Sleep Monitoring Tools at Home and in the Hospital: Bridging Quantified Self and Clinical Sleep Research

by | Aug 3, 2015 | Research Publications

Author(s):

  • Vandenberghe, Bert
  • Geerts, David

Abstract:

The quantified self movement suggests solutions for diverse long-term measurements, including sleep monitoring. However, those solutions do not seem to meet the challenges facing clinical sleep research. Where efforts in the past to describe design frameworks for sleep monitoring tools focused on the sleeper as user, we start from the sleep clinician to find out how sleep monitoring tools can be meaningful in clinical settings. Based on observations in hospital-based sleep centers performing traditional and ambulatory sleep studies, we describe current practices and look at the effect when measurements leave the hospital. We summarize design recommendations for sleep monitoring tools, suitable in and outside the hospital, from the sleep clinician’s perspective. Furthermore, we discuss a future for sleep research where quantified self tools and approaches expand clinical sleep research. This would allow hospital-based sleep centers to deploy current practices in a targeted, meaningful, and accountable way.

Documentation:

https://doi.org/10.4108/icst.pervasivehealth.2015.259267

References:

[1]  American Academy of Sleep Medicine. International classification of sleep disorders, revised: Diagnostic and coding manual. American Academy of Sleep Medicine, 2001.

[2]  Aliakseyeu, D., Du, J., Zwartkruis-Pelgrim, E., and Subramanian, S. Exploring Interaction Strategies in the Context of Sleep. Proceedings of the 13th IFIP TC 13 International Conference on Human-computer Interaction – Volume Part III, Springer-Verlag (2011), 19–36.

[3]  Bardram, J.E., Frost, M., Szántó, K., and Marcu, G. The MONARCA self-assessment system: a persuasive personal monitoring system for bipolar patients. Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium, ACM (2012), 21-30.

[4]  Bauer,J.S.,Consolvo,S.,Greenstein,B.,etal.ShutEye: Encouraging Awareness of Healthy Sleep Recommendations with a Mobile, Peripheral Display. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, ACM (2012), 1401– 1410.

[5]  Beyer,H.andHoltzblatt,K.ContextualDesign: Defining Customer- centered Systems. Morgan Kaufmann, 1998.

[6]  Biggs,J.RunningOnEmpty:WakeMateFindsOut What Happens When Partners Break Up. TechCrunch. http://techcrunch.com/2012/06/28/running-on-empty- wakemate-finds- out-what-happens-when-partners- break-up/.

[7]  Choe,E.K.,Consolvo,S.,Watson,N.F.,andKientz, J.A. Opportunities for Computing Technologies to Support Healthy Sleep Behaviors.

[8] Choe,E.K.DesignofPersuasiveTechnologiesfor Healthy Sleep Behavior. Proceedings of the 13th International Conference on Ubiquitous Computing, ACM (2011), 507–510.

[9] Dolen,B.Exclusive:sleepcoachcompanyZeois shutting down. MobiHealthNews. http://mobihealthnews.com/20772/exclusive-sleep- coach-company-zeo-is-shutting-down/.

[10] Gartenberg,D.,Thornton,R.,Masood,M.,Pfannenstiel, D., Taylor, D., and Parasuraman, R. Collecting Health- related Data on the Smart Phone: Mental Models, Cost of Collection, and Perceived Benefit of Feedback. Personal Ubiquitous Comput. 17, 3 (2013), 561–570.

[11] Han, J., Chong, J.Y., and Kim, S. SNORES: Towards a Less-intrusive Home Sleep Monitoring System Using Wireless Sensor Networks. Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems, ACM (2009), 339–340.

[12] Kelly, J.M., Strecker, R.E., and Bianchi, M.T. Recent Developments in Home Sleep-Monitoring Devices. International Scholarly Research Notices 2012, (2012).

[13] Koreshoff, T.L., Robertson, T., and Leong, T.W. Internet of Things: A Review of Literature and Products. Proceedings of the 25th Australian Computer-Human Interaction Conference: Augmentation, Application, Innovation, Collaboration, ACM (2013), 335–344.

[14] Kushida, C.A., Chang, A., Gadkary, C., Guilleminault, C., Carrillo, O., and Dement, W.C. Comparison of actigraphic, polysomnographic, and subjective assessment of sleep parameters in sleep-disordered patients. Sleep Medicine 2, 5 (2001), 389–396.

[15] Lawson, S., Jamison-Powell, S., Garbett, A., et al. Validating a Mobile Phone Application for the Everyday, Unobtrusive, Objective Measurement of Sleep. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, ACM (2013), 2497–2506.

