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

Reviews in Digital Mental Health (247)

Published on in Vol 6, No 2 (2019): February

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/9819, first published .
Mobile Phone and Wearable Sensor-Based mHealth Approaches for Psychiatric Disorders and Symptoms: Systematic Review

Mobile Phone and Wearable Sensor-Based mHealth Approaches for Psychiatric Disorders and Symptoms: Systematic Review

Mobile Phone and Wearable Sensor-Based mHealth Approaches for Psychiatric Disorders and Symptoms: Systematic Review

Authors of this article:

Jussi Seppälä1, 2 Author Orcid Image ;   Ilaria De Vita3 Author Orcid Image ;   Timo Jämsä4, 5, 6 Author Orcid Image ;   Jouko Miettunen1, 5 Author Orcid Image ;   Matti Isohanni1 Author Orcid Image ;   Katya Rubinstein7 Author Orcid Image ;   Yoram Feldman7 Author Orcid Image ;   Eva Grasa8, 9, 10 Author Orcid Image ;   Iluminada Corripio8, 9, 10 Author Orcid Image ;   Jesus Berdun11 Author Orcid Image ;   Enrico D'Amico3 Author Orcid Image ;   M-RESIST Group12 ;   Maria Bulgheroni3 Author Orcid Image
Article Authors Cited by (90) Tweetations (14) Metrics

