Oresti Banos

University of Granada | UGR · Research Center for Information and Communications Technologies of the University of Granada

How affective experiences, such as feelings, emotions, and moods, fluctuate over time is relevant for understanding and predicting psychological well-being. Here, we present a novel approach to investigate affect dynamics grounded on the concept of multistability, a common behavior of complex systems, characterized by abrupt shifts between two or m...

Background: Human Emotion Recognition (HER) has been a popular field of study in the past years. Despite the great progresses made so far, relatively little attention has been paid to the use of HER in autism. People with autism are known to face problems with daily social communication and the prototypical interpretation of emotional responses, wh...

Type 1 diabetes mellitus (T1D) patients face daily difficulties in keeping their blood glucose levels within appropriate ranges. Several techniques and devices, such as flash glucose meters, have been developed to help T1D patients improve their quality of life. Most recently, the data collected via these devices is being used to train advanced art...

This study presents a model for classifying four strength exercises (chest, back, biceps, and triceps). The system is built on the data collected from an IMU sensor embedded in a wearable wristband device. We gathered data from multiple sessions involving three users while they performed these exercises on fitness machines in real-world scenarios....

Are deep learning techniques being applied to image classification of kidney tumours? This systematic review aims to explore papers using this novel scientific method of deep learning (DL) for the detection of kidney tumours in patients. We can start by arguing that this set of techniques is not widespread as only 8 papers have been found in the la...

Most wearable activity recognition systems are defined to be used for a specific sensor setup. However, changes in the body sensor network are sometimes experienced due to sensor failures or upgrades. In such cases, the default activity recognition models are no longer applicable and a complete retraining of the system is normally needed, which is...

Diabetes is one of the most prevalent diseases of the 21st century, with more than 500 million people affected. Having tools to estimate blood glucose levels is critical for these patients in their management of the disease. In this work, we present a comparison of three neural network architectures based on long short-term memory (LSTM). Their pre...

Understanding how affective experiences, such as feelings, emotions, and moods, fluctuate over time is crucial for assessing psychological well-being (Houben et al., 2015). Here, we present a novel approach to investigate affect dynamics grounded on the concept of multistability, a common behaviour of complex systems, characterized by abrupt shifts...

The coronavirus outbreak has impacted severely the well-being of populations all around the world. All of a sudden, people had to shift to remote work and social distancing measures, which resulted in profound changes to daily routines, causing stress, anxiety, and depression. Hence, it is important to understand the effects of COVID-19 on the well...

Aiming to illuminate the effects of enforced confinements on people's lives, this paper presents a novel dataset that measures human behaviour holistically and longitudinally during the COVID-19 outbreak. In particular, we conducted a study during the first wave of the lockdown, where 21 healthy subjects from the Netherlands and Greece participated...

Mental health disorders increasingly affect people worldwide. As a consequence, more families and relatives find themselves acting as caregivers. Most often, these are untrained people who experience loneliness, abandonment, and often develop signs of depression (i.e., caregiver burden syndrome). In this work, we present HIGEA, a digital system bas...

Ecological momentary interventions (EMIs) are treatments that are provided to patients during their daily lives and in natural settings. These types of interventions are often used to improve self-management of health. Technologies such as smartphones can facilitate delivering EMIs thanks to their ubiquity. EMIs represent a novel approach for the d...

Around 500 million people suffer from mental disorders, from which depression, schizophrenia, and dementia are the most prevalent. In Mexico, roughly 17% of people have at least one mental disorder and one in four will be affected at least once in their lifetime. Pervasive technologies are making it possible to support health professionals in the d...

Mental disorders currently affect more than 500 million people in the world, among which, substance use disorders, such as alcohol, represent a major social problem, especially in developing countries. The use of mobile technologies in combination with behavioral and intervention sampling methodologies such as EMA and EMI allow a collection of info...

Recognizing human activities seamlessly and ubiquitously is now closer than ever given the myriad of sensors readily deployed on and around users. However, the training of recognition systems continues to be both time and resource-consuming, as datasets must be collected ad-hoc for each specific sensor setup a person may encounter in their daily li...

The development of applications with intelligent virtual agents (IVA) often comes with integration of multiple complex components. In this article we present the Agents United Platform: an open source platform that researchers and developers can use as a starting point to setup their own multi-IVA applications. The new platform provides developers...

Diabetic retinopathy is a complication of diabetes mellitus. Its early diagnosis can prevent its progression and avoid the development of other major complications such as blindness. Deep learning and transfer learning appear in this context as powerful tools to aid in diagnosing this condition. The present work proposes to experiment with differen...

People with autism spectrum disorder (ASD) are known to show difficulties in the interpretation of human conversational facial expressions. With the recent advent of artificial intelligence, and more specifically, deep learning techniques, new possibilities arise in this context to support people with autism in the recognition of such expressions....

