Joan Condell

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Papers by Joan Condell

Kinematic Variability in Running: A Caution Regarding Use of the Spanning Set Measure

Journal of Applied Biomechanics, Feb 1, 2012

The spanning set technique quantifies intertrial variability as the span between polynomial curve... more The spanning set technique quantifies intertrial variability as the span between polynomial curves representing upper and lower standard deviation curves of a repeated movement. This study aimed to assess the validity of the spanning set technique in quantifying variability and specifically to determine its sensitivity to variability presented at different phases of a movement cycle. Knee angle data were recorded from a male participant completing 12 overground running trials. Variability was added to each running trial at five different phases of the running stride. Ten variability magnitudes were also used to assess the effect of variability magnitude on the spanning set measure. Variability was quantified in all trials using mean deviation and the spanning set measure. Results of a repeated-measures ANOVA showed significant differences between the spanning set score for trials using different phases of added variability. In contrast, mean deviation values showed no difference related to the phase of added variability. Therefore, the spanning set technique cannot be recommended as a valid measure of intertrial movement variability.

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Radio Communication Protocols in a History Aware Device-free Passive (DfP) Localisation

Springer eBooks, 2011

POS0952 Responsiveness of Spinal Mobility Measurements in Axial Spondyloarthritis Using Conventional and Advanced Metrology: A Pilot Study

Annals of the Rheumatic Diseases, May 19, 2021

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SAT0327 Segmental Relationship Between Mobility, Structural Damage and Disease Activity in Axial Spondyloarthritis

and during pregnancy; moreover, in 4 cases AS was interpreted as contraindication to pregnancy. 1... more and during pregnancy; moreover, in 4 cases AS was interpreted as contraindication to pregnancy. 107 (35.4%) respondents believe that AS medications should be discontinued during pregnancy planning and conception, 75 (24.8%) subjects accepted possible use of AS therapy during this period, while 120 (39.8%) didn't know the answer. 15.2% of respondents were ready to continue on NSAIDs, 20 (6.6%)on glucocorticoids and sulfasalazine, and 21 (7%)on biological drugs (GEBD). Of those who are ready to continue on AS medications at conception, 46 women (61.3%) consulted pregnancy planning with a rheumatologist. Respondents with higher education were slightly more likely to continue on AS therapy at conception (29%) compared to women with vocational college education (11.8%). Age, AS duration, or marital status had no influence on patients' attitude to AS therapy during pregnancy planning and conception. Conclusion: The majority of surveyed female patients changed their attitude to pregnancy after establishing AS diagnosis, although only 13% of them were ready to avoid pregnancy due to AS. No more than 50% of respondents were consulted a rheumatologist before planning pregnancy, and up to one third of them were not receive all expected answers to their questions and recommendations. Only 1/4 of participants accept the idea of continuing AS therapy during pregnancy planning and conception.

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A Review of Identity, Identification and Authentication

International journal for information security research, Jun 30, 2018

Classifying Internet traffic into applications is vital to many areas, from quality of service (Q... more Classifying Internet traffic into applications is vital to many areas, from quality of service (QoS) provisioning, to network management and security. The task is challenging as network applications are rather dynamic in nature, tend to use a web front-end and are typically encrypted, rendering traditional port-based and deep packet inspection (DPI) method unusable. Recent classification studies proposed two alternatives: using the statistical properties of traffic or inferring the behavioural patterns of network applications, both aiming to describe the activity within and among network flows in order to understand application usage and behaviour. The aim of this paper is to propose and investigate a novel feature to define application behaviour as seen through the generated network traffic by considering the timing and pattern of user events during application sessions, leading to an extended traffic feature set based on burstiness. The selected features were further used to train and test a supervised C5.0 machine learning classifier and led to a better characterization of network applications, with a traffic classification accuracy ranging between 90-98%.

