- R Marques d'Avila e Bolama, Dep. Informatica.
- +351-275319700
Nuno Garcia
Universidade de Lisboa, Department of Physics, Faculty Member
- Ambient Assisted Living, Computer Networks, Complex Networks, Next Generation Internet Research, Human Computer Interaction, Bioinformatics, and 20 moreComputer Ethics, Bioengineering, Software Engineering, Biocomputing, Computer Networks and Communications, Computer Science, Network Security, Algorithms, Database Systems, Operating Systems, Biomedical Engineering, Data Structures, PhD Thesis on Optical Burst Switching Networks Architectures and Algorithms, Surface Electromyography, Complexity, Complexity Science and Design, Computer Network architecture, Shortest path with Ant Routing Algorithm in wireless traffic network, Engineering, and Information Technologyedit
- Nuno M. Garcia is Assistant Professor and Computer Science Engineering BSc Course Director at the University of Beira... moreNuno M. Garcia is Assistant Professor and Computer Science Engineering BSc Course Director at the University of Beira Interior (Covilhã, Portugal). He is also Invited Associate Professor at the Universidade Lusófona de Humanidades e Tecnologias (Lisbon, Portugal).edit
Nowadays, individuals have very stressful lifestyles, affecting their nutritional habits. In the early stages of life, teenagers begin to exhibit bad habits and inadequate nutrition. Likewise, other people with dementia, Alzheimer’s... more
Nowadays, individuals have very stressful lifestyles, affecting their nutritional habits. In the early stages of life, teenagers begin to exhibit bad habits and inadequate nutrition. Likewise, other people with dementia, Alzheimer’s disease, or other conditions may not take food or medicine regularly. Therefore, the ability to monitor could be beneficial for them and for the doctors that can analyze the patterns of eating habits and their correlation with overall health. Many sensors help accurately detect food intake episodes, including electrogastrography, cameras, microphones, and inertial sensors. Accurate detection may provide better control to enable healthy nutrition habits. This paper presents a systematic review of the use of technology for food intake detection, focusing on the different sensors and methodologies used. The search was performed with a Natural Language Processing (NLP) framework that helps screen irrelevant studies while following the PRISMA methodology. It ...
Research Interests:
Cardiac diseases have increased over the years; thus, it is essential to predict their possible signs. Accurate prediction efficiently treats the patient’s medical history before the attack occurs. Sensors available in commonly used... more
Cardiac diseases have increased over the years; thus, it is essential to predict their possible signs. Accurate prediction efficiently treats the patient’s medical history before the attack occurs. Sensors available in commonly used devices may strive for the proper and early identification of various cardiac diseases. The primary purpose of this review is to analyze studies related to gender discretization based on data from different sensors including electrocardiography and echocardiography. The analyzed studies were published between 2010 and 2022 in various scientific databases, including PubMed Central, Springer, ACM, IEEE Xplore, MDPI, and Elsevier, based on the analysis of different cardiovascular diseases. It was possible to verify that most of the analyzed studies measured similar parameters as traditional methods including the QRS complex and other waves that characterize the various individuals.
Research Interests:
Cardiovascular diseases have always been here, but there has been an increase in their numbers over time. Even though there are in the digital world a few applications to help with this kind of problem, there are not enough to fulfill the... more
Cardiovascular diseases have always been here, but there has been an increase in their numbers over time. Even though there are in the digital world a few applications to help with this kind of problem, there are not enough to fulfill the needs of the patients. This study reviews mobile applications that allow patients to monitor and report cardiovascular diseases. It presents a review of 14 mobile applications that were free to download in Portugal and classified and compared according to their characteristics. The selection criteria combined the following keywords: “patient”, “cardiac/or heart”, “report”, and (“tracking” or “monitoring”). Based on the analysis, we point out the errors of the applications and present some solutions. To finish, we investigated how mobile applications can help patients track and self-report cardiovascular diseases.
