Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/42672, first published .
Wearable Artificial Intelligence for Anxiety and Depression: Scoping Review

Wearable Artificial Intelligence for Anxiety and Depression: Scoping Review

Wearable Artificial Intelligence for Anxiety and Depression: Scoping Review

Journals

  1. Anmella G, Corponi F, Li B, Mas A, Sanabra M, Pacchiarotti I, Valentí M, Grande I, Benabarre A, Giménez-Palomo A, Garriga M, Agasi I, Bastidas A, Cavero M, Fernández-Plaza T, Arbelo N, Bioque M, García-Rizo C, Verdolini N, Madero S, Murru A, Amoretti S, Martínez-Aran A, Ruiz V, Fico G, De Prisco M, Oliva V, Solanes A, Radua J, Samalin L, Young A, Vieta E, Vergari A, Hidalgo-Mazzei D. Exploring Digital Biomarkers of Illness Activity in Mood Episodes: Hypotheses Generating and Model Development Study. JMIR mHealth and uHealth 2023;11:e45405 View
  2. Diaz-Ramos R, Noriega I, Trejo L, Stroulia E, Cao B. Using Wearable Devices and Speech Data for Personalized Machine Learning in Early Detection of Mental Disorders: Protocol for a Participatory Research Study. JMIR Research Protocols 2023;12:e48210 View
  3. Alexopoulos G. Artificial Intelligence in Geriatric Psychiatry Through the Lens of Contemporary Philosophy. The American Journal of Geriatric Psychiatry 2024;32(3):293 View
  4. Broulidakis M, Kiprijanovska I, Severs L, Stankoski S, Gjoreski M, Mavridou I, Gjoreski H, Cox S, Bradwell D, Stone J, Nduka C. Optomyography-based sensing of facial expression derived arousal and valence in adults with depression. Frontiers in Psychiatry 2023;14 View
  5. Correia Firmino L, Sousa M. Caracterização dos Atendimentos de Saúde Mental de uma Unidade Básica de Saúde na Paraíba: Um Estudo Documental. ID on line. Revista de psicologia 2023;17(68):87 View
  6. Avula V, Amalakanti S. Artificial intelligence in psychiatry, present trends, and challenges: An updated review. Archives of Mental Health 2023 View
  7. Duarte Luiz J, Manassi C, Magnani M, Cruz A, Pimentel T, Verruck S. Lactiplantibacillus plantarum as a promising adjuvant for neurological disorders therapy through the brain-gut axis and related action pathways. Critical Reviews in Food Science and Nutrition 2023:1 View
  8. Abd-Alrazaq A, AlSaad R, Shuweihdi F, Ahmed A, Aziz S, Sheikh J. Systematic review and meta-analysis of performance of wearable artificial intelligence in detecting and predicting depression. npj Digital Medicine 2023;6(1) View
  9. Vieira F, Lotufo Neto F. Um Estudo Sobre o Conceito de Angústia. ID on line. Revista de psicologia 2023;17(67):113 View
  10. Abd-alrazaq A, Alajlani M, Ahmad R, AlSaad R, Aziz S, Ahmed A, Alsahli M, Damseh R, Sheikh J. The Performance of Wearable AI in Detecting Stress Among Students: Systematic Review and Meta-Analysis. Journal of Medical Internet Research 2024;26:e52622 View
  11. Dimitri P, Savage M. Artificial intelligence in paediatric endocrinology: conflict or cooperation. Journal of Pediatric Endocrinology and Metabolism 2024;37(3):209 View
  12. Wadle L, Ebner-Priemer U, Foo J, Yamamoto Y, Streit F, Witt S, Frank J, Zillich L, Limberger M, Ablimit A, Schultz T, Gilles M, Rietschel M, Sirignano L. Speech Features as Predictors of Momentary Depression Severity in Patients With Depressive Disorder Undergoing Sleep Deprivation Therapy: Ambulatory Assessment Pilot Study. JMIR Mental Health 2024;11:e49222 View
  13. Bryan A, Heinz M, Salzhauer A, Price G, Tlachac M, Jacobson N. Behind the Screen: A Narrative Review on the Translational Capacity of Passive Sensing for Mental Health Assessment. Biomedical Materials & Devices 2024;2(2):778 View
  14. Izu L, Scholtz B, Fashoro I. Wearables and Their Potential to Transform Health Management: A Step towards Sustainable Development Goal 3. Sustainability 2024;16(5):1850 View
  15. Chen J, Yuan D, Dong R, Cai J, Ai Z, Zhou S. Artificial intelligence significantly facilitates development in the mental health of college students: a bibliometric analysis. Frontiers in Psychology 2024;15 View
  16. Zafar F, Fakhare Alam L, Vivas R, Wang J, Whei S, Mehmood S, Sadeghzadegan A, Lakkimsetti M, Nazir Z. The Role of Artificial Intelligence in Identifying Depression and Anxiety: A Comprehensive Literature Review. Cureus 2024 View
