La biométrie se réfère à la reconnaissance automatique des individus. Elle est basée sur leurs caractéristiques physiologiques et/ou comportementales. Le contrôle postural, bien que soit une caractéristique comportementale de l'Homme, n'a pas été bien développée dans le domaine de la biométrie. Le travail mené dans cette thèse repose sur l'analyse des signaux stabilométriques et l'application à la biométrie. Dans un premier volet, une étude de l'information posturale, en particulier le signal stabilométrique, est effectuée à travers des méthodes d'analyses classiques à savoir et l'analyse spatio-temporelle, spectrale et stochastique et à travers aussi deux méthodes de décomposition : la décomposition appelée analyse en composantes principales (ACP) et la décomposition en ondelettes. La méthode ACP, basée sur le modèle additif, permet de décomposer le signal en trois composantes: un signal de tendance, un signal d'excursion et un signal de tremblements. La méthode de décomposition en ondelettes permet de décomposer le signal en trois niveaux de signaux de détail et trois niveaux de signaux d'approximation. Suite à l'étude de la stabilité posturale, l'analyse spectrale et l'analyse de la phase des différentes composantes issues de la ACP et de la décomposition en ondelettes, la comparaison de ces deux méthodes conclut que la méthode ACP est plus appropriée que la décomposition en ondelettes pour analyser le stabilogramme. A partir des méthodes de décomposition et des méthodes d'analyses classiques, des paramètres sont extraits afin d'étudier l'effet de différents facteurs sur la stabilité posturale et sur le déplacement du centre de masse. Ces facteurs sont la vision, la direction, la proprioception, l'âge, le genre, la taille et le poids. Un deuxième volet de ce travail est consacré à l'application biométrique, à partir des paramètres extraits et suite à une analyse statistique ANOVA, ceux qui sont les plus discriminatifs sont utilisés pour identifier des sujets et les classer selon leur âge, genre, poids et taille. Cette application biométrique est effectuée par trois méthodes de classification à savoir, K-ppv, ADL et SVM. Les applications biométriques aboutissent à des taux de reconnaissance respectables dépassant 80%. De ce fait, il est à déduire que l'analyse du contrôle postural est prometteuse dans le domaine de la biométrie / Biometrics refers to automatic recognition of individuals. It is based on their physiological and / or behavioral. The postural control, despite that is a human behavioral characteristic, has not been well developed in the field of biometrics. The work performed in this thesis is based on the stabilometric signals analysis ant biometric application. Firstly, a study of the postural information especially the stabilometric signal is carried out through traditional analysis namely temporal, frequency and stochastic analysis and two decomposition methods named principle components analysis (ACP) decomposition and wavelet decomposition. The ACP method, based on the additive model, allows decomposing the signal into three components: a trend signal, a rambling signal and a trembling signal. The wavelet decomposition method allows decomposing the signal into three levels of detail signals and three signal levels of approximation. Through the study of postural stability, spectral analysis and phase analysis of the different components from the ACP and the wavelet decomposition, the comparison of these two methods concludes that the ACP method is more appropriate than the wavelet decomposition to analyze the stabilogram. From the decomposition methods and classical methods of analysis, several parameters are extracted to study the effect of different factors on postural stability and the center of mass displacement. These factors are named vision, direction, proprioception, age, gender, height and weight. A second aspect of this work is devoted to the application of biometrics, from the extracted parameters and through ANOVA statistic analysis, those that are most discriminative are used to identify subjects and classify them according to age, gender, weight and size. This biometric application is performed by three classification methods namely, K-NN, LDA and SVM. Biometric applications result in respectable recognition rate exceeding 80%. Therefore, it is inferred that the analysis of postural control is promising in the field of biometrics

Human postural control is a complex process, but that is critical to understand in order to reduce the prevalence of occupational falls. Localized muscle fatigue (LMF), altered sensory input, and inter-individual differences (e.g. age and gender) have been shown to influence postural control, and numerous methods have been developed in order to quantify such effects. Recently, methods based on statistical mechanics have become popular, and when applied to center of pressure (COP) data, appear to provide new information regarding the postural control system. This study addresses in particular the stabilogram diffusion and Hurst exponent methods. An existing dataset was employed, in which sway during quiet stance was measured under different visual and surface compliance conditions, among both genders and different age groups, as well as before and after induction of localized muscle fatigue at the ankle, knee, torso, and shoulder. The stabilogram diffusion method determines both short-term and long-term diffusion coefficients, which correspond to open- and closed-loop control of posture, respectively. To do so, a "critical point" (or critical time interval) needs to be determined to distinguish between the two diffusion regions. Several limitations are inherent in existing methods to determine this