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This is significant for physical activity promotion because more precise measurement will allow investigators to better understand where, when, and how physical activity is and is not occurring, thus enabling more effective targeting of particular behavior settings. Emerging technologies associated with the measurement and evaluation of physical activity are noteworthy because: (1) Their ease of use and transferability can greatly increase external validity of measures and findings; (2) Technologies can significantly increase the ability to analyze patterns; (3) They can improve the ongoing, systematic collection and analysis of public health surveillance due to real-time capabilities associated with many emerging technologies; (4) There is a need for research and papers about the cyberinfrastructure required to cope with big data (multiple streams, processing, aggregation, visualization, etc.); and (5) Increasingly blurred boundaries between measurement and intervention activity (e.g., the quantified-self /self-tracking movement) may necessitate a reevaluation of the conventional scientific model for designing and evaluating these sorts of studies. There have been many recent, disparate advances related to this topic. Advances such as crowdsourcing allow for input from large, diverse audiences that can help to identify and improve infrastructure for activity (e.g., large group identification of environmental features that are conducive or inhibiting to physical activity on a national and even global scale). Technologies such as Global Positioning Systems (GPS) and accelerometry are now available in many mobile phones and can be used for identifying and promoting activity and also understanding naturalistically-occurring activity. SenseCam and other personal, visual devices and mobile apps provide person point of view context to physical activity lifestyle and timing. Further, multiple sensor systems are enabling better identification of types of activities (like stair climbing and jumping) that could not previously be identified readily using objective measures like pedometers or accelerometers in isolation. The ability of activity sensors to send data to remote servers allows for the incorporation of online technology (e.g., employing an online social-network as a source of inspiration or accountability to achieve physical activity goals), and websites such as Stickk.com enable individuals to make public contracts visible to other users and also incorporates financial incentives and disincentives in order to promote behaviors including physical activity. In addition, the increasing use of active-gaming (e.g., Wii, XBox Kinect) in homes, schools, and other venues further underscores the growing link between technology and physical activity. Improvements in mathematical models and computer algorithms also allow greater capacity for classifying and evaluating physical activity, improving consistency across research studies. Emerging technologies in the promotion and evaluation of physical activity is a significant area of interest because of its ability to greatly increase the amount and quality of global recorded measurements of PA patterns and its potential to more effectively promote PA. Emerging technologies related to physical activity build on our own and others’ interdisciplinary collaborations in employing technology to address public health challenges. This research area is innovative in that is uses emerging resources including social media, crowdsourcing, and online gaming to better understand patterns of physical activity.", "series": "", "seriesNumber": "", "volume": "", "numberOfVolumes": "", "edition": "", "date": "2014-10-23", "publisher": "Frontiers E-books", "place": "", "originalDate": "", "originalPublisher": "", "originalPlace": "", "format": "", "numPages": "141", "ISBN": "978-2-88919-298-4", "DOI": "", "citationKey": "", "url": "", "accessDate": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "en", "libraryCatalog": "Google Books", "callNumber": "", "rights": "", "extra": "", "tags": [], "collections": [ "IXZI5XS6" ], "relations": {}, "dateAdded": "2016-02-17T03:49:04Z", "dateModified": "2016-02-17T03:49:04Z" } }, { "key": "SXIARWPU", "version": 96, "library": { "type": "group", "id": 289837, "name": "Travel Diary", "links": { "alternate": { "href": "https://www.zotero.org/groups/travel_diary", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/289837/items/SXIARWPU", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/travel_diary/items/SXIARWPU", "type": "text/html" } }, "meta": { "createdByUser": { "id": 537726, "username": "armuro", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/armuro", "type": "text/html" } } }, "creatorSummary": "Eagle et al.", "parsedDate": "2009-09-08", "numChildren": 3 }, "data": { "key": "SXIARWPU", "version": 96, "itemType": "journalArticle", "title": "Inferring friendship network structure by using mobile phone data", "creators": [ { "creatorType": "author", "firstName": "Nathan", "lastName": "Eagle" }, { "creatorType": "author", "firstName": "Alex (Sandy)", "lastName": "Pentland" }, { "creatorType": "author", "firstName": "David", "lastName": "Lazer" } ], "abstractNote": "Data collected from mobile phones have the potential to provide insight into the relational dynamics of individuals. This paper compares observational data from mobile phones with standard self-report survey data. We find that the information from these two data sources is overlapping but distinct. For example, self-reports of physical proximity deviate from mobile phone records depending on the recency and salience of the interactions. We also demonstrate that it is possible to accurately infer 95% of friendships based on the observational data alone, where friend dyads demonstrate distinctive temporal and spatial patterns in their physical proximity and calling patterns. These behavioral patterns, in turn, allow the prediction of individual-level outcomes such as job satisfaction.", "publicationTitle": "Proceedings of the National Academy of Sciences", "publisher": "", "place": "", "date": "09/08/2009", "volume": "106", "issue": "36", "section": "", "partNumber": "", "partTitle": "", "pages": "15274-15278", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "PNAS", "DOI": "10.1073/pnas.0900282106", "citationKey": "", "url": "http://www.pnas.org.proxy.lib.umich.edu/content/106/36/15274", "accessDate": "2015-09-21T00:25:00Z", "PMID": "19706491", "PMCID": "", "ISSN": "0027-8424, 1091-6490", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "en", "libraryCatalog": "www.pnas.org.proxy.lib.umich.edu", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "engineering-social systems", "type": 1 }, { "tag": "reality mining", "type": 1 }, { "tag": "relational inference", "type": 1 }, { "tag": "relational 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"creatorType": "author", "firstName": "Li", "lastName": "Shen" }, { "creatorType": "author", "firstName": "Peter R.", "lastName": "Stopher" } ], "abstractNote": "Global Positioning System (GPS) surveys have been conducted for the past decade. Although GPS records were initially regarded as providing “ground truth” of travel, it has been found subsequently that they have some errors. SenseCam, a small passive digital camera, provides a chance to pursue ground truth by capturing images every 20 s on average. This paper discusses how SenseCam could help GPS data collection and shows potential benefits for both SenseCam and GPS research. This paper also investigates the performance of GPS devices in detail in terms of recording data by comparisons between GPS results and SenseCam images. The specific issue of missing GPS data is discussed and examined in this paper.", "publicationTitle": "Transportation Research Part C: Emerging Technologies", "publisher": "", "place": "", "date": "May 2014", "volume": "42", "issue": "", "section": "", "partNumber": "", "partTitle": "", "pages": "76-81", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "Transportation Research Part C: Emerging Technologies", "DOI": "10.1016/j.trc.2014.02.022", "citationKey": "", "url": "http://www.sciencedirect.com/science/article/pii/S0968090X14000643", "accessDate": "2015-09-19T19:26:53Z", "PMID": "", "PMCID": "", "ISSN": "0968-090X", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "ScienceDirect", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "GPS", "type": 1 }, { "tag": "Ground truth", "type": 1 }, { "tag": "SenseCam", "type": 1 }, { "tag": "Travel surveys", "type": 1 }, { "tag": "travel behaviour", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2015-09-19T19:26:53Z", "dateModified": "2015-09-19T19:26:53Z" } }, { "key": "PIVMDE2S", "version": 90, "library": { "type": "group", "id": 289837, "name": "Travel Diary", "links": { "alternate": { "href": "https://www.zotero.org/groups/travel_diary", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/289837/items/PIVMDE2S", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/travel_diary/items/PIVMDE2S", "type": "text/html" }, "up": { "href": "https://api.zotero.org/groups/289837/items/J93K69MN", "type": "application/json" } }, "meta": { "createdByUser": { "id": 537726, "username": "armuro", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/armuro", "type": "text/html" } } } }, "data": { "key": "PIVMDE2S", "version": 90, "parentItem": "J93K69MN", "itemType": "attachment", "linkMode": "linked_url", "title": "ScienceDirect Full Text