Journals

  1. Gründahl M, Deckert J, Hein G. Three Questions to Consider Before Applying Ecological Momentary Interventions (EMI) in Psychiatry. Frontiers in Psychiatry 2020;11 View
  2. Pavlova B, Uher R. Assessment of Psychopathology. JAMA Psychiatry 2020;77(6):557 View
  3. Jacobson N, Summers B, Wilhelm S. Digital Biomarkers of Social Anxiety Severity: Digital Phenotyping Using Passive Smartphone Sensors. Journal of Medical Internet Research 2020;22(5):e16875 View
  4. Zulueta J, Leow A, Ajilore O. Real-Time Monitoring: A Key Element in Personalized Health and Precision Health. Focus 2020;18(2):175 View
  5. Artusi C, Imbalzano G, Sturchio A, Pilotto A, Montanaro E, Padovani A, Lopiano L, Maetzler W, Espay A. Implementation of Mobile Health Technologies in Clinical Trials of Movement Disorders: Underutilized Potential. Neurotherapeutics 2020;17(4):1736 View
  6. Rodriguez-Villa E, Torous J. Regulating digital health technologies with transparency: the case for dynamic and multi-stakeholder evaluation. BMC Medicine 2019;17(1) View
  7. Colombo D, Fernández-Álvarez J, Patané A, Semonella M, Kwiatkowska M, García-Palacios A, Cipresso P, Riva G, Botella C. Current State and Future Directions of Technology-Based Ecological Momentary Assessment and Intervention for Major Depressive Disorder: A Systematic Review. Journal of Clinical Medicine 2019;8(4):465 View
  8. Hanssen E, Balvert S, Oorschot M, Borkelmans K, van Os J, Delespaul P, Fett A. An ecological momentary intervention incorporating personalised feedback to improve symptoms and social functioning in schizophrenia spectrum disorders. Psychiatry Research 2020;284:112695 View
  9. Hilty D. Research Directions for Clinical Care and Technology: the JTIBS Research Column. Journal of Technology in Behavioral Science 2020;5(4):303 View
  10. Hidalgo-Mazzei D, Llach C, Vieta E. mHealth in affective disorders: hype or hope? A focused narrative review. International Clinical Psychopharmacology 2020;35(2):61 View
  11. de Zambotti M, Cellini N, Menghini L, Sarlo M, Baker F. Sensors Capabilities, Performance, and Use of Consumer Sleep Technology. Sleep Medicine Clinics 2020;15(1):1 View
  12. Bauer M, Glenn T, Geddes J, Gitlin M, Grof P, Kessing L, Monteith S, Faurholt-Jepsen M, Severus E, Whybrow P. Smartphones in mental health: a critical review of background issues, current status and future concerns. International Journal of Bipolar Disorders 2020;8(1) View
  13. Holtz B, McCarroll A, Mitchell K. Perceptions and Attitudes Toward a Mobile Phone App for Mental Health for College Students: Qualitative Focus Group Study. JMIR Formative Research 2020;4(8):e18347 View
  14. Rubeis G. E-mental health applications for depression: an evidence-based ethical analysis. European Archives of Psychiatry and Clinical Neuroscience 2021;271(3):549 View
  15. Bardram J, Matic A. A Decade of Ubiquitous Computing Research in Mental Health. IEEE Pervasive Computing 2020;19(1):62 View
  16. H. Birk R, Samuel G. Can digital data diagnose mental health problems? A sociological exploration of ‘digital phenotyping’. Sociology of Health & Illness 2020;42(8):1873 View
  17. Hirjak D, Reininghaus U, Braun U, Sack M, Tost H, Meyer-Lindenberg A. Sektorenübergreifende Therapiekonzepte und innovative Technologien: neue Möglichkeiten für die Versorgung von Patienten mit psychischen Erkrankungen. Der Nervenarzt 2022;93(3):288 View
  18. Hilty D, Armstrong C, Edwards-Stewart A, Gentry M, Luxton D, Krupinski E. Sensor, Wearable, and Remote Patient Monitoring Competencies for Clinical Care and Training: Scoping Review. Journal of Technology in Behavioral Science 2021;6(2):252 View
  19. Hilty D, Armstrong C, Luxton D, Gentry M, Krupinski E. A Scoping Review of Sensors, Wearables, and Remote Monitoring For Behavioral Health: Uses, Outcomes, Clinical Competencies, and Research Directions. Journal of Technology in Behavioral Science 2021;6(2):278 View