Emotions play a very important role in how we think and behave. As such, the emotions we feel every day can compel us to act and influence the decisions and plans we make about our lives. Being able to measure, analyze, and better comprehend how or why our emotions may change is thus of much relevance to understand human behavior and its consequenc...

Background Diabetes mellitus is a metabolic disorder that affects hundreds of millions of people worldwide and causes several million deaths every year. Such a dramatic scenario puts some pressure on administrations, care services, and the scientific community to seek novel solutions that may help control and deal effectively with this condition an...

BACKGROUND Heavy physical and mental loads are typical for professional soccer players during the competitive season. COVID-19 lockdowns had recently forced competitions to be interrupted and later disputed in a shrunken calendar. Wearable sensors and mobile phones could be potentially useful in monitoring players’ training load in such highly dema...

The increase of mental illness cases around the world can be described as an urgent and serious global health threat. Around 500 million people suffer from mental disorders, among which depression, schizophrenia, and dementia are the most prevalent. Revolutionary technological paradigms such as the Internet of Things (IoT) provide us with new capab...

The introduction of mobile technologies in therapeutic exercise interventions has permitted the collection of fine-grained objective quantified information about patients’ health. However, exercise interventions generally fail to leverage these data when personalizing the exercise needs of patients individually. Interventions that include technolog...

Autism spectrum disorder (ASD) is a range of mental disorders of the neurodevelopmental type, characterized by impairments in socialization, communication, and restrictive patterns of interest, estimating to affect about 1 in 59 individuals. In this chapter, we describe the use of smart devices for evaluating the autonomy and behaviors of people wi...

As advances in technology continue relentlessly, intriguing possibilities for smart home services have emerged [...]

The mDurance® system is an innovative digital tool that combines wearable surface electromyography (sEMG), mobile computing and cloud analysis to streamline and automatize the assessment of muscle activity. The tool is particularly devised to support clinicians and sport professionals in their daily routines, as an assessment tool in the prevention...

The COVID-19 outbreak and the ensuing confinement measures are expected to bear a significant psychological impact on the affected populations. To date, all available studies designed to investigate the psychological effects of this unprecedented global crisis are based on cross-sectional surveys that do not capture emotional variations over time....

BACKGROUND Diabetes mellitus is a metabolic disorder suffered by hundreds of millions of people worldwide and causing several million deaths every year. Such a dramatic scenario puts quite some pressure on administrations, care services and the scientific community to seek novel solutions that may help controlling and dealing effectively with this...

The study of cosmic rays remains as one of the most challenging research fields in Physics. From the many questions still open in this area, knowledge of the type of primary for each event remains as one of the most important issues. All of the cosmic rays observatories have been trying to solve this question for at least six decades, but have not...

The COVID-19 outbreak and the ensuing confinement measures are expected to bear a significant psychological impact on the affected populations. Here, we publish a dataset from CoVidAffect, a citizen science project that was launched to provide direct, geolocalized data of changes in subjective feeling and physical arousal following the COVID-19 cri...

Recent technological advances have enabled the continuous and unobtrusive monitoring of human behaviour. However, most of the existing studies focus on detecting human behaviour under the limitation of one behavioural aspect, such as physical behaviour and not addressing human behaviour in a broad sense. For this reason, we propose a novel framewor...

Collecting experimental data from multiple sensing devices has just recently become quite popular in behavioral and social sciences. Among existing devices, mobile phones stand out as they allow researchers to collect data from individuals in an unbiased, precise, unobtrusive, and timely manner. Current mobile sensing applications are typically dev...

The identification of daily life events that trigger significant changes on our affective state has become a fundamental task in emotional research. To achieve it, the affective states must be assessed in real-time, along with situational information that could contextualize the affective data acquired. However, the objective monitoring of the affe...

Lower limb injuries, especially those related to the knee joint, are some of the most common and severe injuries among sport practitioners. Consequently, a growing interest in the identification of subjects with high risk of injury has emerged during last years. One of the most commonly used injury risk factor is the measurement of joint angles dur...

The automatic recognition of physical activities typically involves various signal processing and machine learning steps used to transform raw sensor data into activity labels. One crucial step has to do with the segmentation or windowing of the sensor data stream, as it has clear implications on the eventual accuracy level of the activity recognis...

Personalized emotion recognition provides an individual training model for each target user in order to mitigate the accuracy problem when using general training models collected from multiple users. Existing personalized speech emotion recognition research has a cold-start problem that requires a large amount of emotionally-balanced data samples f...

Human behaviour analysis through smartphone devices has been an active field for more than a decade and there are still a lot of key aspects to be addressed. This paper surveys the state-of-the-art in human behaviour analysis based on smartphones. We categorise prior works into four main sensing modalities related to physical, cognitive, emotional...

Autistic people have difficulties in recognizing and expressing emotions from/to other people. Technologies can help to facilitate the communication and understanding between autistic and other people. This work particularly investigates the requirements autistic adolescents have on technologies that can measure bodily responses to recognize their...