PDF", "accessDate": "2015-05-22T16:39:04Z", "url": "http://www.sciencedirect.com.proxy.lib.umich.edu/science/article/pii/S2352146515000198/pdf?md5=dc59ef963dccdcf5228524aef7124361&pid=1-s2.0-S2352146515000198-main.pdf", "note": "", "contentType": "application/pdf", "charset": "", "tags": [], "relations": {}, "dateAdded": "2015-05-22T16:39:04Z", "dateModified": "2015-05-22T16:39:04Z" } }, { "key": "27GDAUD3", "version": 90, "library": { "type": "group", "id": 289837, "name": "Travel Diary", "links": { "alternate": { "href": "https://www.zotero.org/groups/travel_diary", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/289837/items/27GDAUD3", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/travel_diary/items/27GDAUD3", "type": "text/html" }, "up": { "href": "https://api.zotero.org/groups/289837/items/J93K69MN", "type": "application/json" } }, "meta": { "createdByUser": { "id": 537726, "username": "armuro", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/armuro", "type": "text/html" } } } }, "data": { "key": "27GDAUD3", "version": 90, "parentItem": "J93K69MN", "itemType": "attachment", "linkMode": "linked_url", "title": "ScienceDirect Snapshot", "accessDate": "2015-05-22T16:39:04Z", "url": "http://www.sciencedirect.com.proxy.lib.umich.edu/science/article/pii/S2352146515000198", "note": "", "contentType": "text/html", "charset": "", "tags": [], "relations": {}, "dateAdded": "2015-05-22T16:39:04Z", "dateModified": "2015-05-22T16:39:04Z" } }, { "key": "J93K69MN", "version": 90, "library": { "type": "group", "id": 289837, "name": "Travel Diary", "links": { "alternate": { "href": "https://www.zotero.org/groups/travel_diary", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/289837/items/J93K69MN", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/travel_diary/items/J93K69MN", "type": "text/html" } }, "meta": { "createdByUser": { "id": 537726, "username": "armuro", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/armuro", "type": "text/html" } } }, "creatorSummary": "Vacca and Meloni", "parsedDate": "2015", "numChildren": 2 }, "data": { "key": "J93K69MN", "version": 90, "itemType": "journalArticle", "title": "Understanding Route Switch Behavior: An Analysis Using GPS Based Data", "creators": [ { "creatorType": "author", "firstName": "Alessandro", "lastName": "Vacca" }, { "creatorType": "author", "firstName": "Italo", "lastName": "Meloni" } ], "abstractNote": "The objective of this paper is to study route switch behavior to detect which trip and individual characteristics most influence the choice of multiple routes for the same origin-destination (OD) trip. In this study we used a database of 361 morning commute trips, regarding 66 users, collected in the metropolitan area of Cagliari (Italy) during the “Casteddu Mobility Styles” survey. Data were collected for a 14 days period through a personal probe system called Activity Locator (Meloni et al., 2011), a smartphone that integrates a GPS logger for the acquisition of the routes and an activity/travel diary. Mixed logit models are estimated, in order to take into account the variability of user perception. Results show that route switch behavior is influenced by the number of traffic lights per km, percent of highways, time perception, gender, age, individual income and driving experience in relation with the minutes per km.", "publicationTitle": "Transportation Research Procedia", "publisher": "", "place": "", "date": "2015", "volume": "5", "issue": "", "section": "", "partNumber": "", "partTitle": "", "pages": "56-65", "series": "SIDT Scientific Seminar 2013", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "Transportation Research Procedia", "DOI": "10.1016/j.trpro.2015.01.018", "citationKey": "", "url": "http://www.sciencedirect.com/science/article/pii/S2352146515000198", "accessDate": "2015-05-22T16:39:04Z", "PMID": "", "PMCID": "", "ISSN": "2352-1465", "archive": "", "archiveLocation": "", "shortTitle": "Understanding Route Switch Behavior", "language": "", "libraryCatalog": "ScienceDirect", "callNumber": "", "rights": "", "extra": "", "tags": [ { "tag": "GPS", "type": 1 }, { "tag": "Route choice", "type": 1 }, { "tag": "Route switch", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2015-05-22T16:39:04Z", "dateModified": "2015-05-22T16:39:04Z" } }, { "key": "MRJATKQX", "version": 89, "library": { "type": "group", "id": 289837, "name": "Travel Diary", "links": { "alternate": { "href": "https://www.zotero.org/groups/travel_diary", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/289837/items/MRJATKQX", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/travel_diary/items/MRJATKQX", "type": "text/html" } }, "meta": { "createdByUser": { "id": 537726, "username": "armuro", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/armuro", "type": "text/html" } } }, "creatorSummary": "Gouveia et al.", "parsedDate": "2012-07-07", "numChildren": 2 }, "data": { "key": "MRJATKQX", "version": 89, "itemType": "journalArticle", "title": "Footprint Tracker: reviewing lifelogs and reconstructing daily experiences", "creators": [ { "creatorType": "author", "firstName": "Rúben", "lastName": "Gouveia" }, { "creatorType": "author", "firstName": "Evangelos", "lastName": "Niforatos" }, { "creatorType": "author", "firstName": "Evangelos", "lastName": "Karapanos" } ], "abstractNote": "With the increasing emphasis on how mobile technologies are experienced in everyday life, researchers are increasingly emphasizing the use of in-situ methods such as Experience Sampling and Day Reconstruction. In our line of research we explore the concept of Technology-Assisted Reconstruction, in which passively logged behavior data assist in the later reconstruction of daily experiences. In this paper we introduce Footprint tracker, a web application that supports participants in reviewing lifelogs and reconstructing their daily experiences. We focus on three kinds of data: visual (as captured through Microsoft's sensecam), location, and context (i.e., SMS and calls received and made). We describe how Footprint Tracker supports the user in reviewing these lifelogs and outline a field study that attempts to inquire into whether and how this data support reconstruction from memory.", "publicationTitle": "arXiv:1207.1818 [cs]", "publisher": "", "place": "", "date": "2012-07-07", "volume": "", "issue": "", "section": "", "partNumber": "", "partTitle": "", "pages": "", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "", "citationKey": "", "url": "http://arxiv.org/abs/1207.1818", "accessDate": "2015-03-19T01:02:13Z", "PMID": "", "PMCID": "", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "Footprint Tracker", "language": "", "libraryCatalog": "arXiv.org", "callNumber": "", "rights": "", "extra": "arXiv: 1207.1818", "tags": [ { "tag": "Computer Science - Human-Computer Interaction", "type": 1 } ], "collections": [ "34SMJU6S" ], "relations": {}, "dateAdded": "2015-03-19T01:02:13Z", "dateModified": "2015-03-19T01:02:13Z" } 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"creatorSummary": "Venkatanathan et al.", "parsedDate": "2011", "numChildren": 2 }, "data": { "key": "RXGN4K3Z", "version": 88, "itemType": "bookSection", "title": "Improving Users’ Consistency When Recalling Location Sharing Preferences", "creators": [ { "creatorType": "author", "firstName": "Jayant", "lastName": "Venkatanathan" }, { "creatorType": "author", "firstName": "Denzil", "lastName": "Ferreira" }, { "creatorType": "author", "firstName": "Michael", "lastName": "Benisch" }, { "creatorType": "author", "firstName": "Jialiu", "lastName": "Lin" }, { "creatorType": "author", "firstName": "Evangelos", "lastName": "Karapanos" }, { "creatorType": "author", "firstName": "Vassilis", "lastName": "Kostakos" }, { "creatorType": "author", "firstName": "Norman", "lastName": "Sadeh" }, { "creatorType": "author", "firstName": "Eran", "lastName": "Toch" }, { "creatorType": "editor", "firstName": "Pedro", "lastName": "Campos" }, { "creatorType": "editor", "firstName": "Nicholas", "lastName": "Graham" }, { "creatorType": "editor", "firstName": "Joaquim", "lastName": "Jorge" }, { "creatorType": "editor", "firstName": "Nuno", "lastName": "Nunes" }, { "creatorType": "editor", "firstName": "Philippe", "lastName": "Palanque" }, { "creatorType": "editor", "firstName": "Marco", "lastName": "Winckler" } ], "abstractNote": "This paper presents a study of the effect of one instance of contextual cues, trajectory reminders, on the recollection of location sharing preferences elicited using a retrospective protocol. Trajectory reminders are user interface elements that indicate for a particular location of a person’s trail across a city the locations visited before and after. The results of the study show that reminding users where they have been before and after a specific visited location can elicit more consistent responses in terms of stated location sharing preferences for that location visit. This paper argues that trajectory reminders are useful when collecting preference data with retrospective protocols because they can improve the quality of the collected data.", "bookTitle": "Human-Computer Interaction – INTERACT 2011", "series": "Lecture Notes in Computer Science", "seriesNumber": "6946", "volume": "", "numberOfVolumes": "", "edition": "", "date": "2011", "publisher": "Springer Berlin Heidelberg", "place": "", "originalDate": "", "originalPublisher": "", "originalPlace": "", "format": "", "pages": "380-387", "ISBN": "978-3-642-23773-7, 978-3-642-23774-4", "DOI": "", "citationKey": "", "url": "http://link.springer.com.proxy.lib.umich.edu/chapter/10.1007/978-3-642-23774-4_31", "accessDate": "2015-03-19T01:00:43Z", "ISSN": "", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "en", "libraryCatalog": "link.springer.com.proxy.lib.umich.edu", "callNumber": "", "rights": "©2011 IFIP International Federation for Information Processing", "extra": "", "tags": [ { "tag": "Artificial Intelligence (incl. 