System for activity tracking of patients with chronic kidney disease

Many people suffering from chronic kidney disease are in need of a kidney transplant. A problem in the health care is that patients cannot undergo surgery if they have too much belly fat. Regular exercise and physical activity are therefore crucial for this group of people. A project group at the Skåne University Hospital has recently been established to help patients with chronic kidney disease to lose weight. A question they asked themselves was whether it was possible to use activity tracking devices in the project. The purpose of this thesis is to design and evaluate a system that can be used to track the physical activities of the patients. The system will be built using a Sony SmartBand, a wristband collecting and analyzing data about a user’s daily activities

Continuous physical activity recording - Consumer-based activity trackers in epidemiological studies

Physical activity is an important modifiable lifestyle factor that can improve general health and reduce the risk of disease. Currently, collecting data on physical activity in epidemiological studies are generally limited to long-term but self-reported and inaccurate physical activity questionnaires and/or using short-term but objective and more accurate accelerometers. Consumer-based activity trackers are designed for long-term objective data collection and can therefore potentially be used to close this gap. The objective of this dissertation was therefore to explore and develop new methods for collecting data on physical activity in epidemiological studies using consumer-based activity trackers. The four included papers apply different methods to explore the objective from multiple angles. Results includes an overview of how activity tracker sensor support has changed over time, recommendations when choosing an activity tracker model for future physical activity research, recommendations for increasing activity tracker wear time among participants in clinical studies, as well as knowledge about activity tracker validity and physical activity trends during the Norwegian COVID-19 lockdown in 2020. Finally, the dissertation describes a system for automatic and continuous data collection using consumer-based activity trackers from multiple providers. We show the usability of this system by accessing and analysing historic activity tracker data from participants who wore a tracker before-, during-, and after the COVID-19 lockdown period. The proposed system can be a valuable addition to existing methods for physical activity assessment by contributing to closing the above-mentioned method gap

Understanding security risks and users perception towards adopting wearable Internet of Medical Things

This thesis examines users’ perception of trust within the context of security and privacy of Wearable Internet of Medical Things (WIoMT). WIoMT is a collective term for all medical devices connected to internet to facilitate collection and sharing of health-related data such as blood pressure, heart rate, oxygen level and more. Common wearable devices include smart watches and fitness bands. WIoMT, a phenomenon due to Internet of Things (IoT) has become prevalent in managing the day-to-day activities and health of individuals. This increased growth and adoption poses severe security and privacy concerns. Similar to IoT, there is a need to analyse WIoMT security risks as they are used by individuals and organisations on regular basis, risking personal and confidential information. Additionally, for better implementation, performance, adoption, and secured wearable medical devices, it is crucial to observe users’ perception. Users’ perspectives towards trust are critical for adopting WIoMT. This research aimed to understand users’ perception of trust in the adoption of WIoMT, while also exploring the security risks associated with adopting wearable IoMT. Employing a quantitative method approach, 189 participants from Western Sydney University completed an online survey. The results of the study and research model indicated more than half of the variance (R2 = 0.553) in the Intention to Use WIoMT devices, which was determined by the significant predictors (95% Confidence Interval; p < 0.05), Perceived Usefulness, Perceived Ease of Use and Perceived Security and Privacy. Among these two, the domain Perceived Security and Privacy was found to have significant outcomes. Hence, this study reinforced that a WIoMT user intends to use the device only if he/she trusts the device; trust here has been defined in terms of its usefulness, easy to use and security and privacy features. This finding will be a steppingstone for equipment vendors and manufacturers to have a good grasp on the health industry, since the proper utilisation of WIoMT devices results in the effective and efficient management of health and wellbeing of users. The expected outcome from this research also aims to identify how users’ security and perception matters while adopting WIoMT, which in future can benefit security professionals to examine trust factors when implementing new and advanced WIoMT devices. Moreover, the expected result will help consumers as well as different healthcare industry to create a device which can be easily adopted and used securely by consumers

Automatic Performance Status Evaluation and Physical Activity Recognition in Cancer Patients for Medical Diagnosis Assistance

