MyEvents: a personal visual analytics approach for mining key events and knowledge discovery in support of personal reminiscence

Reminiscence is an important aspect in our life. It preserves precious memories, allows us to form our own identities and encourages us to accept the past. Our work takes advantage of modern sensor technologies to support reminiscence, enabling self-monitoring of personal activities and individual movement in space and time on a daily basis. This paper presents MyEvents, a web-based personal visual analytics platform designed for non-computing experts, that allows for the collection of long-term location and movement data and the generation of event mementos. Our research is focused on two prominent goals in event reminiscence: 1) selection subjectivity and human involvement in the process of self knowledge discovery and memento creation; and 2) the enhancement of event familiarity by presenting target events and their related information for optimal memory recall and reminiscence. A novel multi-significance event ranking model is proposed to determine significant events in the personal history according to user preferences for event category, frequency and regularity. The evaluation results show that MyEvents effectively fulfils the reminiscence goals and tasks.

Correlation between serum esterase polymorphism and production performance of Yuxi fat-tailed sheep

The polymorphism of serum esterase (Es) of Henan Yuxi fat-tailed sheep was detected through polyacrylamide gel electrophoresis (PAGE), and the correlation between serum esterase and productivity was analyzed. The research result indicated that there are two alleles on the Es loci of Henan Yuxi fat-tailed sheep: Es+ and Es-. The gene frequencies of Es+ and Es- were 0.55 and 0.45, respectively. Besides, the frequencies of three genotypes (Es++, Es+- and Es--) are 0.425, 0.250 and 0.325, respectively. The recommended height of Es++ genotype is significantly higher than that of Es+- genotype (P<0.05), but the above two produce indistinctive difference in recommended height with Es-- genotype (P>0.05). The chest circumference of Es++ genotype is significantly higher than that of Es-- (P<0.05), but the above two produce indistinctive difference in chest circumference with Es+- genotype (P>0.05). Es exerts no significant impact on other indexes (P>0.05).Keywords: Henan Yuxi fat-tailed sheep, serum esterase (Es), polymorphismAfrican Journal of Biotechnology Vol. 12(9), pp. 986-98

MyHealthAvatar and CARRE: case studies of interactive visualisation for Internet-enabled sensor-assisted health monitoring and risk analysis

With the progress of wearable sensor technologies, more wearable health sensors have been made available on the market, which enables not only people to monitor their health and lifestyle in a continuous way but also doctors to utilise them to make better diagnoses. Continuous measurement from a variety of wearable sensors implies that a huge amount of data needs to be collected, stored, processed and presented, which cannot be achieved by traditional data processing methods. Visualisation is designed to promote knowledge discovery and utilisation via mature visual paradigms with well-designed user interactions and has become indispensable in data analysis. In this paper we introduce the role of visualisation in wearable sensor-assisted health analysis platforms by case studies of two projects funded by the European Commission: MyHealthAvatar and CARRE. The former focuses on health sensor data collection and lifestyle tracking while the latter aims to provide innovative means for the management of cardiorenal diseases with the assistance of wearable sensors. The roles of visualisation components including timeline, parallel coordinates, map, node-link diagrams, Sankey diagrams, etc. are introduced and discussed

Literature Explorer: effective retrieval of scientific documents through nonparametric thematic topic detection

© 2020 The Authors. Published by Springer. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.1007/s00371-019-01721-7Scientific researchers are facing a rapidly growing volume of literatures nowadays. While these publications offer rich and valuable information, the scale of the datasets makes it difficult for the researchers to manage and search for desired information efficiently. Literature Explorer is a new interactive visual analytics suite that facilitates the access to desired scientific literatures through mining and interactive visualisation. We propose a novel topic mining method that is able to uncover “thematic topics” from a scientific corpus. These thematic topics have an explicit semantic association to the research themes that are commonly used by human researchers in scientific fields, and hence are human interpretable. They also contribute to effective document retrieval. The visual analytics suite consists of a set of visual components that are closely coupled with the underlying thematic topic detection to support interactive document retrieval. The visual components are adequately integrated under the design rationale and goals. Evaluation results are given in both objective measurements and subjective terms through expert assessments. Comparisons are also made against the outcomes from the traditional topic modelling methods.This research is supported by the European Commission with project Dr Inventor (No 611383), MyHealthAvatar (No 60929), and by the UK Engineering and Physical Sciences Research Council with project MyLifeHub (EP/L023830/1).Published onlin

