas as a disordering of the human and cosmic bodies. While the Spanish Conquest destroyed the Inca empire and imposed a new culture on its former inhabitants, however, many of the principles which ordered and interrelated the body and the cosmos in Inca cosmology have survived in the Andes to the present day.

Human body analysis is one of the broadest areas within the computer vision field. Researchers have put a strong effort in the human body analysis area, specially over the last decade, due to the technological improvements in both video cameras and processing power. Human body analysis covers topics such as person detection and segmentation, human motion tracking or action and behavior recognition. Even if human beings perform all these tasks naturally, they build-up a challenging problem from a computer vision point of view. Adverse situations such as viewing perspective, clutter and occlusions, lighting conditions or variability of behavior amongst persons may turn human body analysis into an arduous task. In the computer vision field, the evolution of research works is usually tightly related to the technological progress of camera sensors and computer processing power. Traditional human body analysis methods are based on color cameras. Thus, the information is extracted from the raw color data, strongly limiting the proposals. An interesting quality leap was achieved by introducing the multiview concept. That is to say, having multiple color cameras recording a single scene at the same time. With multiview approaches, 3D information is available by means of stereo matching algorithms. The fact of having 3D information is a key aspect in human motion analysis, since the human body moves in a three-dimensional space. Thus, problems such as occlusion and clutter may be overcome with 3D information. The appearance of commercial depth cameras has supposed a second leap in the human body analysis field. While traditional multiview approaches required a cumbersome and expensive setup, as well as a fine camera calibration; novel depth cameras directly provide 3D information with a single camera sensor. Furthermore, depth cameras may be rapidly installed in a wide range of situations, enlarging the range of applications with respect to multiview approaches. Moreover, since depth cameras are based on infra-red light, they do not suffer from illumination variations. In this thesis, we focus on the study of depth data applied to the human body analysis problem. We propose novel ways of describing depth data through specific descriptors, so that they emphasize helpful characteristics of the scene for further body analysis. These descriptors exploit the special 3D structure of depth data to outperform generalist 3D descriptors or color based ones. We also study the problem of person detection, proposing a highly robust and fast method to detect heads. Such method is extended to a hand tracker, which is used throughout the thesis as a helpful tool to enable further research. In the remainder of this dissertation, we focus on the hand analysis problem as a subarea of human body analysis. Given the recent appearance of depth cameras, there is a lack of public datasets. We contribute with a dataset for hand gesture recognition and fingertip localization using depth data. This dataset acts as a starting point of two proposals for hand gesture recognition and fingertip localization based on classification techniques. In these methods, we also exploit the above mentioned descriptor proposals to finely adapt to the nature of depth data.%, and enhance the results in front of traditional color-based methods.
L’anàlisi del cos humà és una de les àrees més àmplies del camp de la visió per computador. Els investigadors han posat un gran esforç en el camp de l’anàlisi del cos humà, sobretot durant la darrera dècada, degut als grans avenços tecnològics, tant pel que fa a les càmeres com a la potencia de càlcul. L’anàlisi del cos humà engloba varis temes com la detecció i segmentació de persones, el seguiment del moviment del cos, o el reconeixement d'accions. Tot i que els essers humans duen a terme aquestes tasques d'una manera natural, es converteixen en un difícil problema quan s'ataca des de l’òptica de la visió per computador. Situacions adverses, com poden ser la perspectiva del punt de vista, les oclusions, les condicions d’il•luminació o la variabilitat de comportament entre persones, converteixen l’anàlisi del cos humà en una tasca complicada. En el camp de la visió per computador, l’evolució de la recerca va sovint lligada al progrés tecnològic, tant dels sensors com de la potencia de càlcul dels ordinadors. Els mètodes tradicionals d’anàlisi del cos humà estan basats en càmeres de color. Això limita molt els enfocaments, ja que la informació disponible prové únicament de les dades de color. El concepte multivista va suposar salt de qualitat important. En els enfocaments multivista es tenen múltiples càmeres gravant una mateixa escena simultàniament, permetent utilitzar informació 3D gràcies a algorismes de combinació estèreo. El fet de disposar d’informació 3D es un punt clau, ja que el cos humà es mou en un espai tri-dimensional. Això doncs, problemes com les oclusions es poden apaivagar si es disposa de informació 3D. L’aparició de les càmeres de profunditat comercials ha suposat un segon salt en el camp de l’anàlisi del cos humà. Mentre els mètodes multivista tradicionals requereixen un muntatge pesat i car, i una celebració precisa de totes les càmeres; les noves càmeres de profunditat ofereixen informació 3D de forma directa amb un sol sensor. Aquestes càmeres es poden instal•lar ràpidament en una gran varietat d'entorns, ampliant enormement l'espectre d'aplicacions, que era molt reduït amb enfocaments multivista. A més a més, com que les càmeres de profunditat estan basades en llum infraroja, no pateixen problemes relacionats amb canvis d’il•luminació. En aquesta tesi, ens centrem en l'estudi de la informació que ofereixen les càmeres de profunditat, i la seva aplicació al problema d’anàlisi del cos humà. Proposem noves vies per descriure les dades de profunditat mitjançant descriptors específics, capaços d'emfatitzar característiques de l'escena que seran útils de cara a una posterior anàlisi del cos humà. Aquests descriptors exploten l'estructura 3D de les dades de profunditat per superar descriptors 3D generalistes o basats en color. També estudiem el problema de detecció de persones, proposant un mètode per detectar caps robust i ràpid. Ampliem aquest mètode per obtenir un algorisme de seguiment de mans que ha estat utilitzat al llarg de la tesi. En la part final del document, ens centrem en l’anàlisi de les mans com a subàrea de l’anàlisi del cos humà. Degut a la recent aparició de les càmeres de profunditat, hi ha una manca de bases de dades públiques. Contribuïm amb una base de dades pensada per la localització de dits i el reconeixement de gestos utilitzant dades de profunditat. Aquesta base de dades és el punt de partida de dues contribucions sobre localització de dits i reconeixement de gestos basades en tècniques de classificació. En aquests mètodes, també explotem les ja mencionades propostes de descriptors per millor adaptar-nos a la naturalesa de les dades de profunditat.