Behavioral sensing systems collect data from smartphones, wearables, and other devices with the aim of analyzing and making sense of them. In this work, we present InCense IoT, a collective sensing system which uses mobile and ubiquitous sensors for collecting behavior data of groups of participants in shared spaces. This paper describes the concep...

Performance Status (PS) variability is a powerful tool to evaluate overall condition, treatment needs and survival chances of cancer patients. Traditionally, its assessment has relied on the experience of oncologists when interpreting results of clinical tests and when interviewing the patients. Meanwhile, consumer-level activity trackers have obta...

The fluctuation of affective states is a contributing factor to sport performance variability. The context surrounding athletes during their daily life and the evolution of their physiological variables beyond sport events are relevant factors, as they modulate the affective state of the subject over time. However, traditional procedures to assess...

INTRODUCTION: Low Back Pain is a common muscular disorder that most adults would experience over their lives. In healthy patients at the end of a lumbar flexion occur a phenomenon called the Flexion Relaxation Phenomenon. Ratios between different phases of lumbar flexion can help diagnosing LBP patients. The aim of this work is to create an automat...

Smartphones are revolutionizing the way people perceive and interact with both physical and cyber worlds. Mobile coaching (m-coaching) is expected to become a crucial contributor to such a revolution by enabling a new way of providing and receiving personalized healthcare.

People living in both developed and developing countries face serious health challenges related to sedentary lifestyles. It is therefore essential to find new ways to improve health so that people can live longer and age well. With an ever-growing number of smart sensing systems developed and deployed across the globe, experts are primed to help co...

As the population ages, cognitive decline is becoming a worldwide threat to older adults’ independence and quality of life. Cognitive decline involves problems with memory, language, thinking and judgement, thus severely compromising multiple aspects of people’s everyday life. Diagnosis of cognitive disorders is currently performed through clinical...

E-coaching is an emerging computing area in which intelligent systems are used to encourage progress toward specific health-related goals by providing tailored training and guidance. Progress in this field could well be a key enabler of increasing health span and well-being for our increasingly care-demanding society.

Personalized services have greater impact on user experience to effect the level of user satisfaction. Many approaches provide personalized services in the form of an adaptive user interface. The focus of these approaches is limited to specific domains rather than a generalized approach applicable to every domain. In this paper, we proposed a domai...

Facial expression recognition (FER) is one of the most active areas of research in computer science, due to its importance in a large number of application domains. Over the years, a great number of FER systems have been implemented, each surpassing the other in terms of classification accuracy. However, one major weakness found in the previous stu...

A modern way of life needs a modern way of coaching. Despite the proliferation of ICT solutions for personalized health care, there is still no easy way to provide older adults with integrated coaching services. In this paper we introduce the concept of Council of Coaches — a radically new virtual coaching concept based on multiple autonomous, embo...

Unwholesome lifestyles can reduce lifespan by several years or even decades. Therefore, raising awareness and promoting healthier behaviors prove essential to revert this dramatic panorama. Virtual coaching systems are at the forefront of digital solutions to educate people and procure a more effective health self-management. Despite their increasi...

Low back pain remains a major cause of absenteeism in the world. In addition to its socio-economic impact, the age at which the first symptoms appear is decreasing. Consequently, there are more experts who start incorporating prevention plans for the lumbar area in their work routines. In addition, the continued market growth of wearable sensors an...

Smart coaching systems are named to play a central role in both prevention and intervention strategies for behavioral change. While relevant progresses have been made in terms of automatic and continuous monitoring of behavioral aspects, e.g. amount and variety of physical activity, coaching and feedback techniques are still in an infancy stage. Cu...

Joints angles are some of the most common measurements for the evaluation of lower limb injury risk, specially of lower limb joints. The 2D projections of these angles, as the Frontal Plane Projection Angle (FPPA), are widely used as an estimation of the angle value. Traditional procedures to measure 2D angles imply huge time investments, primarily...

Breast cancer is the most common tumor in western women and statistically 1 out of 8 women will develop breast cancer over their lifetime. Once overcome it, the stage of rehabilitation that the patient should follow is critical to recover from the su�ered illness. In this paper, a system composed of 3 applications, one for smartwatches, one for sma...

Activity recognition through smartphones has been proposed for a variety of applications. The orientation of the smartphone has a significant effect on the recognition accuracy; thus, researchers generally propose using features invariant to orientation or displacement to achieve this goal. However, those features reduce the capability of the recog...

An enormous effort has been made during the recent years towards the recognition of human activity based on wearable sensors. Despite the wide variety of proposed systems, most existing solutions have in common to solely operate on predefined settings and constrained sensor setups. Real-world activity recognition applications and users rather deman...

The evaluation of cancer patients’ recovery is still under the big subjectivity of physicians. Many different systems have been successfully implemented for physical activity evaluation, nonetheless there is still a big leap into Performance Status evaluation with ECOG and Karnofsky’s Performance Status scores. An automatic system for data recoveri...