Research Interests:
Research Interests:
Research Interests:
Over the past decades, the application of computer science and engineering principles to the field of Human-Computer Interaction (HCI) has proven to be of paramount importance, leading to remarkable technical, methodological and... more
Over the past decades, the application of computer science and engineering principles to the field of Human-Computer Interaction (HCI) has proven to be of paramount importance, leading to remarkable technical, methodological and scientific achievements (Stephen, 2009). Biomedical signals are a particularly popular topic within the global research community. Recent examples spread through academia and industry, including initiatives such as the brain-computer interface (BCI) research program at Facebook Reality Labs (Tekla, 2020), the heart rate enhanced communication being explored by Snap, Inc. Research (Liu et al., 2021), or the work of Yamaha Corporation and world-renowned dancer Kaiji Moriyama on the use of Electromyography (EMG) to control a piano (Yamaha Corporation, 2018). Nowadays, biomedical signals applied to HCI drive researchers in areas ranging from computer science and electrical engineering to social sciences, being one of the areas with high potential to enhance the ...
Research Interests:
Research Interests:
Image analysis is a well-researched area, although some open prob-lems have still to be addressed. Deserving further investigation, we consider the problem of detecting natural or artificial areas in images. This paper describes the... more
Image analysis is a well-researched area, although some open prob-lems have still to be addressed. Deserving further investigation, we consider the problem of detecting natural or artificial areas in images. This paper describes the initial research towards this goal, based on Shannon’s concept of entropy of in-formation, as a mean to allow the detection of areas that are more irregular and thus, probably natural, or more regular, and thus probably artificial. This paper also describes the limitations of this research, and points out future research prob-lems regarding the automatic identification of artificial and natural zones in an im-age.
Research Interests:
Generally, a massive number of mobile applications is growing day today. There are several types of applications. However, healthcare applications are critical domain nowadays in the scientific field. Consequently, it is crucial to... more
Generally, a massive number of mobile applications is growing day today. There are several types of applications. However, healthcare applications are critical domain nowadays in the scientific field. Consequently, it is crucial to understand how the current state of the art in this domain in non-European countries is such as Georgia. Therefore, this paper presents a study concerning the current scenario on e-health applications which is available for Georgian citizens. Furthermore, this paper examines which are the barriers of development of e-health and m-health in the before mentioned country. The results show a limited number of existing applications. This study analysis 11 mobile applications. In total, 55% of the analyzed apps only support the Georgian language and 36% are informative mobile applications. However, the available mobile apps in the Georgian language does not provide communication between doctors and patients which is a critical limitation. The results will be he...
Research Interests:
Research Interests:
Research Interests:
The recognition of Activities of Daily Living (ADL) and their environments based on sensors available in off-the-shelf mobile devices is an emerging topic. These devices are capable to acquire and process the sensors' data for the... more
The recognition of Activities of Daily Living (ADL) and their environments based on sensors available in off-the-shelf mobile devices is an emerging topic. These devices are capable to acquire and process the sensors' data for the correct recognition of the ADL and their environments, providing a fast and reliable feedback to the user. However, the methods implemented in a mobile application for this purpose should be adapted to the low resources of these devices. This paper focuses on the demonstration of a mobile application that implements a framework, that forks their implementation in several modules, including data acquisition, data processing, data fusion and classification methods based on the sensors? data acquired from the accelerometer, gyroscope, magnetometer, microphone and Global Positioning System (GPS) receiver. The framework presented is a function of the number of sensors available in the mobile devices and implements the classification with Deep Neural Network...
Research Interests:
Research Interests:
Background:Mobile applications can be used for the monitoring of lifestyles and physical activity. It can be installed in commodity mobile devices, which are currently used by different types of people in their daily activities worlwide... more
Background:Mobile applications can be used for the monitoring of lifestyles and physical activity. It can be installed in commodity mobile devices, which are currently used by different types of people in their daily activities worlwide .Objective:This paper reviews and categorizes the mobile applications related to diet, nutrition, health, physical activity and education, showing the analysis of 73 mobile applications available on Google Play Store with the extraction of the different features.Methods:The mobile applications were analyzed in relation to each proposed category and their features, starting with the definition of the search keywords used in the Google Play Store. Each mobile application was installed on a smartphone, and validated whether it was researched in scientific studies. Finally, all mobile applications and features were categorized.Results:These mobile applications were clustered into four groups, including diet and nutrition, health, physical activity and ed...
