Recently, the popular use of wearable devices and mobile apps makes the effectively capture of lifelogging physical activity data in an Internet of Things (IoT) environment possible. The effective collection of measur...
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ISBN:
(纸本)9781509001552
Recently, the popular use of wearable devices and mobile apps makes the effectively capture of lifelogging physical activity data in an Internet of Things (IoT) environment possible. The effective collection of measures of physical activity in the long term is beneficial to interdisciplinary healthcare research and collaboration from clinicians, researchers to patients. However, due to heterogeneity of connected devices and rapid change of diverse life patterns in an IoT environment, lifelogging physical activity information captured by mobile devices usually contains much uncertainty. In this paper, we provide a comprehensive review of existing life-logging physical activity measurement devices, and identify regular and irregular uncertainties of these activity measures in an IoT environment. We then project the distribution of irregular uncertainty by defining a walking speed related score named as Daily Activity in Physical Space (DAPS). Finally, we present an ellipse fitting model based validity improvement method for reducing uncertainties of life-logging physical activity measures in an IoT environment. The experimental results reflect that the proposed method effectively improves the validity of physical activity measures in a healthcare platform.
The wide-spread use of wearable devices and mobile apps in the Internet of Things (IoT) environments makes effectively capture of life-logging personal health data come true. A long-term collection of these health dat...
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ISBN:
(纸本)9781509001552
The wide-spread use of wearable devices and mobile apps in the Internet of Things (IoT) environments makes effectively capture of life-logging personal health data come true. A long-term collection of these health data will benefit to interdisciplinary healthcare research and collaboration. But most wearable devices and mobile apps in the market focus on personal fitness plan and lack of compatibility and extensibility to each other. Existing IoT based platforms rarely achieve a successful heterogeneous life-logging data aggregation. Also, the demand on high security increases difficulties of designing reliable platform for integrating and managing multi-resource life-logging health data. This paper investigates the possibility of collecting and aggregating life-logging data with the use of wearable devices, mobile apps and social media. It compares existing personal health data collection solutions and identifies essential needs of designing a life-logging data aggregator in the IoT environments. An integrated data collection solution with high secure standard is proposed and deployed on a state-of-the-art interdisciplinary healthcare platform: MHA [15] by integrating five life-logging resources: Fitbit, Moves, Facbook, Twitter, etc. The preliminary experiment demonstrates that it successfully record, store and reuse the unified and structured personal health information in a long term, including activities, location, exercise, sleep, food, heat rate and mood.
As a key health indictor, daily physical activity (PA) data has great significance on diagnosis and treatment of many chronic diseases. Numerous studies have been carried out for accurately monitoring and assessing ph...
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ISBN:
(纸本)9781509001552
As a key health indictor, daily physical activity (PA) data has great significance on diagnosis and treatment of many chronic diseases. Numerous studies have been carried out for accurately monitoring and assessing physical activity. Most attentions of these studies focus on designing standalone highly accurate wearable sensors or investigating advance machine learning algorithms to train these PA data in a controlled environment. But the wide use of cost-effective wearable devices and mobile apps makes it possible to monitor and access PA into a more open and connective Internet of Things (IoT) environment. Yet, it still lacks of a systemic survey on how to effectively transfer classic PA monitoring and assessment (PAMA) technologies into a heterogeneous device connected IoT environment. In an effect to understand the development of IoT technologies in PAMA, this paper reviews current research of PAMA technologies from an IoT layer-based perspective, and also identifies research challenges and future trends. A main contribution of this review paper is that it is first attempt to categorize classic PAMA technologies into an IoT architecture systematically.
We present in this paper a novel study aiming at identifying the differences in visual search patterns between physicians of diverse levels of expertise during the screening of colonoscopy videos. Physicians were clus...
