Matias Garcia-Constantino

University of Ulster · School of Computing and Mathematics

Poverty elimination is an essential and unavoidable step in human development. Predicting poverty is the first crucial step in addressing this issue, especially in developing countries where it remains a significant concern. The main objectives of this paper are: (i) to explore and analyze the multidimensional poverty data in Pattani province, and...

In the contemporary landscape, technology holds pivotal significance across diverse domains, including academia and industry. The Faculty of Industrial Engineering at Telkom University faces challenges in optimizing the value derived from its IT investments to meet evolving market demands. To address this, IT governance methodologies are essential,...

Taiwan is highly mountainous, making it the world's fourth-highest island. The main island is distinguished by the contrast between its eastern two-thirds, which consist primarily of rough forest-covered mountains. Taiwan's climate is influenced by the east Asian monsoon, whereas regions of central and southern Taiwan have a tropical monsoon climat...

Sensor Data Fusion (SDT) algorithms and models have been widely used in diverse applications. One of the main challenges of SDT includes how to deal with heterogeneous and complex datasets with different formats. The present work utilised both homogenous and heterogeneous datasets to propose a novel SDT framework. It compares data mining-based fusi...

Sensor fusion algorithms and models have been widely used in recent times. Although research evidence has informed the use of sensor fusion models in diverse applications, there is room for improvement, especially in home-based health monitoring applications which require less supervision and technical knowledge of users. The present work compares...

There is a growing need to introduce and develop formal techniques for computational models capable of faithfully modelling systems of high complexity and concurrent. Such systems are the ambient intelligent systems. This article proposes an efficient framework for the automated modelling and verification of the behavioural models capturing daily a...

Prolonged waiting time has been identified as a common shortcoming in different clinical labs and has been associated with delayed diagnosis, untimely treatment, cost overruns, a major risk of more severe health complications, and higher mortality rates. The problem is even more sharpened if the target population is composed of pregnant women who m...

Land Surface Temperature (LST) is an important factor in ground surface energy balance and in universal climatology studies. Elevation, Land Cover (LC), and vegetation index are three factors that influence ground surface variation, and their influences vary depending on geography. This study aimed to: (i) investigate the seasonal patterns and tren...

Domestic violence between partners and family members is a worldwide problem increasing every day. As per academic studies and media articles, it escalated during the COVID-19 outbreak. Domestic violence can portray verbally and physically in several ways (for instance, between partners or against children and older people). Deep Learning (DL) comb...

This paper proposes a novel approach to identify personalised abnormal behaviour in Activities of Daily Living (ADLs) using accelerometer sensor data. The ADLs considered are: (i) preparing and drinking tea, and (ii) preparing and drinking coffee.Abnormal behaviour identified in the context of these activities can be an indicator of a progressive h...

Recent advances in the development of sensor technology and in the improvement of their connectivity have allowed a widespread application of the Internet of Things (IoT) in different areas (e.g. connected health, smart homes, smart cities, etc.). Many approaches in the literature have focused on the application of IoT in home kitchens for the purp...

The accurate recognition of activities is fundamental for following up on the health progress of people with dementia (PwD), thereby supporting subsequent diagnosis and treatments. When monitoring the activities of daily living (ADLs), it is feasible to detect behaviour patterns, parse out the disease evolution, and consequently provide effective a...

Dangerous driving can cause accidents, injuries and loss of life. An efficient assessment helps to identify the absence or degree of dangerous driving to take the appropriate decisions while driving. Previous studies assess dangerous driving through two approaches: (i) using electronic devices or sensors that provide objective variables (accelerati...

This book was born in the classroom, written by undergraduate and postgraduate thesis students from different universities around the world. The authors address diverse topics such as digital humanities, library information services, information asymmetry, digital preservation, D-Space, editorial processes, scientific communication, social media me...

The classifier selection problem in Assistive Technology Adoption refers to selecting the classification algorithms that have the best performance in predicting the adoption of technology, and is often addressed through measuring different single performance indicators. Satisfactory classifier selection can help in reducing time and costs involved...

Medical advances have allowed people to live longer and this has presented different challenges to support them to keep living independently at home. The COVID-19 pandemic has affected the situation with less care staff and resources available for the elderly, which have also been spending more time at their homes without external contact. Elderly...