Sobresaliente (10)The evaluation of cancer patients’ recovery is still under a big grade of subjectivity from the physicians’ diagnoses. Different systems have been successfully implemented for general physical activity evaluation, nonetheless there is still a big leap of improvement into Performance Status (PS) evaluation with ECOG and Karnofsky’s Performance Status (KPS) scores. In this project an automatic system for patients’ biomonitoring based on Android technology with smartphones and wearables has been designed. As a result, objective data is provided for the oncologists’ diagnoses along with new algorithms for physical activity and PS assessment, having the latter applied to ECOG and KPS no precedent known. Furthermore, the basics for prospective implementation of gamification has been designed for boosting patients’ motivation in their recovery.La evaluación de la recuperación de pacientes con cáncer está caracterizada por un alto grado de subjetividad en los diagnósticos del personal médico. Se han implementado con éxito diferentes sistemas para la evaluación de la actividad fı́sica, sin embargo, aún existe un amplio margen de evolución dentro de la medida de la capacidad funcional con las escalas ECOG y de Karnofsky. En este proyecto se ha diseñado un sistema automático para la biomonitorización de pacientes basado en tecnologı́a Android con smartphones y wearables. Con esto se provee a los oncólogos de datos objetivos para sus diagnósticos junto con nuevos algoritmos para la evaluación de la actividad fı́sica y la capacidad funcional, estos últimos aplicados a ECOG y la escala de Karnofsky sin precedente alguno. Además, se han sentado las bases y el diseño de una futura implementación de gamificación para favorecer la motivación del paciente en su recuperación.Beca Iniciación a la Investigación de la Universidad de GranadaDepartamento de Arquitectura y Tecnología de Computadores, Universidad de Granad

A step away from impaired well-being: a latent growth curve analysis of an intervention with activity trackers among employees

The present study evaluated the effectiveness of a workplace intervention combining activity trackers (behavioural approach) with an online coach (cognitive approach) in order to increase employees’ number of steps and improve their impaired well-being (i.e., emotional strain and negative affect). To analyse the intervention’s effectiveness, the study applied latent growth curve modelling. Moreover, we tested whether work-related and personal resources (i.e., job control and self-efficacy) moderated the intervention’s effectiveness and whether an increase in number of steps was associated with an improvement in impaired well-being. During the intervention, data were collected at six measurement points from 108 mainly low active employees. The results revealed that employees increased their number of steps until the second intervention week; this increase was not moderated by job control or self-efficacy. Moreover, the intervention was effective in decreasing emotional strain and negative affect over the course of the intervention. Further analyses showed that the increase in number of steps was related to the decrease in negative affect, whereas no such association was found for the increase in number of steps and the decrease in emotional strain. In conclusion, the findings showed that our intervention was effective in improving physical activity and impaired well-being among employees.Peer Reviewe

A predictive model for the acceptance of wearable ubiquitous activity monitoring devices