Most efforts to recognise emotions from the human body have focused on expressive gestures which are archetypal and exaggerated expressions of emotions. The principal contribution of this dissertation is the influence of emotional states from everyday actions such as walking, knocking and throwing. The implementation of the system draws inspiration from a variety of disciplines including psychology, character animation and speech recognition. Complex actions are modelled using Hidden Markov Models and motion primitives. This dissertation describes a holistic approach which models emotional, action and personal influences in order to maximise the discriminability of different emotion classes. A pipeline is developed which incrementally removes the biases introduced by different action contexts and individual differences. The resulting signal is described in terms of posture and dynamic features and classified into one of several emotion classes using statistically trained Support Vector Machines. The system also goes beyond isolated expressions and is able to classify natural action sequences. I use Level Building to segment action sequences and combine component classifications using an incremental voting scheme which is suitable for online applications. The system is comprehensively evaluated along a number of dimensions using a corpus of motion-captured actions. For isolated actions I evaluate the generalisation performance to new subjects. For action sequences I study the effects of reusing models trained on the isolated cases vs. adapting models to connected samples. The dissertation also evaluates the role of modelling the influence of individual user differences.

This thesis provides results from affinity based studies where human body fluids were profiled to find markers for neurological diseases. Both proteins and autoantibodies were analysed using microarray technologies that can profile hundreds of analytes and hundreds of samples in parallel using small sample volumes. A central element in this work was to develop and apply new methods to study cerebrospinal fluid (CSF), which is the fluid in direct contact with the brain. CSF contains proteins reflecting the physiological state of the central nervous system and therefore offers a unique insight into proteins associated to neurological disorders. As a complement to CSF, bloodderived samples such as serum and plasma, were also investigated as these represent potential sources of disease related proteins. The work presented here summarises the development of assay protocols to study protein and autoantibodies in CSF and blood using planar and bead-based microarrays. In Paper I, an antibody-based protocol was developed to enable multiplexed protein profiling in CSF. The protocol was then applied for a first analysis within multiple sclerosis (MS) patients. In Paper II, the results were further evaluated in additional CSF as well as plasma samples. Based on the CSF analysis we found two proteins associated to MS; GAP43, a protein related to disease progression and SERPINA3, a protein involved in inflammation. In addition, four other proteins; IRF8, METTL14, IL7 and SLC30A7, were found to have altered plasma levels between the patient groups. The expression of these proteins were further investigated by immunofluorescent staining of human brain tissue, revealing differential localisation of proteins in diseased and healthy brain. In Paper III, a study on extensive protein profiling of plasma in the context of another neurodegenerative disorder, amyotrophic lateral sclerosis (ALS), is described. The levels of three proteins, namely NEFM, RGS18 and SCL25A20, were found to be elevated in ALS patients compared to controls. Among these, NEFM also indicated association to disease subtype as the levels were elevated in patients with definite compared to suspected diagnosis. In addition to antibodies, we also utilised antigens on microarrays to screen for the presence of autoantibodies in body fluids. In Paper IV, a strategy for this analysis was developed using protein fragments and two types of microarrays. This strategy was then applied for profiling of the autoantibody repertoire of MS patients, revealing 51 protein fragments with potential disease relevance. Interestingly, comparison of plasma and CSF samples obtained from the same patients indicated high concordance of antibodies between the two body fluids. In Paper V, a similar strategy was applied to narcolepsy, another neurological disorder. Our investigation of antibodies in serum revealed higher reactivity towards METTL22, NT5C1A and TMEM134 compared to controls in two independent sample materials. In conclusion, the presented work constitutes a framework of proteomic assays for enhanced exploration of proteins and autoantibodies in neuroscience. Moreover, we have reported identification of several potential disease markers to be further investigated within neurological disorders.

