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Lifelogging as a Viable Data Source for NeuroIS Researchers: A Review of Neurophysiological Data Types Collected in the Lifelogging Literature

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Information Systems and Neuroscience

Part of the book series: Lecture Notes in Information Systems and Organisation ((LNISO,volume 16))

Abstract

Based on this review, we argue for the consideration of lifelogging as an additional data source in NeuroIS research. Lifelogging itself is a concept which describes a behavior in which individuals, based on the use of computer technology, track (parts of) their lives, including the quantification of their well-being (e.g., continuous recording of an individual’s heart rate via a digital wrist watch). This relatively new form of behavior generates a viable data source for future NeuroIS studies, predominantly for those conducted in field settings. By analyzing how frequently the major types of neurophysiological data have thus far been collected in lifelogging publications, we reveal how much attention different types of neurophysiological data have received in the context of longitudinal field studies. In essence, lifelogging data constitute a viable data base for NeuroIS researchers, one that is readily available and is predicted to grow in the future because an increasing number of people worldwide are tracking their daily lives to a growing extent.

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Notes

  1. 1.

    A similar criterion has previously been applied in a literature review by Riedl [20].

  2. 2.

    It has to be noted that we do not claim that the 36 publications which we identified constitute an exhaustive list of available publications.

References

  1. Fischer, T., Riedl, R.: Neurois in situ: On the Need for NeuroIS Research in the Field to Study Organizational Phenomena. In: Liang, T.-P., Yen, N.-S. (eds.) Workshop on Information and Neural Decision Sciences, pp. 20–21 (2014)

    Google Scholar 

  2. Dodge, M., Kitchin, R.: ‘Outlines of a world coming into existence’: Pervasive computing and the ethics of forgetting. Environ. Plann. Plann. Des. 34, 431–445 (2007)

    Article  Google Scholar 

  3. Bush, V.: As we may think. The Atlantic Monthly, pp. 112–124 (1945)

    Google Scholar 

  4. Gurrin, C., Smeaton, A.F., Doherty, A.R.: LifeLogging: Personal big data. Found. Trends Inf. Retr. 8, 1–125 (2014)

    Article  Google Scholar 

  5. Bell, G.: A personal digital store. Comm. ACM 44, 86–91 (2001)

    Article  Google Scholar 

  6. O’Hara, K., Morris, R., Shadbolt, N., Hitch, G.J., Hall, W., Beagrie, N.: Memories for life: A review of the science and technology. J. R. Soc. Interface 3, 351–365 (2006)

    Article  Google Scholar 

  7. Sellen, A.J., Whittaker, S.: Beyond total capture. Comm. ACM 53, 70 (2010)

    Article  Google Scholar 

  8. Swan, M.: The quantified self: Fundamental disruption in big data science and biological discovery. Big Data 1, 85–99 (2013)

    Article  Google Scholar 

  9. Weiss, M.: Effects of work stress and social support on information systems managers. MIS Q. 7, 29 (1983)

    Article  Google Scholar 

  10. Sethi, V., King, R.C., Quick, J.C.: What causes stress in information system professionals? Comm. ACM 47, 99–102 (2004)

    Article  Google Scholar 

  11. Riedl, R., Kindermann, H., Auinger, A., Javor, A.: Technostress from a neurobiological perspective—System breakdown increases the stress hormone cortisol in computer users. Bus. Inf. Syst. Eng. 4, 61–69 (2012)

    Article  Google Scholar 

  12. Riedl, R., Kindermann, H., Auinger, A., Javor, A.: Computer breakdown as a stress factor during task completion under time pressure: Identifying gender differences based on skin conductance. Adv. Hum.-Comput. Interact. 2013, 1–8 (2013)

    Article  Google Scholar 

  13. Wang, P., Smeaton, A.F.: Using visual lifelogs to automatically characterize everyday activities. Inf. Sci. 230, 147–161 (2013)

    Article  Google Scholar 

  14. Fox, S., Duggan, M.: Tracking for Health. Pew Research Center’s Internet & American Life Project. Pew Research Center (2013)