[16] Li, I., Dey, A.K., and Forlizzi, J. Understanding My Data, Myself: Supporting Self-reflection with Ubicomp Technologies. Proceedings of the 13th International Conference on Ubiquitous Computing, ACM (2011), 405–414.

[17] Paalasmaa, J., Waris, M., Toivonen, H., Leppakorpi, L., and Partinen, M. Unobtrusive online monitoring of sleep at home. 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), (2012), 3784–3788.

[18] Pirzadeh, A., He, L., and Stolterman, E. Personal Informatics and Reflection: A Critical Examination of the Nature of Reflection. CHI ’13 Extended Abstracts on Human Factors in Computing Systems, ACM (2013), 1979–1988.

[19] Rivas-Echeverría, C., Acosta, E., Rivas-Echeverría, F., Molina, L., González, S., and Sánchez, R. Features and Applications of an Information System Developed for a Sleep Clinic. Proceedings of the 9th WSEAS International Conference on Computational Intelligence, Man-machine Systems and Cybernetics, World Scientific and Engineering Academy and Society (WSEAS) (2010), 209–215.

[20] Shambroom, J.R., Fábregas, S.E., and Johnstone, J. Validation of an automated wireless system to monitor sleep in healthy adults. Journal of Sleep Research 21, 2 (2012), 221–230.

[21] Verbraecken, J., Raymann, R., and Eijsvogel, M. Ambulante P(S)G. In Leerboek slaap en slaapstoornissen. Acco, 2013, 167-172.

[22] Wright,A.Patient,HealThyself.Commun.ACM56,8(2013),16–18.

[23] Chen,Y.,Tang,C.,Cheng,K.,andPark,S.Y.Bridgingclinicalandnon- clinical health practices: opportunities and challenges. CHI ’12 Extended Abstracts on Human Factors in Computing Systems, ACM (2012), 2723-2726.

[24] Zhang, J., Zhang, Q., Wang, Y., and Qiu, C. A Real- time Auto- adjustable Smart Pillow System for Sleep Apnea Detection and Treatment. Proceedings of the 12th International Conference on Information Processing in Sensor Networks, ACM (2013), 179–190.

[25] Zhao, W., Wang, X., and Wang, Y. Automated Sleep Quality Measurement Using EEG Signal: First Step Towards a Domain Specific Music Recommendation System. Proceedings of the International Conference on Multimedia, ACM (2010), 1079–10.

Sleep Monitoring Tools at Home and in the Hospital: Bridging Quantified Self and Clinical Sleep Research

by | Aug 3, 2015 | Research Publications

Author(s):

  • Vandenberghe, Bert
  • Geerts, David

Abstract:

The quantified self movement suggests solutions for diverse long-term measurements, including sleep monitoring. However, those solutions do not seem to meet the challenges facing clinical sleep research. Where efforts in the past to describe design frameworks for sleep monitoring tools focused on the sleeper as user, we start from the sleep clinician to find out how sleep monitoring tools can be meaningful in clinical settings. Based on observations in hospital-based sleep centers performing traditional and ambulatory sleep studies, we describe current practices and look at the effect when measurements leave the hospital. We summarize design recommendations for sleep monitoring tools, suitable in and outside the hospital, from the sleep clinician’s perspective. Furthermore, we discuss a future for sleep research where quantified self tools and approaches expand clinical sleep research. This would allow hospital-based sleep centers to deploy current practices in a targeted, meaningful, and accountable way.

Document:

http://dx.doi.org/10.4108/icst.pervasivehealth.2015.259267

References:

