This paper is in the following e-collection/theme issue:

Wearables and MHealth Reviews (236) Digital Biomarkers and Digital Phenotyping (155) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1159) Wearable Devices and Sensors (734)

Published on in Vol 7, No 8 (2019): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/12649, first published .
Passive Sensing of Health Outcomes Through Smartphones: Systematic Review of Current Solutions and Possible Limitations

Passive Sensing of Health Outcomes Through Smartphones: Systematic Review of Current Solutions and Possible Limitations

Passive Sensing of Health Outcomes Through Smartphones: Systematic Review of Current Solutions and Possible Limitations

Authors of this article:

Alina Trifan 1, 2 Author Orcid Image ;   Maryse Oliveira 1, 2 Author Orcid Image ;   José Luís Oliveira 1, 2 Author Orcid Image
Article Authors Cited by (68) Tweetations (21) Metrics

Journals

  1. Biebl J, Huber S, Rykala M, Kraft E, Lorenz A. Attitudes and Expectations of Health Care Professionals Toward App-Based Therapy in Patients with Osteoarthritis of the Hip or Knee: Questionnaire Study. JMIR mHealth and uHealth 2020;8(10):e21704 View
  2. Milne-Ives M, Lam C, Van Velthoven M, Meinert E. Mobile Apps for Health Behavior Change: Protocol for a Systematic Review. JMIR Research Protocols 2020;9(1):e16931 View
  3. Marsch L. Digital health and addiction. Current Opinion in Systems Biology 2020;20:1 View
  4. Ferrari M, Schick A. Teenagers, screens and social media: a commentary on Orben’s narrative review. Social Psychiatry and Psychiatric Epidemiology 2020;55(8):973 View
  5. Marsch L. Digital health data-driven approaches to understand human behavior. Neuropsychopharmacology 2021;46(1):191 View
  6. Huang E, Onnela J. Augmented Movelet Method for Activity Classification Using Smartphone Gyroscope and Accelerometer Data. Sensors 2020;20(13):3706 View
  7. Henson P, Barnett I, Keshavan M, Torous J. Towards clinically actionable digital phenotyping targets in schizophrenia. npj Schizophrenia 2020;6(1) View
  8. Miaskowski C, Blyth F, Nicosia F, Haan M, Keefe F, Smith A, Ritchie C. A Biopsychosocial Model of Chronic Pain for Older Adults. Pain Medicine 2020;21(9):1793 View
  9. Milne-Ives M, Lam C, De Cock C, Van Velthoven M, Meinert E. Mobile Apps for Health Behavior Change in Physical Activity, Diet, Drug and Alcohol Use, and Mental Health: Systematic Review. JMIR mHealth and uHealth 2020;8(3):e17046 View
  10. Meegahapola L, Gatica-Perez D. Smartphone Sensing for the Well-Being of Young Adults: A Review. IEEE Access 2021;9:3374 View
  11. Rosa C, Marsch L, Winstanley E, Brunner M, Campbell A. Using digital technologies in clinical trials: Current and future applications. Contemporary Clinical Trials 2021;100:106219 View
  12. Behar J, Liu C, Kotzen K, Tsutsui K, Corino V, Singh J, Pimentel M, Warrick P, Zaunseder S, Andreotti F, Sebag D, Kopanitsa G, McSharry P, Karlen W, Karmakar C, Clifford G. Remote health diagnosis and monitoring in the time of COVID-19. Physiological Measurement 2020;41(10):10TR01 View
  13. Kohli M, Moore D, Moore R. Using health technology to capture digital phenotyping data in HIV-associated neurocognitive disorders. AIDS 2021;35(1):15 View
  14. Sandifer P, Knapp L, Lichtveld M, Manley R, Abramson D, Caffey R, Cochran D, Collier T, Ebi K, Engel L, Farrington J, Finucane M, Hale C, Halpern D, Harville E, Hart L, Hswen Y, Kirkpatrick B, McEwen B, Morris G, Orbach R, Palinkas L, Partyka M, Porter D, Prather A, Rowles T, Scott G, Seeman T, Solo-Gabriele H, Svendsen E, Tincher T, Trtanj J, Walker A, Yehuda R, Yip F, Yoskowitz D, Singer B. Framework for a Community Health Observing System for the Gulf of Mexico Region: Preparing for Future Disasters. Frontiers in Public Health 2020;8 View