    Google Scholar 

  15. California Institute for Telecommunications and Information Technology: Personal Data for the Public Good. New Opportunities to Enrich Understanding of Individual and Population Health (2014)

    Google Scholar 

  16. Worldwide Wearables Market Forecast to Reach 45.7 Million Units Shipped in 2015 and 126.1 Million Units in 2019, According to IDC (2015)

    Google Scholar 

  17. Nack, F.: You must remember this. IEEE Multimed. 12, 4–7 (2005)

    Article  Google Scholar 

  18. Bell, G., Gemmell, J.: A digital life. Sci. Am. 296, 58–65 (2007)

    Article  Google Scholar 

  19. Ivonin, L., Chang, H.-M., Chen, W., Rauterberg, M.: Unconscious emotions: Quantifying and logging something we are not aware of. Pers. Ubiquit. Comput. 17, 663–673 (2013)

    Article  Google Scholar 

  20. Riedl, R.: On the biology of technostress: Literature review and research agenda. Database Adv. Inform. Syst. 44, 18–55 (2013)

    Article  Google Scholar 

  21. O’Hara, K., Tuffield, M.M., Shadbolt, N.: Lifelogging: Privacy and empowerment with memories for life. Ident. Inform. Soc. 1, 155–172 (2008)

    Article  Google Scholar 

  22. Jacquemard, T., Novitzky, P., O’Brolcháin, F., Smeaton, A.F., Gordijn, B.: Challenges and opportunities of lifelog technologies: A literature review and critical analysis. Sci. Eng. Ethics 20, 379–409 (2014)

    Article  Google Scholar 

  23. Gemmell, J., Bell, G., Lueder, R.: MyLifeBits: A personal database for everything. Comm. ACM 49, 88–95 (2006)

    Article  Google Scholar 

  24. Choudhury, T., Borriello, G., Consolvo, S., Haehnel, D., Harrison, B., Hemingway, B., Hightower, J., Klasnja, P., Koscher, K., LaMarca, A., et al.: The mobile sensing platform: An embedded activity recognition system. IEEE Pervasive Comput. 7, 32–41 (2008)

    Article  Google Scholar 

  25. Anderson, I., Maitland, J., Sherwood, S., Barkhuus, L., Chalmers, M., Hall, M., Brown, B., Muller, H.: Shakra: Tracking and sharing daily activity levels with unaugmented mobile phones. Mobile Network Appl. 12, 185–199 (2007)

    Article  Google Scholar 

  26. Berry, E., Kapur, N., Williams, L., Hodges, S.E., Watson, P., Smyth, G., Srinivasan, J., Smith, R., Wilson, B., Wood, K.: The use of a wearable camera, SenseCam, as a pictorial diary to improve autobiographical memory in a patient with limbic encephalitis: A preliminary report. Neuropsychol. Rehabil. 17, 582–601 (2007)

    Article  Google Scholar 

  27. Gyorbiro, N., Fabian, A., Hományi, G.: An activity recognition system for mobile phones. Mobile Network Appl. 14, 82–91 (2009)

    Article  Google Scholar 

  28. Whittaker, S., Bergman, O., Clough, P.: Easy on that trigger dad: A study of long term family photo retrieval. Pers. Ubiquit. Comput. 14, 31–43 (2010)

    Article  Google Scholar 

  29. Blum, M., Pentland, A., Troster, G.: InSense: Interest-based life logging. IEEE Multimed. 13, 40–48 (2006)

    Article  Google Scholar 

  30. Hodges, S., Berry, E., Wood, K.: SenseCam: A wearable camera that stimulates and rehabilitates autobiographical memory. Memory 19, 685–696 (2011)

    Article  Google Scholar 

  31. Lee, H., Smeaton, A.F., O’Connor, N.E., Jones, G., Blighe, M., Byrne, D., Doherty, A., Gurrin, C.: Constructing a SenseCam visual diary as a media process. Multimed. Syst. 14, 341–349 (2008)

