Gijs Geleijnse

Toward a persuasive mobile application to reduce sedentary behavior

Prolonged sitting is a potential health risk, not only for people with an inactive lifestyle but also for those who meet the daily physical activity recommendations. Mobile applications that trigger people to take regular breaks from sitting seem promising. In this paper, we present the results of our quest to create effective persuasive mobile applications aimed at reducing sedentary behavior. First, we developed SitCoach, a mobile application to nudge office workers from their seats. SitCoach monitors physical activity and sedentary behavior and provides timely persuasive messages suggesting active breaks. A user test showed that users had little awareness of the risks of prolonged sitting and considered their ability to take active breaks to be highly dependent on external factors. The results from this study formed the basis for a second experiment, which was more extensive in duration and number of participants. In this 6-week experiment, office workers received timely persuasive messages on their smart phones, advising them to take an active break whenever they were sitting behind their computer for too long. Compared to a Control group who did not receive these messages, a significant decrease in computer activity was achieved. The studies show the potential and limitations of using a smart phone as a platform for reducing sedentary behavior. We conclude with recommendations to create effective mobile applications that motivate people to take regular breaks from sitting.

Deriving a recipe similarity measure for recommending healthful meals

A recipe recommender system may stimulate healthful and varied eating, when the presented recipes fit the lifestyle of the user. As consumers face the barrier to change their eating and cooking behavior, we aim for a strategy to provide more healthful variations to routine recipes. In this paper, a similarity measure for recipes is derived by taking a user-centered approach. Such a measure can be used to recommend healthier alternatives to commonly selected meals, which are perceived to be similar. Recipes presented using this strategy may fit the demand for health and variation within the boundaries of a busy lifestyle. Having derived and evaluated a recipe similarity measure, we explore its use through an at-home trial.

A personalized recipe advice system to promote healthful choices

We present a prototype of a personalized recipe advice system, which facilitates its users to make health-aware meal choices based on past selections. To stimulate the adoption of a healthier lifestyle, a goal setting mechanism is applied in combination with personalized recipe suggestions.

Comparing text entry methods for interactive television applications

We evaluate and compare the user acceptance of alternative text input methods for an interactive TV application. We are interested in whether remote control-based input methods are acceptable alternatives to the standard keyboard, when the user is assisted with intelligent text entry methods when entering a search term. The users are asked to search for music videos by entering text using a remote control or a standard QWERTY keyboard. The text input methods are evaluated with the HED/UT questionnaire. The results show that the standard keyboard with intelligence is better rated in these dimensions than the methods using the remote control. However, there is no negative attitude towards the methods using the remote control when using intelligent text input.

Enriching music with synchronized lyrics, images and colored lights

We present a method to synchronize popular music with its lyrics at the stanza level. First we apply an algorithm to segment audio content into harmonically similar and/or contrasting progressions, i.e. the stanzas. We map the stanzas found to a sequence of labels, where stanzas with a similar progression are mapped to the same label. The lyrics are analyzed as well to compute a second sequence of labels. Using dynamic programming, an optimal match is found between the two sequences, resulting in a stanza-level synchronization of the lyrics and the audio. The synchronized lyrics can be used to compute a synchronized slide show to accompany the music, where the images are retrieved using the lyrics. For an additional enrichment of the experience, colored light effects are synchronized with the music that are computed from the sets of images. The song segmentation can be done reliably, while the mapping of the audio segments and lyrics gives encouraging results.

Heuristic Approaches for the Quartet Method of Hierarchical Clustering

Given a set of objects and their pairwise distances, we wish to determine a visual representation of the data. We use the quartet paradigm to compute a hierarchy of clusters of the objects. The method is based on an NP-hard graph optimization problem called the Minimum Quartet Tree Cost problem. This paper presents and compares several heuristic approaches to approximate the optimal hierarchy. The performance of the algorithms is tested through extensive computational experiments and it is shown that the Reduced Variable Neighborhood Search heuristic is the most effective approach to the problem, obtaining high-quality solutions in short computational running times.