  20. Aubourg T, Demongeot J, Provost H, Vuillerme N. Exploitation of Outgoing and Incoming Telephone Calls in the Context of Circadian Rhythms of Social Activity Among Elderly People: Observational Descriptive Study. JMIR mHealth and uHealth 2020;8(11):e13535 View
  21. Berger T, Bur O, Krieger T. Internet-Interventionen in der Psychotherapie. Fortschritte der Neurologie · Psychiatrie 2020;88(10):677 View
  22. Isohanni M, Jääskeläinen E, Miller B, Hulkko A, Tiihonen J, Möller H, Hartikainen S, Huhtaniska S, Lieslehto J. Medication management of antipsychotic treatment in schizophrenia—A narrative review. Human Psychopharmacology: Clinical and Experimental 2021;36(2) View
  23. Habets J, Heijmans M, Leentjens A, Simons C, Temel Y, Kuijf M, Kubben P, Herff C. A Long-Term, Real-Life Parkinson Monitoring Database Combining Unscripted Objective and Subjective Recordings. Data 2021;6(2):22 View
  24. Yunusova A, Lai J, Rivera A, Hu S, Labbaf S, Rahmani A, Dutt N, Jain R, Borelli J. Assessing the Mental Health of Emerging Adults Through a Mental Health App: Protocol for a Prospective Pilot Study. JMIR Research Protocols 2021;10(3):e25775 View
  25. Chan E, Sun Y, Aitchison K, Sivapalan S. Mobile App–Based Self-Report Questionnaires for the Assessment and Monitoring of Bipolar Disorder: Systematic Review. JMIR Formative Research 2021;5(1):e13770 View
  26. Maatoug R, Peiffer-Smadja N, Delval G, Brochu T, Pitrat B, Millet B. Ecological Momentary Assessment Using Smartphones in Patients With Depression: Feasibility Study. JMIR Formative Research 2021;5(2):e14179 View
  27. 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
  28. Tonti S, Marzolini B, Bulgheroni M. Smartphone-Based Passive Sensing for Behavioral and Physical Monitoring in Free-Life Conditions: Technical Usability Study. JMIR Biomedical Engineering 2021;6(2):e15417 View
  29. Opoku Asare K, Terhorst Y, Vega J, Peltonen E, Lagerspetz E, Ferreira D. Predicting Depression From Smartphone Behavioral Markers Using Machine Learning Methods, Hyperparameter Optimization, and Feature Importance Analysis: Exploratory Study. JMIR mHealth and uHealth 2021;9(7):e26540 View
  30. Lopez-Morinigo J, Barrigón M, Porras-Segovia A, Ruiz-Ruano V, Escribano Martínez A, Escobedo-Aedo P, Sánchez Alonso S, Mata Iturralde L, Muñoz Lorenzo L, Artés-Rodríguez A, David A, Baca-García E. Use of Ecological Momentary Assessment Through a Passive Smartphone-Based App (eB2) by Patients With Schizophrenia: Acceptability Study. Journal of Medical Internet Research 2021;23(7):e26548 View
  31. Rauschenberg C, Boecking B, Paetzold I, Schruers K, Schick A, van Amelsvoort T, Reininghaus U. A Compassion-Focused Ecological Momentary Intervention for Enhancing Resilience in Help-Seeking Youth: Uncontrolled Pilot Study. JMIR Mental Health 2021;8(8):e25650 View
  32. Lee E, Torous J, De Choudhury M, Depp C, Graham S, Kim H, Paulus M, Krystal J, Jeste D. Artificial Intelligence for Mental Health Care: Clinical Applications, Barriers, Facilitators, and Artificial Wisdom. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging 2021;6(9):856 View
  33. Kozlov E, McDarby M, Prescott M, Altman M. Assessing the Care Modality Preferences and Predictors for Digital Mental Health Treatment Seekers in a Technology-Enabled Stepped Care Delivery System: Cross-sectional Study. JMIR Formative Research 2021;5(9):e30162 View
  34. Barrigon M, Porras-Segovia A, Courtet P, Lopez-Castroman J, Berrouiguet S, Pérez-Rodríguez M, Artes A, Baca-Garcia E. Smartphone-based Ecological Momentary Intervention for secondary prevention of suicidal thoughts and behaviour: protocol for the SmartCrisis V.2.0 randomised clinical trial. BMJ Open 2022;12(9):e051807 View
  35. Stuart T, Hanna J, Gutruf P. Wearable devices for continuous monitoring of biosignals: Challenges and opportunities. APL Bioengineering 2022;6(2) View
  36. 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
  37. Chia A, Zhang M. Digital phenotyping in psychiatry: A scoping review. Technology and Health Care 2022;30(6):1331 View
  38. Fonseka L, Woo B. Wearables in Schizophrenia: Update on Current and Future Clinical Applications. JMIR mHealth and uHealth 2022;10(4):e35600 View
