Lesson Learned from Collecting Quantified Self Information via Mobile and Wearable Devices
The ubiquity and affordability of mobile and wearable devices has enabled us to continually and digitally record our daily life activities. Consequently, we are seeing the growth of data collection experiments in several scientific disciplines. Although these have yielded promising results, mobile a...
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| Format: | Article |
| Language: | English |
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MDPI AG
2015-11-01
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| Series: | Journal of Sensor and Actuator Networks |
| Subjects: | |
| Online Access: | http://www.mdpi.com/2224-2708/4/4/315 |
| _version_ | 1818264946240126976 |
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| author | Reza Rawassizadeh Elaheh Momeni Chelsea Dobbins Pejman Mirza-Babaei Ramin Rahnamoun |
| author_facet | Reza Rawassizadeh Elaheh Momeni Chelsea Dobbins Pejman Mirza-Babaei Ramin Rahnamoun |
| author_sort | Reza Rawassizadeh |
| collection | DOAJ |
| description | The ubiquity and affordability of mobile and wearable devices has enabled us to continually and digitally record our daily life activities. Consequently, we are seeing the growth of data collection experiments in several scientific disciplines. Although these have yielded promising results, mobile and wearable data collection experiments are often restricted to a specific configuration that has been designed for a unique study goal. These approaches do not address all the real-world challenges of “continuous data collection” systems. As a result, there have been few discussions or reports about such issues that are faced when “implementing these platforms” in a practical situation. To address this, we have summarized our technical and user-centric findings from three lifelogging and Quantified Self data collection studies, which we have conducted in real-world settings, for both smartphones and smartwatches. In addition to (i) privacy and (ii) battery related issues; based on our findings we recommend further works to consider (iii) implementing multivariate reflection of the data; (iv) resolving the uncertainty and data loss; and (v) consider to minimize the manual intervention required by users. These findings have provided insights that can be used as a guideline for further Quantified Self or lifelogging studies. |
| first_indexed | 2024-12-12T19:42:59Z |
| format | Article |
| id | doaj.art-9c1bb5a4f2fd41b3b1f386b50a5229f1 |
| institution | Directory Open Access Journal |
| issn | 2224-2708 |
| language | English |
| last_indexed | 2024-12-12T19:42:59Z |
| publishDate | 2015-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Journal of Sensor and Actuator Networks |
| spelling | doaj.art-9c1bb5a4f2fd41b3b1f386b50a5229f12022-12-22T00:14:09ZengMDPI AGJournal of Sensor and Actuator Networks2224-27082015-11-014431533510.3390/jsan4040315jsan4040315Lesson Learned from Collecting Quantified Self Information via Mobile and Wearable DevicesReza Rawassizadeh0Elaheh Momeni1Chelsea Dobbins2Pejman Mirza-Babaei3Ramin Rahnamoun4Department of Computer Science and Engineering, University of California Riverside, Riverside 92521, CA, USAFaculty of Computer Science, University of Vienna, Vienna A-1090, AustriaDepartment of Computer Science, Liverpool John Moores University, Liverpool L33AF, UKInstitute of Technology, University of Ontario, Oshawa L1H7K4, ON, CanadaIslamic Azad University Central Tehran Branch, Tehran 1469669191, IranThe ubiquity and affordability of mobile and wearable devices has enabled us to continually and digitally record our daily life activities. Consequently, we are seeing the growth of data collection experiments in several scientific disciplines. Although these have yielded promising results, mobile and wearable data collection experiments are often restricted to a specific configuration that has been designed for a unique study goal. These approaches do not address all the real-world challenges of “continuous data collection” systems. As a result, there have been few discussions or reports about such issues that are faced when “implementing these platforms” in a practical situation. To address this, we have summarized our technical and user-centric findings from three lifelogging and Quantified Self data collection studies, which we have conducted in real-world settings, for both smartphones and smartwatches. In addition to (i) privacy and (ii) battery related issues; based on our findings we recommend further works to consider (iii) implementing multivariate reflection of the data; (iv) resolving the uncertainty and data loss; and (v) consider to minimize the manual intervention required by users. These findings have provided insights that can be used as a guideline for further Quantified Self or lifelogging studies.http://www.mdpi.com/2224-2708/4/4/315lifeloggingQuantified Selfuser experimentsmartwatchsmartphonedata collection |
| spellingShingle | Reza Rawassizadeh Elaheh Momeni Chelsea Dobbins Pejman Mirza-Babaei Ramin Rahnamoun Lesson Learned from Collecting Quantified Self Information via Mobile and Wearable Devices Journal of Sensor and Actuator Networks lifelogging Quantified Self user experiment smartwatch smartphone data collection |
| title | Lesson Learned from Collecting Quantified Self Information via Mobile and Wearable Devices |
| title_full | Lesson Learned from Collecting Quantified Self Information via Mobile and Wearable Devices |
| title_fullStr | Lesson Learned from Collecting Quantified Self Information via Mobile and Wearable Devices |
| title_full_unstemmed | Lesson Learned from Collecting Quantified Self Information via Mobile and Wearable Devices |
| title_short | Lesson Learned from Collecting Quantified Self Information via Mobile and Wearable Devices |
| title_sort | lesson learned from collecting quantified self information via mobile and wearable devices |
| topic | lifelogging Quantified Self user experiment smartwatch smartphone data collection |
| url | http://www.mdpi.com/2224-2708/4/4/315 |
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