    Article  Google Scholar 

  32. Ogata, H., Li, M., Hou, B., Uosaki, N., El-Bishouty, M.M., Yano, Y.: SCROLL: Supporting to share and reuse ubiquitous learning log in the context of language learning. Res. Pract. Technol. Enhanc. Learn. 6, 69–82 (2011)

    Google Scholar 

  33. Doherty, A.R., Caprani, N., Conaire, C.Ó., Kalnikaite, V., Gurrin, C., Smeaton, A.F., O’Connor, N.E.: Passively recognising human activities through lifelogging. Comput. Hum. Behav. 27, 1948–1958 (2011)

    Article  Google Scholar 

  34. Kelly, P., Doherty, A.R., Berry, E., Hodges, S.E., Batterham, A.M., Foster, C.: Can we use digital life-log images to investigate active and sedentary travel behaviour? Results from a pilot study. Int. J. Behav. Nutr. Phys. Act. 8, 44 (2011)

    Article  Google Scholar 

  35. Cho, S.-B., Kim, K.-J., Hwang, K.S., Song, I.-J.: AniDiary: Daily cartoon-style diary exploits Bayesian networks. IEEE Pervasive Comput. 6, 66–75 (2007)

    Article  Google Scholar 

  36. Whittaker, S., Tucker, S., Swampillai, K., Laban, R.: Design and evaluation of systems to support interaction capture and retrieval. Pers. Ubiquit. Comput. 12, 197–221 (2008)

    Article  Google Scholar 

  37. Jacques, P.L.S., Conway, M.A., Lowder, M.W., Cabeza, R.: Watching my mind unfold versus yours: An fMRI study using a novel camera technology to examine neural differences in self-projection of self versus other perspectives. J. Cognit. Neurosci. 23, 1275–1284 (2011)

    Article  Google Scholar 

  38. Doherty, A.R., Moulin, C.J.A., Smeaton, A.F.: Automatically assisting human memory: A SenseCam browser. Memory 19, 785–795 (2011)

    Article  Google Scholar 

  39. Vemuri, S., Bender, W.: Next-generation personal memory aids. BT Technol. J. 22, 125–138 (2004)

    Article  Google Scholar 

  40. Berry, E., Hampshire, A., Rowe, J., Hodges, S., Kapur, N., Watson, P., Browne, G., Smyth, G., Wood, K., Owen, A.M.: The neural basis of effective memory therapy in a patient with limbic encephalitis. J. Neurol. Neurosurg. Psych. 80, 1202–1205 (2009)

    Article  Google Scholar 

  41. Lee, M.-W., Khan, A.M., Kim, T.-S.: A single tri-axial accelerometer-based real-time personal life log system capable of human activity recognition and exercise information generation. Pers. Ubiquit. Comput. 15, 887–898 (2011)

    Article  Google Scholar 

  42. Doherty, A.R., Pauly-Takacs, K., Caprani, N., Gurrin, C., Moulin, C.J.A., O’Connor, N.E., Smeaton, A.F.: Experiences of aiding autobiographical memory using the SenseCam. Hum. Comput. Interact. 27, 151–174 (2012)

    Google Scholar 

  43. Hwang, K.-S., Cho, S.-B.: Landmark detection from mobile life log using a modular Bayesian network model. Expert Syst. Appl. 36, 12065–12076 (2009)

    Article  Google Scholar 

  44. Whittaker, S., Kalnikaite, V., Petrelli, D., Sellen, A.J., Villar, N., Bergman, O., Clough, P., Brockmeier, J.: Socio-technical lifelogging: Deriving design principles for a future proof digital past. Hum. Comput. Interact. 27, 37–62 (2012)

    Google Scholar 

  45. Rawassizadeh, R., Tomitsch, M., Wac, K., Tjoa, A.M.: UbiqLog: A generic mobile phone-based life-log framework. Pers. Ubiquit. Comput. 17, 621–637 (2013)

    Article  Google Scholar 

  46. Gurrin, C., Qiu, Z., Hughes, M., Caprani, N., Doherty, A.R., Hodges, S.E., Smeaton, A.F.: The smartphone as a platform for wearable cameras in health research. Am. J. Prev. Med. 44, 308–313 (2013)

