research-article

Prompto: Investigating Receptivity to Prompts Based on Cognitive Load from Memory Training Conversational Agent

Authors:

Samantha W. T. Chan,

Shardul Sapkota,

Rebecca Mathews,

Suranga NanayakkaraAuthors Info & Claims

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Volume 4, Issue 4

Article No.: 121, Pages 1 - 23

https://doi.org/10.1145/3432190

Published: 18 December 2020 Publication History

Abstract

Prospective memory lapses, which involve forgetting to perform intended actions, affect independent living in older adults. Although memory training using smartphone applications could address them, users are sometimes unaware of available times for training or forget about it, presenting a need for proactive prompts. Existing applications mostly provide time-based prompts and prompts based on users' cognitive contexts remain an under-explored area. We developed Prompto, a conversational memory coach that detects physiological signals to suggest training sessions when users are relaxed and potentially more receptive. Our study with 21 older adults showed that users were more receptive to prompts and memory training under low cognitive load than under high cognitive load. Interviews and an in-the-wild deployment of Prompto indicated that majority of users appreciated the concept, found it helpful and were likely to respond to its prompts. We contribute towards developing technologies with cognitive context-aware prompting based on users' physiological readings.

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References

[1]

Christoph Anderson, Isabel Hübener, Ann-Kathrin Seipp, Sandra Ohly, Klaus David, and Veljko Pejovic. 2018. A Survey of Attention Management Systems in Ubiquitous Computing Environments. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 2, 2, Article 58 (July 2018), 27 pages. https://doi.org/10.1145/3214261

Digital Library

[2]

Seyed Ali Bahrainian and Fabio Crestani. 2017. Towards the Next Generation of Personal Assistants: Systems That Know When You Forget. In Proceedings of the ACM SIGIR International Conference on Theory of Information Retrieval (Amsterdam, The Netherlands) (ICTIR '17). Association for Computing Machinery, New York, NY, USA, 169--176. https://doi.org/10.1145/3121050.3121071

Digital Library

[3]

Marta Barontini, Julio O. Lázzari, Gloria Levin, Inés Armando, and Susana J. Basso. 1997. Age-related changes in sympathetic activity: biochemical measurements and target organ responses. Archives of Gerontology and Geriatrics 25, 2 (1997), 175--186. https: //doi.org/10.1016/S0167-4943(97)00008-3

[4]

Mathias Benedek and Christian Kaernbach. 2010. A continuous measure of phasic electrodermal activity. Journal of Neuroscience Methods 190, 1 (2010), 80--91. https://doi.org/10.1016/j.jneumeth.2010.04.028

[5]

J. H. M. Bergmann and A. H. McGregor. 2011. Body-worn sensor design: what do patients and clinicians want? Annals of Biomedical Engineering 39, 9 (2011), 2299--2312. https://doi.org/10.1007/s10439-011-0339-9

[6]

Timothy W. Bickmore, Lisa Caruso, Kerri Clough-Gorr, and Tim Heeren. 2005. "It's just like you talk to a friend" relational agents for older adults. Interacting with Computers 17, 6 (2005), 711--735. https://doi.org/10.1016/j.intcom.2005.09.002

Digital Library

[7]

Virginia Braun, Victoria Clarke, Nikki Hayfeld, and Gareth Terry. 2018. Thematic Analysis. Springer Singapore, Singapore, 1--18. https://doi.org/10.1007/978-981-10-2779-6_103-1

[8]

R. N. Brewer, M. R. Morris, and S. E. Lindley. 2017. How to Remember What to Remember: Exploring Possibilities for Digital Reminder Systems. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 1, 3, Article 38 (Sept. 2017), 20 pages. https://doi.org/10.1145/3130903

Digital Library

[9]

Sarah Susanne Brom and Matthias Kliegel. 2014. Improving everyday prospective memory performance in older adults: Comparing cognitive process and strategy training. Psychology and Aging 29, 3 (2014), 744--755. https://doi.org/10.1037/a0037181

[10]

Christina Burkard, Lucien Rochat, Anaëlle Blum, Joëlle Emmenegger, Anne-Claude Juillerat Van der Linden, and Martial Van der Linden. 2014. A daily-life-oriented intervention to improve prospective memory and goal-directed behaviour in ageing: A pilot study. Neuropsychological Rehabilitation 24, 2 (2014), 266--295. https://doi.org/10.1080/09602011.2014.887023

[11]

A. J. M. M. Camm, Marek Malik, J. T. G. B. Bigger, Günter Breithardt, Sergio Cerutti, R. Cohen, Philippe Coumel, E. Fallen, H. Kennedy, R. E. Kleiger, et al. 1996. Heart rate variability. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. Circulation 93, 5 (1996), 1043--1065. https://doi.org/10.1161/01.CIR.93.5.1043