Research Interests:
Several types of sensors have been available in off-the-shelf mobile devices, including motion, magnetic, vision, acoustic, and location sensors. This paper focuses on the fusion of the data acquired from motion and magnetic sensors,... more
Several types of sensors have been available in off-the-shelf mobile devices, including motion, magnetic, vision, acoustic, and location sensors. This paper focuses on the fusion of the data acquired from motion and magnetic sensors, i.e., accelerometer, gyroscope and magnetometer sensors, for the recognition of Activities of Daily Living (ADL) using pattern recognition techniques. The system developed in this study includes data acquisition, data processing, data fusion, and artificial intelligence methods. Artificial Neural Networks (ANN) are included in artificial intelligence methods, which are used in this study for the recognition of ADL. The purpose of this study is the creation of a new method using ANN for the identification of ADL, comparing three types of ANN, in order to achieve results with a reliable accuracy. The best accuracy was obtained with Deep Learning, which, after the application of the L2 regularization and normalization techniques on the sensors’ data, repor...
Research Interests:
Research Interests:
Research Interests:
Background:Off-the-shelf-mobile devices have several sensors available onboard that may be used for the recognition of Activities of Daily Living (ADL) and the environments where they are performed. This research is focused on the... more
Background:Off-the-shelf-mobile devices have several sensors available onboard that may be used for the recognition of Activities of Daily Living (ADL) and the environments where they are performed. This research is focused on the development of Ambient Assisted Living (AAL) systems, using mobile devices for the acquisition of the different types of data related to the physical and physiological conditions of the subjects and the environments. Mobile devices with the Android Operating Systems are the least expensive and exhibit the biggest market while providing a variety of models and onboard sensors.Objective:This paper describes the implementation considerations, challenges and solutions about a framework for the recognition of ADL and the environments, provided as an Android library. The framework is a function of the number of sensors available in different mobile devices and utilizes a variety of activity recognition algorithms to provide a rapid feedback to the user.Methods:T...
Research Interests:
Research Interests:
Mobile applications have become a must in every user’s smart device, and many of these applications make use of the device sensors’ to achieve its goal. Nevertheless, it remains fairly unknown to the user to which extent the data the... more
Mobile applications have become a must in every user’s smart device, and many of these applications make use of the device sensors’ to achieve its goal. Nevertheless, it remains fairly unknown to the user to which extent the data the applications use can be relied upon and, therefore, to which extent the output of a given application is trustworthy or not. To help developers and researchers and to provide a common ground of data validation algorithms and techniques, this paper presents a review of the most commonly used data validation algorithms, along with its usage scenarios, and proposes a classification for these algorithms. This paper also discusses the process of achieving statistical significance and trust for the desired output.
Research Interests:
Research Interests:
The use of wearable technologies in medicine and health care has become of important in order to considerably improve benefits for patients and health service providers. Within telemedicine, biomedical clothing plays a crucial role. The... more
The use of wearable technologies in medicine and health care has become of important in order to considerably improve benefits for patients and health service providers. Within telemedicine, biomedical clothing plays a crucial role. The main technology advances and the research of the Textile and Paper Materials Research Unit (UMTP) and of the Assisted Living Computing and Telecommunications Laboratory (ALLab) teams, in the area, will be addressed. Issues that remain unsolved will be presented. The chapter presents an overview of the key concepts for telemedicine and the role of textile electrodes and their integration in smart clothing. The development of software algorithms that specifically handle signals that are collected using biomedical clothing, integrating resiliency and a proper set of alarms, is presented and discussed in the context of classical biomedical signal processing. Finally, biomedical clothing design will be discussed in social, psychological, and esthetical co...