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"", "partTitle": "", "pages": "44-47", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "", "DOI": "10.1109/MPRV.2013.21", "citationKey": "", "url": "http://pascal.computer.org.proxy.lib.umich.edu/csdl/mags/pc/2013/01/mpc2013010044.html", "accessDate": "2015-02-12T19:54:04Z", "PMID": "", "PMCID": "", "ISSN": "1536-1268", "archive": "", "archiveLocation": "", "shortTitle": "Wearable Cameras", "language": "", "libraryCatalog": "CrossRef", "callNumber": "", "rights": "", "extra": "", "tags": [], "collections": [], "relations": {}, "dateAdded": "2015-02-12T19:54:04Z", "dateModified": "2015-02-12T19:54:04Z" } }, { "key": "PM53995C", "version": 86, "library": { "type": "group", "id": 289837, "name": "Travel Diary", "links": { "alternate": { "href": "https://www.zotero.org/groups/travel_diary", "type": "text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/289837/items/PM53995C", "type": "application/json" }, "alternate": { "href": 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"text/html" } } }, "links": { "self": { "href": "https://api.zotero.org/groups/289837/items/7RHHSCTB", "type": "application/json" }, "alternate": { "href": "https://www.zotero.org/groups/travel_diary/items/7RHHSCTB", "type": "text/html" } }, "meta": { "createdByUser": { "id": 537726, "username": "armuro", "name": "", "links": { "alternate": { "href": "https://www.zotero.org/armuro", "type": "text/html" } } }, "creatorSummary": "Gemming et al.", "parsedDate": "2013-10", "numChildren": 2 }, "data": { "key": "7RHHSCTB", "version": 86, "itemType": "journalArticle", "title": "Feasibility of a SenseCam-assisted 24-h recall to reduce under-reporting of energy intake", "creators": [ { "creatorType": "author", "firstName": "L.", "lastName": "Gemming" }, { "creatorType": "author", "firstName": "A.", "lastName": "Doherty" }, { "creatorType": "author", "firstName": "P.", "lastName": "Kelly" }, { "creatorType": "author", "firstName": "J.", "lastName": "Utter" }, { "creatorType": "author", "firstName": "C.", "lastName": "Ni Mhurchu" } ], "abstractNote": "Background/Objectives: The SenseCam is a camera worn on a lanyard around the neck that automatically captures point-of-view images in response to movement, heat and light (every 20–30 s). This device may enhance the accuracy of self-reported dietary intake by assisting participants’ recall of food and beverage consumption. It was the objective of this study to evaluate if the wearable camera, SenseCam, can enhance the 24-h dietary recall by providing visual prompts to improve recall of food and beverage consumption.\nSubject/Methods: Thirteen volunteer adults in Oxford, United Kingdom, were recruited. Participants wore the SenseCam for 2 days while continuing their usual daily activities. On day 3, participants’ diets were assessed using an interviewer-administered 24-h recall. SenseCam images were then shown to the participants and any additional dietary information that participants provided after viewing the images was recorded. Energy and macronutrient intakes were compared between the 24-h recall and 24-h recall+SenseCam.\nResults: Data from 10 participants were included in the final analysis (8 males and 2 females), mean age 33±11 years, mean BMI 25.9±5.1 kg/m2. Viewing the SenseCam images increased self-reported energy intake by approximately 1432±1564 kJ or 12.5% compared with the 24-h recall alone (P=0.02). The increase was predominantly due to reporting of 41 additional foods (241 vs 282 total foods) across a range of food groups. Eight changes in portion size were made, which resulted in a negligible change to energy intake.\nConclusions: Wearable cameras are promising method to enhance the accuracy of self-reported dietary assessment methods.", "publicationTitle": "European Journal of Clinical Nutrition", "publisher": "", "place": "", "date": "October 2013", "volume": "67", "issue": "10", "section": "", "partNumber": "", "partTitle": "", "pages": "1095-1099", "series": "", "seriesTitle": "", "seriesText": "", "journalAbbreviation": "Eur J Clin Nutr", "DOI": "10.1038/ejcn.2013.156", "citationKey": "", "url": "http://www.nature.com.proxy.lib.umich.edu/ejcn/journal/v67/n10/abs/ejcn2013156a.html", "accessDate": "2015-02-12T19:53:41Z", "PMID": "", "PMCID": "", "ISSN": "0954-3007", "archive": "", "archiveLocation": "", "shortTitle": "", "language": "", "libraryCatalog": "www.nature.com.proxy.lib.umich.edu", "callNumber": "", "rights": "© 2013 Nature Publishing Group", "extra": "", "tags": [ { "tag": "SenseCam", "type": 1 }, { "tag": "nutrition assessment", "type": 1 }, { "tag": "photography", "type": 1 }, { "tag": "under-reporting", "type": 1 }, { "tag": "wearable camera", "type": 1 } ], "collections": [], "relations": {}, "dateAdded": "2015-02-12T19:53:41Z", "dateModified": "2015-02-12T19:53:41Z" } } ]