Challenges and Future of Wearable Technology in Human Motor-Skill Learning and Optimization

Learning how to move is a challenging task. Even the most basic motor skill of walking requires years to develop and can quickly deteriorate due to aging and sedentary lifestyles. More specialized skills such as ballet and acrobatic kicks in soccer require “talent” and years of extensive practice to fully master. These practices can easily cause injuries if conducted improperly. 3D motion capture technologies are currently the best way to acquire human motor skill in biomechanical feedback training. Owing to their tremendous promise for a plethora of applications, wearable technologies have garnered great interest in biofeedback training. Using wearable technology, some physical activity parameters can be tracked in real time and a noninvasive way to indicate the physical progress of a trainee. Yet, the application of biomechanical wearables in human motor-skill learning, training, and optimization is still in its infant phase due to the absence of a reliable method. This chapter elaborates challenges faced by developing wearable biomechanical feedback devices and forecasts potential breakthroughs in this area. The overarching goal is to foster interdisciplinary studies on wearable technology to improve how we move

Theoretical results on a weightless neural classifier and application to computational linguistics

WiSARD é um classificador n-upla, historicamente usado em tarefas de reconhecimento de padrões em imagens em preto e branco. Infelizmente, não era comum que este fosse usado em outras tarefas, devido á sua incapacidade de arcar com grandes volumes de dados por ser sensível ao conteúdo aprendido. Recentemente, a técnica de bleaching foi concebida como uma melhoria à arquitetura do classificador n-upla, como um meio de coibir a sensibilidade da WiSARD. Desde então, houve um aumento na gama de aplicações construídas com este sistema de aprendizado. Pelo uso frequente de corpora bastante grandes, a etiquetação gramatical multilíngue encaixa-se neste grupo de aplicações. Esta tese aprimora o mWANN-Tagger, um etiquetador gramatical sem peso proposto em 2012. Este texto mostra que a pesquisa em etiquetação multilíngue com WiSARD foi intensificada através do uso de linguística quantitativa e que uma configuração de parâmetros universal foi encontrada para o mWANN-Tagger. Análises e experimentos com as bases da Universal Dependencies (UD) mostram que o mWANN-Tagger tem potencial para superar os etiquetadores do estado da arte dada uma melhor representação de palavra. Esta tese também almeja avaliar as vantagens do bleaching em relação ao modelo tradicional através do arcabouço teórico da teoria VC. As dimensões VC destes foram calculadas, atestando-se que um classificador n-upla, seja WiSARD ou com bleaching, que possua N memórias endereçadas por n-uplas binárias tem uma dimensão VC de exatamente N (2n − 1) + 1. Um paralelo foi então estabelecido entre ambos os modelos, onde deduziu-se que a técnica de bleaching é uma melhoria ao método n-upla que não causa prejuízos à sua capacidade de aprendizado.WiSARD é um classificador n-upla, historicamente usado em tarefas de reconhecimento de padrões em imagens em preto e branco. Infelizmente, não era comum que este fosse usado em outras tarefas, devido á sua incapacidade de arcar com grandes volumes de dados por ser sensível ao conteúdo aprendido. Recentemente, a técnica de bleaching foi concebida como uma melhoria à arquitetura do classificador n-upla, como um meio de coibir a sensibilidade da WiSARD. Desde então, houve um aumento na gama de aplicações construídas com este sistema de aprendizado. Pelo uso frequente de corpora bastante grandes, a etiquetação gramatical multilíngue encaixa-se neste grupo de aplicações. Esta tese aprimora o mWANN-Tagger, um etiquetador gramatical sem peso proposto em 2012. Este texto mostra que a pesquisa em etiquetação multilíngue com WiSARD foi intensificada através do uso de linguística quantitativa e que uma configuração de parâmetros universal foi encontrada para o mWANN-Tagger. Análises e experimentos com as bases da Universal Dependencies (UD) mostram que o mWANN-Tagger tem potencial para superar os etiquetadores do estado da arte dada uma melhor representação de palavra. Esta tese também almeja avaliar as vantagens do bleaching em relação ao modelo tradicional através do arcabouço teórico da teoria VC. As dimensões VC destes foram calculadas, atestando-se que um classificador n-upla, seja WiSARD ou com bleaching, que possua N memórias endereçadas por n-uplas binárias tem uma dimensão VC de exatamente N (2n − 1) + 1. Um paralelo foi então estabelecido entre ambos os modelos, onde deduziu-se que a técnica de bleaching é uma melhoria ao método n-upla que não causa prejuízos à sua capacidade de aprendizado