critical point. To address this, a new algorithm was developed, based on a wavelet transform of COP data. The new algorithm is able to detect local maxima over specified frequency bands within COP data; therefore it can identify postural control mechanisms correspondent to those frequency bands. Results showed that older adults had smaller critical time intervals, and indicating that sway control of older adults was essentially different from young adults. Diffusion coefficients show that among young adults, torso LMF significantly compromised sway stability. In contrast, older adults appeared more resistance to LMF. Similar to earlier work, vision was found to play a crucial role in maintaining sway stability, and that stability was worse under eyes-closed (EC) than eyes-opened (EO) conditions. It was also found that the short-term Hurst exponent was not successful at detecting the effects of LMF on sway stability, likely because of a small sample size. The new critical point identification algorithm was verified to have better sensitivity and reliability than the traditional approach. The new algorithm can be used in future work to aid in the assessment of postural control and the mechanisms underlying this control. / Master of Science

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No. of bitstreams: 2 Dissertação - Renata da Costa Barbosa - 2014.pdf: 2041466 bytes, checksum: b05943f80e79bca8b9f3398d1706e187 (MD5) license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) Previous issue date: 2014-11-28 / Understanding how the postural control system is impaired with aging can help identify elderly at risk of falling. In order to study the postural control, center of pressure (CP) behavior can be analyzed. Classical descriptors are commonly used for the CP analysis, however, modern descriptors have been developed aiming to provide more information about the underlying processes involved in the postural control. Aims: Analyze and compare classical and modern descriptors used to analyze the postural control in elderly subjects in quiet standing posture, using data acquired from a force platform in horizontal and inclined surfaces. Methods: The study sample consisted of 17 elderly subjects who remained on a force platform in the upright posture for 70 seconds. The data acquisition was performed with the platform on a horizontal surface and again on a surface inclined at 14 degrees with dorsiflexion and later with plantar flexion of the ankle. For each slope, the procedure was repeated three times with eyes open (EO ) and three times with eyes closed (EC). The initial 10 seconds were discarded and then, CP times series were analyzed in the anteroposterior (AP) and mediolateral (ML) directions. The classical descriptors used were in the time in the frequency domain and the modern descriptors were: Detrended Fluctuations Analysis (DFA), Stabilogram Diffusion Analysis (SDA) and the Sway Density Curve (SDC). Results: In the classical analysis, the results showed significant differences in all comparisons made and, in the modern analysis, the variables provided by the SDA and SDC also showed significant differences between comparisons, however, the DFA did not provide any difference between the conditions. Conclusion: Results provided by the classical variables and by the SDA and the SDC suggest a lower stability of elderly subjects in the inclined surface with dorsiflexion followed by plantar flexion and the eyes closed condition. More studies with the modern descriptors are necessary to better understand their results. / Entender como o sistema de controle postural é comprometido com o processo de envelhecimento pode contribuir na identificação de idosos com risco de quedas. Para estudar o controle postural pode-se analisar o comportamento do Centro de Pressão (CP). Descritores clássicos comumente são utilizados para a análise do CP, no entanto, descritores modernos têm sido desenvolvidos, com o intuito de fornecer mais informações sobre os processos subjacentes ao controle postural. Objetivos: Analisar e comparar descritores clássicos e modernos para análise do controle postural em sujeitos idosos na postura ereta quieta, utilizando dados adquiridos na plataforma de força no plano e com inclinação. Métodos: A amostra do estudo foi composta por 17 indivíduos idosos que permaneceram sobre uma plataforma de força na postura ortostática por 70 segundos. A aquisição dos dados foi realizada com uma plataforma sobre uma superfície horizontal e depois sobre uma superfície inclinada a 14 graus nas posições de flexão dorsal e flexão plantar do tornozelo. Para cada inclinação, o procedimento foi repetido três vezes com os olhos abertos (OA) e três vezes com os olhos fechados (OF). Depois de descartados os 10 s iniciais, foram analisadas as séries temporais do CP na direção anteroposterior (AP) e mediolateral (ML). Foram utilizados alguns descritores clássicos no domínio do tempo e da frequência e os descritores modernos: Detrended Fluctuation Analysis (DFA), Stabilogram Diffusion Analysis (SDA) e pela Sway Density Curve (SDC). Resultados: Na análise clássica os resultados indicaram diferenças significativas em todas as comparações realizadas, na análise moderna, as variáveis fornecidas pela SDA e pela SDC também apresentaram diferenças significativas entre as comparações, porém, a DFA não conseguiu apontar tais diferenças. Conclusão: Os resultados fornecidos pelas variáveis clássicas, SDA e a SDC sugerem uma menor estabilidade de sujeitos idosos na superfície inclinada com flexão dorsal seguida da flexão plantar e na condição de olho fechado. Ainda são necessários a realização de mais estudos utilizando tais descritores para uma melhor compreensão de seus resultados.