  15. Mollard E, Michaud K. Self-Management of Rheumatoid Arthritis: Mobile Applications. Current Rheumatology Reports 2021;23(1) View
  16. Poudyal A, van Heerden A, Hagaman A, Islam C, Thapa A, Maharjan S, Byanjankar P, Kohrt B. What Does Social Support Sound Like? Challenges and Opportunities for Using Passive Episodic Audio Collection to Assess the Social Environment. Frontiers in Public Health 2021;9 View
  17. Doarn C. A New Beginning. Telemedicine and e-Health 2021;27(2):115 View
  18. Dong G, Boukhechba M, Shaffer K, Ritterband L, Gioeli D, Reilley M, Le T, Kunk P, Bauer T, Chow P. Using Graph Representation Learning to Predict Salivary Cortisol Levels in Pancreatic Cancer Patients. Journal of Healthcare Informatics Research 2021;5(4):401 View
  19. Wetzel B, Pryss R, Baumeister H, Edler J, Gonçalves A, Cohrdes C. “How Come You Don’t Call Me?” Smartphone Communication App Usage as an Indicator of Loneliness and Social Well-Being across the Adult Lifespan during the COVID-19 Pandemic. International Journal of Environmental Research and Public Health 2021;18(12):6212 View
  20. Abo-Tabik M, Benn Y, Costen N. Are Machine Learning Methods the Future for Smoking Cessation Apps?. Sensors 2021;21(13):4254 View
  21. Xu X, Mankoff J, Dey A. Understanding practices and needs of researchers in human state modeling by passive mobile sensing. CCF Transactions on Pervasive Computing and Interaction 2021;3(4):344 View
  22. Müller S, Chen X, Peters H, Chaintreau A, Matz S. Depression predictions from GPS-based mobility do not generalize well to large demographically heterogeneous samples. Scientific Reports 2021;11(1) View
  23. Qirtas M, Zafeiridi E, Pesch D, White E. Loneliness and Social Isolation Detection Using Passive Sensing Techniques: Scoping Review. JMIR mHealth and uHealth 2022;10(4):e34638 View
  24. Ren B, Xia C, Gehrman P, Barnett I, Satterthwaite T. Measuring Daily Activity Rhythms in Young Adults at Risk of Affective Instability Using Passively Collected Smartphone Data: Observational Study. JMIR Formative Research 2022;6(9):e33890 View
  25. Baumeister H, Garatva P, Pryss R, Ropinski T, Montag C. Digitale Phänotypisierung in der Psychologie – ein Quantensprung in der psychologischen Forschung?. Psychologische Rundschau 2023;74(2):89 View
  26. Costa A, Milne R. Understanding ‘passivity’ in digital health through imaginaries and experiences of coronavirus disease 2019 contact tracing apps. Big Data & Society 2022;9(1):205395172210911 View
  27. Ross G, Zhao Y, Bosman A, Geballa-Koukoula A, Zhou H, Elliott C, Nielen M, Rafferty K, Salentijn G. Best practices and current implementation of emerging smartphone-based (bio)sensors – Part 1: Data handling and ethics. TrAC Trends in Analytical Chemistry 2023;158:116863 View
  28. Kumar S, Datta D, Dong G, Cai L, Boukhechba M, Barnes L. Leveraging Mobile Sensing and Bayesian Change Point Analysis to Monitor Community-scale Behavioral Interventions: A Case Study on COVID-19. ACM Transactions on Computing for Healthcare 2022;3(4):1 View
  29. Bettis A, Burke T, Nesi J, Liu R. Digital Technologies for Emotion-Regulation Assessment and Intervention: A Conceptual Review. Clinical Psychological Science 2022;10(1):3 View
  30. Dirgová Luptáková I, Kubovčík M, Pospíchal J. Wearable Sensor-Based Human Activity Recognition with Transformer Model. Sensors 2022;22(5):1911 View
