Smartphone-Based Platform for Affect Monitoring through Flexibly Managed Experience Sampling Methods

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 affective states and the context is still in an early stage. Mobile technologies can help to achieve this task providing immediate and objective data of the users’ context and facilitating the assessment of their affective states. Previous works have developed mobile apps for monitoring affective states and context, but they use a fixed methodology which does not allow for making changes based on the progress of the study. This work presents a multimodal platform which leverages the potential of the smartphone sensors and the Experience Sampling Methods (ESM) to provide a continuous monitoring of the affective states and the context in an ubiquitous way. The platform integrates several elements aimed to expedite the real-time management of the ESM questionnaires. In order to show the potential of the platform, and evaluate its usability and its suitability for real-time assessment of affective states, a pilot study has been conducted. The results demonstrate an excellent usability level and a good acceptance from the users and the specialists that conducted the study, and lead to some suggestions for improving the data quality of mobile context-aware ESM-based systems.This work has been partially supported by the Spanish Ministry of Science, Innovation and Universities (MICINN) Projects PGC2018-098813-B-C31 and RTI2018-101674-B-I00 together with the European Fund for Regional Development (FEDER). This work has also been partially supported by the FPU Spanish Grant FPU16/04376 and the Dutch UT-CTIT project HoliBehave

Ubiquitous Computing and Ambient Intelligence—UCAmI

The Ubiquitous Computing (UC) idea envisioned by Weiser in 1991 [1] has recently evolved to a more general paradigm known as Ambient Intelligence (AmI) that represents a new generation of user-centred computing environments and systems. These solutions aim to find new ways to better integrate information technology into everyday life devices and activities. AmI environments are integrated by several autonomous computational devices of modern life ranging from consumer electronics to mobile phones. Ideally, people in an AmI environment will not notice these devices, but will benefit from the services these solutions provide them. Such devices are aware of the people present in those environments by reacting to their gestures, actions, and context [2]. Recently the interest in AmI environments has grown considerably due to new challenges posed by society’s demand for highly innovative services, such as smart environments, Ambient Assisted Living (AAL), e-Health, Internet of Things, and intelligent systems, among others.The Ubiquitous Computing (UC) idea envisioned by Weiser in 1991 [1] has recently evolved to a more general paradigm known as Ambient Intelligence (AmI) that represents a new generation of user-centred computing environments and systems. These solutions aim to find new ways to better integrate information technology into everyday life devices and activities. AmI environments are integrated by several autonomous computational devices of modern life ranging from consumer electronics to mobile phones. Ideally, people in an AmI environment will not notice these devices, but will benefit from the services these solutions provide them. Such devices are aware of the people present in those environments by reacting to their gestures, actions, and context [2]. Recently the interest in AmI environments has grown considerably due to new challenges posed by society’s demand for highly innovative services, such as smart environments, Ambient Assisted Living (AAL), e-Health, Internet of Things, and intelligent systems, among others

CoVidAffect, real-time monitoring of mood variations following the COVID-19 outbreak in Spain

The COVID-19 outbreak and the ensuing confnement measures are expected to bear a signifcant psychological impact on the afected populations. To date, all available studies designed to investigate the psychological efects of this unprecedented global crisis are based on cross-sectional surveys that do not capture emotional variations over time. Here, we present the data from CoVidAfect, a nationwide citizen science project aimed to provide longitudinal data of mood changes following the COVID-19 outbreak in the spanish territory. Spain is among the most afected countries by the pandemic, with one of the most restrictive and prolonged lockdowns worldwide. The project also collected a baseline of demographic and socioeconomic data. These data can be further analyzed to quantify emotional responses to specifc measures and policies, and to understand the efect of context variables on psychological resilience. Importantly, to our knowledge this is the frst dataset that ofers the opportunity to study the behavior of emotion dynamics in a prolonged lockdown situation.Spanish Ministry of Science, Innovation and Universities (MICINN) PGC2018-098813-B-C31 RTI2018-101674-B-I00European Union (EU)Project MONITOR-COVID - Andalucian Ministry of Economic Transformation, Industry, Knowledge and Universities CV20-29556FPU Spanish Grant FPU16/04376Dutch UT-CTIT project HoliBehav

Corona Health -- A Study- and Sensor-based Mobile App Platform Exploring Aspects of the COVID-19 Pandemic