There is a global challenge related to the increasing number of People with Dementia (PwD) and the diminishing capacity of governments, health systems, and caregivers to provide the best care for them. Cost-effective technology solutions that enable and ensure a good quality of life for PwD via monitoring and interventions have been investigated co...

Citation: Ekerete, I.; Garcia-Constantino, M.; Diaz-Skeete, Y.; Nugent, C.; McLaughlin, J. Abstract: The ability to monitor Sprained Ankle Rehabilitation Exercises (SPAREs) in home environments can help therapists ascertain if exercises have been performed as prescribed. Whilst wearable devices have been shown to provide advantages such as high acc...

The scale of Internet of Things (IoT) systems has expanded in recent times and, in tandem with this, IoT solutions have developed symbiotic relationships with technologies, such as edge Computing. IoT has leveraged edge computing capabilities to improve the capabilities of IoT solutions, such as facilitating quick data retrieval, low latency respon...

This paper proposes the fusion of Unobtrusive Sensing Solutions (USSs) for human Activity Recognition and Classification (ARC) in home environments. It also considers the use of data mining models and methods for cluster-based analysis of datasets obtained from the USSs. The ability to recognise and classify activities performed in home environment...

The ability to monitor Sprained Ankle Rehabilitation Exercises (SPAREs) in home environments can help therapists to ascertain if exercises have been performed as prescribed. Whilst wearable devices have been shown to provide advantages such as high accuracy and precision during monitoring activities, disadvantages such as limited battery life, user...

Activities of daily living (ADL) systems have been playing an important role in assessing and monitoring the quality of life of elderly people for many years. With the recent advancement and integration of Internet of Things (IoT) devices within ADL systems, the number and quality of services offered has increased significantly. One of these vital...

Background Office work generally consists of high amounts of sedentary behaviour (SB) which has been associated with negative health consequences. We developed the “WorktivIty” mobile app to help office workers reduce their SB through self-monitoring and feedback on sedentary time, prompts to break sedentary time, and educational facts. The aim of...

In fuzzy systems, membership functions determine the groups to which a variable can belong to, and these groups are static or only have one setting in some aspect. However, fuzzy systems typically require to model the dynamic environment they represent. Still, this behavior does not reflect the membership groups in a conventional way. Thus, convent...

Artificial Neural Networks (ANNs) were created inspired by the neural networks in the human brain and have been widely applied in speech processing. The application areas of ANN include: Speech recognition, speech emotion recognition, language identification, speech enhancement, and speech separation, amongst others. Likewise, given that speech pro...

Knee Osteoarthritis (OA) is one of the most prominent diseases in an ageing society and has affected over 10 million people in Thailand. When people suffer from OA, it is very difficult to recover. Therefore, early detection and prevention are important. The typical way to detect OA is by using X-ray imaging. This research study is focused on early...

Activity recognition is one of the most active areas of research in ubiquitous computing. In particular, gait activity recognition is useful to identify various risk factors in people’s health that are directly related to their physical activity. One of the issues in activity recognition, and gait in particular, is that often datasets are unbalance...

Recently, the number of People with Dementia (PwD) has been rising exponentially across the world. The main symptoms that PwD experience include impairments of reasoning, memory, and thought. Owing to the burden faced by this chronic condition, Assistive Technology-based solutions (ATS) have been prescribed as a form of treatment. Nevertheless, it...

This paper proposes the fusion of data from unobtrusive sensing solutions for the recognition and classification of activities in home environments. The ability to recognize and classify activities can help in the objective monitoring of health and wellness trends in ageing adults. While the use of video and stereo cameras for monitoring activities...

Introduction: As high amounts of occupational sitting have been associated with negative health consequences, designing workplace interventions to reduce sedentary behaviour (SB) is of public health interest. Digital technology may serve as a cost-effective and scalable platform to deliver such an intervention. This study describes the iterative d...

Objective: The aim of the study was to evaluate a technological solution in the form of an App to implement and measure person-centredness in nursing. The focus was to enhance the knowledge transfer of a set of person-centred key performance indicators and the corresponding measurement framework used to inform improvements in the experience of car...