Research Interests:
Research Interests:
The need for large-bandwidth networks is in continuous growth. Such demands are attributed to the user desire to have everything on-line. To support needs, all-optical networks, with their large bandwidth lend themselves considerable... more
The need for large-bandwidth networks is in continuous growth. Such demands are attributed to the user desire to have everything on-line. To support needs, all-optical networks, with their large bandwidth lend themselves considerable attention from both industry and academia. As a result, some optical switching paradigms have been proposed such as optical circuit switching, optical packet switching and optical burst switching. Among these paradigms, Optical Burst Switching (OBS) is seen as a viable solution. However, lack of mature optical memory makes burst loss ratio in OBS critical which needs to be solved before OBS can really be used in telecommunication networks. Many solutions have been proposed and evaluated to address this issue. These solutions can be categorised into two categories: architectural solutions and procedural solutions. Architectural solutions deal with the architectural design of OBS and these solutions are further classified into two classes: non-slotted and slotted OBS. Procedural solutions deal with the improvement of the operation of OBS networks in terms of burst assembly, routing, switching, scheduling, signalling, etc. In this paper, we focus on architectural solutions where we investigate QoS performance of non-slotted and slotted OBS in terms of burst loss ratio and throughput. Simulation results show that slotted outperforms non-slotted OBS; the results also demonstrate that higher priority bursts outperforms lower priority ones.
Research Interests:
Rehabilitation aims to increase the independence and physical function after injury, surgery, or other trauma, so that patients can recover to their previous ability as much as possible. To be able to measure the degree of recovery and... more
Rehabilitation aims to increase the independence and physical function after injury, surgery, or other trauma, so that patients can recover to their previous ability as much as possible. To be able to measure the degree of recovery and impact of the treatment, various functional performance tests are used. The Eight Hop Test is a hop exercise that is directly linked to the rehabilitation of people suffering from tendon and ligament injuries on the lower limb. This paper presents a systematic review on the use of sensors for measuring functional movements during the execution of the Eight Hop Test, focusing primarily on the use of sensors, related diseases, and different methods implemented. Firstly, an automated search was performed on the publication databases: PubMed, Springer, ACM, IEEE Xplore, MDPI, and Elsevier. Secondly, the publications related to the Eight-Hop Test and sensors were filtered according to several search criteria and 15 papers were finally selected to be analyz...
Research Interests:
Falling is a commonly occurring mishap with elderly people, which may cause serious injuries. Thus, rapid fall detection is very important in order to mitigate the severe effects of fall among the elderly people. Many fall monitoring... more
Falling is a commonly occurring mishap with elderly people, which may cause serious injuries. Thus, rapid fall detection is very important in order to mitigate the severe effects of fall among the elderly people. Many fall monitoring systems based on the accelerometer have been proposed for the fall detection. However, many of them mistakenly identify the daily life activities as fall or fall as daily life activity. To this aim, an efficient machine learning-based fall detection algorithm has been proposed in this paper. The proposed algorithm detects fall with efficient sensitivity, specificity, and accuracy as compared to the state-of-the-art techniques. A publicly available dataset with a very simple and computationally efficient set of features is used to accurately detect the fall incident. The proposed algorithm reports and accuracy of 99.98% with the Support Vector Machine(SVM) classifier.
Research Interests:
Context: Ethics have broad applications in different fields of study and different contexts. Like other fields of study, ethics have a significant impact on the decisions made in computing concerning software artifact production and its... more
Context: Ethics have broad applications in different fields of study and different contexts. Like other fields of study, ethics have a significant impact on the decisions made in computing concerning software artifact production and its processes. Hence, in this research, ethics is considered in the context of requirements engineering during the software development process. Objective: The aim of this paper is to discuss the investigation results regarding ethical problems of requirements engineering processes by taking sample software developing companies and exposing existing research gaps. Method: This research uses interviewing, focus group discussions, purposive sampling, and qualitative analysis research methods. Result: This research finds an absence of industry practices, professional responsibility code of conduct standards, and other guidelines within companies when integrating ethical concerns of software during requirements engineering. It also indicates that almost all ...