  17. Ahmed M, Hasan T, Islam S, Ahmed N. Investigating Rhythmicity in App Usage to Predict Depressive Symptoms: Protocol for Personalized Framework Development and Validation Through a Countrywide Study. JMIR Research Protocols 2024;13:e51540 View
  18. Hurwitz E, Butzin-Dozier Z, Master H, O'Neil S, Walden A, Holko M, Patel R, Haendel M. Harnessing Consumer Wearable Digital Biomarkers for Individualized Recognition of Postpartum Depression Using the All of Us Research Program Data Set: Cross-Sectional Study. JMIR mHealth and uHealth 2024;12:e54622 View
  19. Huțul T, Popescu A, Karner‐Huțuleac A, Holman A, Huțul A. Who's willing to lay on the virtual couch? Attitudes, anthropomorphism and need for human interaction as factors of intentions to use chatbots for psychotherapy. Counselling and Psychotherapy Research 2024;24(4):1479 View
  20. Haghayegh F, Norouziazad A, Haghani E, Feygin A, Rahimi R, Ghavamabadi H, Sadighbayan D, Madhoun F, Papagelis M, Felfeli T, Salahandish R. Revolutionary Point‐of‐Care Wearable Diagnostics for Early Disease Detection and Biomarker Discovery through Intelligent Technologies. Advanced Science 2024 View
  21. Ahmed N, Reagu S, Alkhoori S, Cherchali A, Purushottamahanti P, Siddiqui U. Improving Mental Health Outcomes in Patients with Major Depressive Disorder in the Gulf States: A Review of the Role of Electronic Enablers in Monitoring Residual Symptoms. Journal of Multidisciplinary Healthcare 2024;Volume 17:3341 View
  22. Schulz D, Lillo-Navarro C, Slors M, Hrabéczy A, Reuter M. Understanding societal challenges: a NeurotechEU perspective. Frontiers in Neuroscience 2024;18 View
  23. Borghare P, Methwani D, Pathade A. A Comprehensive Review on Harnessing Wearable Technology for Enhanced Depression Treatment. Cureus 2024 View
  24. Xian X, Chang A, Xiang Y, Liu M. Debate and Dilemmas Regarding Generative AI in Mental Health Care: Scoping Review. Interactive Journal of Medical Research 2024;13:e53672 View
  25. Reutens S, Dandolo C, Looi R, Karystianis G, Looi J. The uses and misuses of artificial intelligence in psychiatry: Promises and challenges. Australasian Psychiatry 2024 View
  26. Walschots Q, Zarchev M, Unkel M, Kamperman A. Using Wearable Technology to Detect, Monitor, and Predict Major Depressive Disorder—A Scoping Review and Introductory Text for Clinical Professionals. Algorithms 2024;17(9):408 View
  27. Hartnagel L, Emden D, Foo J, Streit F, Witt S, Frank J, Limberger M, Schmitz S, Gilles M, Rietschel M, Hahn T, Ebner-Priemer U, Sirignano L. Momentary Depression-Severity Prediction in Acutely Depressed Patients undergoing Sleep Deprivation Therapy: Speech-based Machine Learning (Preprint). JMIR Mental Health 2024 View
  28. Pavlopoulos A, Rachiotis T, Maglogiannis I. An Overview of Tools and Technologies for Anxiety and Depression Management Using AI. Applied Sciences 2024;14(19):9068 View
  29. Lipschitz J, Lin S, Saghafian S, Pike C, Burdick K. Digital phenotyping in bipolar disorder: Using longitudinal Fitbit data and personalized machine learning to predict mood symptomatology. Acta Psychiatrica Scandinavica 2024 View
  30. Dias S, Jelinek H, Hadjileontiadis L, Saikia M. Wearable neurofeedback acceptance model for students’ stress and anxiety management in academic settings. PLOS ONE 2024;19(10):e0304932 View
  31. Kim H, Cho G. Computer-Assisted Mental Health Solutions in Depression Treatment. Journal of Korean Maternal and Child Health 2024;28(4):150 View
  32. Xie X, Fu J, Chen L, Gao Z, Zhang R, Li G. Assessment tools of the fear of falling: A scoping review. Geriatric Nursing 2024;60:643 View
  33. Paraschiv E, Băjenaru L, Petrache C, Bica O, Nicolau D. AI-Driven Neuro-Monitoring: Advancing Schizophrenia Detection and Management Through Deep Learning and EEG Analysis. Future Internet 2024;16(11):424 View
  34. Chen T. Can heart rate sequences from wearable devices predict day-long mental states in higher education students: a signal processing and machine learning case study at a UK university. Brain Informatics 2024;11(1) View

Books/Policy Documents

  1. Pimpalkar A, Gandhewar N, Shelke N, Somkunwar R, Raymond V. Intelligent Solutions for Cognitive Disorders. View
  2. Campos T, Monsalve L. Advances in Bioengineering and Clinical Engineering. View