1,721,044 research outputs found
“I Have to Do Something About It” - An Exploration of How Dashboards Invoke Self-Reflections in Chronic Obstructive Pulmonary Disease Patients
Full text linkChronic Obstructive Pulmonary Disease (COPD) patients need to track their symptoms for health professionals to adapt treatments in a timely manner in case of health deterioration. Clinicians typically analyzed the tracked data and recommended actions to patients who acted as mere data collectors. Consequently, patients have little agency and motivation to self-track. Two studies investigated how digital dashboards influenced patients’ motivation, agency, and reflections. Study 1 (one week) focused on how five patients used a paper diary to self-track and reflect on their symptoms. Additionally, the patients evaluated a tablet-based digital dashboard using four data visualisations. Study 2 looked at how five patients tracked and reflected on their data using a tablet-based dashboard for two weeks. By using reflective questions to prompt patients to compare and reflect on time series charts with data annotations, patients gained new knowledge about what factors might influence their symptoms and identified actions to improve their health (e.g. increase oxygen supplements). This strengthened their sense of agency and motivated them to participate more in the management of their condition.</p
Patient Data Work with Consumer Self-tracking:Exploring Affective and Temporal Dimensions in Chronic Self-care
Full text linkEmerging studies are reporting on the implications of self-tracked data in patients’ everyday life and how it influences self-care activities in chronic care. The increased uptake of consumer wearable activity trackers in healthcare contexts and the wider application of advanced analytics is changing the temporal scope from ‘past-centric’ to ‘future-centric’ personal informatics. At the same time, a stream of research is making clear that experiences of emotion are constitutive of patient data work suggesting that the micro practices of engaging with personal data has an important affective dimension. We conducted an exploratory interview study with five chronic heart patients with an implanted cardiac device to conceptualize the data work, which is involved in making sense of self-tracked data from a consumer wearable activity tracker (Fitbit Alta HR). In this paper, we contribute to understanding patient data work as seven forms of micro practices: Verifying, Questioning, Motivating, Reacting, Accepting, Distancing, and Sharing. We discuss how these practices relate to temporal and affective dimensions of engaging with self-tracked data in chronic care and point to future research.</p
Heart Rate During Sleep Measured Using Finger-, Wrist-and Chest-Worn Devices: A Comparison Study
No full textISSN:1867-8211ISSN:1867-822XISSN:1867-822
A quantitative comparison of manual vs. automated facial coding using real life observations of fathers
No full textThis work explores the application of an automated facial recognition software “FaceReader” [1] to videos of fathers (n = 36), taken using headcams worn by their infants during interactions in the home. We evaluate the use of FaceReader as an alternative method to manual coding – which is both time and labour intensive – and advance understanding of the usability of this software in naturalistic interactions. Using video data taken from the Avon Longitudinal Study of Parents and Children (ALSPAC), we first manually coded fathers’ facial expressions according to an existing coding scheme, and then processed the videos using FaceReader. We used contingency tables and multivariate logistic regression models to compare the manual and automated outputs. Our results indicated low levels of facial recognition by FaceReader in naturalistic interactions (approximately 25.17% compared to manual coding), and we discuss potential causes for this (e.g., problems with lighting, the headcams themselves, and speed of infant movement). However, our logistic regression models showed that when the face was found, FaceReader predicted manually coded expressions with a mean accuracy of M = 0.84 (range = 0.67–0.94), sensitivity of M = 0.64 (range = 0.27–0.97), and specificity of M = 0.81 (range = 0.51–0.97).</p
Compliance and Usability of an Asthma Home Monitoring System
Full text linkAsthma monitoring is an important aspect of patient self-management. However, due to its repetitive nature, patients can find long-term monitoring tedious. Mobile health can provide an avenue to monitor asthma without needing high levels of active engagement, and instead rely on passive monitoring. In our recent AAMOS-00 study, we collected mobile health data over six months from 22 asthma patients using passive and active monitoring technology, including smartwatch, peak flow measurements, and daily asthma diaries. Compliance to smartwatch monitoring was found to lie between the compliance to complete daily asthma diaries and measuring daily peak flow. However, some study participants faced technical issues with the devices which could have affected the relative compliance of the monitoring tasks. Moreover, as evidenced by standard usability questionnaires, we found that the AAMOS-00 study’s data collection system was similar in quality to other studies and published apps
Experiencer: An Open-Source Context-Sensitive Wearable Experience Sampling Tool
No full textWe introduce Experiencer, a newly developed Experience Sampling Method (ESM) software for commodity-level smartwatches. We designed this software mainly to address the compliance-related challenges, such as dropouts of study participants, that generations of ESM software solutions have faced. Dropouts are often caused by the inconvenient frequency and timing of the ESM prompts. This can partly be mitigated by utilizing physiological smartwatch sensors to learn which prompting moments are both convenient to the study participant and also relevant to the ESM study designer. Experiencer enables researchers to configure context-sensitive sampling protocols, providing access to raw sensor data, within the boundaries of European privacy legislation. In this paper, we describe the technical capabilities of our software, compare its features with the state-of-the-art, and showcase its application in studies that used Experiencer
Accurate telemonitoring of Parkinson’s disease symptom severity using nonlinear speech signal processing and statistical machine learning
Full text linkThis study focuses on the development of an objective, automated method to extract clinically useful information from sustained vowel phonations in the context of Parkinson’s disease (PD). The aim is twofold: (a) differentiate PD subjects from healthy controls, and (b) replicate the Unified Parkinson’s Disease Rating Scale (UPDRS) metric which provides a clinical impression of PD symptom severity. This metric spans the range 0 to 176, where 0 denotes a healthy person and 176 total disability. Currently, UPDRS assessment requires the physical presence of the subject in the clinic, is subjective relying on the clinical rater’s expertise, and logistically costly for national health systems. Hence, the practical frequency of symptom tracking is typically confined to once every several months, hindering recruitment for large-scale clinical trials and under-representing the true time scale of PD fluctuations.We develop a comprehensive framework to analyze speech signals by: (1) extracting novel, distinctive signal features, (2) using robust feature selection techniques to obtain a parsimonious subset of those features, and (3a) differentiating PD subjects from healthy controls, or (3b) determining UPDRS using powerful statistical machine learning tools. Towards this aim, we also investigate 10 existing fundamental frequency (F_0) estimation algorithms to determine the most useful algorithm for this application, and propose a novel ensemble F_0 estimation algorithm which leads to a 10% improvement in accuracy over the best individual approach. Moreover, we propose novel feature selection schemes which are shown to be very competitive against widely-used schemes which are more complex. We demonstrate that we can successfully differentiate PD subjects from healthy controls with 98.5% overall accuracy, and also provide rapid, objective, and remote replication of UPDRS assessment with clinically useful accuracy (approximately 2 UPDRS points from the clinicians’ estimates), using only simple, self-administered, and non-invasive speech tests.The findings of this study strongly support the use of speech signal analysis as an objective basis for practical clinical decision support tools in the context of PD assessment
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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