Research Interests:
a series of events taking a global perspective on population health, from national to crosscountry approaches, multiplatform technologies, from drug design to medicine accessibility, everything under mobile, ubiquitous, and personalized... more
a series of events taking a global perspective on population health, from national to crosscountry approaches, multiplatform technologies, from drug design to medicine accessibility, everything under mobile, ubiquitous, and personalized characteristics of new age population. Recent advances in technology and computational science influenced a large spectrum of branches in approaching population health. Despite significant progresses, many challenges exist, including health informatics, crosscountry platforms interoperability, system and laws harmonization, protection of health data, practical solutions, accessibility to health services, and many others. Along with technological progress, personalized medicine, ambient assistance and pervasive health complement patient needs. A combination of classical and information-driven approach is developing now, where diagnosis systems, data protection mechanisms, remote assistance and hospital-processes are converging. The conference had the ...
a stage to present and evaluate the advances in emerging solutions for next-generation architectures, devices, and communications protocols. Particular focus was aimed at optimization, quality, discovery, protection, and user profile... more
a stage to present and evaluate the advances in emerging solutions for next-generation architectures, devices, and communications protocols. Particular focus was aimed at optimization, quality, discovery, protection, and user profile requirements supported by special approaches such as network coding, configurable protocols, context-aware optimization, ambient systems, anomaly discovery, and adaptive mechanisms. Next-generation large distributed networks and systems require substantial reconsideration of existing 'de facto' approaches and mechanisms to sustain an increasing demand on speed, scale, bandwidth, topology and flow changes, user complex behavior, security threats, and service and user ubiquity. As a result, growing research and industrial forces are focusing on new approaches for advanced communications considering new devices and protocols, advanced discovery mechanisms, and programmability techniques to express, measure, and control the service quality, security...
in Porto, Portugal, continued a series of events meant to present and evaluate the advances in emerging solutions for next-generation architectures, devices, and communications protocols. Particular focus was aimed at optimization,... more
in Porto, Portugal, continued a series of events meant to present and evaluate the advances in emerging solutions for next-generation architectures, devices, and communications protocols. Particular focus was aimed at optimization, quality, discovery, protection, and user profile requirements supported by special approaches such as network coding, configurable protocols, context-aware optimization, ambient systems, anomaly discovery, and adaptive mechanisms. Next-generation large distributed networks and systems require substantial reconsideration of exiting 'de facto' approaches and mechanisms to sustain an increasing demand on speed, scale, bandwidth, topology and flow changes, user complex behavior, security threats, and service and user ubiquity. As a result, growing research and industrial forces are focusing on new approaches for advanced communications considering new devices and protocols, advanced discovery mechanisms, and programmability techniques to express, meas...
Research Interests: Computer Science and IEEE
Research Interests:
Research Interests:
The tremendous applications of human activity recognition are surging its span from health monitoring systems to virtual reality applications. Thus, the automatic recognition of daily life activities has become significant for numerous... more
The tremendous applications of human activity recognition are surging its span from health monitoring systems to virtual reality applications. Thus, the automatic recognition of daily life activities has become significant for numerous applications. In recent years, many datasets have been proposed to train the machine learning models for efficient monitoring and recognition of human daily living activities. However, the performance of machine learning models in activity recognition is crucially affected when there are incomplete activities in a dataset, i.e., having missing samples in dataset captures. Therefore, in this work, we propose a methodology for extrapolating the missing samples of a dataset to better recognize the human daily living activities. The proposed method efficiently pre-processes the data captures and utilizes the k-Nearest Neighbors (KNN) imputation technique to extrapolate the missing samples in dataset captures. The proposed methodology elegantly extrapolate...
Research Interests:
Research Interests:
This paper presents a PhD project related to the use of multi-sensor data fusion techniques, applied to the sensors embedded in mobile devices, as a mean to identify user’s daily activities. It introduces some basic concepts, such as the... more
This paper presents a PhD project related to the use of multi-sensor data fusion techniques, applied to the sensors embedded in mobile devices, as a mean to identify user’s daily activities. It introduces some basic concepts, such as the definition of activities of daily living, mobile platforms/sensors, multisensor technologies, data fusion, and data imputation. These techniques have already been applied to fuse the data acquired with different sensors, but due to memory constraints, battery life and processing power of these devices, not all the techniques are suited to be used in these environments. This paper explains an overview about the state of the research in this topic, explaining the methodology to create a best effort method to recognize a large number of activities of daily living using a mobile device.