[12]

Cameron Camp, Michael Bird, Catherine Cherry, et al. 2000. Retrieval strategies as a rehabilitation aid for cognitive loss in pathological ageing. In Cognitive rehabilitation in old age. Oxford University Press. http://hdl.handle.net/1885/89084

[13]

Joana Campos and Ana Paiva. 2010. May: My memories are yours. In International Conference on Intelligent Virtual Agents. Springer, 406--412. https://doi.org/10.1007/978-3-642-15892-6_44

[14]

Samantha W. T. Chan. 2020. Biosignal-Sensitive Memory Improvement and Support Systems. In Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems (Honolulu, HI, USA) (CHI EA '20). Association for Computing Machinery, New York, NY, USA, 1--7. https://doi.org/10.1145/3334480.3375031

[15]

Samantha W. T. Chan, Thisum Buddhika, Haimo Zhang, and Suranga Nanayakkara. 2019. ProspecFit: In Situ Evaluation of Digital Prospective Memory Training for Older Adults. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 3, 3, Article 77 (Sept. 2019), 20 pages. https://doi.org/10.1145/3351235

Digital Library

[16]

Samantha W. T. Chan, Haimo Zhang, and Suranga Nanayakkara. 2019. Prospero: A Personal Wearable Memory Coach. In Proceedings of the 10th Augmented Human International Conference 2019 (Reims, France) (AH2019). Association for Computing Machinery, New York, NY, USA, Article 26, 5 pages. https://doi.org/10.1145/3311823.3311870

Digital Library

[17]

Fang Chen, Jianlong Zhou, Yang Wang, Kun Yu, Syed Z. Arshad, Ahmad Khawaji, and Dan Conway. 2016. Stress and Cognitive Load. Springer International Publishing, Cham, 185--194. https://doi.org/10.1007/978-3-319-31700-7_12

[18]

Xing-jie Chen, Ya Wang, Lu-lu Liu, Ji-fang Cui, Ming-yuan Gan, David HK Shum, and Raymond C. K. Chan. 2015. The efect of implementation intention on prospective memory: a systematic and meta-analytic review. Psychiatry research 226, 1 (2015), 14--22. https://doi.org/10.1016/j.psychres.2015.01.011

[19]

Woohyeok Choi, Sangkeun Park, Duyeon Kim, Youn-kyung Lim, and Uichin Lee. 2019. Multi-Stage Receptivity Model for Mobile Just-In-Time Health Intervention. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 3, 2, Article 39 (June 2019), 26 pages. https://doi.org/10.1145/3328910

Digital Library

[20]

Minsoo Choy, Daehoon Kim, Jae-Gil Lee, Heeyoung Kim, and Hiroshi Motoda. 2016. Looking Back on the Current Day: Interruptibility Prediction Using Daily Behavioral Features. In Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing (Heidelberg, Germany) (UbiComp '16). Association for Computing Machinery, New York, NY, USA, 1004--1015. https://doi.org/10.1145/2971648.2971649

Digital Library

[21]

Sarah Clinch and Cecilia Mascolo. 2018. Learning from Our Mistakes: Identifying Opportunities for Technology Intervention against Everyday Cognitive Failure. IEEE Pervasive Computing 17, 2 (2018), 22--33. https://doi.org/10.1109/MPRV.2018.022511240

[22]

Posit Science Corporation. 2002. BrainHQ. Retrieved 2019-07-03 from https://www.brainhq.com/

[23]

Tilman Dingler, Dominik Weber, Martin Pielot, Jennifer Cooper, Chung-Cheng Chang, and Niels Henze. 2017. Language Learning On-the-Go: Opportune Moments and Design of Mobile Microlearning Sessions. In Proceedings of the 19th International Conference on Human-Computer Interaction with Mobile Devices and Services (Vienna, Austria) (MobileHCI '17). Association for Computing Machinery, New York, NY, USA, Article 28, 12 pages. https://doi.org/10.1145/3098279.3098565

Digital Library

[24]

Sidney D'Mello. 2014. Emotional rollercoasters: day differences in affect incidence during learning. In The Twenty-Seventh International Flairs Conference. https://www.aaai.org/ocs/index.php/FLAIRS/FLAIRS14/paper/view/7777

[25]

Sidney D'Mello and Art Graesser. 2013. AutoTutor and Affective Autotutor: Learning by Talking with Cognitively and Emotionally Intelligent Computers That Talk Back. ACM Trans. Interact. Intell. Syst. 2, 4, Article 23 (Jan. 2013), 39 pages. https://doi.org/10.1145/2395123.2395128

