63 research outputs found

    Fall prevention strategy for an active orthotic system

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    Dissertação de mestrado integrado em Engenharia Biomédica (especialização em Eletrónica Médica)Todos os anos, são reportadas cerca de 684,000 quedas fatais e 37.3 milhões de quedas não fatais que requerem atenção médica, afetando principalmente a população idosa. Assim, é necessário identificar eficientemente indivíduos com alto risco de queda, a partir da população alvo idosa, e prepará los para superar perturbações da marcha inesperadas. Uma estratégia de prevenção de queda capaz de eficientemente e atempadamente detetar e contrariar os eventos de perdas de equilíbrio (PDE) mais frequentes pode reduzir o risco de queda. Como slips foram identificados como a causa mais prevalente de quedas, estes eventos devem ser abordados como foco principal da estratégia. No entanto, há falta de estratégias de prevenção de quedas por slip. Esta dissertação tem como objetivo o design de uma estratégia de prevenção de quedas de slips baseada na conceção das etapas de atuação e deteção. A estratégia de atuação foi delineada com base na resposta biomecânica humana a slips, onde o joelho da perna perturbada (leading) apresenta um papel proeminente para contrariar LOBs induzidas por slips. Quando uma slip é detetada, a estratégia destaca uma ortótese de joelho que providencia um torque assisstivo para prevenir a queda. A estratégia de deteção considerou as propriedades atrativas dos controladores Central Pattern Generator (CPG) para prever parâmetros da marcha. Algoritmos baseados em threshold monitorizam o erro de previsão do CPG, que aumenta após uma perturbação inesperada na marcha, para a deteção de slips. O ângulo do joelho e a velocidade angular da canela foram selecionados como os parâmetros de monitorização da marcha. Um protocolo experimental concebido para provocar perturbações de slip a sujeitos humanos permitiu a recolha de dados destas variáveis para posteriormente validar o algoritmo de deteção de perturbações. Algoritmos CPG foram capazes de produzir aproximações aceitáveis dos sinais de marcha em estado estacionário do ângulo do joelho e da velocidade angular da canela com sucesso. Além disso, o algoritmo de threshold adaptativo detetou LOBs induzidas por slips eficientemente. A melhor performance global foi obtida usando este algoritmo para monitorizar o ângulo do joelho, que detetou quase 80% (78.261%) do total de perturbações com um tempo médio de deteção (TMD) de 250 ms. Além disso, uma média de 0.652 falsas perturbações foram detetadas por cada perturbação corretamente identificada. Estes resultados sugerem uma performance aceitável de deteção de perturbações do algoritmo, de acordo com os requisitos especificados para a deteção.Every year, an estimated 684,000 fatal falls and 37.3 million non-fatal falls requiring medical attention are reported, mostly affecting the older population. Thus, it is necessary to effectively screen high fall risk individuals from targeted elderly populations and prepare them to successfully overcome unexpected gait perturbations. A fall prevention strategy capable of effectively and timely detect and counteract the most frequent loss of balance (LOB) events may reduce the fall risk. Since slips were identified as the main contributors to falls, these events should be addressed as a main focus of the strategy. Nonetheless, there is a lack of slip-induced fall prevention strategies. This dissertation aims the design of a slip-related fall prevention strategy based on the conception of an actuation and a detection stage. The actuation strategy was delineated based on the human biomechanical reactions to slips, where the perturbed (leading) leg’s knee joint presents a prominent role to counteract slip-induced LOBs. Thereby, upon the detection of a slip, this strategy highlighted a knee orthotic device that provides an assistive torque to prevent the falls. The detection strategy considered the attractive properties of biological-inspired Central Pattern Generator (CPG) controllers to predict gait parameters. Threshold-based algorithms monitored the CPG’s prediction error produced, which increases upon an unexpected gait perturbation, to perform slip detection. The knee angle and shank angular velocity were selected as the monitoring gait parameters. An experimental protocol designed to provoke slip perturbations to human subjects allowed to collect data from these variables to further validate the perturbation detection algorithm. CPG algorithms were able to successfully produce acceptable estimations of the knee angle and shank angular velocity signals during steady-state walking. Furthermore, an adaptive threshold algorithm effectively detected slip-induced LOBs. The best overall performance was obtained using this algorithm to monitor the knee angle from the perturbed leg, which detected almost 80% (78.261%) of the total perturbations with a mean detection time (MDT) of 250 ms. In addition, a mean of 0.652 false perturbations were detected for each correct perturbation identified. These results suggest an acceptable perturbation detection performance of the algorithm implemented in light of the detection requirements specified

