physiological signals and patients' information behavior

Physiological signals & patients’ information

behavior

Zhaopeng XingMaster of Professional Science

CandidateNOV 30, 2016

Health Informatics Seminar Final Presentation

Sensor-Based Data Collection for Personal, Clinical, and Public Health (Robert Furberg)

The validity and reliability of consumers’ activity trackers

Physiological signal detection and processing Integration of heterogeneous data

Heart Rate Electrodermal activity (EDA)

Queries formulating, relevance assessment Participant’s self-report and researcher’s

observation

Information searching behavior

Psychological signals?

Affective, cognitive and psychological perspectives

• Can eyes reveal interest? Implicit queries from gaze patterns (Ajanki, A., 2009)

• Affective Signals as Implicit Indicators of Information Relevancy and Information Processing Strategies (Gonzalez-Ibañez, R. I., 2015)

Can eyes reveal interest? Implicit queries from gaze patterns (Ajanki, A., 2009)• Using eye movement to formulate queries and predict

the relevance of content

Results: Eye movements provide a useful implicit feedback channel of content relevance

• One’s eye movement pattern is consistent when seeing relevant content in a certain domain

Affective Signals as Implicit Indicators of Information Relevancy and Information Processing Strategies (Gonzalez-Ibañez, R. I., 2015)Use feelings, facial expressions, and electrodermal activity (EDA) to determine the influence of affective states on : • Searchers process information• Relevance judgments• Completion of search tasks

Results: Smiles and EDA can be implicit indicators of progress and completion of search tasks

Implication: Medical search engine

Hospital information websitePatient education system Digital health application

……

Thanks

Reference Ajanki, A., Hardoon, D. R., Kaski, S., Puolamäki, K., & Shawe-Taylor,

J. (2009). Can eyes reveal interest? Implicit queries from gaze patterns. User Modeling and User-Adapted Interaction, 19(4), 307-339.

Cline, R. J., & Haynes, K. M. (2001). Consumer health information seeking on the Internet: the state of the art. Health education research, 16(6), 671-692.

Gonzalez-Ibañez, R. I., & Shah, C. (2015). Affective Signals as Implicit Indicators of Information Relevancy and Information Processing Strategies. iConference 2015 Proceedings.

McMullan, M. (2006). Patients using the Internet to obtain health information: how this affects the patient–health professional

relationship. Patient education and counseling, 63(1), 24-28.

O'Brien, H. L., Gwizdka, J., Lopatovska, I., & Mostafa, J. (2015). Psycho- physiological Methods in Information Science: Fit or Fad?. iConference 2015 Proceedings.

Reference (Cont.)

Further reading Hardoon, D.R., Ajanki, A., Puolamaki, K., Shawe-Taylor, J., Kaski, S.: Information retrieval

by inferring implicit queries from eye retrieval by inferring implicit queries from eyemovements. In: 11th Intelligence and Statistics. San Juan. Electronic proceedings at http://www.stat.umn.edu/~aistat/proceedings/start.htm (2007)

Howard, D.L., Crosby, M.E.: Snapshots from the eye: towards strategies for viewing biblographic citations. In: Savendy, G., Smith, M.J. (eds.) Human-Computer Interaction: Software and Hardware Interfaces, pp. 488–493. Elsevier, Amsterdam (1993)

Ghaddar, S. F., Valerio, M. A., Garcia, C. M., & Hansen, L. (2012). Adolescent health literacy: the importance of credible sources for online health information. Journal of school health, 82(1), 28-36.

Metzger, M. J. (2007). Making sense of credibility on the Web: Models for evaluatingonline information and recommendations for future research. Journal of the

American Society for Information Science and Technology, 58(13), 2078-2091.

Miller, L. M. S., & Bell, R. A. (2012). Online Health Information Seeking The Influence of Age, Information Trustworthiness, and Search Challenges. Journal of aging and health, 24(3), 525-541.

Salojärvi, J., Puolamäki, K., Simola, J., Kovanen, L., Kojo, I. Kaski, S.: Inferring relevance from eye movements: feature extraction. Technical Report A82, Helsinki University of Technology, Publications in Computer and Information Science. http://www.cis.hut.fi/eyechallenge2005/ (2005b)

Further reading (Cont.)