QC 20150116

Perceiving other people is a seemingly effortless process. Yet within a few hundred milliseconds we are aware of who we are looking at, what this person is doing, and even what this person feels. We derive this information from the form and motion of the face and body. Faces may be particularly important for some aspects of person perception (e. g., identity recognition), whereas bodies may be more important for others (e. g., action recognition). Furthermore, information from the body is important in cases where it is not possible to perceive the details of the face, for instance when the face is occluded, or when we see someone from a distance. In most cases, however, it is likely that information from both the face and the body are perceived in parallel and are integrated at an early stage. Previous research on person perception has mostly focused on the brain mechanisms underlying face perception. Much less research has focused on the brain mechanismsu nderlying body perception,w hich is the topic of this thesis. Using functional magnetic resonance imaging (fMRI) I provide evidence for a previously unknown body-selective visual area that overlaps a face-selective area. By employing novel analysis techniques that take into account patterns of activation across voxels I show that body- and face-selective areas can be functionally dissociated. Finally, I show that, in contrast to frontal and parietal action-recognition areas, visual body-selective areasd o not contain a dynamic representationo f observeda ctions. Together, thesef indings increaseo ur understandingo f the brain mechanismsu nderlying body, face and action perception, by showing both similarities and dissimilarities in the brain structures involved in these processes.

The objective of this project is to use digital imaging devices to monitor a delineated area of the public space and to register statistics about people moving across this area. A feasible detecting approach, which is based on background subtraction, has been developed and has been tested on 39 images. Individual pedestrians in images can be detected and counted. The approach is suitably used to detect and count pedestrians without overlapping. Accuracy rate of detection is higher than 80%.

Wireless capsule endoscopy (WCE) offers a patient-friendly, non-invasive and painless investigation of the entire small intestine, where other conventional wired endoscopic instruments can barely reach. As a critical component of the capsule endoscopic examination, physicians need to know the precise position of the endoscopic capsule in order to identify the position of intestinal disease after it is detected by the video source. To define the position of the endoscopic capsule, we need to have a map of inside the human body. However, since the shape of the small intestine is extremely complex and the RF signal propagates differently in the non-homogeneous body tissues, accurate mapping and localization inside small intestine is very challenging. In this dissertation, we present an in-body simultaneous localization and mapping technique (Body-SLAM) to enhance the positioning accuracy of the WCE inside the small intestine and reconstruct the trajectory the capsule has traveled. In this way, the positions of the intestinal diseases can be accurately located on the map of inside human body, therefore, facilitates the following up therapeutic operations. The proposed approach takes advantage of data fusion from two sources that come with the WCE: image sequences captured by the WCE's embedded camera and the RF signal emitted by the capsule. This approach estimates the speed and orientation of the endoscopic capsule by analyzing displacements of feature points between consecutive images. Then, it integrates this motion information with the RF measurements by employing a Kalman filter to smooth the localization results and generate the route that the WCE has traveled. The performance of the proposed motion tracking algorithm is validated using empirical data from the patients and this motion model is later imported into a virtual testbed to test the performance of the alternative Body-SLAM algorithms. Experimental results show that the proposed Body-SLAM technique is able to provide accurate tracking of the WCE with average error of less than 2.3cm.