[26]

Damien Elmes. 2015. Anki. Retrieved 2019-07-24 from http://ankisrs.net

[27]

Michael W. Eysenck. 2012. Fundamentals of Cognition. Psychology Press. https://books.google.com/books?id=CVeacQAACAAJ

[28]

Joel E. Fischer, Nick Yee, Victoria Bellotti, Nathan Good, Steve Benford, and Chris Greenhalgh. 2010. Effects of Content and Time of Delivery on Receptivity to Mobile Interruptions. In Proceedings of the 12th International Conference on Human Computer Interaction with Mobile Devices and Services (Lisbon, Portugal) (MobileHCI '10). Association for Computing Machinery, New York, NY, USA, 103--112. https://doi.org/10.1145/1851600.1851620

Digital Library

[29]

Pascal E. Fortin, Elisabeth Sulmont, and Jeremy Cooperstock. 2019. Detecting Perception of Smartphone Notifications Using Skin Conductance Responses. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (Glasgow, Scotland Uk) (CHI '19). Association for Computing Machinery, New York, NY, USA, 1--9. https://doi.org/10.1145/3290605.3300420

Digital Library

[30]

Lex Fridman, Bryan Reimer, Bruce Mehler, and William T. Freeman. 2018. Cognitive Load Estimation in the Wild. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (Montreal QC, Canada) (CHI '18). Association for Computing Machinery, New York, NY, USA, 1--9. https://doi.org/10.1145/3173574.3174226

[31]

Nicola J. Gates, Perminder S. Sachdev, Maria A. Fiatarone Singh, and Michael Valenzuela. 2011. Cognitive and memory training in adults at risk of dementia: a systematic review. BMC geriatrics 11, 1 (2011), 55. https://doi.org/10.1186/1471-2318-11-55

[32]

Tony Gillie and Donald Broadbent. 1989. What makes interruptions disruptive? A study of length, similarity, and complexity. Psychological research 50, 4 (1989), 243--250. https://doi.org/10.1007/BF00309260

[33]

Peter M. Gollwitzer. 1993. Goal achievement: The role of intentions. European review of social psychology 4, 1 (1993), 141--185. https://doi.org/10.1080/14792779343000059

[34]

Peter M. Gollwitzer. 1999. Implementation intentions: strong effects of simple plans. American psychologist 54, 7 (1999), 493. https://doi.org/10.1037/0003-066X.54.7.493

[35]

Peter M. Gollwitzer and Paschal Sheeran. 2006. Implementation intentions and goal achievement: A meta-analysis of effects and processes. Advances in experimental social psychology 38 (2006), 69--119. https://doi.org/10.1016/S0065-2601(06)38002-1

[36]

Eija Haapalainen, SeungJun Kim, Jodi F. Forlizzi, and Anind K. Dey. 2010. Psycho-Physiological Measures for Assessing Cognitive Load. In Proceedings of the 12th ACM International Conference on Ubiquitous Computing (Copenhagen, Denmark) (UbiComp '10). Association for Computing Machinery, New York, NY, USA, 301--310. https://doi.org/10.1145/1864349.1864395

[37]

Joshua Harman. 2001. Creating a Memory Palace Using a Computer. In CHI '01 Extended Abstracts on Human Factors in Computing Systems (Seattle, Washington) (CHI EA '01). Association for Computing Machinery, New York, NY, USA, 407--408. https://doi.org/10.1145/634067.634306

Digital Library

[38]

Sandra G. Hart. 2006. NASA-task load index (NASA-TLX); 20 years later. In Proceedings of the Human Factors and Ergonomics Society Annual Meeting, Vol. 50. Sage publications Sage CA: Los Angeles, CA, 904--908. https://doi.org/10.1177/154193120605000909

[39]

Jennifer A. Healey and Rosalind W. Picard. 2005. Detecting stress during real-world driving tasks using physiological sensors. IEEE Transactions on Intelligent Transportation Systems 6, 2 (2005), 156--166. https://doi.org/10.1109/TITS.2005.848368

Digital Library

[40]

Alexandra Hering, Matthias Kliegel, Peter G. Rendell, Fergus I. M. Craik, and Nathan S. Rose. 2018. Prospective memory is a key predictor of functional independence in older adults. Journal of the International Neuropsychological Society 24, 6 (2018), 640--645. https://doi.org/10.1017/S1355617718000152

[41]

Alexandra Hering, Peter G. Rendell, Nathan S. Rose, Katharina M. Schnitzspahn, and Matthias Kliegel. 2014. Prospective memory training in older adults and its relevance for successful aging. Psychological Research 78, 6 (2014), 892--904. https://doi.org/10.1007/s00426-014-0566-4