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ISBN:
(纸本)9781450327510
We present in this paper a novel study aiming at identifying the differences in visual search patterns between physicians of diverse levels of expertise during the screening of colonoscopy videos. Physicians were clustered into two groups -experts and novices- according to the number of procedures performed, and fixations were captured by an eye-tracker device during the task of polyp search in different video sequences. These fixations were integrated into heat maps, one for each cluster. The obtained maps were validated over a ground truth consisting of a mask of the polyp, and the comparison between experts and novices was performed by using metrics such as reaction time, dwelling time and energy concentration ratio. Experimental results show a statistically significant difference between experts and novices, and the obtained maps show to be a useful tool for the characterisation of the behaviour of each group.
In many biomedical applications, it is often desired to simulate, analyse and visualise the dynamics of a particular patient based on a patient-specific musculoskeletal model. However, reconstructing a patient-specifi...
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In many biomedical applications, it is often desired to simulate, analyse and visualise the dynamics of a particular patient based on a patient-specific musculoskeletal model. However, reconstructing a patient-specifi...
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In many biomedical applications, it is often desired to simulate, analyse and visualise the dynamics of a particular patient based on a patient-specific musculoskeletal model. However, reconstructing a patient-specific model directly from medical images is highly labour intensive, and impractical in the clinical context. A more efficient method is to derive it from an atlas musculoskeletal model using patient-specific hints. In this paper, Laplacian mesh processing is introduced to deform an atlas model to a patient-specific model, based on patient-specific landmarks extracted from two orthogonal clinical images and using least-squares error optimization. Muscle attachment landmarks and motion landmarks in the atlas are also transformed as part of the process. Drift and inter-surface penetrations are prevented by supplementary inter-surface landmarks. Mesh simplification and reconstruction are used to avoid out-of-memory failures that may result from trying to deform models at high resolution.
Halos are usually used to enhance depth perception and display spatial relationships in illustrative visualization. In this paper, we present a simple and effective method to create volumetric halo illustration. In th...
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This paper proposes an easy way to perform web-based 3D interactive visualisation, which accepts two data resources, local and remote, as input and copes with two types of algorithm, built-in and remote. The focus of ...
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This paper proposes an easy way to perform web-based 3D interactive visualisation, which accepts two data resources, local and remote, as input and copes with two types of algorithm, built-in and remote. The focus of this paper is the biomedical area. Today's web technology makes it possible to use software maintained on a remote server. The approach described provides a virtual client environment, in which users can employ remotely installed software interactively using any standard browser. The proposed approach is a generic one and can be used in many other application areas.
Simulators of tumour growth can estimate the evolution of tumour volume and the quantity of various categories of cells as functions of time. However, the execution time of each simulation often takes several dozens o...
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Simulators of tumour growth can estimate the evolution of tumour volume and the quantity of various categories of cells as functions of time. However, the execution time of each simulation often takes several dozens of minutes (depending upon the dataset resolution), which clearly prevents easy interaction. The modern graphics processing unit (GPU) is not only a powerful graphics engine but also a highly parallel programmable processor featuring peak arithmetic performance and memory bandwidth that substantially outpaces its CPU counterpart. However, despite this, the GPU is little used in the context of the Virtual Physiological Human (VPH). This paper provides a case study to demonstrate the performance advantages that can be gained by using the GPU appropriately in the context of a VPH project in which the study of tumour growth is a central activity. We also analyse the algorithm performance on different modern parallel processing architectures, including multicore CPU and many-core GPU.
Medical visualisation is an indispensable means for doctors and researchers to better explore and analyse medical images. The EC-funded ContraCancrum project, which aims at more predictable tumour simulation and treat...
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Medical visualisation is an indispensable means for doctors and researchers to better explore and analyse medical images. The EC-funded ContraCancrum project, which aims at more predictable tumour simulation and treatment, uses visualisation as an important tool to interactively display tumour development and tumour simulation. This paper presents CCVis - the visualisation tool in ContraCancrum - which is a Qt-based plug in of the DrEye platform. CCVis uses a unified architecture for visualisation of the patient image data and tumour simulation data. It provides axis-aligned and arbitrary slice views, is surface rendering and volume ray casting as well as time-varying visualisation of patient image series and simulation data. Statistics in tumour simulation are plotted as 2D graphs. Major extensions of the Visualization Toolkit (VTK) are made to meet the demands for label highlighting and multi-dimensional transfer function.
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