The measurement of total body volume (V) (excluding lung volume) together with total body mass (m) is required in order to determine body density (d = m/V). From this, and using certain simplifying assumptions, it is possible to derive body composition in terms of fat mass (FM) and fat free mass (FFM) for the two-compartment model. The standard method for determining body volume (and hence body composition) is the densitometric (underwater weighing) technique based on Archimedes' principle. Three variables, notably residual lung volume (RV), total body mass (m) and submerged body mass are measured. RV is normally determined using a gas dilution technique while total body mass is simply measured using an accurate weighing scale. The submerged body mass is measured while the subject is totally submerged in a tank of water. This method, although relatively accurate, requires substantial apparatus and is time consuming. An alternative method, based on a polytropic thermodynamic process, is described for body volume measurement and thereby for body composition assessment. Previous use of this method by Taylor, et al. (1985) and Gundlach and Visscher (1986) were successful, but complex in terms of operating system. The described system comprises of a Perspex, sealed chamber. A cycling piston communicates with the chamber and imposes a minute sinusoidal pressure variation which is then measured. With a subject situated inside the chamber an increased pressure variation, caused by the decreased chamber volume, is then measured and processed to yield the displaced, or body volume. Subject comfort, above all, is greatly enhanced, in comparison to the underwater weighing method. A substantial advantage of the method appears to be that RV need no longer be measured. Variables such as a rise of temperature and humidity caused by the subject, as well as pressure variations due to respiration, were expected and found. These were analyzed both theoretically and experimentally and where necessary the data were modified to account for these variables using a personal computer. Calibration and preliminary validation of the instrument has been carried out using underwater weighing, bioimpedance and skinfold analyses and the error of measurement assessed. It appears that the described plethysmographic method is capable of measuring body volume and thus compares favourably to the underwater weighing method. Even though other groups have succeeded in employing similar principles, a substantially simpler mechanism has been used here.

With the recent developments in Computer Vision and Pattern Recognition, surveillance applications are equipped with the capabilities of event/activity understanding and interpretation which usually require recognizing humans in real world scenes. Real world scenes such as airports, streets and train stations are complex because they involve many people, complicated occlusions and cluttered backgrounds. Although complex real world scenes exist, human detectors have the capability to locate pedestrians accurately even in complex scenes and visual trackers have the capability to track targets in cluttered environments. The integration of visual object detection and tracking, which are the fundamental features of available surveillance applications, is one of the solutions for multi-human tracking problem in crowded scenes which is studied in this thesis. In this thesis, human body part detectors, which are capable of detecting human heads and human upper body parts, are trained with Support Vector Machines (SVM) by using Histogram of Oriented Gradients (HOG), which is one of the state-of-the-art descriptor for human detection. The training process is elaborated by investigating the effects of the parameters of the HOG descriptor. The human heads and upper body parts are searched in the region of interests (ROI) computed by detecting motion. In addition, these human body part detectors are integrated with a multi-human tracker which solves the data association problem with the Multi Scan Markov Chain Monte Carlo Data Association (MCMCDA) algorithm. Associated measurements of human upper body part locations are used for state correction for each track. State estimation is done through Kalman Filter. The performance of detectors are evaluated using MIT Pedestrian dataset and INRIA Human dataset.

Le contenu visuel se concentre souvent sur les humains. L’analyse automatique des humains à partir de données visuelles revêt donc une grande importance pour de nombreuses applications. Le but de cette thèse est d’apprendre des représentations visuelles pour l’analyse des humains. Un accent particulier est mis sur deux domaines étroitement liés de la vision artificielle : l’analyse du corps humain et la reconnaissance des actions. En résumé, nos contributions sont les suivantes : (i) nous générons des données synthétiques photoréalistes de personnes permettant l’entraînement de CNNs pour l’analyse du corps humain, (ii) nous proposons une architecture multitâche permettant d’obtenir une représentation volumétrique du corps à partir d’une seule image, (iii) nous étudions les avantages des convolutions temporelles à long terme pour la reconnaissance de l’action humaine à l’aide de CNNs 3D, (iv) nous incorporons une fonction de coût de similarité des vidéos multi-vues pour concevoir des représentations invariantes au changement de vue
The focus of visual content is often people. Automatic analysis of people from visual data is therefore of great importance for numerous applications in content search, autonomous driving, surveillance, health care, and entertainment. The goal of this thesis is to learn visual representations for human understanding. Particular emphasis is given to two closely related areas of computer vision: human body analysis and human action recognition. In summary, our contributions are the following: (i) we generate photo-realistic synthetic data for people that allows training CNNs for human body analysis, (ii) we propose a multi-task architecture to recover a volumetric body shape from a single image, (iii) we study the benefits of long-term temporal convolutions for human action recognition using 3D CNNs, (iv) we incorporate similarity training in multi-view videos to design view-independent representations for action recognition