    Article  Google Scholar 

  47. Abe, M., Morinishi, Y., Maeda, A., Aoki, M., Inagaki, H.: A life log collector integrated with a remote-controller for enabling user centric services. IEEE Trans. Consum. Electron 55, 295–302 (2009)

    Article  Google Scholar 

  48. Byrne, D., Doherty, A.R., Snoek, C.G.M., Jones, G.J.F., Smeaton, A.F.: Everyday concept detection in visual lifelogs: Validation, relationships and trends. Multimed. Tool. Appl. 49, 119–144 (2010)

    Article  Google Scholar 

  49. Browne, G., Berry, E., Kapur, N., Hodges, S., Smyth, G., Watson, P., Wood, K.: SenseCam improves memory for recent events and quality of life in a patient with memory retrieval difficulties. Memory 19, 713–722 (2011)

    Article  Google Scholar 

  50. Doherty, A.R., Smeaton, A.F.: Automatically augmenting lifelog events using pervasively generated content from millions of people. Sensors 10, 1423–1446 (2010)

    Article  Google Scholar 

  51. Pauly-Takacs, K., Moulin, C.J.A., Estlin, E.J.: SenseCam as a rehabilitation tool in a child with anterograde amnesia. Memory 19, 705–712 (2011)

    Article  Google Scholar 

  52. Kikhia, B., Hallberg, J., Bengtsson, J.E., Savenstedt, S., Synnes, K.: Building digital life stories for memory support. Int. J. Comput. Healthc. 1, 161–176 (2010)

    Article  Google Scholar 

  53. Brindley, R., Bateman, A., Gracey, F.: Exploration of use of SenseCam to support autobiographical memory retrieval within a cognitive-behavioural therapeutic intervention following acquired brain injury. Memory 19, 745–757 (2011)

    Article  Google Scholar 

  54. Ryoo, D.-w., Bae, C.: Design of the wearable gadgets for life-log services based on UTC. IEEE Trans. Consum. Electron 53, 1477–1482 (2007)

    Article  Google Scholar 

  55. Kalnikaite, V., Whittaker, S.: A saunter down memory lane: Digital reflection on personal mementos. Int. J. Hum.-Comput. Stud. 69, 298–310 (2011)

    Article  Google Scholar 

  56. Ogata, H., Misumi, T., Matsuka, T., El-Bishouty, M.M., Yano, Y.: A framework for capturing, sharing and comparing learning experiences in a ubiquitous learning environment. Res. Pract. Technol. Enhanc. Learn. 03, 297–312 (2008)

    Article  Google Scholar 

  57. Wang, P., Smeaton, A.F.: Semantics-based selection of everyday concepts in visual lifelogging. Int. J. Multimedia. Inform. Retrieval 1, 87–101 (2012)

    Article  Google Scholar 

  58. Hodges, S.E., Williams, L., Berry, E., Izadi, S., Srinivasan, J., Butler, A., Smyth, G., Kapur, N., Wood, K.: SenseCam: A retrospective memory aid. In: Hutchison, D., Kanade, T., Kittler, J., Kleinberg, J.M., Mattern, F., Mitchell, J.C., Naor, M., Nierstrasz, O., Pandu Rangan, C., Steffen, B., et al. (eds.) UbiComp 2006: Ubiquitous Computing, 4206, pp. 177–193. Springer, Berlin (2006)

    Chapter  Google Scholar 

  59. Dimoka, A., Banker, R.D., Benbasat, I., Davis, F.D., Dennis, A.R., Gefen, D., Gupta, A., Ischebeck, A., Kenning, P.H., Pavlou, P.A., et al.: On the use of neurophysiological tools in is research: Developing a research agenda for NeuroIS. MIS Q. 36, 679–702 (2012)

    Google Scholar 

  60. Riedl, R., Banker, R.D., Benbasat, I., Davis, F.D., Dennis, A.R., Dimoka, A., Gefen, D., Gupta, A., Ischebeck, A., Kenning, P., et al.: On the foundations of NeuroIS: Reflections on the Gmunden Retreat 2009. Comm. Assoc. Inform. Syst. 27, 243–264 (2010)