Visual Analytics for Health Monitoring and Risk Management in CARRE

With the rise of wearable sensor technologies, an increasing number of wearable health and medical sensors are available on the market, which enables not only people but also doctors to utilise them to monitor people’s health in such a consistent way that the sensors may become people’s lifetime companion. The consistent measurements from a variety of wearable sensors implies that a huge amount of data needs to be processed, which cannot be achieved by traditional processing methods. Visual analytics is designed to promote knowledge discovery and utilisation of big data via mature visual paradigms with well-designed user interactions and has become indispensable in big data analysis. In this paper we introduce the role of visual analytics for health monitoring and risk management in the European Commission funded project CARRE which aims to provide innovative means for the management of cardiorenal diseases with the assistance of wearable sensors. The visual analytics components of timeline and parallel coordinates for health monitoring and of node-link diagrams, chord diagrams and sankey diagrams for risk analysis are presented to achieve ubiquitous and lifelong health and risk monitoring to promote people’s health

Breast cancer survival analysis with molecular subtypes : an initial step

As a predominant threat to women's health world-wide, breast cancer has become increasingly important in on-cology research. The discovery of molecular subtypes of breast cancer has led to more subtype oriented treatment and prognosis prediction. Effective prognosis models help to estimate the recurrence as well as the quality and duration of survival, leading to more personalized treatments. However, most traditional prognostic models either ignore molecular subtypes or only make limited use of them. The roles of molecular subtypes in the development and treatment of breast cancer have not been fully revealed. With the over 1200 cases collected by Sir Run Run Shaw Hospital of Zhejiang University in the past two decades, we aim to improve understanding of molecular subtypes and their impacts on the prognosis via data analysis in the long run. As the initial stage, this short paper presents our preliminary work of logistic regression experiments with the data. Though molecular subtypes have not been included the tentative model, they are to be explored further in following stages

Examining sensor-based physical activity recognition and monitoring for healthcare using Internet of Things: A systematic review.

Due to importantly beneficial effects on physical and mental health and strong association with many rehabilitation programs, Physical Activity Recognition and Monitoring (PARM) have been considered as a key paradigm for smart healthcare. Traditional methods for PARM focus on controlled environments with the aim of increasing the types of identifiable activity subjects complete and improving recognition accuracy and system robustness by means of novel body-worn sensors or advanced learning algorithms. The emergence of the Internet of Things (IoT) enabling technology is transferring PARM studies to open and connected uncontrolled environments by connecting heterogeneous cost-effective wearable devices and mobile apps. Little is currently known about whether traditional PARM technologies can tackle the new challenges of IoT environments and how to effectively harness and improve these technologies. In an effort to understand the use of IoT technologies in PARM studies, this paper will give a systematic review, critically examining PARM studies from a typical IoT layer-based perspective. It will firstly summarize the state-of-the-art in traditional PARM methodologies as used in the healthcare domain, including sensory, feature extraction and recognition techniques. The paper goes on to identify some new research trends and challenges of PARM studies in the IoT environments, and discusses some key enabling techniques for tackling them. Finally, this paper consider some of the successful case studies in the area and look at the possible future industrial applications of PARM in smart healthcare

Life-logging data aggregation solution for interdisciplinary healthcare research and collaboration

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 stateof-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

WebGL-based interactive rendering of whole body anatomy for web-oriented visualisation of avatar-centered digital health data

The visualisation of whole-body anatomy has a variety of applications in health-related analysis and simulation. However, the rendering of complex 3D human anatomy models is generally performed by standalone applications rather than via a web interface, as rendering large 3D models has always been a weak spot of traditional web browsers. Consequently, online access to, and exploration of, the human anatomy in 3D has not been feasible in the past. With the advent of WebGL and HTML5, high performance OpenGL rendering seamlessly integrated with the web interface is now within reach, and this opens the possibility of visualising avatar-centered health data via a web interface. In this paper, a WebGL-based prototype for rendering whole-body anatomy is introduced, and the technical details are presented