Pneumonia caused by COVID-19 is a severe health risk that sometimes leads to fatal outcomes. Due to constraints in medical care systems, technological solutions should be applied to diagnose, monitor, and alert about the disease’s... more
Pneumonia caused by COVID-19 is a severe health risk that sometimes leads to fatal outcomes. Due to constraints in medical care systems, technological solutions should be applied to diagnose, monitor, and alert about the disease’s progress for patients receiving care at home. Some sleep disturbances, such as obstructive sleep apnea syndrome, can increase the risk for COVID-19 patients. This paper proposes an approach to evaluating patients’ sleep quality with the aim of detecting sleep disturbances caused by pneumonia and other COVID-19-related pathologies. We describe a non-invasive sensor network that is used for sleep monitoring and evaluate the feasibility of an approach for training a machine learning model to detect possible COVID-19-related sleep disturbances. We also discuss a cloud-based approach for the implementation of the proposed system for processing the data streams. Based on the preliminary results, we conclude that sleep disturbances are detectable with affordable ...
Research Interests:
As the number of published scientific articles increases, the analysis of trends and state-of-the-art in software engineering is becoming very time-consuming and laborious task. To address the ever-growing demands for systematic... more
As the number of published scientific articles increases, the analysis of trends and state-of-the-art in software engineering is becoming very time-consuming and laborious task. To address the ever-growing demands for systematic literatures review techniques, rapid review and scoping reviews techniques have emerged. We used an NLP powered tool, which employs the PRISMA surveying methodology, to automate most of the review processes. We used it to automatically review relevant articles indexed in IEEE Xplore, PubMed and Springer digital libraries on the topic “Software Development for Enhanced Living Environments and Ambient Assisted Living”. The relevant articles identified by the NLP toolkit contained up to 21 properties clustered into 3 logical groups. We discovered that Software Development for Enhanced and Assisted living environments attracted an increased attention from the scientific communities over the last 10 years and showed several trends in the specific research topics ...
Research Interests:
The Universidade da Beira Interior (UBI), Covilhã, Portugal in the medical degree course uses simulation in an integrated and comprehensive program as a pedagogical tool.
Research Interests:
Abstract Atrial Fibrillation (AF) is a type of arrhythmia characterized by irregular heartbeats, with four types, two of which are complicated to diagnose using standard techniques such as Electrocardiogram (ECG). However, and because... more
Abstract Atrial Fibrillation (AF) is a type of arrhythmia characterized by irregular heartbeats, with four types, two of which are complicated to diagnose using standard techniques such as Electrocardiogram (ECG). However, and because smart wearables are increasingly a piece of commodity equipment, there are several ways of detecting and predicting AF episodes using only an ECG exam, allowing physicians easier diagnosis. By searching several databases, this study presents a review of the articles published in the last ten years, focusing on those who reported studies using Artificial Intelligence (AI) for prediction of AF. The results show that only twelve studies were selected for this systematic review, where three of them applied deep learning techniques (25%), six of them used machine learning methods (50%) and three others focused on applying general artificial intelligence models (25%). To conclude, this study revealed that the prediction of AF is yet an under-developed field in the context of AI, and deep learning techniques are increasing the accuracy, but these are not as frequently applied as it would be expected. Also, more than half of the selected studies were published since 2016, corroborating that this topic is very recent and has a high potential for additional research.
Research Interests:
The ubiquity of mobile devices and the pervasive Internet raised a new paradigm in care models, based more on contacts than on visits. However, the effects of assistive computerised systems on practitioners and patients remain... more
The ubiquity of mobile devices and the pervasive Internet raised a new paradigm in care models, based more on contacts than on visits. However, the effects of assistive computerised systems on practitioners and patients remain understudied, and their promise of increasing self-care, acceptability, and accuracy of healthcare monitoring mostly untested. Similarly, evidence remains controversial concerning the effectiveness of providing support to caregivers of Alzheimer’s disease patients, through technological devices integrated with existing care services. This paper aims to contribute further results and evidences gained from experimental trials, related to two different solutions: an electronic pain monitoring system, and a technological kit to support Alzheimer’s patients caregivers. The positive outcomes suggest to further extend similar studies, to better clarify the role and realistic expectations on the use of ICT in healthcare.