[42]

Linda Hirsch, Anton Björsell, Mikael Laaksoharju, and Mohammad Obaid. 2017. Investigating Design Implications Towards a Social Robot as a Memory Trainer. In Proceedings of the 5th International Conference on Human Agent Interaction (Bielefeld, Germany) (HAI '17). Association for Computing Machinery, New York, NY, USA, 5--10. https://doi.org/10.1145/3125739.3125755

Digital Library

[43]

Nis Hjortskov, Dag Rissén, Anne Katrine Blangsted, Nils Fallentin, Ulf Lundberg, and Karen Søgaard. 2004. The efect of mental stress on heart rate variability and blood pressure during computer work. European Journal of Applied Physiology 92, 1-2 (2004), 84--89. https://doi.org/10.1007/s00421-004-1055-z

[44]

Joyce Ho and Stephen S. Intille. 2005. Using Context-Aware Computing to Reduce the Perceived Burden of Interruptions from Mobile Devices. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Portland, Oregon, USA) (CHI '05). Association for Computing Machinery, New York, NY, USA, 909--918. https://doi.org/10.1145/1054972.1055100

[45]

Paul Hoskinson. 2008. Brain Workshop. Retrieved 2019-08-24 from http://brainworkshop.sourceforge.net/

[46]

Apple Inc. 2011. Siri. Retrieved 2019-07-03 from https://www.apple.com/siri/

[47]

Amazon.com Inc. 2014. Alexa. Retrieved 2019-08-29 from https://www.amazon.com/b?node=17934671011

[48]

Empatica Inc. 2013. E4 Wristband. Retrieved 2019-08-09 from https://www.empatica.com/research/e4/

[49]

Empatica Inc. 2020. E4 data -IBI expected signal. Retrieved 2020-08-12 from https://support.empatica.com/hc/en-us/articles/ 360030058011-E4-data-IBI-expected-signal

[50]

Empatica Inc. 2020. What should I know to use EDA data in my experiment? Retrieved 2020-08-12 from https://support.empatica. com/hc/en-us/articles/203621955

[51]

Fitbit Inc. 2007. Fitbit. Retrieved 2019-08-29 from https://www.ftbit.com

[52]

Shamsi T. Iqbal and Eric Horvitz. 2010. Notifcations and Awareness: A Field Study of Alert Usage and Preferences. In Proceedings of the 2010 ACM Conference on Computer Supported Cooperative Work (Savannah, Georgia, USA) (CSCW '10). Association for Computing Machinery, New York, NY, USA, 27--30. https://doi.org/10.1145/1718918.1718926

[53]

John G. Kreifeldt and Mary E. McCarthy. 1981. Interruption as a test of the user-computer interface. (1981). https://ntrs.nasa.gov/ citations/19820005848

[54]

Kubios. 2020. About HRV -Kubios HRV. Retrieved 2020-08-12 from https://www.kubios.com/about-hrv/

[55]

Lumos Labs. 2007. Lumosity. Retrieved 2019-07-03 from https://www.lumosity.com/

[56]

Peng Liao, Walter Dempsey, Hillol Sarker, Syed Monowar Hossain, Mustafa al'Absi, Predrag Klasnja, and Susan Murphy. 2018. Just-in-Time but Not Too Much: Determining Treatment Timing in Mobile Health. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 2, 4, Article 179 (Dec. 2018), 21 pages. https://doi.org/10.1145/3287057

Digital Library

[57]

Han Lin, Jinghua Hou, Han Yu, Zhiqi Shen, and Chunyan Miao. 2015. An Agent-Based Game Platform for Exercising People's Prospective Memory. In 2015 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT), Vol. 3. 235--236. https://doi.org/10.1109/WI-IAT.2015.42

[58]

Google LLC. 2010. Dialogflow. Retrieved 2019-08-09 from https://dialogfow.com/

[59]

Google LLC. 2016. Google Assistant. Retrieved 2019-07-03 from https://assistant.google.com/

[60]

Tom Lovett, Eamonn O'Neill, James Irwin, and David Pollington. 2010. The Calendar as a Sensor: Analysis and Improvement Using Data Fusion with Social Networks and Location. In Proceedings of the 12th ACM International Conference on Ubiquitous Computing (Copenhagen, Denmark) (UbiComp '10). Association for Computing Machinery, New York, NY, USA, 3--12. https://doi.org/10.1145/ 1864349.1864352

Digital Library

[61]

CogniFit Ltd. 1999. CogniFit. Retrieved 2019-07-04 from https://www.cognift.com/

[62]