Physical and mental well-being during the COVID-19 pandemic is typically assessed via surveys, which might make it difficult to conduct longitudinal studies and might lead to data suffering from recall bias. Ecological momentary assessment (EMA) driven smartphone apps can help alleviate such issues, allowing for in situ recordings. Implementing such an app is not trivial, necessitates strict regulatory and legal requirements, and requires short development cycles to appropriately react to abrupt changes in the pandemic. Based on an existing app framework, we developed Corona Health, an app that serves as a platform for deploying questionnaire-based studies in combination with recordings of mobile sensors. In this paper, we present the technical details of Corona Health and provide first insights into the collected data. Through collaborative efforts from experts from public health, medicine, psychology, and computer science, we released Corona Health publicly on Google Play and the Apple App Store (in July, 2020) in 8 languages and attracted 7,290 installations so far. Currently, five studies related to physical and mental well-being are deployed and 17,241 questionnaires have been filled out. Corona Health proves to be a viable tool for conducting research related to the COVID-19 pandemic and can serve as a blueprint for future EMA-based studies. The data we collected will substantially improve our knowledge on mental and physical health states, traits and trajectories as well as its risk and protective factors over the course of the COVID-19 pandemic and its diverse prevention measures

The EFL students’ online reading determinants: Perceiving from their selected folklore readings

In an attempt to increase reading performance at university level. This study aims at perceiving the experiential determinants of EFL students’ online reading performance. Data were collected from 182 undergraduate students’ self-rated questionnaire based on the assigned Indonesian folklores in English version through the online reading platforms. Data analysis used descriptive statistics and factor analysis. The results showed that EFL students’ reading habits and reading frequencies and trends were very supportive, whilst reading effectiveness and reading for pleasure supported their reading performance. Tests of chi-square’s four variables were statistically significant indicating the proportional majority of online reading activity. Meanwhile, the Principal Components Analysis (PCA) indicated two components and variables under the eigenvalues’ square root. The interpretation of two components was coherent with the pilot results on the online reading readability scale, analyzed the use of positive and negative affect items as undertaken from the pattern and structure matrix for PCA with the Obliging rotation. EFL students’ online reading is engaging accordingly since students accomplished their reading performance based on individual accessibilities and habits to understand the contents of genres. This study concludes that EFL students’ online reading performance has been practically facilitated by the technology devices multiply. Hence, four online reading variables increased EFL students’ reading awareness and performance accordingly

Grasp Your Pain: A Tangible Tool to Explore the Logging and Assessment of Pain

Pain is a subjective and innate experience that can be difficult to describe. Chronic pain is associated with decreased quality of life, and it is prevalent in cancer populations. With a growing elderly population, the global cancer burden is expected to rapidly advance in the coming years. Expressing pain and symptom experiences is essential for patients to receive proper treatment and care. Self-reporting tools are useful and reliable measures of patients' symptoms. A commonly used assessment form in palliative care is ESAS-r, the revised Edmonton Symptom Assessment System. It lets the patient rate a list of symptoms, on a scale from 0 to 10, depending on their intensity. Research suggests that ESAS-r only captures a snapshot of the patients' symptom profile, and that is burdensome to patients and clinical staff. There is a need for self-assessment tools that are easy to use, non-intrusive, and can be used in situ. The research in this thesis explores the use of a tangible tool (Grasp), and squeezing as an input method to log pain/symptoms experiences. Grasp consists of a small stone-like object. When squeezed, it logs the time and duration of the interaction. Squeezes are then visualized on an accompanying interface. Through a Mixed Methods Research approach, a pilot study and clinical trial were conducted. The former gathered participant (N=8) opinions on Grasp, and the use of squeeze duration to log experiences. The latter explored the implementation of Grasp alongside ESAS-r in a cancer ward (nurses = 6, patients = 8). Two broad research questions were examined: RQ1: How can tangible interaction through Grasp support the logging of experiences? and RQ2: How do palliative cancer patients and nurses experience Grasp as a tool for the logging, assessment, and communication of pain and symptoms compared to ESAS-r? Findings from the pilot suggest that there is potential in using Grasp and squeeze duration to log events, and that interacting with the tool potentially can help distract or externalize from negative experiences. Participants from both studies found Grasp easy to use, and visualizations intuitive and meaningful. Nurses and patients were generally satisfied with Grasp as a tool, and it helped paint a wider image of the patients' symptoms compared to ESAS-r alone. However, patients were sometimes too ill to use Grasp, and the research was limited by barriers related to clinical environments. Further research is needed to explore the potential of tangible interaction and squeezing as an input method with other patient groups. There is also the aspect of the affective interaction that should be investigated further.Masteroppgave i informasjonsvitenskapINFO390MASV-INF