BACKGROUND There is a global challenge related to the increase in the number of people with dementia (PwD) and the diminishing capacity of governments, health systems, and caregivers to provide the best care for them. Cost-effective technology solutions that enable and ensure a good quality of life for PwD via monitoring patients and interventions...

This paper presents a probabilistic approach for the identification of abnormal behaviour in Activities of Daily Living (ADLs) from sensor data collected from 30 participants. The ADLs considered are: (i) preparing and drinking tea, and (ii) preparing and drinking coffee. Abnormal behaviour identified in the context of these activities can be an in...

Activity recognition is an important task in many fields, such as ambient intelligence, pervasive healthcare, and surveillance. In particular, the recognition of human gait can be useful to identify the characteristics of the places or physical spaces, such as whether the person is walking on level ground or walking down stairs in which people move...

INTRODUCTION: Dementia is a syndrome characterised by a decline in memory, language, and problem-solving thataffects the ability of patients to perform everyday activities. Patients with dementia tend to experience episodes of anxietyand remain for extended periods, which affects their quality of life.OBJECTIVES: To design AnxiDetector, a system ca...

Activity recognition, a key component in pervasive healthcare monitoring, relies on classification algorithms that require labeled data of individuals performing the activity of interest to train accurate models. Labeling data can be performed in a lab setting where an individual enacts the activity under controlled conditions. The ubiquity of mobi...

Foot ulcers are a common complication of diabetes and are the leading cause of amputation amongst those with diabetes. Research has shown that, an increase of two degrees Celsius in the skin temperature on the plantar surface of the foot can be an early indication of injury or inflammation. Early detection and treatment of a hotspot region may redu...

This paper presents a probabilistic approach for the identification of abnormal behaviour in Activities of Daily Living (ADLs) from dense sensor data collected from 30 participants. The ADLs considered are related to preparing and drinking (i) tea, and (ii) coffee. Abnormal behaviour identified in the context of these activities can be an indicator...

This paper proposes a non-obtrusive system that measures upper extremity velocity during post-stroke rehabilitation exercises within a home environment using a Distance2Go Doppler radar sensing solution. Experimental results are compared with that of an accelerometer in instances of flexion, extension, abduction and adduction. The results demonstra...

In this paper we introduce the Worktivity mobile app as a potential solution to help reduce occupational sitting in an office environment. Worktivity functions by sending hourly reminders to stand up or move in addition to showing factual information related to the benefits of being active within the office environment. The Worktivity app was used...

Purpose: Occupational sedentary behaviour (SB) is a public health concern associated with negative physical and psychological health consequences (1, 2). Reducing SB in office workers can be challenging due to the need to complete desk-bound work. There is evidence to suggest sit-stand workstations can reduce SB without negative effects on producti...

The effectiveness of document Information Extraction (IE) is greatly affected by the structure and layout of the documents being considered. In the case of legal documents relating to commercial law, an additional challenge is the many different and varied formats, structures and layouts used. In this paper, we present work on a flexible and scalab...

Using current sensing technology, a wealth of data on driving sessions is potentially available through a combination of vehicle sensors and drivers' physiology sensors (heart rate, breathing rate, skin temperature, etc.). Our hypothesis is that it should be possible to exploit the combination of time series produced by such multiple sensors during...

This paper presents an investigation into the summarisation of the free text element of questionnaire data using hierarchical text classifi-cation. The process makes the assumption that text summarisation can be achieved using a classification approach whereby several class labels can be associated with documents which then constitute the summarisa...

An investigation into the extraction of useful information from the free text element of questionnaires, using a semi-automated summarisation extraction technique to generate text summarisation classifiers, is described. A realisation of the proposed technique, SARSET (Semi-Automated Rule Summarisation Extraction Tool), is presented and evaluated u...

An investigation into the use of negation in Inductive Rule Learning (IRL) for text classification is described. The use of negated features in the IRL process has been shown to improve effectiveness of classification. However, although in the case of small datasets it is perfectly feasible to include the potential negation of all possible features...

An investigation into the potential effectiveness of generating text classifiers from secondary data for the purpose of text summarisation is described. The application scenario assumes a questionnaire corpus where we wish to provide a summary regarding the nature of the free text element of such questionnaires, but no suitable training data is ava...