Conference Paper2026

A Privacy-by-Design Framework for Digital Phenotyping: On-Device AI for Accurate Behavioral Research Without Compromising User Trust

Istiaq Ahmed, Faiza Omar Arpita, Ashraful Islam, Saadia Binte Alam, Moinul Islam Zaber, M Ashraful Amin

International Conference on Human-Computer Interaction

In: Human-Centered Design, Operation and Evaluation of Mobile Communications

Springer Nature Switzerland, pp. 319-336, ISBN: 9783032305480

DOI: 10.1007/978-3-032-30549-7_19URL

Keywords

  • on-device AI
  • digital phenotyping
  • privacy by design
  • participant recruitment and retention
  • edge AI
  • Federated learning
  • self-report questionnaire
  • data anonymization
  • user trust
  • recall bias

CCDS Authors

Istiaq Ahmed
Istiaq Ahmed

Istiaq Ahmed

  • Research Assistant, HCI Wing

Published at

CHI, HCII

Ashraful Islam, PhD
Ashraful Islam

Ashraful Islam, PhD

  • Center Director, CCDS
  • Director, HCI Wing

Published at

CHI, UIST, UbiComp, IJCNN, ICIP, HCII, ICDMW, BLP, Pattern Recognition, IEEE Internet of Things Journal, JMIR, JMIR Human Factors, JMIR Formative Research, IEEE Access, Smart Agricultural Technology, Diabetes Research and Clinical Practice, PLOS ONE

Saadia Binte Alam, PhD
Saadia Binte Alam, PhD

Saadia Binte Alam, PhD

  • Director, MIRA & WiSE Wings

  • Associate Professor

    Department of Computer Science and Engineering

    Independent University, Bangladesh (IUB)

Published at

HCII, Scientific Reports, Cognitive Computation, Neural Computing and Applications

Moinul I Zaber, PhD
Moinul I Zaber, PhD

Moinul I Zaber, PhD

  • Director, HCI Wing
  • Supervisor, DS Wing

  • Professor

    Department of Computer Science & Engineering

    University of Dhaka, Bangladesh

  • Visiting Academic

    Department of Computer Science and Technology

    University of Cambridge, United Kingdom

  • Research Fellow

    Institute of Development Studies (Sussex), United Kingdom

Published at

ICPR, HCII, JMIR

Prof. M Ashraful Amin, PhD
M Ashraful Amin, PhD

Prof. M Ashraful Amin, PhD

  • Founder Director, CCDS
  • Director, AI/ML, HCI & DS Wings

Published at

ACL, CHI, UbiComp, ECAI, WACV, PAKDD, IJCNN, ICPR, ICIP, HCII, CLEF, BLP, Scientific Reports, Pattern Recognition, JMIR, IEEE Access, Smart Agricultural Technology, Frontiers in Computational Neuroscience, Diabetes Research and Clinical Practice, PLOS ONE

