3,117 research outputs found

    Can smartwatches replace smartphones for posture tracking?

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    This paper introduces a human posture tracking platform to identify the human postures of sitting, standing or lying down, based on a smartwatch. This work develops such a system as a proof-of-concept study to investigate a smartwatch's ability to be used in future remote health monitoring systems and applications. This work validates the smartwatches' ability to track the posture of users accurately in a laboratory setting while reducing the sampling rate to potentially improve battery life, the first steps in verifying that such a system would work in future clinical settings. The algorithm developed classifies the transitions between three posture states of sitting, standing and lying down, by identifying these transition movements, as well as other movements that might be mistaken for these transitions. The system is trained and developed on a Samsung Galaxy Gear smartwatch, and the algorithm was validated through a leave-one-subject-out cross-validation of 20 subjects. The system can identify the appropriate transitions at only 10 Hz with an F-score of 0.930, indicating its ability to effectively replace smart phones, if needed

    Smart objects as building blocks for the internet of things

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    The combination of the Internet and emerging technologies such as nearfield communications, real-time localization, and embedded sensors lets us transform everyday objects into smart objects that can understand and react to their environment. Such objects are building blocks for the Internet of Things and enable novel computing applications. As a step toward design and architectural principles for smart objects, the authors introduce a hierarchy of architectures with increasing levels of real-world awareness and interactivity. In particular, they describe activity-, policy-, and process-aware smart objects and demonstrate how the respective architectural abstractions support increasingly complex application

    Surveying human habit modeling and mining techniques in smart spaces

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    A smart space is an environment, mainly equipped with Internet-of-Things (IoT) technologies, able to provide services to humans, helping them to perform daily tasks by monitoring the space and autonomously executing actions, giving suggestions and sending alarms. Approaches suggested in the literature may differ in terms of required facilities, possible applications, amount of human intervention required, ability to support multiple users at the same time adapting to changing needs. In this paper, we propose a Systematic Literature Review (SLR) that classifies most influential approaches in the area of smart spaces according to a set of dimensions identified by answering a set of research questions. These dimensions allow to choose a specific method or approach according to available sensors, amount of labeled data, need for visual analysis, requirements in terms of enactment and decision-making on the environment. Additionally, the paper identifies a set of challenges to be addressed by future research in the field

    Analysis of Android Device-Based Solutions for Fall Detection

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    Falls are a major cause of health and psychological problems as well as hospitalization costs among older adults. Thus, the investigation on automatic Fall Detection Systems (FDSs) has received special attention from the research community during the last decade. In this area, the widespread popularity, decreasing price, computing capabilities, built-in sensors and multiplicity of wireless interfaces of Android-based devices (especially smartphones) have fostered the adoption of this technology to deploy wearable and inexpensive architectures for fall detection. This paper presents a critical and thorough analysis of those existing fall detection systems that are based on Android devices. The review systematically classifies and compares the proposals of the literature taking into account different criteria such as the system architecture, the employed sensors, the detection algorithm or the response in case of a fall alarms. The study emphasizes the analysis of the evaluation methods that are employed to assess the effectiveness of the detection process. The review reveals the complete lack of a reference framework to validate and compare the proposals. In addition, the study also shows that most research works do not evaluate the actual applicability of the Android devices (with limited battery and computing resources) to fall detection solutions.Ministerio de Economía y Competitividad TEC2013-42711-

    Cloud-based platform for intelligent healthcare monitoring and risk prevention in hazardous manufacturing contexts

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    This paper presents an intelligent cloud-based platform for workers healthcare monitoring and risk prevention in potentially hazardous manufacturing contexts. The platform is structured according to sequential modules dedicated to data acquisition, processing and decision-making support. Several sensors and data sources, including smart wearables, machine tool embedded sensors and environmental sensors, are employed for data collection, comprising information on offline clinical background, operational and environmental data. The cloud data processing module is responsible for extracting relevant features from the acquired data in order to feed a machine learning-based decision-making support system. The latter provides a classification of workers’ health status so that a prompt intervention can be performed in particularly challenging scenarios

    Wearable Sensors and Smart Devices to Monitor Rehabilitation Parameters and Sports Performance: An Overview

