Published on in Vol 9, No 10 (2021): October
Preprints (earlier versions) of this paper are
available at
https://preprints.jmir.org/preprint/24872, first published
.

Journals
- Ahmed A, Ramesh J, Ganguly S, Aburukba R, Sagahyroon A, Aloul F. Investigating the Feasibility of Assessing Depression Severity and Valence-Arousal with Wearable Sensors Using Discrete Wavelet Transforms and Machine Learning. Information 2022;13(9):406 View
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- Lee T, Kim G, Choi M. Identification of Geriatric Depression and Anxiety Using Activity Tracking Data and Minimal Geriatric Assessment Scales. Applied Sciences 2022;12(5):2488 View
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- Tonn P, Seule L, Degani Y, Herzinger S, Klein A, Schulze N. Digital Content-Free Speech Analysis Tool to Measure Affective Distress in Mental Health: Evaluation Study. JMIR Formative Research 2022;6(8):e37061 View
- Neumann D, Tiberius V, Biendarra F. Adopting wearables to customize health insurance contributions: a ranking-type Delphi. BMC Medical Informatics and Decision Making 2022;22(1) View
- Cotes R, Boazak M, Griner E, Jiang Z, Kim B, Bremer W, Seyedi S, Bahrami Rad A, Clifford G. Multimodal Assessment of Schizophrenia and Depression Utilizing Video, Acoustic, Locomotor, Electroencephalographic, and Heart Rate Technology: Protocol for an Observational Study. JMIR Research Protocols 2022;11(7):e36417 View
- Dhinagaran D, Martinengo L, Ho M, Joty S, Kowatsch T, Atun R, Tudor Car L. Designing, Developing, Evaluating, and Implementing a Smartphone-Delivered, Rule-Based Conversational Agent (DISCOVER): Development of a Conceptual Framework. JMIR mHealth and uHealth 2022;10(10):e38740 View
- Choi J, Lee S, Kim S, Kim D, Kim H. Depressed Mood Prediction of Elderly People with a Wearable Band. Sensors 2022;22(11):4174 View
- Phiri B, Fèvre D, Hidano A. Uptrend in global managed honey bee colonies and production based on a six-decade viewpoint, 1961–2017. Scientific Reports 2022;12(1) View
- Maatoug R, Oudin A, Adrien V, Saudreau B, Bonnot O, Millet B, Ferreri F, Mouchabac S, Bourla A. Digital phenotype of mood disorders: A conceptual and critical review. Frontiers in Psychiatry 2022;13 View
- Dillenseger A, Weidemann M, Trentzsch K, Inojosa H, Haase R, Schriefer D, Voigt I, Scholz M, Akgün K, Ziemssen T. Digital Biomarkers in Multiple Sclerosis. Brain Sciences 2021;11(11):1519 View
- Modde Epstein C, McCoy T. Linking Electronic Health Records With Wearable Technology From the All of Us Research Program. Journal of Obstetric, Gynecologic & Neonatal Nursing 2023;52(2):139 View
- Watanabe K, Tsutsumi A. The Passive Monitoring of Depression and Anxiety Among Workers Using Digital Biomarkers Based on Their Physical Activity and Working Conditions: 2-Week Longitudinal Study. JMIR Formative Research 2022;6(11):e40339 View
- Takano A, Ono K, Nozawa K, Sato M, Onuki M, Sese J, Yumoto Y, Matsushita S, Matsumoto T. