The purpose of the study was to evaluate the effects of goal setting and fitness trackers to increase daily step counts in adolescents with intellectual disability. An A-B-A-B withdrawal research design was implemented to evaluate the effectiveness of the intervention. The results indicated that goal setting and fitness trackers were effective in increasing daily step counts for two out of three participants.

The usage of eye trackers is becoming more and more popular in the field of information visualization. In this project two eye trackers, The Eye Tribe nd Mirametrix S2, are used to obtain eye tracking data for visualizations. It is planned to use the eye trackers with OnGraX, a network visualization system, where they will provide data for the implementation of visualizations, specifically, heatmaps. OnGraX already uses heatmaps to show regions in a network that have been in the viewport of the user. One aim of this thesis will be the comparison between the two eye trackers, and if the use of eye tracking data gives better results thatn the already existing viewport-based approach. At the same time, we provide the foundation for adaptive visualizations with OnGraX. Our research problem is also of interest for visualization in general, because it will help to improve and develop eye tracking technology in this context. To support the outcome of our implementation, we carried out a user study. As a result, we concluded that one of the two eye trackers appears to have more capabilities than the other, and that using the eye tracking data is a more preferred way of depicting the heatmaps on OnGraX.

The Quantified Self movement has led to an increased routine use of consumer wearables, generating large amounts of person-generated wearable device data. This has become an opportunity to researchers to conduct research with large-scale person-generated wearable device data without having to collect data in a costly and time-consuming way. However, there are known challenges of wearable device data such as missing data or inaccurate data which raises the need to assess the quality of data before conducting research. Currently, there is a lack of in-depth understanding on data quality challenges of using person-generated wearable device data for research purposes, and how data quality assessment should be conducted. Data quality assessment could be especially a burden to those without the domain knowledge on a specific data type, which might be the case for emerging biomedical data sources. The goal of this dissertation is to advance the knowledge on data quality challenges and assessment of person-generated wearable device data and facilitate data quality assessment for those without the domain knowledge on the emerging data type. The dissertation consists of two aims: (1) identifying data quality dimensions important for assessing the quality of person-generated wearable device data for research purposes, (2) designing and evaluating an interactive data quality characterization tool that supports researchers in assessing the fitness-for-use of fitness tracker data. In the first aim, a multi-method approach was taken, conducting literature review, survey, and focus group discussion sessions. We found that intrinsic data quality dimensions applicable to electronic health record data such as conformance, completeness, and plausibility are applicable to person-generated wearable device data. In addition, contextual/fitness-for-use dimensions such as breadth and density completeness, and temporal data granularity were identified given the fact that our focus was on assessing data quality for research purposes. In the second aim, we followed an iterative design process from understanding informational needs to designing a prototype, and evaluating the usability of the final version of a tool. The tool allows users to customize the definition of data completeness (fitness-for-use measures), and provides data summarization on the cohort that meets that definition. We found that the interactive tool that incorporates fitness-for-use measures and allows customization on data completeness, can support assessing fitness-for-use assessment more accurately and in less time than a tool that only presents information on intrinsic data quality measures.

Half of American women do not sustain recommended levels of physical activity (PA). Wearable activity trackers (WATs) may increase both awareness of, and PA if worn daily. Thus, WATs should include features and designs that encourage daily use. This study aimed to determine WAT features and designs most appealing to women and the motivational effects of various WATs. For this mixed-method pilot study, 15 women each trialed three WATs; documented daily PA levels; and rated their satisfaction with each device's comfort, features, and motivational effect. Additionally, participants shared experiences and feedback in focus groups. Features that promote adoption of WATs among women are, 1) comfort 2) extended battery life, 3) durability, 4) immediate PA feedback, 5) intuitive PA sensing, and 6) programmability. WATs with these preferred qualities may effectively motivate women to increase PA, leading to improved overall health, and reduce healthcare costs.