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Power and Network Status Aware Media Applications

The area of computing incorporates a vast range of devices with different capabilities in terms o... more The area of computing incorporates a vast range of devices with different capabilities in terms of battery life, network connectivity, processing power and disk management. An endless battery life and flawless connectivity to multiple wireless access points are increasingly essential for the mobile device user. Nevertheless the battery life and the capability of being able to connect to wireless networks will fluctuate greatly between each device. Portable multimedia devices such as Personal Digital Assistants (PDA’s) and Smartphones with restricted memory will also vary greatly; however, users of these devices will expect optimal multimedia delivery. Therefore we need an intelligent middleware application that will take a critical role for the coordination between the devices hardware and software so that the user can get the full potential from the device. We document the development of an intelligent media player application which can adapt to platform state changes using the Intel Mobile SDK. The application can detect and respond appropriately to changes in network connectivity, network connection quality and power consumption optimization and then gracefully handle intermittent connectivity.

Online educational resources for health professionals caring for pregnant women with heart disease: a scoping literature review using Arksey and O’Malley’s methodological framework: A scoping literature review using Arksey and O’Malley’s methodological framework

Evidence Based Midwifery, Jun 1, 2018

An overview of the benefits of peer mentoring for PASS leaders

Journal of Learning Development in Higher Education, May 3, 2016

PASS, which stands for Peer Assisted Study Sessions, is a long running and internationally renown... more PASS, which stands for Peer Assisted Study Sessions, is a long running and internationally renowned form of peer learning that involves trained higher year students (PASS leaders) working in pairs to facilitate regular study groups with students in the year below. Not only does it aim to widen participation by providing a support mechanism aimed at helping students stay in Higher Education but the use of PASS has been shown to enhance academic performance and promote the development of skills and attributes to strengthen employability. This is particularly the case for PASS leaders who are often described as the 'real winners' in the process. However, research in this area is limited. With this in mind, this paper sets out to describe the particular benefits of PASS for peer leaders and, in so doing, draws on some peer mentoring research, much of which has been conducted in an American and Australian context. As such, the paper should be of particular interest to those wishing to determine whether the various claims can be generalised to the PASS process, as it currently exists within the UK.

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Bridging the Gap between Online and Offline Applications with the Google Gears API: A Case Study for Diabetics

Monocular Omnidirectional Vision based Robot Localisation and Mapping

Towards Autonomous Robotic Systems, Sep 1, 2008

The ability to localise in an unknown environment is of key importance in many robot applications... more

Human hand motion capture in image sequences for real-time animation systems

The Imaging Science Journal, Dec 1, 2008

This extended abstract details previous methods for motion tracking and capture in 3D animation a... more This extended abstract details previous methods for motion tracking and capture in 3D animation and in particular that of hand motion tracking and capture. The research aims to enable gesture capture with interpretation of the captured gestures and control of the target 3D animation software. This stage of the project involves the development and testing of a motion analysis system. A motion analysis system is being built from algorithms recently developed. The authors review current software and research methods available in this area and describe current work-in-progress. Motion capture is a technique of digitally recording the movements of real entities, usually humans. It was originally developed as an analysis tool in biomechanics research, but has grown increasingly important as a source of motion data for computer animation. In this context it has been widely used for both cinema and video games. Hand motion capture and tracking in particular has received a lot of attention because of its critical role in the design of new Human Computer Interaction methods and gesture analysis. One of the main difficulties is the capture of human hand motion.

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Software and Methods for Motion Capture and Tracking in Animation

CGVR, Jun 3, 2006

This extended abstract details previous methods for motion tracking and capture in 3D animation a... more This extended abstract details previous methods for motion tracking and capture in 3D animation and in particular that of hand motion tracking and capture. Our research aims to enable gesture capture with interpretation of the captured gestures and control of the target 3D animation software. This stage of the project involves the development and testing of a motion analysis system. A motion analysis system is being built from algorithms recently developed. We review current software and research methods available in this area and describe our work-inprogress. Motion capture is a technique of digitally recording the movements of real entities, usually humans. It was originally developed as an analysis tool in biomechanics research, but has grown increasingly important as a source of motion data for computer animation. In this context it has been widely used for both cinema and video games. Hand motion capture and tracking in particular has received a lot of attention because of its critical role in the design of new Human Computer Interaction methods and gesture analysis. One of the main difficulties is the capture of human hand motion.

