{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,15]],"date-time":"2025-08-15T02:19:15Z","timestamp":1755224355228,"version":"3.43.0"},"reference-count":15,"publisher":"Association for Computing Machinery (ACM)","issue":"2","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["GetMobile: Mobile Comp. and Comm."],"published-print":{"date-parts":[[2025,8,11]]},"abstract":"<jats:p>Personal Informatics (PI) systems, such as apps and wearables that help users track physical activity, sleep, heart rate, or stress, have become critical tools for self-monitoring and health research. As these systems increasingly drive personal and clinical decisionmaking, it's vital to understand how equitable and representative they really are. Real-world harms have already surfaced in adjacent domains: health sensors like pulse oximeters underperform on darker skin tones [1], and female speakers and non-US nationalities experience significant performance degradation in automated speaker recognition [2]. These failures aren't just technical - they're structural, human-centric, and societal. Yet, despite their growing influence, PI systems remain critically under-researched from a fairness and equity perspective [3]. Our research, detailed in [4], investigates this question by examining when, how, and for whom bias arises in the lifecycle of PI systems.<\/jats:p>","DOI":"10.1145\/3760535.3760541","type":"journal-article","created":{"date-parts":[[2025,8,12]],"date-time":"2025-08-12T15:03:23Z","timestamp":1755011003000},"page":"26-30","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Uncovering the Hidden Biases in Personal Informatics"],"prefix":"10.1145","volume":"29","author":[{"given":"Sofia","family":"Yfantidou","sequence":"first","affiliation":[{"name":"Kinetic Analysis B.V., Netherlands"}]},{"given":"Pavlos","family":"Sermpezis","sequence":"additional","affiliation":[{"name":"Aristotle University of Thessaloniki, , Greece"}]},{"given":"Athena","family":"Vakali","sequence":"additional","affiliation":[{"name":"Aristotle University of Thessaloniki, , Greece"}]},{"given":"Ricardo","family":"Baeza-Yates","sequence":"additional","affiliation":[{"name":"AI Institute, Barcelona Supercomputing Cente, Spain"}]}],"member":"320","published-online":{"date-parts":[[2025,8,12]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMc2029240"},{"key":"e_1_2_1_2_1","volume-title":"Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency.","author":"Hutiri W.T.","unstructured":"W.T. Hutiri and A. Yi Ding. 2022. Bias in automated speaker recognition. Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency."},{"key":"e_1_2_1_3_1","unstructured":"S. Yfantidou M. Constantinides D. Spathis A. Vakali D. Quercia and F. Kawsar. 2023. Beyond accuracy: a critical review of fairness in machine learning for mobile and wearable computing. arXiv preprint arXiv:2303.15585."},{"key":"e_1_2_1_4_1","volume-title":"Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 1--30","author":"Yfantidou S.","unstructured":"S. Yfantidou, P. Sermpezis, A. Vakali and R. Baeza- Yates. 2023. Uncovering bias in personal informatics. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 1--30."},{"key":"e_1_2_1_5_1","volume-title":"Proceedings of the 1st ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization.","author":"Suresh H.","unstructured":"H. Suresh and J. Guttag. 2021. A framework for understanding sources of harm throughout the machine learning life cycle. Proceedings of the 1st ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization."},{"key":"e_1_2_1_6_1","unstructured":"P.J. Cho J. Yi E. Ho M.M.H. Shandhi Y. Dinh A. Patil and L. Martin. 2022. Demographic imbalances resulting from the bring-yourown- device study design. JMIR mHealth and uHealth vol. 10 no. 4 e29510."},{"key":"e_1_2_1_7_1","doi-asserted-by":"crossref","unstructured":"M.V. McConnell A. Shcherbina A. Pavlovic J.R. Homburger R.L. Goldfeder D. Waggot and M.K. Cho. 2017. Feasibility of obtaining measures of lifestyle from a smartphone app: the MyHeart Counts Cardiovascular Health Study. JAMA Cardiology 67--76.","DOI":"10.1001\/jamacardio.2016.4395"},{"key":"e_1_2_1_8_1","doi-asserted-by":"crossref","unstructured":"S. Yfantidou C. Karagianni S. Efstathiou A. Vakali J. Palotti D.P. Giakatos T. Marchioro A. Kazlouski E. Ferrari and S Girdzijauskas. 2022. LifeSnaps a 4-month multi-modal dataset capturing unobtrusive snapshots of our lives in the wild. Scientific Data 663.","DOI":"10.1038\/s41597-022-01764-x"},{"key":"e_1_2_1_9_1","unstructured":"A.E. Johnson T.J. Pollard L. Shen L.-w. H. Lehman M. Feng M. Ghassemi B. Moody P. Szolovits L.A. Celi and R.G. Mark. 2016. MIMIC-III a freely accessible critical care database. Scientific Data 1--9."},{"key":"e_1_2_1_10_1","volume-title":"More Active People for a Healthier World,\" World Health Organization","author":"W. H. Organization","year":"2019","unstructured":"W. H. Organization. Gobal Action Plan on Physical Activity 2018--2030: More Active People for a Healthier World,\" World Health Organization, 2019."},{"key":"e_1_2_1_11_1","volume-title":"Facts and Figures","year":"2024","unstructured":"International Telecommunication Union, \"Measuring Digital Development: Facts and Figures 2024,\" International Telecommunication Union, 2024."},{"key":"e_1_2_1_12_1","volume-title":"IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS).","author":"Rudovic O.","unstructured":"O. Rudovic, Y. Utsumi, J. Lee, J. Hernandez, E. Castell\u00f3 Ferrer, B. Schuller and R. W. Picard. 2018. CultureNet: a deep learning approach for engagement intensity estimation from face images of children with autism. IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS)."},{"key":"e_1_2_1_13_1","doi-asserted-by":"crossref","unstructured":"R.B. Parikh S. Teeple and A.S. Navathe. 2019. Addressing bias in artificial intelligence in health care. JAMA 2377--2378.","DOI":"10.1001\/jama.2019.18058"},{"key":"e_1_2_1_14_1","doi-asserted-by":"crossref","unstructured":"M. Van Ryn D. Burgess J. Malat and J. Griffin. 2006. Physicians' perceptions of patients' social and behavioral characteristics and race disparities in treatment recommendations for men with coronary artery disease. American Journal of Public Health 351--357.","DOI":"10.2105\/AJPH.2004.041806"},{"key":"e_1_2_1_15_1","volume-title":"Digital Divide Risks Becoming 'New Face of Inequality,' Deputy Secretary-General Warns General Assembly,\" United Nations","author":"Mohammed A.","year":"2021","unstructured":"A. Mohammed. \"With Almost Half of World's Population Still Offline, Digital Divide Risks Becoming 'New Face of Inequality,' Deputy Secretary-General Warns General Assembly,\" United Nations, 2021."}],"container-title":["GetMobile: Mobile Computing and Communications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3760535.3760541","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,12]],"date-time":"2025-08-12T15:04:19Z","timestamp":1755011059000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3760535.3760541"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,11]]},"references-count":15,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2025,8,11]]}},"alternative-id":["10.1145\/3760535.3760541"],"URL":"https:\/\/doi.org\/10.1145\/3760535.3760541","relation":{},"ISSN":["2375-0529","2375-0537"],"issn-type":[{"value":"2375-0529","type":"print"},{"value":"2375-0537","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,8,11]]},"assertion":[{"value":"2025-08-12","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}