Sofie: Smart Operating System For Internet Of Everything

The proliferation of Internet of Things and the success of rich cloud services have pushed the horizon of a new computing paradigm, Edge computing, which calls for processing the data at the edge of the network. Applications such as cloud offloading, smart home, and smart city are idea area for Edge computing to achieve better performance than cloud computing. Edge computing has the potential to address the concerns of response time requirement, battery life constraint, bandwidth cost saving, as well as data safety and privacy. However, there are still some challenges for applying Edge computing in our daily life. The missing of the specialized operating system for Edge computing is holding back the flourish of Edge computing applications. Service management, device management, component selection as well as data privacy and security is also not well supported yet in the current computing structure. To address the challenges for Edge computing systems and applications in these aspects, we have planned a series of empirical and theoretical research. We propose SOFIE: Smart Operating System For Internet Of Everything. SOFIE is the operating system specialized for Edge computing running on the Edge gateway. SOFIE could establish and maintain a reliable connection between cloud and Edge device to handle the data transportation between gateway and Edge devices; to provide service management and data management for Edge applications; to protect data privacy and security for Edge users; to guarantee the wellness of the Edge devices. Moreover, SOFIE also provide a naming mechanism to connect Edge device more efficiently. To solve the component selection problem in Edge computing paradigm, SOFIE also include our previous work, SURF, as a model to optimize the performance of the system. Finally, we deployed the design of SOFIE on an IoT/M2M system and support semantics with access control

ATOPE+: An mHealth System to Support Personalized Therapeutic Exercise Interventions in Patients With Cancer

The authors express their gratitude to the patients and experts for their participation in the evaluation of ATOPEC. They also express their gratitude to the anonymous reviewers for the instructive criticism of an earlier version of this article.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 technology-driven personalization strategies typically rely on the use of expensive laboratory equipment with expert supervision, or in the self-management of patients to meet the prescribed exercise levels by an activity tracker. These methods often do not perform better than non technology-driven methods, therefore more sophisticated strategies are required to improve the personalization process. In this paper we present ATOPE+, an mHealth system to support personalized exercise interventions in patients with cancer based on workload-recovery ratio estimation. ATOPE+ enables the remote assessment of workload-recovery ratio to provide optimal exercise dosage by means of a knowledge-based system and by combining physiological data from heterogeneous data sources in a multilevel architecture. The results show that ATOPE+ is a system ready to be used in the context of a clinical trial after being tested with patients with breast cancer and conducting an usability evaluation by clinical experts.Spanish Ministry of Science, Innovation, and Universities (MICINN) PGC2018-098813-B-C31 RTI2018-101674-B-I00Health Research Funds of the Carlos III Health Institute PI18/01840German Research Foundation (DFG) FPU16/04201 FPU17/0093

Wearable and interactive mixed reality solutions for fault diagnosis and assistance in manufacturing systems: Implementation and testing in an aseptic bottling line

Abstract Thanks to the spread of technologies stemming from the fourth industrial revolution, also the topic of fault diagnosis and assistance in industrial contexts has benefited. Indeed, several smart tools were developed for assisting with maintenance and troubleshooting, without interfering with operations and facilitating tasks. In line with that, the present manuscript aims at presenting a web smart solution with two possible applications installed on an Android smartphone and Microsoft HoloLens. The solution aims at alerting the operators when an alarm occurs on a machine through notifications, and then at providing the instructions needed for solving the alarm detected. The two devices were tested by the operators of an industrial aseptic bottling line consisting of five machines in real working conditions. The usability of both devices was positively rated by these users based on the System Usability Scale (SUS) and additional appropriate statements. Moreover, the in situ application brought out the main difficulties and interesting issues for the practical implementation of the solutions tested

Wearable and interactive mixed reality solutions for fault diagnosis and assistance in manufacturing systems: Implementation and testing in an aseptic bottling line

Thanks to the spread of technologies stemming from the fourth industrial revolution, also the topic of fault diagnosis and assistance in industrial contexts has benefited. Indeed, several smart tools were developed for assisting with maintenance and troubleshooting, without interfering with operations and facilitating tasks. In line with that, the present manuscript aims at presenting a web smart solution with two possible applications installed on an Android smartphone and Microsoft HoloLens. The solution aims at alerting the operators when an alarm occurs on a machine through notifications, and then at providing the instructions needed for solving the alarm detected. The two devices were tested by the operators of an industrial aseptic bottling line consisting of five machines in real working conditions. The usability of both devices was positively rated by these users based on the System Usability Scale (SUS) and additional appropriate statements. Moreover, the in situ application brought out the main difficulties and interesting issues for the practical implementation of the solutions tested