Akhil Mathur, Nicholas D. Lane, and Fahim Kawsar. 2016. Engagement-Aware Computing: Modelling User Engagement from Mobile Contexts. In Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing (Heidelberg, Germany) (UbiComp '16). Association for Computing Machinery, New York, NY, USA, 622--633. https://doi.org/10.1145/2971648.2971760

Digital Library

[63]

Mark A. McDaniel, Daniel C. Howard, and Karin M. Butler. 2008. Implementation intentions facilitate prospective memory under high attention demands. Memory & Cognition 36, 4 (2008), 716--724. https://doi.org/10.3758/MC.36.4.716

[64]

Abhinav Mehrotra and Mirco Musolesi. 2017. Intelligent Notifcation Systems: A Survey of the State of the Art and Research Challenges. CoRR abs/1711.10171 (2017). arXiv:1711.10171 http://arxiv.org/abs/1711.10171

[65]

Abhinav Mehrotra, Veljko Pejovic, Jo Vermeulen, Robert Hendley, and Mirco Musolesi. 2016. My Phone and Me: Understanding People's Receptivity to Mobile Notifcations. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (San Jose, California, USA) (CHI '16). Association for Computing Machinery, New York, NY, USA, 1021--1032. https://doi.org/10.1145/ 2858036.2858566

Digital Library

[66]

LoungeV Films Relaxing Music and Nature Sounds. 2008. Relaxing Music with Amazing Nature Scenery HD Video 1080p -6 Hours. Retrieved 2019-08-24 from https://www.youtube.com/watch?v=TdpBRZ0dZhw

[67]

Nargess Nourbakhsh, Yang Wang, and Fang Chen. 2013. GSR and Blink Features for Cognitive Load Classifcation. In Human-Computer Interaction - INTERACT 2013, Paula Kotzé, Gary Marsden, Gitte Lindgaard, Janet Wesson, and Marco Winckler (Eds.). Springer Berlin Heidelberg, Berlin, Heidelberg, 159--166. https://doi.org/10.1007/978-3-642-40483-2_11

[68]

Seo Jin Oh, Sungmin Seo, Ji Hyun Lee, Myeong Ju Song, and Min-Sup Shin. 2018. Effects of smartphone-based memory training for older adults with subjective memory complaints: a randomized controlled trial. Aging & Mental Health 22, 4 (2018), 526--534. https://doi.org/10.1080/13607863.2016.1274373 28071929.

[69]

Cathy Pearl. 2016. Designing Voice User Interfaces: Principles of Conversational Experiences. "O'Reilly Media, Inc.". https://dl.acm.org/citation.cfm?id=3086829

Digital Library

[70]

Simon T. Perrault, Eric Lecolinet, Yoann Pascal Bourse, Shengdong Zhao, and Yves Guiard. 2015. Physical Loci: Leveraging Spatial, Object and Semantic Memory for Command Selection. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (CHI '15). ACM, New York, NY, USA, 299--308. https://doi.org/10.1145/2702123.2702126

Digital Library

[71]

Bastian Pfleging, Drea K. Fekety, Albrecht Schmidt, and Andrew L. Kun. 2016. A Model Relating Pupil Diameter to Mental Workload and Lighting Conditions. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (San Jose, California, USA) (CHI '16). Association for Computing Machinery, New York, NY, USA, 5776--5788. https://doi.org/10.1145/2858036.2858117

[72]

Martin Pielot, Bruno Cardoso, Kleomenis Katevas, Joan Serrà, Aleksandar Matic, and Nuria Oliver. 2017. Beyond Interruptibility: Predicting Opportune Moments to Engage Mobile Phone Users. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 1, 3, Article 91 (Sept. 2017), 25 pages. https://doi.org/10.1145/3130956

Digital Library

[73]

Martin Pielot, Rodrigo de Oliveira, Haewoon Kwak, and Nuria Oliver. 2014. Didn't You See My Message? Predicting Attentiveness to Mobile Instant Messages. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Toronto, Ontario, Canada) (CHI '14). Association for Computing Machinery, New York, NY, USA, 3319--3328. https://doi.org/10.1145/2556288.2556973

Digital Library

[74]

David M. W. Powers, Martin H. Luerssen, Trent W. Lewis, Richard E. Leibbrandt, Marissa Milne, John Pashalis, and Kenneth Treharne. 2010. MANA for the Ageing. In Proceedings of the 2010 Workshop on Companionable Dialogue Systems. Association for Computational Linguistics, 7--12. https://www.aclweb.org/anthology/W10-2702.pdf

[75]

Laura Ramos, Elise van den Hoven, and Laurie Miller. 2016. Designing for the Other 'Hereafter': When Older Adults Remember about Forgetting. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (San Jose, California, USA) (CHI '16). Association for Computing Machinery, New York, NY, USA, 721--732. https://doi.org/10.1145/2858036.2858162