Les problèmes liés à l'équilibre sont diagnostiqués à l'aide de systèmes de cartographies des pressions plantaires ou de plateformes de force mesurant le déplacement du centre de pressions. Ces systèmes professionnels sont restreints à une utilisation en milieu médical, et on constate qu'aucun dispositif de surveillance de l'équilibre ne donne entière satisfaction en termes de mobilité et d'acceptabilité. Dans le contexte de la télémédecine et de l'e-santé, notre objectif a consisté à développer des outils pour la surveillance ambulatoire de l'équilibre postural, et contribuer à la compréhension du contrôle de l'équilibre. Nous avons d'abord entrepris une étude théorique de la faisabilité de la mesure des pressions plantaires et du déplacement dynamique du centre de pression, à partir d'un nombre très réduit de capteurs. Nous avons proposé pour cela un modèle mécanique simplifié du pied, ainsi que les hypothèses spécifiques à ces applications. Le modèle décrit la relation physique entre la posture du pied et la répartition des pressions plantaires suivant ses caractéristiques biomécaniques. Sur la base d'un prototype de semelle instrumentée à 3 capteurs uniquement, nous avons vérifié expérimentalement la capacité du système et des méthodes à générer le stabilogramme et les cartographies de pressions plantaires. Ceux-ci ont été comparés à un système matriciel de référence, et caractérisés en termes d'incertitude dans le cas du pied normal en position debout et durant la marche. Les stabilogrammes ainsi mesurés peuvent être analysés pour caractériser la signature de l'équilibre. Nous proposons un modèle spécifique à trois dimensions, décrivant la dynamique de l'équilibre et permettant d'identifier, par simulation, les principaux paramètres physiologiques qui assurent le maintien de l'équilibre postural. / Problems of balance are often diagnosed thanks to plantar pressure cartography systems or forces platform that measure the center of pressure displacement. These professional systems are restricted in use to medical environments, and until now, the balance monitoring systems do not offer complete satisfaction in terms of mobility and acceptability. In order to overcome these limitation and in the context of telemedicine and e-health, we aimed to develop tools for ambulatory monitoring of postural equilibrium and to understand the balance control. We have first undertaken a theoretical study on the feasibility of measuring plantar pressure and dynamic displacement of the center of pressure, from a very small number of sensors. For these applications, we have proposed a simplified mechanical foot model, as well as related assumptions. The model describes the physical relationship between foot posture and distribution of plantar pressures following its biomechanical characteristics. Based on a prototype of an instrumented insole with only 3 sensors, we have verified experimentally the ability of the system and the methods to generate both the stabilogram and the plantar pressure maps. Comparison is made with a matrix reference system, and characterization in terms of uncertainty in the case of normal foot in standing position and during walking is detailed. The measured stabilogram can be analyzed to characterize the signature of balance. We have also proposed a specific three-dimensional model describing the dynamics of balance. Based on simulation, it leads to identify the main physiological parameters related to balance control.