Research Interests:
The User Datagram Protocol (UDP) and other similar protocols send application data from the source to the destination machine inside segments, without foreseeing for any type of control on the transmission or success metrics. These... more
The User Datagram Protocol (UDP) and other similar protocols send application data from the source to the destination machine inside segments, without foreseeing for any type of control on the transmission or success metrics. These protocols are very convenient for real time transmission. To sustain the increased functionality and features of the connection-oriented protocol, a set of mechanisms is implemented based on some specific fields of the segment header. These mechanisms result in a significant overhead in terms of the increased number of transmitted packets. This may further translate into significant delays, because of the additional number of switching and routing tasks, and eventually, because of more complex communications procedures, such as e.g. transmission window resizing, and of course, acknowledgement and sequence numbers updating. The two extremes of these communication modalities, one that has no control at all, and the other one that allows for full control, ha...
Research Interests:
Cloud computing recently offers immense benefits. But higher education institutions (HEIs) are hesitating to adopt. As a result, they are not benefited more from such technology. This is because key adoption capabilities are not explored... more
Cloud computing recently offers immense benefits. But higher education institutions (HEIs) are hesitating to adopt. As a result, they are not benefited more from such technology. This is because key adoption capabilities are not explored in detail in HEIs context. In addition to this, there is no comprehensive empirically validated adoption readiness assessment model which helps them to adopt Cloud solutions efficiently. Hence, to fill this gap this study identifies the critical capabilities and develops a model to assess Cloud computing adoption readiness of higher education institutions before initiating the adoption. Resource based view theory was used as theoretical lens to identify capabilities and to build the model. The conceptual model considers adoption readiness and adoption success from technological, human, organizational, financial and external environment dimensions. The model proposes that the degree to which an organization holds these capabilities is related to the ...
Research Interests:
Novel information and communication technologies create possibilities to change the future of health care. Ambient Assisted Living (AAL) is seen as a promising supplement of the current care models. The main goal of AAL solutions is to... more
Novel information and communication technologies create possibilities to change the future of health care. Ambient Assisted Living (AAL) is seen as a promising supplement of the current care models. The main goal of AAL solutions is to apply ambient intelligence technologies to enable elderly people to continue to live in their preferred environments. Applying trained models from health data is challenging because the personalized environments could differ significantly than the ones which provided training data. This paper investigates the effects on activity recognition accuracy using single accelerometer of personalized models compared to models built on general population. In addition, we propose a collaborative filtering based approach which provides balance between fully personalized models and generic models. The results show that the accuracy could be improved to 95% with fully personalized models, and up to 91.6% with collaborative filtering based models, which is significa...
Research Interests:
Healthcare treatments might benefit from advances in artificial intelligence and technological equipment such as smartphones and smartwatches. The presence of cameras in these devices with increasingly robust and precise pattern... more
Healthcare treatments might benefit from advances in artificial intelligence and technological equipment such as smartphones and smartwatches. The presence of cameras in these devices with increasingly robust and precise pattern recognition techniques can facilitate the estimation of the wound area and other telemedicine measurements. Currently, telemedicine is vital to the maintenance of the quality of the treatments remotely. This study proposes a method for measuring the wound area with mobile devices. The proposed approach relies on a multi-step process consisting of image capture, conversion to grayscale, blurring, application of a threshold with segmentation, identification of the wound part, dilation and erosion of the detected wound section, identification of accurate data related to the image, and measurement of the wound area. The proposed method was implemented with the OpenCV framework. Thus, it is a solution for healthcare systems by which to investigate and treat peopl...
Research Interests:
Most mobile devices include motion, magnetic, acoustic, and location sensors. They allow the implementation of a framework for the recognition of Activities of Daily Living (ADL) and its environments, composed by the acquisition,... more
Most mobile devices include motion, magnetic, acoustic, and location sensors. They allow the implementation of a framework for the recognition of Activities of Daily Living (ADL) and its environments, composed by the acquisition, processing, fusion, and classification of data. This study compares different implementations of artificial neural networks, concluding that the obtained results were 85.89% and 100% for the recognition of standard ADL. Additionally, for the identification of standing activities with Deep Neural Networks (DNN) respectively, and 86.50% for the identification of the environments with Feedforward Neural Networks. Numerical results illustrate that the proposed framework can achieve robust performance from the data fusion of off-the-shelf mobile devices.