[76]

Lazlo Ring, Lin Shi, Kathleen Totzke, and Timothy Bickmore. 2015. Social support agents for older adults: longitudinal affective computing in the home. Journal on Multimodal User Interfaces 9, 1 (2015), 79--88. https://doi.org/10.1007/s12193-014-0157-0

[77]

Nathan S. Rose, Peter G. Rendell, Alexandra Hering, Matthias Kliegel, Gavin M. Bidelman, and Fergus I. M. Craik. 2015. Cognitive and neural plasticity in older adults' prospective memory following training with the Virtual Week computer game. Frontiers in Human Neuroscience 9 (2015). https://doi.org/10.3389/fnhum.2015.00592

[78]

Oscar Rosello, Marc Exposito, and Pattie Maes. 2016. NeverMind: Using Augmented Reality for Memorization. In Proceedings of the 29th Annual Symposium on User Interface Software and Technology (UIST '16 Adjunct). ACM, New York, NY, USA, 215--216. https://doi.org/10.1145/2984751.2984776

Digital Library

[79]

Sherry Ruan, Liwei Jiang, Justin Xu, Bryce Joe-Kun Tham, Zhengneng Qiu, Yeshuang Zhu, Elizabeth L. Murnane, Emma Brunskill, and James A. Landay. 2019. QuizBot: A Dialogue-Based Adaptive Learning System for Factual Knowledge. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (Glasgow, Scotland Uk) (CHI '19). Association for Computing Machinery, New York, NY, USA, 1--13. https://doi.org/10.1145/3290605.3300587

[80]

Sherry Ruan, Jacob O. Wobbrock, Kenny Liou, Andrew Ng, and James Landay. 2016. Speech is 3x faster than typing for english and mandarin text entry on mobile devices. arXiv preprint arXiv:1608.07323 (2016). https://hci.stanford.edu/research/speech/paper/speech_paper.pdf

[81]

Hugues Sansen, Gérard Chollet, Cornelius Glackin, Kristiina Jokinen, and Badii A. Torres. 2016. The Roberta IRONSIDE Project A Cognitive and Physical Robot Coach for Dependent Persons. Handicap 2016, Paris (2016). http://www.iieta.org/sites/default/files/Journals/MMC/MMC_C/2016.77.2_15.pdf

[82]

Hillol Sarker, Moushumi Sharmin, Amin Ahsan Ali, Md. Mahbubur Rahman, Rummana Bari, Syed Monowar Hossain, and Santosh Kumar. 2014. Assessing the Availability of Users to Engage in Just-in-Time Intervention in the Natural Environment. In Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing (Seattle, Washington) (UbiComp '14). Association for Computing Machinery, New York, NY, USA, 909--920. https://doi.org/10.1145/2632048.2636082

Digital Library

[83]

Fred Shaffer and J. P. Ginsberg. 2017. An overview of heart rate variability metrics and norms. Frontiers in Public Health 5 (2017), 258. https://www.frontiersin.org/article/10.3389/fpubh.2017.00258

[84]

Tejal M. Shah, Michael Weinborn, Giuseppe Verdile, Hamid R. Sohrabi, and Ralph N. Martins. 2017. Enhancing Cognitive Functioning in Healthly Older Adults: a Systematic Review of the Clinical Significance of Commercially Available Computerized Cognitive Training in Preventing Cognitive Decline. Neuropsychology Review 27, 1 (2017), 62--80. https://doi.org/10.1007/s11065-016-9338-9

[85]

Evelyn Shatil, Jaroslava Mikulecka, Francesco Bellotti, and Vladimír Bureš. 2014. Novel television-based cognitive training improves working memory and executive function. PLoS One 9, 7 (2014), e101472. https://doi.org/10.1371/journal.pone.0101472

[86]

Yu Shi, Natalie Ruiz, Ronnie Taib, Eric Choi, and Fang Chen. 2007. Galvanic Skin Response (GSR) as an Index of Cognitive Load. In CHI '07 Extended Abstracts on Human Factors in Computing Systems (San Jose, CA, USA) (CHI EA '07). Association for Computing Machinery, New York, NY, USA, 2651--2656. https://doi.org/10.1145/1240866.1241057

Digital Library

[87]

Glenn E. Smith, Patricia Housen, Kristine Yaffe, Ronald Ruff, Robert F. Kennison, Henry W. Mahncke, and Elizabeth M. Zelinski. 2009. A Cognitive Training Program Based on Principles of Brain Plasticity: Results from the Improvement in Memory with Plasticity-based Adaptive Cognitive Training (IMPACT) Study. Journal of the American Geriatrics Society 57, 4 (2009), 594--603. https://doi.org/10.1111/j.1532- 5415.2008.02167.x