    Google Scholar 

  61. Riedl, R., Davis, F.D., Hevner, A.R.: Towards a NeuroIS research methodology: Intensifying the discussion on methods, tools, and measurement. J. Assoc. Inform. Syst. 15, i–xxxv (2014)

    Google Scholar 

  62. Pantelopoulos, A., Bourbakis, N.G.: A survey on wearable sensor-based systems for health monitoring and prognosis. IEEE Trans. Syst. Man Cybern. C Appl. Rev. 40, 1–12 (2010)

    Article  Google Scholar 

  63. Appelboom, G., Camacho, E., Abraham, M.E., Bruce, S.S., Dumont, E.L., Zacharia, B.E., D’Amico, R., Slomian, J., Reginster, J.Y., Bruyère, O., et al.: Smart wearable body sensors for patient self-assessment and monitoring. Arch Public Health 72, 28 (2014)

    Article  Google Scholar 

  64. Healey, J., Picard, R.W.: StartleCam: A cybernetic wearable camera. In: Proceedings of the Second International Symposium on Wearable Computers, pp. 42–49 (1998)

    Google Scholar 

  65. Hori, T., Aizawa, K.: Context-based video retrieval system for the life-log applications. In: Sebe, N., Lew, M.S., Djeraba, C. (eds.) Proceedings of the 5th ACM SIGMM International Workshop on Multimedia Information Retrieval, pp. 31–38. ACM (2003)

    Google Scholar 

  66. Matthews, R., McDonald, N.J., Hervieux, P., Turner, P.J., Steindorf, M.A.: A wearable physiological sensor suite for unobtrusive monitoring of physiological and cognitive state. In: Proceedings of 29th Annual IEEE International Conference of the Engineering in Medicine and Biology Society, pp. 5276–5281. IEEE (2007)

    Google Scholar 

  67. Healey, J.A., Picard, R.W.: Detecting stress during real-world driving tasks using physiological sensors. IEEE Trans. Intell. Transport. Syst. 6, 156–166 (2005)

    Article  Google Scholar 

  68. McDuff, D., Karlson, A., Kapoor, A., Roseway, A., Czerwinski, M.: AffectAura: An intelligent system for emotional memory. In: Konstan, J.A., Chi, E.H., Höök, K. (eds.) Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems, pp. 849–858 (2012)

    Google Scholar 

  69. Schaaff, K., Degen, R., Adler, N., Adam, M.T.P.: Measuring affect using a standard mouse device. Biomed. Eng./Biomedizinische Technik 57, 761–764 (2012)

    Google Scholar 

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Author information

Authors and Affiliations

  1. University of Applied Sciences Upper Austria, Steyr, Austria

    Thomas Fischer

  2. University of Appl. Sc. Upper Austria, Steyr, Oberösterreich, Austria

    René Riedl

  3. University of Linz, Linz, Austria

    René Riedl

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  1. Thomas Fischer
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  2. René Riedl
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Correspondence to Thomas Fischer .

Editor information

Editors and Affiliations

  1. Informaton Systems, Texas Tech University, Lubbock, Texas, USA

    Fred D. Davis

  2. University of Appl. Sc. Upper Austria, Steyr, Oberösterreich, Austria

    René Riedl

  3. Department of Information Systems, University of Liechtenstein, Vaduz, Liechtenstein

    Jan vom Brocke

  4. Department of Information Technology, HEC Montréal , Montréal, Québec, Canada

    Pierre-Majorique Léger

  5. Department of Information Systems, Kennesaw State University, Kennesaw, Georgia, USA

    Adriane B. Randolph

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Fischer, T., Riedl, R. (2017). Lifelogging as a Viable Data Source for NeuroIS Researchers: A Review of Neurophysiological Data Types Collected in the Lifelogging Literature. In: Davis, F., Riedl, R., vom Brocke, J., Léger, PM., Randolph, A. (eds) Information Systems and Neuroscience. Lecture Notes in Information Systems and Organisation, vol 16. Springer, Cham. https://doi.org/10.1007/978-3-319-41402-7_21

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