References

  1. 1.Nicola Rieke, Jonny Hancox, Wenqi Li, Fausto Milletarì, Holger R. Roth, Shadi Albarqouni, Spyridon Bakas, Mathieu N. Galtier, Bennett A. Landman, Klaus Maier-Hein, Sébastien Ourselin, Micah Sheller, Ronald M. Summers, Andrew Trask, Daguang Xu, Maximilian Baust, M. Jorge Cardoso. (2020). The future of digital health with federated learning. npj Digital Medicine, 3(1), 119[10.1038/s41746-020-00323-1]
  2. 2.Jiasi Chen, Xukan Ran. (2019). Deep Learning With Edge Computing: A Review. Proceedings of the IEEE, 107(8), 1655–1674[10.1109/jproc.2019.2921977]
  3. 3.John Torous, Mathew V Kiang, Jeanette Lorme, Jukka-Pekka Onnela. (2016). New Tools for New Research in Psychiatry: A Scalable and Customizable Platform to Empower Data Driven Smartphone Research. JMIR Mental Health, 3(2), e16[10.2196/mental.5165]
  4. 4.Jukka-Pekka Onnela, Scott L Rauch. (2016). Harnessing Smartphone-Based Digital Phenotyping to Enhance Behavioral and Mental Health. Neuropsychopharmacology, 41(7), 1691–1696[10.1038/npp.2016.7]
  5. 5.Alon Jacovi, Ana Marasović, Tim Miller, Yoav Goldberg. (2021). Formalizing Trust in Artificial Intelligence. , 624–635[10.1145/3442188.3445923]
  6. 6.Jeffrey Boase, Rich Ling. (2013). Measuring Mobile Phone Use: Self-Report Versus Log Data. Journal of Computer-Mediated Communication, 18(4), 508–519[10.1111/jcc4.12021]
  7. 7.Saleh Afroogh, Ali Akbari, Emmie Malone, Mohammadali Kargar, Hananeh Alambeigi. (2024). Trust in AI: progress, challenges, and future directions. Humanities and Social Sciences Communications, 11(1)[10.1057/s41599-024-04044-8]
  8. 8.Kit Huckvale, John Torous, Mark E. Larsen. (2019). Assessment of the Data Sharing and Privacy Practices of Smartphone Apps for Depression and Smoking Cessation. JAMA Network Open, 2(4), e192542[10.1001/jamanetworkopen.2019.2542]
  9. 9.John Rooksby, Alistair Morrison, Dave Murray-Rust. (2019). Student Perspectives on Digital Phenotyping. , 1–14[10.1145/3290605.3300655]
  10. 10.David C. Mohr, Katie Shilton, Matthew Hotopf. (2020). Digital phenotyping, behavioral sensing, or personal sensing: names and transparency in the digital age. npj Digital Medicine, 3(1), 45[10.1038/s41746-020-0251-5]
  11. 11.Mark de Reuver, Harry Bouwman. (2014). Dealing with self-report bias in mobile Internet acceptance and usage studies. Information & Management, 52(3), 287–294[10.1016/j.im.2014.12.002]
  12. 12.Amin Aminifar, Matin Shokri, Amir Aminifar. (2024). Privacy-preserving edge federated learning for intelligent mobile-health systems. Future Generation Computer Systems, 161, 625–637[10.1016/j.future.2024.07.035]
  13. 13.Schenelle Dayna Dlima, Santosh Shevade, Sonia Rebecca Menezes, Aakash Ganju. (2022). Digital Phenotyping in Health Using Machine Learning Approaches: Scoping Review. JMIR Bioinformatics and Biotechnology, 3(1), e39618[10.2196/39618]
  14. 14.Christos Papadopoulos, Konstantinos-Filippos Kollias, George F. Fragulis. (2024). Recent Advancements in Federated Learning: State of the Art, Fundamentals, Principles, IoT Applications and Future Trends. Future Internet, 16(11), 415[10.3390/fi16110415]
  15. 15.Nadia Binte Alam, Mohsin Surani, Chayon Kumar Das, Domenico Giacco, Swaran P. Singh, Sagar Jilka. (2025). Challenges and standardisation strategies for sensor-based data collection for digital phenotyping. Communications Medicine, 5(1), 360[10.1038/s43856-025-01013-3]
  16. 16.Laddawan Kaewkitipong, Charlie Chen, Jiangxue Han, Peter Ractham. (2022). Human–Computer Interaction (HCI) and Trust Factors for the Continuance Intention of Mobile Payment Services. Sustainability, 14(21), 14546[10.3390/su142114546]
  17. 17.Mohammadjavad Shabankareh, Seyed Sina Khamoushi Sahne, Alireza Nazarian, Pantea Foroudi. (2025). The impact of AI perceived transparency on trust in AI recommendations in healthcare applications. Asia-Pacific Journal of Business Administration[10.1108/apjba-12-2024-0690]
  18. 18.Rajesh Kumar Chaudhary, Ravinder Kumar, Nitin Saxena. (2024). A systematic review on federated learning system: a new paradigm to machine learning. Knowledge and Information Systems, 67(2), 1811–1914[10.1007/s10115-024-02257-6]
  19. 19.Hyunsoo Lee, Yugyeong Jung, Hei Yiu Law, Seolyeong Bae, Uichin Lee. (2024). PriviAware: Exploring Data Visualization and Dynamic Privacy Control Support for Data Collection in Mobile Sensing Research. , 1–17[10.1145/3613904.3642815]
  20. 20.Leheng Lin, Laurent H Wang. (2025). From screens to sensors: a contextual integrity approach to understanding privacy norms across mobile health contexts. Journal of Computer-Mediated Communication, 31(1)[10.1093/jcmc/zmaf022]
← All publications