[88]

Mika P. Tarvainen, Juha-Pekka Niskanen, Jukka A. Lipponen, Perttu O. Ranta-Aho, and Pasi A. Karjalainen. 2014. Kubios HRV-heart rate variability analysis software. Computer methods and programs in biomedicine 113, 1 (2014), 210--220. https://doi.org/10.1016/j.cmpb.2013.07.024

[89]

Julian F. Thayer, Anita L. Hansen, Evelyn Saus-Rose, and Bjorn H. Johnsen. 2009. Heart rate variability, prefrontal neural function, and cognitive performance. Annals of Behavioral Medicine 37, 2 (2009), 141--153. https://doi.org/10.1007/s12160-009-9101-z

[90]

Myrthe Tielman, Marieke van Meggelen, Mark A. Neerincx, and Willem-Paul Brinkman. 2015. An Ontology-Based Question System for a Virtual Coach Assisting in Trauma Recollection. In International Conference on Intelligent Virtual Agents. Springer Cham, 17--27. https://doi.org/10.1007/978-3-319-21996-7_2

[91]

Liam D. Turner, Stuart M. Allen, and Roger M. Whitaker. 2017. Reachable but not receptive: Enhancing smartphone interruptibility prediction by modelling the extent of user engagement with notifications. Pervasive and Mobile Computing 40 (2017), 480--494. https://doi.org/10.1016/j.pmcj.2017.01.011

Digital Library

[92]

Marieke van Dooren, J. J. G. (Gert-Jan) de Vries, and Joris H. Janssen. 2012. Emotional sweating across the body: Comparing 16 different skin conductance measurement locations. Physiology & Behavior 106, 2 (2012), 298--304. https://doi.org/10.1016/j.physbeh.2012.01.020

[93]

Laura Pfeifer Vardoulakis, Lazlo Ring, Barbara Barry, Candace L. Sidner, and Timothy Bickmore. 2012. Designing Relational Agents as Long Term Social Companions for Older Adults. In International Conference on Intelligent Virtual Agents. Springer, 289--302. https://doi.org/10.1007/978-3-642-33197-8_30

Digital Library

[94]

Aku Visuri, Niels van Berkel, Chu Luo, Jorge Goncalves, Denzil Ferreira, and Vassilis Kostakos. 2017. Predicting Interruptibility for Manual Data Collection: A Cluster-Based User Model. In Proceedings of the 19th International Conference on Human-Computer Interaction with Mobile Devices and Services (Vienna, Austria) (MobileHCI '17). Association for Computing Machinery, New York, NY, USA, Article 12, 14 pages. https://doi.org/10.1145/3098279.3098532

Digital Library

[95]

Piotr A. Wozniak and Edward J. Gorzelanczyk. 1994. Optimization of repetition spacing in the practice of learning. Acta Neurobiologiae Experimentalis 54 (1994), 59--59. https://ane.pl/pdf/5409.pdf

[96]

Ramin Yaghoubzadeh, Marcel Kramer, Karola Pitsch, and Stefan Kopp. 2013. Virtual Agents as Daily Assistants for Elderly or Cognitively Impaired People. In International workshop on intelligent virtual agents. Springer, 79--91. https://doi.org/10.1007/978-3-642-40415-3_7

[97]

Yuki Yamada, Keisuke Irie, Kota Gushima, Fumiko Ishizawa, Mohammed Al Sada, and Tatsuo Nakajima. 2017. HoloMoL: Human Memory Augmentation with Mixed-reality Technologies. In Proceedings of the 21st International Academic Mindtrek Conference (AcademicMindtrek '17). ACM, New York, NY, USA, 235--238. https://doi.org/10.1145/3131085.3131097

Digital Library

[98]

Xi Yang, Marco Aurisicchio, and Weston Baxter. 2019. Understanding Affective Experiences with Conversational Agents. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (Glasgow, Scotland Uk) (CHI '19). Association for Computing Machinery, New York, NY, USA, 1--12. https://doi.org/10.1145/3290605.3300772

Digital Library

[99]

Akihito Yoshii, Helena Malmivirta, Mika Luimula, Paula Pitkäkangas, and Tatsuo Nakajima. 2015. Designing a Map-Based Application and a Conversational Agent for Addressing Memory Problems. In International Conference on Human-Computer Interaction. Springer, 340--345. https://doi.org/10.1007/978-3-319-21380-4_58

[100]

Fengpeng Yuan, Xianyi Gao, and Janne Lindqvist. 2017. How Busy Are You? Predicting the Interruptibility Intensity of Mobile Users. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (Denver, Colorado, USA) (CHI '17). Association for Computing Machinery, New York, NY, USA, 5346--5360. https://doi.org/10.1145/3025453.3025946