Acceptance of wearable ubiquitous activity monitoring devices that track activity has been a hot topic for the last decade. Several theories have been made, particularly how to think about the Technology Acceptance Model (TAM). These theories have been used in different situations to learn more about how people and organizations accept new technology. Even though the TAM is mature and works in different situations, there is not much published research that tries to expand its ability to predict how people will react to wearable ubiquitous activity monitoring devices. One reason for this gap could be that the TAM is based on the idea that people's acceptance behavior can only be predicted by two beliefs: Perceived Ease of Use (PEOU) and Perceived Usefulness (PU). Literature shows that PU and PEOU beliefs are not enough. This means that they may not be able to explain why people accept new things, like Activity Trackers (AT). Because of this, it is important to include any other factors that can help predict how likely people are to use activity trackers. As an extension of research on the TAM, this study created and tested two models of how people accept and use wearable ubiquitous activity monitoring devices, with two questionnaires with more than 200 respondents that shield light on the subject. The proposed models added key concepts from the research stream on how people accept information systems to the theoretical framework of the TAM and Health Information Technology Acceptance Model (HITAM). The resulting models were analyzed using a variety of statistical techniques including Structural Equation Analysis. The first model was reanalyzed via qualitative analysis with 20 interviews, and reanalyzed via another quantitative method of Artificial Neural Networks (ANN). The most significant contributions of this dissertation are: 1. The construction of two models that predict activity tracking adoption and usage. 2. Guidelines for designing activity trackers. These contributions can help promote activity trackers as an essential piece of equipment that helps monitor progress during workouts as well as other times, such as when the user is at rest or sleeping. We will see that by being continually reminded to walk about and avoid sitting for extended periods of time or doing nothing at all, this helps a person build healthy behaviors. Additionally, activity trackers should be designed to maintain a person's motivation to finish the daily activity routine, which is necessary for people to accomplish their health and fitness objectives. This thesis contributes with two quantitative models for the acceptance and use of activity trackers, and creates recommendations for different types of users.A aceitação de dispositivos ubíquos vestíveis de monitorização de atividade que rastreiam a atividade tem sido um tema cálido na última década. Várias teorias foram concebidas, principalmente como pensar o Modelo de Aceitação de Tecnologia (TAM). Essas teorias têm sido usadas em diferentes situações para aprender mais sobre como as pessoas e as organizações aceitam novas tecnologias. Conquanto o TAM seja maturo e funcione em diferentes situações, não há muitas investigações publicadas que tentem expandir a sua capacidade de prever como as pessoas reagirão a dispositivos ubíquos vestíveis de monitoramento de atividade. Uma razão para essa lacuna pode ser porque o TAM é baseado na ideia de que o comportamento de aceitação das pessoas só pode ser previsto por duas asseverações: Facilidade de Uso Percebida (PEOU) e Utilidade Percebida (PU). A literatura mostra que as asseverações nas PU e PEOU não são suficientes. Isso significa que essas duas asseverações podem não ser capazes de explicar o porquê de as pessoas aceitarem coisas novas, como monitores de atividade (AT). Por isso, é importante incluir quaisquer outros fatores que possam ajudar a prever a probabilidade de as pessoas usarem monitorizadores de atividade. Como extensão da pesquisa sobre o TAM, esta investigação criou e testou dois modelos de como as pessoas aceitam e usam dispositivos ubíquos vestíveis de monitorização de atividade, com dois questionários com mais de 200 repostas cada, que clarificam o assunto. Os modelos propostos agregaram conceitos-chave da pesquisa sobre como as pessoas aceitam os sistemas de informação ao referencial teórico do TAM e do Modelo de Aceitação de Tecnologia da Informação em Saúde (HITAM). Os modelos resultantes foram analisados usando uma variedade de técnicas estatísticas, incluindo Modelação de Equações Estruturais. O primeiro modelo foi reanalisado por meio de uma análise qualitativa com 20 entrevistas, e de novo reanalisado por meio de outro método quantitativo com Redes Neurais Artificiais (RNA). A construção de dois modelos que predizem a adoção e uso do monitorização da atividade é a contribuição mais significativa que pode ser retirada deste trabalho, juntamente com as diretrizes para o design de monitorizadores de atividade. Essas contribuições podem ajudar a promover os monitorizadores de atividade como um equipamento essencial que ajuda a monitorizar a evolução durante os treinos e em outros momentos, como quando o utilizador está em repouso ou dormindo. Ao ser continuamente lembrado para andar e evitar ficar sentado por longos períodos de tempo ou não fazer nada, isso ajuda o utilizador a construir comportamentos saudáveis. Além disso, os monitorizadores de atividade devem ser projetados para manter a motivação de uma pessoa em concluir a rotina diária de atividades, o que é necessário para que as pessoas atinjam seus objetivos de saúde e condição física. Esta tese contribui com modelos quantitativos para a aceitação e uso de monitorizadores de atividades e cria recomendações para diferentes tipos de utilizadores

Multi-sensor movement analysis for transport safety and health applications

Recent increases in the use of and applications for wearable technology has opened up many new avenues of research. In this paper, we consider the use of lifelogging and GPS data to extend fine-grained movement analysis for improving applications in health and safety. We first design a framework to solve the problem of indoor and outdoor movement detection from sensor readings associated with images captured by a lifelogging wearable device. Second we propose a set of measures related with hazard on the road network derived from the combination of GPS movement data, road network data and the sensor readings from a wearable device. Third, we identify the relationship between different socio-demographic groups and the patterns of indoor physical activity and sedentary behaviour routines as well as disturbance levels on different road settings