  39. ter Harmsel J, Smulders L, Noordzij M, Swinkels L, Goudriaan A, Popma A, van der Pol T. Forensic Psychiatric Outpatients’ and Therapists’ Perspectives on a Wearable Biocueing App (Sense-IT) as an Addition to Aggression Regulation Therapy: Qualitative Focus Group and Interview Study. JMIR Formative Research 2023;7:e40237 View
  40. Melia R, Monahan L, Duggan J, Bogue J, O’Sullivan M, Young K, Chambers D, McInerney S. Exploring the experiences of mental health professionals engaged in the adoption of mobile health technology in Irish mental health services. BMC Psychiatry 2021;21(1) View
  41. Meyerhoff J, Liu T, Kording K, Ungar L, Kaiser S, Karr C, Mohr D. Evaluation of Changes in Depression, Anxiety, and Social Anxiety Using Smartphone Sensor Features: Longitudinal Cohort Study. Journal of Medical Internet Research 2021;23(9):e22844 View
  42. 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
  43. Herrman H, Patel V, Kieling C, Berk M, Buchweitz C, Cuijpers P, Furukawa T, Kessler R, Kohrt B, Maj M, McGorry P, Reynolds C, Weissman M, Chibanda D, Dowrick C, Howard L, Hoven C, Knapp M, Mayberg H, Penninx B, Xiao S, Trivedi M, Uher R, Vijayakumar L, Wolpert M. Time for united action on depression: a Lancet–World Psychiatric Association Commission. The Lancet 2022;399(10328):957 View
  44. Szinay D, Forbes C, Busse H, DeSmet A, Smit E, König L. Is the uptake, engagement, and effectiveness of exclusively mobile interventions for the promotion of weight‐related behaviors equal for all? A systematic review. Obesity Reviews 2023;24(3) View
  45. 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
  46. Chen Z, Kulkarni P, Galatzer-Levy I, Bigio B, Nasca C, Zhang Y. Modern views of machine learning for precision psychiatry. Patterns 2022;3(11):100602 View
  47. Anmella G, Faurholt‐Jepsen M, Hidalgo‐Mazzei D, Radua J, Passos I, Kapczinski F, Minuzzi L, Alda M, Meier S, Hajek T, Ballester P, Birmaher B, Hafeman D, Goldstein T, Brietzke E, Duffy A, Haarman B, López‐Jaramillo C, Yatham L, Lam R, Isometsa E, Mansur R, McIntyre R, Mwangi B, Vieta E, Kessing L. Smartphone‐based interventions in bipolar disorder: Systematic review and meta‐analyses of efficacy. A position paper from the International Society for Bipolar Disorders (ISBD) Big Data Task Force. Bipolar Disorders 2022;24(6):580 View
  48. Berger T, Bur O, Krieger T. Internet-Interventionen in der Psychotherapie. PSYCH up2date 2019;13(05):435 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. Furukawa T, Bighelli I. Digital aids for relapse prevention in schizophrenia. The Lancet Psychiatry 2022;9(6):424 View
  51. Thati R, Dhadwal A, Kumar P, P S. A novel multi-modal depression detection approach based on mobile crowd sensing and task-based mechanisms. Multimedia Tools and Applications 2023;82(4):4787 View
  52. Nepal S, Wang W, Sharma B, Paudel P. Current practices in mental health sensing. XRDS: Crossroads, The ACM Magazine for Students 2021;28(1):28 View
  53. Moukaddam N, Sano A, Salas R, Hammal Z, Sabharwal A. Turning data into better mental health: Past, present, and future. Frontiers in Digital Health 2022;4 View
  54. Grasa E, Seppälä J, Alonso-Solis A, Haapea M, Isohanni M, Miettunen J, Caro Mendivelso J, Almazan C, Rubinstein K, Caspi A, Unoka Z, Farkas K, Usall J, Ochoa S, van der Graaf S, Jewell C, Triantafillou A, Stevens M, Reixach E, Berdun J, Corripio I. m-RESIST, a Mobile Therapeutic Intervention for Treatment-Resistant Schizophrenia: Feasibility, Acceptability, and Usability Study. JMIR Formative Research 2023;7:e46179 View
  55. Rajinikanth A, Clark D, Kapsetaki M. A Novel System to Monitor Tic Attacks for Tourette Syndrome Using Machine Learning and Wearable Technology: Preliminary Survey Study and Proposal for a New Sensing Device. JMIR Neurotechnology 2023;2:e43351 View
  56. 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
  57. Sander M. Digital Health Applications in der Neurologie und Psychiatrie. Nervenheilkunde 2023;42(09):642 View