Digital Library

[101]

Fred R. H. Zijlstra, Robert A. Roe, Anna B. Leonora, and Irene Krediet. 1999. Temporal factors in mental work: Effects of interrupted activities. Journal of Occupational and Organizational Psychology 72, 2 (1999), 163--185. https://doi.org/10.1348/096317999166581

[102]

Thomas D. Zimmermann and Beat Meier. 2010. The effect of implementation intentions on prospective memory performance across the lifespan. Applied Cognitive Psychology 24, 5 (2010), 645--658. https://doi.org/10.1002/acp.1576

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Zulfikar WChan SMaes P(2024)Memoro: Using Large Language Models to Realize a Concise Interface for Real-Time Memory AugmentationProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642450(1-18)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642450
Zon MGanesh GDeen MFang Q(2023)Context-Aware Medical Systems within Healthcare Environments: A Systematic Scoping Review to Identify Subdomains and Significant Medical ContextsInternational Journal of Environmental Research and Public Health10.3390/ijerph2014639920:14(6399)Online publication date: 19-Jul-2023
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Laporte MGjoreski MLangheinrich M(2023)LAUREATEProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36108927:3(1-41)Online publication date: 27-Sep-2023
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Index Terms

Prompto: Investigating Receptivity to Prompts Based on Cognitive Load from Memory Training Conversational Agent
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. HCI design and evaluation methods
      1. User studies
    2. Interaction paradigms
      1. Natural language interfaces

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cover image Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies

Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies Volume 4, Issue 4

December 2020

1356 pages

EISSN:2474-9567

DOI:10.1145/3444864

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Published: 18 December 2020

Published in IMWUT Volume 4, Issue 4

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Zulfikar WChan SMaes P(2024)Memoro: Using Large Language Models to Realize a Concise Interface for Real-Time Memory AugmentationProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642450(1-18)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642450
Zon MGanesh GDeen MFang Q(2023)Context-Aware Medical Systems within Healthcare Environments: A Systematic Scoping Review to Identify Subdomains and Significant Medical ContextsInternational Journal of Environmental Research and Public Health10.3390/ijerph2014639920:14(6399)Online publication date: 19-Jul-2023
https://doi.org/10.3390/ijerph20146399
Laporte MGjoreski MLangheinrich M(2023)LAUREATEProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36108927:3(1-41)Online publication date: 27-Sep-2023
https://dl.acm.org/doi/10.1145/3610892
Nanayakkara SInami MMueller FHuber JGupta CJouffrais CKunze KPatibanda RChan SMesserschmidt MWard JMcGill MMarky K(2023)Exploring the Design Space of Assistive AugmentationProceedings of the Augmented Humans International Conference 202310.1145/3582700.3582729(371-373)Online publication date: 12-Mar-2023
https://dl.acm.org/doi/10.1145/3582700.3582729
Chan SZhang HNanayakkara S(2023)Eye Movement Analysis of Human Visual Recognition Processes with Camera Eye Tracker: Higher Mean and Variance of Fixation Duration for Familiar ImagesExtended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544549.3585782(1-8)Online publication date: 19-Apr-2023
https://dl.acm.org/doi/10.1145/3544549.3585782
Iovine ANarducci FMusto Cde Gemmis MSemeraro G(2023)Virtual Customer Assistants in finance: From state of the art and practices to design guidelinesComputer Science Review10.1016/j.cosrev.2023.10053447(100534)Online publication date: Feb-2023
https://doi.org/10.1016/j.cosrev.2023.100534
Keller RWangenheim FMair JKowatsch T(2023)Receptivity to mobile health interventionsDigital Therapeutics for Mental Health and Addiction10.1016/B978-0-323-90045-4.00006-X(65-77)Online publication date: 2023
https://doi.org/10.1016/B978-0-323-90045-4.00006-X
Dissanayake VTang VElvitigala DWen EWu MNanayakkara S(2022)TroiProceedings of the ACM on Human-Computer Interaction10.1145/35467386:MHCI(1-22)Online publication date: 20-Sep-2022
https://dl.acm.org/doi/10.1145/3546738
Gupta KChan SPai YStrachan NSu JSumich ANanayakkara SBillinghurst M(2022)Total VREcallProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/35346156:2(1-21)Online publication date: 7-Jul-2022
https://dl.acm.org/doi/10.1145/3534615
Kabir KKenfield SVan Blarigan EChan JWiese J(2022)Ask the UsersProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/35346126:2(1-21)Online publication date: 7-Jul-2022
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