    Expressive social exchange between humans and robots

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    Thesis (Sc.D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2000.Includes bibliographical references (p. 253-264).Sociable humanoid robots are natural and intuitive for people to communicate with and to teach. We present recent advances in building an autonomous humanoid robot, Kismet, that can engage humans in expressive social interaction. We outline a set of design issues and a framework that we have found to be of particular importance for sociable robots. Having a human-in-the-loop places significant social constraints on how the robot aesthetically appears, how its sensors are configured, its quality of movement, and its behavior. Inspired by infant social development, psychology, ethology, and evolutionary perspectives, this work integrates theories and concepts from these diverse viewpoints to enable Kismet to enter into natural and intuitive social interaction with a human caregiver, reminiscent of parent-infant exchanges. Kismet perceives a variety of natural social cues from visual and auditory channels, and delivers social signals to people through gaze direction, facial expression, body posture, and vocalizations. We present the implementation of Kismet's social competencies and evaluate each with respect to: 1) the ability of naive subjects to read and interpret the robot's social cues, 2) the robot's ability to perceive and appropriately respond to naturally offered social cues, 3) the robot's ability to elicit interaction scenarios that afford rich learning potential, and 4) how this produces a rich, flexible, dynamic interaction that is physical, affective, and social. Numerous studies with naive human subjects are described that provide the data upon which we base our evaluations.by Cynthia L. Breazeal.Sc.D

    A Linear Physiological Visual-Vestibular Interaction Model for the Prediction of Motion Sickness Incidence

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    Visually Guided Control of Movement

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    The papers given at an intensive, three-week workshop on visually guided control of movement are presented. The participants were researchers from academia, industry, and government, with backgrounds in visual perception, control theory, and rotorcraft operations. The papers included invited lectures and preliminary reports of research initiated during the workshop. Three major topics are addressed: extraction of environmental structure from motion; perception and control of self motion; and spatial orientation. Each topic is considered from both theoretical and applied perspectives. Implications for control and display are suggested

    Conference on Intelligent Robotics in Field, Factory, Service, and Space (CIRFFSS 1994), volume 1

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    The AIAA/NASA Conference on Intelligent Robotics in Field, Factory, Service, and Space (CIRFFSS '94) was originally proposed because of the strong belief that America's problems of global economic competitiveness and job creation and preservation can partly be solved by the use of intelligent robotics, which are also required for human space exploration missions. Individual sessions addressed nuclear industry, agile manufacturing, security/building monitoring, on-orbit applications, vision and sensing technologies, situated control and low-level control, robotic systems architecture, environmental restoration and waste management, robotic remanufacturing, and healthcare applications

    Robotics 2010

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    Without a doubt, robotics has made an incredible progress over the last decades. The vision of developing, designing and creating technical systems that help humans to achieve hard and complex tasks, has intelligently led to an incredible variety of solutions. There are barely technical fields that could exhibit more interdisciplinary interconnections like robotics. This fact is generated by highly complex challenges imposed by robotic systems, especially the requirement on intelligent and autonomous operation. This book tries to give an insight into the evolutionary process that takes place in robotics. It provides articles covering a wide range of this exciting area. The progress of technical challenges and concepts may illuminate the relationship between developments that seem to be completely different at first sight. The robotics remains an exciting scientific and engineering field. The community looks optimistically ahead and also looks forward for the future challenges and new development

    Development of a simulation tool for measurements and analysis of simulated and real data to identify ADLs and behavioral trends through statistics techniques and ML algorithms

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    openCon una popolazione di anziani in crescita, il numero di soggetti a rischio di patologia è in rapido aumento. Molti gruppi di ricerca stanno studiando soluzioni pervasive per monitorare continuamente e discretamente i soggetti fragili nelle loro case, riducendo i costi sanitari e supportando la diagnosi medica. Comportamenti anomali durante l'esecuzione di attività di vita quotidiana (ADL) o variazioni sulle tendenze comportamentali sono di grande importanza.With a growing population of elderly people, the number of subjects at risk of pathology is rapidly increasing. Many research groups are studying pervasive solutions to continuously and unobtrusively monitor fragile subjects in their homes, reducing health-care costs and supporting the medical diagnosis. Anomalous behaviors while performing activities of daily living (ADLs) or variations on behavioral trends are of great importance. To measure ADLs a significant number of parameters need to be considering affecting the measurement such as sensors and environment characteristics or sensors disposition. To face the impossibility to study in the real context the best configuration of sensors able to minimize costs and maximize accuracy, simulation tools are being developed as powerful means. This thesis presents several contributions on this topic. In the following research work, a study of a measurement chain aimed to measure ADLs and represented by PIRs sensors and ML algorithm is conducted and a simulation tool in form of Web Application has been developed to generate datasets and to simulate how the measurement chain reacts varying the configuration of the sensors. Starting from eWare project results, the simulation tool has been thought to provide support for technicians, developers and installers being able to speed up analysis and monitoring times, to allow rapid identification of changes in behavioral trends, to guarantee system performance monitoring and to study the best configuration of the sensors network for a given environment. The UNIVPM Home Care Web App offers the chance to create ad hoc datasets related to ADLs and to conduct analysis thanks to statistical algorithms applied on data. To measure ADLs, machine learning algorithms have been implemented in the tool. Five different tasks have been identified. To test the validity of the developed instrument six case studies divided into two categories have been considered. To the first category belong those studies related to: 1) discover the best configuration of the sensors keeping environmental characteristics and user behavior as constants; 2) define the most performant ML algorithms. The second category aims to proof the stability of the algorithm implemented and its collapse condition by varying user habits. Noise perturbation on data has been applied to all case studies. Results show the validity of the generated datasets. By maximizing the sensors network is it possible to minimize the ML error to 0.8%. Due to cost is a key factor in this scenario, the fourth case studied considered has shown that minimizing the configuration of the sensors it is possible to reduce drastically the cost with a more than reasonable value for the ML error around 11.8%. Results in ADLs measurement can be considered more than satisfactory.INGEGNERIA INDUSTRIALEopenPirozzi, Michel