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Vid sökning på internet via en webbläsare finns en mängd tredjepartsaktörer aktiva som samlar in information om användarens beteende. Det saknas idag en transparens gentemot användaren om vilka aktörer, vilken information och vad informationen används till. Genom simulerad surfning undersöks vilken utsträckning datainsamling sker. I studien undersöks de i dagsläget största aktörerna och deras respektive informationshantering. Studien visar på fem stora tjänster inom rekommenderat material och data-analys varav två företag undersöks vidare. Företagens informationshantering analyseras i uppsatsen utifrån respektive företags sekretessavtal. Undersökningen visar att en stor datainsamling sker utan att det är uppenbart för användaren. / When searching on the Internet via a web browser there is a variety of third-party actors active that collects information about the user’s behavior. Today, there is a missing transparency for the user about the actors, what information is gathered and what the information is used for. By simulating web browsing the extent of data collecting is researched. This study examines the current situation of major actors and their respective information. The study revealed five major services within recommended materials and data analysis. Two companies were investigated further. These companies are analyzed in the article based on each company’s privacy policy. The study shows that a lot of data is being gathered without it being obvious to the user.

Os parâmetros acústicos da voz abordados em diversas pesquisas de análise digital da voz, apresentam-se válidos para o uso em processo diagnóstico e terapêutico. O grupo de parâmetros de perturbação da voz necessita do conhecimento de todos os períodos do trecho de sinal de voz analisado, para ter seu valor calculado. Esta tarefa é desempenhada pelos determinadores de pitch, e a sua precisão determina a confiabilidade que se pode ter nos parâmetros calculados. Este trabalho visa estudar diversos métodos propostos ao longo dos anos e estabelecer qual destes tem a melhor precisão e robustez, quando utilizados com vozes patológicas. Estuda-se também algoritmos estimadores de pitch como uma ferramenta de auxílio para a correção e ajuste dos determinadores. Os resultados obtidos demonstram a necessidade de modificações externas e internas aos algoritmos determinadores e estimadores, para alcançarem a robustez e precisão desejada. Dois algoritmos determinadores, determinador por autocorrelação e por extração de harmônicas, mostraram-se dentro das metas estabelecidas e confirmam-se como os mais promissores em aplicações para obtenção de parâmetros acústicos da voz. / Several researches of digital speech processing validate the use of acoustic parameters of the voice in diagnosis and therapeutic processes. Perturbation parameters need the knowledge of all the periods of the analyzed voice signal, to have their values calculated. This task is carried out by the pitch trackers and their precision determines the reliability off the evaluated parameters. The purpose of this work is to study several methods proposed along the years and to establish which algorithm has the best precision and robustness, when used with pathological voices. The pitch estimation is also studied as an aid tool for the correction and adjustment of the pitch trackers. The results demonstrate the need of external and internal modifications of the trackers and detector algorithms to reach the wanted robustness and precision. The algorithms for autocorrelation and for extraction of harmonics are confirmed as the most promising in applications for obtaining of acoustic parameters of the voice.

Os parâmetros acústicos da voz abordados em diversas pesquisas de análise digital da voz, apresentam-se válidos para o uso em processo diagnóstico e terapêutico. O grupo de parâmetros de perturbação da voz necessita do conhecimento de todos os períodos do trecho de sinal de voz analisado, para ter seu valor calculado. Esta tarefa é desempenhada pelos determinadores de pitch, e a sua precisão determina a confiabilidade que se pode ter nos parâmetros calculados. Este trabalho visa estudar diversos métodos propostos ao longo dos anos e estabelecer qual destes tem a melhor precisão e robustez, quando utilizados com vozes patológicas. Estuda-se também algoritmos estimadores de pitch como uma ferramenta de auxílio para a correção e ajuste dos determinadores. Os resultados obtidos demonstram a necessidade de modificações externas e internas aos algoritmos determinadores e estimadores, para alcançarem a robustez e precisão desejada. Dois algoritmos determinadores, determinador por autocorrelação e por extração de harmônicas, mostraram-se dentro das metas estabelecidas e confirmam-se como os mais promissores em aplicações para obtenção de parâmetros acústicos da voz. / Several researches of digital speech processing validate the use of acoustic parameters of the voice in diagnosis and therapeutic processes. Perturbation parameters need the knowledge of all the periods of the analyzed voice signal, to have their values calculated. This task is carried out by the pitch trackers and their precision determines the reliability off the evaluated parameters. The purpose of this work is to study several methods proposed along the years and to establish which algorithm has the best precision and robustness, when used with pathological voices. The pitch estimation is also studied as an aid tool for the correction and adjustment of the pitch trackers. The results demonstrate the need of external and internal modifications of the trackers and detector algorithms to reach the wanted robustness and precision. The algorithms for autocorrelation and for extraction of harmonics are confirmed as the most promising in applications for obtaining of acoustic parameters of the voice.