Creating a dead poets society: extracting a social network of historical persons from the web

We present a simple method to extract information from search engine snippets. Although the techniques presented are domain independent, this work focuses on extracting biographical information of historical persons from multiple unstructured sources on the Web. We first similarly find a list of persons and their periods of life by querying the periods and scanning the retrieved snippets for person names. Subsequently, we find biographical information for the persons extracted. In order to get insight in the mutual relations among the persons identified, we create a social network using co-occurrences on the Web. Although we use uncontrolled and unstructured Web sources, the information extracted is reliable. Moreover we show that Web Information Extraction can be used to create both informative and enjoyable applications.

Depression as an independent prognostic factor for all-cause mortality after a hospital admission for worsening heart failure

BACKGROUND Depression is associated with increased mortality amongst patients with chronic heart failure (HF). Whether depression is an independent predictor of outcome in patients admitted for worsening of HF is unclear. METHODS OPERA-HF is an observational study enrolling patients hospitalized with worsening HF. Depression was assessed by the Hospital Anxiety and Depression Scale (HADS-D) questionnaire. Comorbidity was assessed by the Charlson Comorbidity Index (CCI). Kaplan-Meier and Cox regression analyses were used to estimate the association between depression and all-cause mortality. RESULTS Of 242 patients who completed the HADS-D questionnaire, 153, 54 and 35 patients had no (score 0-7), mild (score 8-10) or moderate-to-severe (score 11-21) depression, respectively. During follow-up, 35 patients died, with a median time follow-up of 360days amongst survivors (interquartile range, IQR 217-574days). In univariable analysis, moderate-to-severe depression was associated with an increased risk of death (HR: 4.9; 95% CI: 2.3 to 10.2; P<0.001) compared to no depression. Moderate-to-severe depression also predicted all-cause mortality after controlling for age, CCI score, NYHA class IV, NT-proBNP and treatment with mineralocorticoid receptor antagonist, beta-blocker and diuretics (HR: 3.0; 95% CI: 1.3 to 7.0; P<0.05). CONCLUSIONS Depression is strongly associated with an adverse outcome in the year following discharge after an admission to hospital for worsening HF. The association is only partly explained by the severity of HF or comorbidity. Further research is required to demonstrate whether recognition and treatment of depression improves patient outcomes.

Guidance and support for healthy food preparation in an augmented kitchen

An important barrier to healthful eating is a lack of cooking competence. To assist people who are motivated to increase their cooking competence, we envision a context-aware kitchen that offers a recipe retrieval and recommendation system. Preceding the system design we conducted an at-home observation study to identify a meaningful set of utensils that can provide insights into the cooking process. Accelerometers embedded into these utensils provide relevant context information for the recipe recommender system to select the meals that fit the users meal preferences and cooking competence.

Enriching text with images and colored light

We present an unsupervised method to enrich textual applications with relevant images and colors. The images are collected by querying large image repositories and subsequently the colors are computed using image processing. A prototype system based on this method is presented where the method is applied to song lyrics. In combination with a lyrics synchronization algorithm the system produces a rich multimedia experience. In order to identify terms within the text that may be associated with images and colors, we select noun phrases using a part of speech tagger. Large image repositories are queried with these terms. Per term representative colors are extracted using the collected images. Hereto, we either use a histogram-based or a mean shift-based algorithm. The representative color extraction uses the non-uniform distribution of the colors found in the large repositories. The images that are ranked best by the search engine are displayed on a screen, while the extracted representative colors are rendered on controllable lighting devices in the living room. We evaluate our method by comparing the computed colors to standard color representations of a set of English color terms. A second evaluation focuses on the distance in color between a queried term in English and its translation in a foreign language. Based on results from three sets of terms, a measure of suitability of a term for color extraction based on KL Divergence is proposed. Finally, we compare the performance of the algorithm using either the automatically indexed repository of Google Images and the manually annotated Flickr.com. Based on the results of these experiments, we conclude that using the presented method we can compute the relevant color for a term using a large image repository and image processing.