  58. Kjell O, Kjell K, Schwartz H. Beyond rating scales: With targeted evaluation, large language models are poised for psychological assessment. Psychiatry Research 2024;333:115667 View
  59. Zierer C, Behrendt C, Lepach-Engelhardt A. Digital biomarkers in depression: A systematic review and call for standardization and harmonization of feature engineering. Journal of Affective Disorders 2024;356:438 View
  60. Khosravi M, Azar G. A systematic review of reviews on the advantages of mHealth utilization in mental health services: A viable option for large populations in low-resource settings. Cambridge Prisms: Global Mental Health 2024;11 View
  61. Monosov I, Zimmermann J, Frank M, Mathis M, Baker J. Ethological computational psychiatry: Challenges and opportunities. Current Opinion in Neurobiology 2024;86:102881 View
  62. Jin M, Shi P, Sun Z, Zhao N, Shi M, Wu M, Ye C, Lin C, Fu L. Advancements in Polymer-Assisted Layer-by-Layer Fabrication of Wearable Sensors for Health Monitoring. Sensors 2024;24(9):2903 View
  63. Bidargaddi N, Leibbrandt R, Paget T, Verjans J, Looi J, Lipschitz J. Remote sensing mental health: A systematic review of factors essential to clinical translation from validation research. DIGITAL HEALTH 2024;10 View
  64. Grosman-Rimon L, Wegier P. With advancement in health technology comes great responsibility – Ethical and safety considerations for using digital health technology: A narrative review. Medicine 2024;103(33):e39136 View
  65. Hagenberg J, Brückl T, Erhart M, Kopf-Beck J, Ködel M, Rehawi G, Röh-Karamihalev S, Sauer S, Yusupov N, Rex-Haffner M, Spoormaker V, Sämann P, Binder E, Knauer-Arloth J. Dissecting depression symptoms: Multi-omics clustering uncovers immune-related subgroups and cell-type specific dysregulation. Brain, Behavior, and Immunity 2025;123:353 View
  66. Edler J, Winter M, Steinmetz H, Cohrdes C, Baumeister H, Pryss R. Predicting Depressive Symptoms Using GPS-Based Regional Data in Germany With the CORONA HEALTH App During the COVID-19 Pandemic: Cross-Sectional Study. Interactive Journal of Medical Research 2024;13:e53248 View
  67. Amourizi F, Dashtian K, Zare-Dorabei R, Hajati S. Transformative personalized oxalate biomarker analysis through a wrist-worn microneedle device integrated with duplex nanozyme toolbox. Sensors and Actuators B: Chemical 2025;423:136731 View
  68. Fechtelpeter J, Rauschenberg C, Jalalabadi H, Boecking B, van Amelsvoort T, Reininghaus U, Durstewitz D, Koppe G. A control theoretic approach to evaluate and inform ecological momentary interventions. International Journal of Methods in Psychiatric Research 2024;33(4) View
  69. Bosma C, Wojcik C, Haigh E. Evaluating Individual Differences in Emotion Regulation in Response to Sadness Using Digital Phenotyping. Journal of Technology in Behavioral Science 2024 View
  70. Takeshige M, Oka T, Ohwan M, Hirai K. Exploring the Utility of a Machine Learning Approach with Mobile‐Based Cognitive Function Tasks for Detecting Depression. Japanese Psychological Research 2024 View

Books/Policy Documents

  1. Iyawa G, Ondiek C, Osakwe J. Smart Medical Data Sensing and IoT Systems Design in Healthcare. View
  2. Iyawa G, Langan-Martin J, Sevalie S, Masikara W. Impacts of Information Technology on Patient Care and Empowerment. View
  3. Iyawa G, Langan-Martin J, Sevalie S, Masikara W. Research Anthology on Mental Health Stigma, Education, and Treatment. View
  4. Anmella G, Hidalgo-Mazzei D, Vieta E. Digital Mental Health. View
  5. Ranallo P, Tenenbaum J. Mental Health Informatics. View
  6. Hilty D, Peled A, Luxton D. Tasman’s Psychiatry. View
  7. Mondragón-González S, Burguière E, N’diaye K. Machine Learning for Brain Disorders. View
  8. Kalyani G, Suneetha M, Janakiramaiah B, Battineni G. Computational Methods in Psychiatry. View
  9. Hilty D, Peled A, Luxton D. Tasman’s Psychiatry. View
  10. Perna G, Nemeroff C. Precision Psychiatry: Using Neuroscience Insights to Inform Personally Tailored, Measurement-Based Care. View