  31. Mendes J, Moura I, Van de Ven P, Viana D, Silva F, Coutinho L, Teixeira S, Rodrigues J, Teles A. Sensing Apps and Public Data Sets for Digital Phenotyping of Mental Health: Systematic Review. Journal of Medical Internet Research 2022;24(2):e28735 View
  32. Baumgartner S, Sumter S, Petkevič V, Wiradhany W. A Novel iOS Data Donation Approach: Automatic Processing, Compliance, and Reactivity in a Longitudinal Study. Social Science Computer Review 2023;41(4):1456 View
  33. Zhang X, Yang Y, Cao J, Qi Z, Li G. Point‐of‐care CRISPR/Cas biosensing technology: A promising tool for preventing the possible COVID‐19 resurgence caused by contaminated cold‐chain food and packaging. Food Frontiers 2023;4(1):207 View
  34. Girousse E, Vuillerme N. The Use of Passive Smartphone Data to Monitor Anxiety and Depression Among College Students in Real-World Settings: Protocol for a Systematic Review. JMIR Research Protocols 2022;11(12):e38785 View
  35. Parker H, Burkart S, Reesor-Oyer L, Smith M, Dugger R, von Klinggraeff L, Weaver R, Beets M, Armstrong B. Feasibility of Measuring Screen Time, Activity, and Context Among Families With Preschoolers: Intensive Longitudinal Pilot Study. JMIR Formative Research 2022;6(9):e40572 View
  36. Moura I, Teles A, Viana D, Marques J, Coutinho L, Silva F. Digital Phenotyping of Mental Health using multimodal sensing of multiple situations of interest: A Systematic Literature Review. Journal of Biomedical Informatics 2023;138:104278 View
  37. Goulding E, Dopke C, Rossom R, Michaels T, Martin C, Ryan C, Jonathan G, McBride A, Babington P, Bernstein M, Bank A, Garborg C, Dinh J, Begale M, Kwasny M, Mohr D. A Smartphone-Based Self-management Intervention for Individuals With Bipolar Disorder (LiveWell): Empirical and Theoretical Framework, Intervention Design, and Study Protocol for a Randomized Controlled Trial. JMIR Research Protocols 2022;11(2):e30710 View
  38. Hauser T, Skvortsova V, De Choudhury M, Koutsouleris N. The promise of a model-based psychiatry: building computational models of mental ill health. The Lancet Digital Health 2022;4(11):e816 View
  39. Huang E, Yan K, Onnela J. Smartphone-Based Activity Recognition Using Multistream Movelets Combining Accelerometer and Gyroscope Data. Sensors 2022;22(7):2618 View
  40. Zhu T, Kuang L, Daniels J, Herrero P, Li K, Georgiou P. IoMT-Enabled Real-Time Blood Glucose Prediction With Deep Learning and Edge Computing. IEEE Internet of Things Journal 2023;10(5):3706 View
  41. Peyroteo M, Ferreira I, Elvas L, Ferreira J, Lapão L. Remote Monitoring Systems for Patients With Chronic Diseases in Primary Health Care: Systematic Review. JMIR mHealth and uHealth 2021;9(12):e28285 View
  42. Wang Z, Xiong H, Zhang J, Yang S, Boukhechba M, Zhang D, Barnes L, Dou D. From Personalized Medicine to Population Health: A Survey of mHealth Sensing Techniques. IEEE Internet of Things Journal 2022;9(17):15413 View
  43. Gopalakrishnan A, Venkataraman R, Gururajan R, Zhou X, Genrich R. Mobile phone enabled mental health monitoring to enhance diagnosis for severity assessment of behaviours: a review. PeerJ Computer Science 2022;8:e1042 View
  44. Kulkarni P, Kirkham R, McNaney R. Opportunities for Smartphone Sensing in E-Health Research: A Narrative Review. Sensors 2022;22(10):3893 View
  45. Valentine L, D’Alfonso S, Lederman R. Recommender systems for mental health apps: advantages and ethical challenges. AI & SOCIETY 2023;38(4):1627 View