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    A quantitative evaluation of kinetic parameters, the joint’s range of motion, heart rate, and breathing rate, can be employed in sports performance tracking and rehabilitation monitoring following injuries or surgical operations. However, many of the current detection systems are expensive and designed for clinical use, requiring the presence of a physician and medical staff to assist users in the device’s positioning and measurements. The goal of wearable sensors is to overcome the limitations of current devices, enabling the acquisition of a user’s vital signs directly from the body in an accurate and non–invasive way. In sports activities, wearable sensors allow athletes to monitor performance and body movements objectively, going beyond the coach’s subjective evaluation limits. The main goal of this review paper is to provide a comprehensive overview of wearable technologies and sensing systems to detect and monitor the physiological parameters of patients during post–operative rehabilitation and athletes’ training, and to present evidence that supports the efficacy of this technology for healthcare applications. First, a classification of the human physiological parameters acquired from the human body by sensors attached to sensitive skin locations or worn as a part of garments is introduced, carrying important feedback on the user’s health status. Then, a detailed description of the electromechanical transduction mechanisms allows a comparison of the technologies used in wearable applications to monitor sports and rehabilitation activities. This paves the way for an analysis of wearable technologies, providing a comprehensive comparison of the current state of the art of available sensors and systems. Comparative and statistical analyses are provided to point out useful insights for defining the best technologies and solutions for monitoring body movements. Lastly, the presented review is compared with similar ones reported in the literature to highlight its strengths and novelties

    Smart working technologies in industry 4.0 : contributions to different manufacturing activities and workers’ skills

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    A Indústria 4.0 é considerada a quarta revolução industrial porque utiliza uma ampla integração de tecnologias de informação e de operação na fabricação industrial. Apesar dessa perspectiva tecnológica, diversos estudos vêm evidenciando a importância de considerar o fator humano para o desenvolvimento de um sistema de manufatura inteligente. Nesse sentido, a dimensão denominada como Smart Working precisa ser melhor investigada, uma vez que entender como as tecnologias afetam os trabalhadores e as habilidades desses são cruciais para o bom desempenho das fábricas. Em razão disso, o objetivo desta dissertação foi entender como as Smart Working Technologies (SWT) podem contribuir para as atividades e as habilidades dos trabalhadores da manufatura. Para tanto, primeiramente foi realizada uma análise abrangente da literatura para identificar as SWT e seus impactos nas capacidades dos trabalhadores em suas atividades de manufatura. Deste modo, foram analisados 80 artigos que relacionam as SWT em oito atividades de manufatura. Posteriormente, foi selecionada uma das SWT mais relevantes conforme a literatura, os robôs colaborativos, para identificar os efeitos das tecnologias nas habilidades dos trabalhadores. Deste modo, foram analisados 138 casos de aplicação reportados por uma das empresas fornecedoras líderes mundiais, bem como três entrevistas com empresas adotantes da tecnologia. Os resultados apontam que existem 15 SWT que podem ser implementadas nas atividades de manufatura e relacionadas às capacidades dos trabalhadores. Além disso, os resultados também apontam que podem existir quatro efeitos das SWT nas habilidades dos trabalhadores. Estes achados demonstram que de acordo com a estratégia da empresa uma SWT pode impactar de diferentes formas os trabalhadores.Industry 4.0 is considered the fourth industrial revolution because it uses a broad integration of information and operating technologies in industrial manufacturing. Despite this technological perspective, several studies have highlighted the importance of considering the human factor to develop a smart manufacturing system. In this sense, the Smart Working dimension needs to be further investigated since understanding how technologies affect workers and their skills are crucial for factories' good performance. Therefore, the objective of this dissertation was to understand how Smart Working Technologies (SWT) can contribute to the activities and skills of manufacturing workers. To this end, firstly a systematic literature review was carried out to identify SWTs and their impacts on workers' capabilities in their manufacturing activities. Thus, 80 articles relating to SWT in eight manufacturing activities were analyzed. Subsequently, one of the most relevant SWTs according to the literature, collaborative robots, was selected to identify the effects of technologies on workers' skills. In this way, 138 application cases reported by one of the world's leading supplier companies were analyzed, as well as three interviews with companies that adopted the technology. The results show that there are 15 SWT that can be implemented in manufacturing activities and related to workers' capabilities. In addition, the results also point out that there may be four effects of SWT on workers' skills. According to the company's strategy, these findings demonstrate that an SWT can impact workers in different ways

    Human Activity Recognition with Smart Watch based on H-SVM

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    A Cloud Robotics Solution to Improve Social Assistive Robots for Active and Healthy Aging

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    Technological innovation in robotics and ICT represents an effective solution to tackle the challenge of providing social sustainable care services for the ageing population. The recent introduction of cloud technologies is opening new opportunities for the provisioning of advanced robotic services based on the cooperation of a number of connected robots, smart environments and devices improved by the huge cloud computational and storage capability. In this context, this paper aims to investigate and assess the potentialities of a cloud robotic system for the provisioning of assistive services for the promotion of active and healthy ageing. The system comprised two different smart environments, located in Italy and Sweden, where a service robot is connected to a cloud platform for the provisioning of localization based services to the users. The cloud robotic services were tested in the two realistic environments to assess the general feasibility of the solution and demonstrate the ability to provide assistive location based services in a multiple environment framework. The results confirmed the validity of the solution but also suggested a deeper investigation on the dependability of the communication technologies adopted in such kind of systems
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