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History Aware Device-free Passive (DfP) Localisation

Image Processing and Communications, 2011

Novelty Detection as an Intrinsic Motivation for Cumulative Learning Robots

Springer eBooks, Nov 10, 2012

ABSTRACT Novelty detection is an inherent part of intrinsic motivations and constitutes an import... more ABSTRACT Novelty detection is an inherent part of intrinsic motivations and constitutes an important research issue for the effective and long-term operation of intelligent robots designed to learn, act and make decisions based on their cumulative knowledge and experience. Our approach to novelty detection is from the perspective that the robot ignores perceptions that are already known, but is able to identify anything different. This is achieved by developing biologically inspired novelty detectors based on habituation. Habituation is a type of non-associative learning used to describe the behavioural phenomenon of decreased responsiveness of a cognitive organism to a recently and frequently presented stimulus, and it has been observed in a number of biological organisms. This chapter first considers the relationship between intrinsic motivations and novelty detection and outlines some works on intrinsic motivations. It then presents a critical review of the methods of novelty detection published by the authors. A brief summary of some key recent surveys in the field is then provided. Finally, key open challenges that need to be considered in the design of novelty detection filters for cumulative learning tasks are discussed.

Experiences of using the Honest Broker Service for analysis of a maternity dataset and a prescribing dataset to determine the profile of women in Northern Ireland who have accessed maternity services and who have heart conditions

Seat Booking System for a Cineplex

Computer and Information Science, Apr 19, 2008

Support Vector Machine Classification in a Device-Free Passive Localisation (DfPL) Scenario

Advances in intelligent systems and computing, 2013

A multimodal smartphone sensor system for behaviour measurement and health status inference

Information Fusion, 2020

Smartphones are becoming increasingly pervasive in almost every aspect of daily life. With smartp... more Smartphones are becoming increasingly pervasive in almost every aspect of daily life. With smartphones being equipped with multiple sensors, they provide an opportunity to automatically extract information relating to daily life. Information relating to daily life could have major benefits in the area of health informatics. Research shows that there is a need for more objective and accurate means of measuring health status. Hence, this work investigates the use of multi-modal smartphone sensors to measure human behaviour and generate behaviour profiles which can be used to make objective predictions related to health status. Three sensor modalities are used to compute behaviour profiles for three different components of human behaviour. Motion sensors are utilised to measure physical activity, location sensors are utilised to measure travel behaviour and sound sensors are used to measure voice activity related behaviour. Sensor fusion, using a genetic algorithm, is performed to find complementary and cooperative features. Using a behaviour feature composed of motion, sound and locations data, results show that a Support Vector Machine (SVM) can predict 10 different health metrics with an error that does not exceed a clinical error benchmark.

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A survey of active and passive indoor localisation systems

Computer Communications, Sep 1, 2012

In recent years the need for indoor localisation has increased. Earlier systems have been deploye... more In recent years the need for indoor localisation has increased. Earlier systems have been deployed in order to demonstrate that indoor localisation can be done. Many researchers are referring to location estimation as a crucial component in numerous applications. There is no standard in indoor localisation thus the selection of an existing system needs to be done based on the environment being tracked, the accuracy and the precision required. Modern localisation systems use various techniques such as Received Signal Strength Indicator (RSSI), Time of Arrival (TOA), Time Difference of Arrival (TDOA) and Angle of Arrival (AOA). This paper is a survey of various active and passive localisation techniques developed over the years. The majority of the localisation techniques are part of the active systems class due to the necessity of tags/electronic devices carried by the person being tracked or mounted on objects in order to estimate their position. The second class called passive localisation represents the estimation of a person's position without the need for a physical device i.e. tags or sensors. The assessment of the localisation systems is based on the wireless technology used, positioning algorithm, accuracy and precision, complexity, scalability and costs. In this paper we are comparing various systems presenting their advantages and disadvantages.

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Peer Assisted Study Sessions: The Evaluation of a Cross-Faculty Initiative in Ulster

Pogue, Armstrong, Green, McGrath explore degree classifications and look in particular at the BSc... more Pogue, Armstrong, Green, McGrath explore degree classifications and look in particular at the BSc Accounting degree, and find there is an improvement in average award performance when the second year performance contributes 25% to the overall mark. They propose that because of the 25% weighting, students perceived second year performance as more important than previously and that their increased effort led to improved second year performance and, in turn, improved degree classifications.

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Joan Condell

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