    Neuromuscular Control Strategy during Object Transport while Walking: Adaptive Integration of Upper and Lower Limb Movements

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    When carrying an object while walking, a significant challenge for the central nervous system (CNS) is to preserve the object’s stability against the inter-segmental interaction torques and ground reaction forces. Studies documented several strategies used by the CNS: modulation of grip force (GF), alterations in upper limb kinematics, and gait adaptations. However, the question of how the CNS organizes the multi-segmental joint and muscle coordination patterns to deal with gait-induced perturbations remains poorly understood. This dissertation aimed to explore the neuromuscular control strategy utilized by the CNS to transport an object during walking successfully. Study 1 examined the inter-limb coordination patterns of the upper limbs when carrying a cylinder-shaped object while walking on a treadmill. It was predicted that transporting an object in one hand would affect the movement pattern of the contralateral arm to maintain the overall angular momentum. The results showed that transporting an object caused a decreased anti-phase coordination, but it did not induce significant kinematic and muscle activation changes in the unconstrained arm. Study 2 examined muscle synergy patterns for upper limb damping behavior by using non-negative matrix factorization (NNMF) method. Four synergies were identified, showing a proximal-to-distal pattern of activation preceding heel contacts. Study 3 examined the effect of different precision demands (carrying a cup with or without a ball) and altered visual information (looking forward vs. looking at an object) on the upper limb damping behavior and muscle synergies. Increasing precision demand induced stronger damping behavior and increased the electromyography (EMG) activation of wrist/hand flexors and extensors. The NNMF results replicated Study 2 in that the stabilization of proximal joints occurred before the distal joints. The results indicated that the damping incorporates tonic and phasic muscle activation to ensure object stabilization. Overall, three experiments showed that the CNS adopts a similar synergy pattern regardless of task constraint or altered gaze direction while modulating the amount of muscle activation for object stabilization. Kinematic changes can differ depending on the different levels of constraint, as shown in the smaller movement amplitude of the shoulder joint in the transverse plane during the task with higher precision demand

    Proceedings of the Post-Graduate Conference on Robotics and Development of Cognition, 10-12 September 2012, Lausanne, Switzerland

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    The aim of the Postgraduate Conference on Robotics and Development of Cognition (RobotDoC-PhD) is to bring together young scientists working on developmental cognitive robotics and its core disciplines. The conference aims to provide both feedback and greater visibility to their research as lively and stimulating discussion can be held amongst participating PhD students and senior researchers. The conference is open to all PhD students and post-doctoral researchers in the field. RobotDoC-PhD conference is an initiative as a part of Marie-Curie Actions ITN RobotDoC and will be organized as a satellite event of the 22nd International Conference on Artificial Neural Networks ICANN 2012

    Proceedings of the Post-Graduate Conference on Robotics and Development of Cognition, 10-12 September 2012, Lausanne, Switzerland

    Get PDF
    The aim of the Postgraduate Conference on Robotics and Development of Cognition (RobotDoC-PhD) is to bring together young scientists working on developmental cognitive robotics and its core disciplines. The conference aims to provide both feedback and greater visibility to their research as lively and stimulating discussion can be held amongst participating PhD students and senior researchers. The conference is open to all PhD students and post-doctoral researchers in the field. RobotDoC-PhD conference is an initiative as a part of Marie-Curie Actions ITN RobotDoC and will be organized as a satellite event of the 22nd International Conference on Artificial Neural Networks ICANN 2012
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