  46. Koutsouleris N, Hauser T, Skvortsova V, De Choudhury M. From promise to practice: towards the realisation of AI-informed mental health care. The Lancet Digital Health 2022;4(11):e829 View
  47. González-Pérez A, Matey-Sanz M, Granell C, Casteleyn S. Using mobile devices as scientific measurement instruments: Reliable android task scheduling. Pervasive and Mobile Computing 2022;81:101550 View
  48. De Calheiros Velozo J, Habets J, George S, Niemeijer K, Minaeva O, Hagemann N, Herff C, Kuppens P, Rintala A, Vaessen T, Riese H, Delespaul P. Designing daily-life research combining experience sampling method with parallel data. Psychological Medicine 2022:1 View
  49. Lee J, Solomonov N, Banerjee S, Alexopoulos G, Sirey J. Use of Passive Sensing in Psychotherapy Studies in Late Life: A Pilot Example, Opportunities and Challenges. Frontiers in Psychiatry 2021;12 View
  50. Shausan A, Nazarathy Y, Dyda A. Emerging data inputs for infectious diseases surveillance and decision making. Frontiers in Digital Health 2023;5 View
  51. Lee K, Lee T, Yefimova M, Kumar S, Puga F, Azuero A, Kamal A, Bakitas M, Wright A, Demiris G, Ritchie C, Pickering C, Nicholas Dionne-Odom J. Using digital phenotyping to understand health-related outcomes: A scoping review. International Journal of Medical Informatics 2023;174:105061 View
  52. Marciano L, Vocaj E, Bekalu M, La Tona A, Rocchi G, Viswanath K. The Use of Mobile Assessments for Monitoring Mental Health in Youth: Umbrella Review. Journal of Medical Internet Research 2023;25:e45540 View
  53. Chow P, Roller D, Boukhechba M, Shaffer K, Ritterband L, Reilley M, Le T, Kunk P, Bauer T, Gioeli D. Mobile sensing to advance tumor modeling in cancer patients: A conceptual framework. Internet Interventions 2023;34:100644 View
  54. Knights J, Shen J, Mysliwiec V, DuBois H. Associations of smartphone usage patterns with sleep and mental health symptoms in a clinical cohort receiving virtual behavioral medicine care: a retrospective study. Sleep Advances 2023;4(1) View
  55. Torres W, Abbott M, Wang Y, Stuart H. Skin Sensitivity Assessment Using Smartphone Haptic Feedback. IEEE Open Journal of Engineering in Medicine and Biology 2023;4:216 View
  56. Wiedermann M, Rose A, Maier B, Kolb J, Hinrichs D, Brockmann D, Levine B. Evidence for positive long- and short-term effects of vaccinations against COVID-19 in wearable sensor metrics. PNAS Nexus 2023;2(7) View
  57. Zhang X, Lewis S, Carter L, Bucci S. A Digital System (YouXin) to Facilitate Self-Management by People With Psychosis in China: Protocol for a Nonrandomized Validity and Feasibility Study With a Mixed Methods Design. JMIR Research Protocols 2023;12:e45170 View
  58. Gleeson J, McGuckian T, Fernandez D, Fraser M, Pepe A, Taskis R, Alvarez-Jimenez M, Farhall J, Gumley A. Systematic review of early warning signs of relapse and behavioural antecedents of symptom worsening in people living with schizophrenia spectrum disorders. Clinical Psychology Review 2023:102357 View

Books/Policy Documents

  1. Kasparbauer A, Reisner V, Schenk C, Glas A, Lutfi H, Blanco O, Spittler T. The Future Circle of Healthcare. View
  2. Thapa S, Tay L, Hou D. Examining and Exploring the Shifting Nature of Occupational Stress and Well-Being. View
  3. Garatva P, Terhorst Y, Messner E, Karlen W, Pryss R, Baumeister H. Digital Phenotyping and Mobile Sensing. View
  4. Li X, Jiang A. Design, User Experience, and Usability. View
  5. Lăbuşcă L, Herea D, Chiriac H, Lupu N. Magnetic Sensors and Actuators in Medicine. View
  6. Sachin D, Annappa B, Ambesenge S. Proceedings of 7th ASRES International Conference on Intelligent Technologies. View