[1]American Academy of Sleep Medicine. International classification of sleep disorders, revised: Diagnostic and coding manual. American Academy of Sleep Medicine, 2001. [2]Aliakseyeu, D., Du, J., Zwartkruis-Pelgrim, E., and Subramanian, S. Exploring Interaction Strategies in the Context of Sleep. Proceedings of the 13th IFIP TC 13 International Conference on Human-computer Interaction -Volume Part III, Springer-Verlag (2011), 19–36. [3]Bardram, J.E., Frost, M., Szántó, K., and Marcu, G. The MONARCA self-assessment system: a persuasive personal monitoring system for bipolar patients. Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium, ACM (2012), 21-30.[4]Bauer,J.S.,Consolvo,S.,Greenstein,B.,etal.ShutEye: Encouraging Awareness of Healthy Sleep Recommendations with a Mobile, Peripheral Display. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, ACM (2012), 1401–1410.[5]Beyer,H.andHoltzblatt,K.ContextualDesign: Defining Customer-centered Systems. Morgan Kaufmann, 1998. [6]Biggs,J.RunningOnEmpty:WakeMateFindsOutWhat Happens When Partners Break Up. TechCrunch. http://techcrunch.com/2012/06/28/running-on-empty-wakemate-finds-out-what-happens-when-partners-break-up/. [7]Choe,E.K.,Consolvo,S.,Watson,N.F.,andKientz, J.A. Opportunities for Computing Technologies to Support Healthy Sleep Behaviors. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, ACM (2011), 3053–3062. [8]Choe,E.K.DesignofPersuasiveTechnologiesfor Healthy Sleep Behavior. Proceedings of the 13th International Conference on Ubiquitous Computing, ACM (2011), 507–510. [9]Dolen,B.Exclusive:sleepcoachcompanyZeois shutting down. MobiHealthNews. http://mobihealthnews.com/20772/exclusive-sleep-coach-company-zeo-is-shutting-down/. [10]Gartenberg,D.,Thornton,R.,Masood,M.,Pfannenstiel, D., Taylor, D., and Parasuraman, R. Collecting Health-related Data on the Smart Phone: Mental Models, Cost of Collection, and Perceived Benefit of Feedback. Personal Ubiquitous Comput. 17, 3 (2013), 561–570. [11]Han, J., Chong, J.Y., and Kim, S. SNORES: Towards a Less-intrusive Home Sleep Monitoring System Using Wireless Sensor Networks. Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems, ACM (2009), 339–340.[12]Kelly, J.M., Strecker, R.E., and Bianchi, M.T. Recent Developments in Home Sleep-Monitoring Devices. International Scholarly Research Notices 2012, (2012).[13]Koreshoff, T.L., Robertson, T., and Leong, T.W. Internet of Things: A Review of Literature and Products. Proceedings of the 25th Australian Computer-Human Interaction Conference: Augmentation, Application, Innovation, Collaboration, ACM (2013), 335–344.[14]Kushida, C.A., Chang, A., Gadkary, C., Guilleminault, C., Carrillo, O., and Dement, W.C. Comparison of actigraphic, polysomnographic, and subjective assessment of sleep parameters in sleep-disordered patients. Sleep Medicine 2, 5 (2001), 389–396.[15]Lawson, S., Jamison-Powell, S., Garbett, A., et al. Validating a Mobile Phone Application for the Everyday, Unobtrusive, Objective Measurement of Sleep. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, ACM (2013), 2497–2506.[16]Li, I., Dey, A.K., and Forlizzi, J. Understanding My Data, Myself: Supporting Self-reflection with Ubicomp Technologies. Proceedings of the 13th International Conference on Ubiquitous Computing, ACM (2011), 405–414.[17]Paalasmaa, J., Waris, M., Toivonen, H., Leppakorpi, L., and Partinen, M. Unobtrusive online monitoring of sleep at home. 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), (2012), 3784–3788.[18]Pirzadeh, A., He, L., and Stolterman, E. Personal Informatics and Reflection: A Critical Examination of the Nature of Reflection. CHI ’13 Extended Abstracts on Human Factors in Computing Systems, ACM (2013), 1979–1988.[19]Rivas-Echeverría, C., Acosta, E., Rivas-Echeverría, F., Molina, L., González, S., and Sánchez, R. Features and Applications of an Information System Developed for a Sleep Clinic. Proceedings of the 9th WSEAS International Conference on Computational Intelligence, Man-machine Systems and Cybernetics, World Scientific and Engineering Academy and Society (WSEAS) (2010), 209–215.[20]Shambroom, J.R., Fábregas, S.E., and Johnstone, J. Validation of an automated wireless system to monitor sleep in healthy adults. Journal of Sleep Research 21, 2 (2012), 221–230.[21]Verbraecken, J., Raymann, R., and Eijsvogel, M. Ambulante P(S)G. In Leerboek slaap en slaapstoornissen. Acco, 2013, 167-172.[22]Wright, A. Patient, Heal Thyself. Commun. ACM 56, 8 (2013), 16–18.[23]Chen, Y., Tang, C., Cheng, K., and Park, S.Y. Bridging clinical and non-clinical health practices: opportunities and challenges. CHI ’12 Extended Abstracts on Human Factors in Computing Systems, ACM (2012), 2723-2726.[24]Zhang, J., Zhang, Q., Wang, Y., and Qiu, C. A Real-time Auto-adjustable Smart Pillow System for Sleep Apnea Detection and Treatment. Proceedings of the 12th International Conference on Information Processing in Sensor Networks, ACM (2013), 179–190.[25]Zhao, W., Wang, X., and Wang, Y. Automated Sleep Quality Measurement Using EEG Signal: First Step Towards a Domain Specific Music Recommendation System. Proceedings of the International Conference on Multimedia, ACM (2010), 1079–10.