Exercise or activity in high ambient temperatures offers a particular challenge to the thermoregulatory system. It is likely that mechanisms such as sweat evaporation alone are not sufficient for maintaining body temperature within a safe limit (~36.5-38.5˚C) and below 40˚C, which may result in impaired physiological function and performance. Exogenous cooling may be of benefit prior to, during and after events that place increased thermal strain due to increased metabolic heat production and elevated environmental temperatures upon the thermoregulatory system. Conversely, in situations where it is not possible to maintain body temperature via either continued physical activity or elevated ambient temperatures, exogenous heating may be required in order to allow optimal physiological performance. Few studies have directly aligned cooling devices with data detailing effective target regions for cooling to allow a pre-cooling garment to be of minimal weight but maximal cooling efficiency. Conversely, no study has considered the effect of muscle temperature maintenance during rest periods on subsequent power-based activities. The aim of this thesis was to determine ways in which body temperature manipulation is capable of improving exercise performance in both power and endurance-based events. It was hypothesised that the manipulation of body temperature will result in subsequent changes in body temperature that would improve performance. Specifically, the use of pre-cooling would result in a reduction of body temperature and improve endurance exercise performance. Conversely, maintaining Tm following warm up completion would have a beneficial effect on sprint and power related performance. Study one set out to determine differences in regional body heat loss in 12 individual anatomical zones using a water perfused suit. Data obtained from this initial study allowed for the specific targeting of regions that were identified as having high rates of heat loss in subsequent studies that focused on pre-cooling and performance. The anatomical regions identified as having high potential affinity for heat exchange with the surrounding environment and cooling devices were the hands, forearms, upper and lower back and torso. Subsequent studies demonstrated that cooling of these areas was capable of lowering thermal sensation and improving thermal comfort prior to and during exercise in moderate environmental conditions (24˚C, 50% RH). In these moderate conditions, there was no statistically significant improvement in treadmill based self-paced 5000m running performance. However, in hot conditions (35˚C 50% RH), the use of a cooling vest and sleeves did yield a significant improvement in cycling time trial performance, which equated to 4.8%. This leads to the suggestion that there may be a threshold ambient temperature, above which pre-cooling becomes an important tool in maximizing performance potential. A parallel area of investigation, on the other side of the temperature spectrum, was the effect of muscle temperature manipulation on power-based exercise performance. The relationship between increased muscle temperature and power output is well established, however little is known about the effect of enforced rest or recovery between two bouts of exercise. Therefore, two studies were conducted to establish what affect a delay between warm up completion and exercise has on muscle temperature and subsequent sprint cycling performance. It was shown that with 30-minutes of rest between exercise bouts wearing tracksuit trousers, muscle temperature declined significantly (~1-1.5˚C). This decline was attenuated with the use of external passive electrical heating during the recovery compared to recovery completed in tracksuit trousers alone. The attenuated decline in muscle temperature following the use of the heated trousers resulted in an improvement in sprint cycling performance (~9%), with the use of insulated trousers having no effect on any variables measured, all relative to wearing tracksuit trousers in the rest period. In a follow-up study, the effect of implementing the heated trousers during the warm up and in addition to the rest period had on muscle temperature increase and sprint performance. A secondary area of investigation in this study was to determine the linearity of muscle temperature decline following warm up cessation. This study demonstrated that there was no additional benefit of combining passive heating with an active warm up on either muscle temperature elevations or subsequent sprint performance compared to the active warm up alone. It was shown that when the no heating was used at any stage, muscle temperature declined exponentially. However, when the heated trousers were used during recovery and/or during warm up, muscle temperature levelled off at a higher value towards the end of the recovery period. This study was also able to show significant improvements in absolute, relative and mean power output following the use of the heated trousers in the warm up and recovery, or the recovery alone. This thesis has identified ways in which body temperature may be manipulated in order to benefit both sprint and endurance exercise performance, using both pre-cooling and active heating. A novel concept for minimizing muscle temperature decline during periods of inactivity between different rounds of competition was shown to maximize sprint performance yielding significant improvements in peak and mean power outputs.