Comparação de desempenho entre os modelos neurais ágeis ELM e WiSARD

Neural models are popular in machine learning. Agile neural models are a subset of this kind of models and are characterized by presenting a significantly faster training time, being applied mainly in online learning domains. Two examples of agile neural models are the Extreme Learning Machine (ELM), a single hidden layer feedforward neural network which synaptic weights do not need to be iteractively adjusted, and the Wilkes, Stonham and Aleksander Recognition Device (WiSARD), a weightless neural network model with multiple discriminators that use neurons based on RAM memory structures. In this work, a comparative study between ELM and WiSARD models is made, aiming to evaluate both models performance when applied to different datasets having different characteristics. The evaluation is made by comparing test accuracy, training and testing times metrics, as well as the amount of RAM memory consumed by the models.Modelos neurais são populares na área de aprendizado de máquina. Dentre os vários tipos de modelos desta classe, os modelos neurais ágeis se destacam por apresentarem tempo de treinamento consideravelmente inferior, sendo utilizados principalmente em domínios de aprendizado online. Dois exemplos deste tipo de modelo são a Extreme Learning Machine (ELM), que é uma rede neural com uma única camada oculta cujos pesos sinápticos não precisam ser ajustados, e a Wilkes, Stonham and Aleksander Recognition Device (WiSARD), um modelo de rede neural sem pesos com múltiplos discriminadores que utilizam neurônios implementados como estruturas de memória RAM. Neste trabalho, ´e realizado um estudo comparativo entre os modelos neurais ágeis ELM e WiSARD, visando avaliar o desempenho de ambos quando aplicados a diferentes conjuntos de dados com diferentes características. A avaliação é feita a partir da comparação das métricas de acurácia de teste, tempos de treinamento e de teste, além do uso de memória RAM dos dois modelos

Aerospace Medicine and Biology: A continuing bibliography with indexes, supplement 165, March 1977

This bibliography lists 198 reports, articles, and other documents introduced into the NASA scientific and technical information system in February 1977

The application of artificial neural networks to interpret acoustic emissions from submerged arc welding

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Automated fusion welding processes play a fundamental role in modern manufacturing industries. The proliferation of joint geometries together with the large permutation of associated process variable configurations has given rise to research into complex system modelling and control strategies. Many of these techniques have involved monitoring of not only the electrical characteristics of the process but visual and acoustic information. Acoustic information derived from certain welding processes is well documented as it is an established fact that skilled manual welders utilise such information as an aid to creating an optimum weld. The experimental investigation presented in this thesis is dedicated to the feasibility of monitoring airborne acoustic emissions of Submerged Arc Welding (SAW) for diagnostic and real time control purposes. The experimental method adopted for this research takes a cybernetic approach to data processing and interpretation in an attempt to replicate the robustness of human biological functions. A custom designed audio hardware system was used to analyse signals obtained from bead on mild steel plate fusion welds. Time and frequency domains were used in an attempt to establish salient characteristics or identify the signatures associated with changes of the process variables. The featured parameters were voltage / current and weld travel speed, due to their ease of validation. However, consideration has also been given to weld defect prediction due to process instabilities. As the data proved to be highly correlated and erratic when subjected to off line statistical analysis, extensive investigation was given to the application of artificial neural networks to signal processing and real time control scenarios. As a consequence, a dedicated neural based software system was developed, utilising supervised and unsupervised neural techniques to monitor the process. The research was aimed at proving the feasibility of monitoring the electrical process parameters and stability of the welding process in real time. It was shown to be possible, by the exploitation of artificial neural networks, to generate a number of monitoring parameters indicative of the welding process state. The limitations of the present neural method and proposed developments are discussed, together with an overview of applied neural network technology and its impact on artificial intelligence and robotic control. Further developments are considered together with recommendations for future areas of research

Biomedical and Human Factors Requirements for a Manned Earth Orbiting Station

This report is the result of a study conducted by Republic Aviation Corporation in conjunction with Spacelabs, Inc.,in a team effort in which Republic Aviation Corporation was prime contractor. In order to determine the realistic engineering design requirements associated with the medical and human factors problems of a manned space station, an interdisciplinary team of personnel from the Research and Space Divisions was organized. This team included engineers, physicians, physiologists, psychologists, and physicists. Recognizing that the value of the study is dependent upon medical judgments as well as more quantifiable factors (such as design parameters) a group of highly qualified medical consultants participated in working sessions to determine which medical measurements are required to meet the objectives of the study. In addition, various Life Sciences personnel from NASA (Headquarters, Langley, MSC) participated in monthly review sessions. The organization, team members, consultants, and some of the part-time contributors are shown in Figure 1. This final report embodies contributions from all of these participants

The role of the body in the experience of installation art: a case study of visitors' bodily, emotional, and transformative experiences in Tomás Saraceno's “in orbit”

Installation art, with its immersive and participatory character, has been argued to require the use and awareness of the body, which potentially constitute key parts of the artwork's experience and appreciation. Heightened body awareness is even argued to be a key to particularly profound emotional or even transformative states, which have been frequently ascribed to this genre. However, the body in the experience of installation art has rarely been empirically considered. To address this gap, we investigated the body's role in the experience of Tomás Saraceno's in orbit installation. Based on a list of self-report items created from a review of the theoretical literature, we—for the first time—captured (quantitatively and qualitatively): what kind of subjective bodily experiences visitors (N = 230) reported, how these items grouped into clusters (using network science), and how these relate to emotion, art appraisal, and transformative outcomes. Network analysis of the items determined four communities related to “interoception,” “presence,” “disturbance,” and “proprioception.” Proprioception (e.g., awareness of balance/movement/weight) turned out to be a significant determinant of art appreciation in our study, and, together with “disturbing” body experiences (feeling awkward/watched/chills), coincided with transformation. We also assessed individual differences in body awareness yet did not find that these moderate those relationships. We suggest future research on installation art based on a more unified assessment of the role of the body in embodied-enactive aesthetics and its relation to the intensity and impact of art experience in general.Peer Reviewe

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 373)

This bibliography lists 206 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during Feb. 1993. Subject coverage includes: aerospace medicine and physiology, pharmacology, toxicology, environmental effect, life support systems and man/system technology, protective clothing, exobiology and extraterrestrial life, planetary biology, and flight crew behavior and performance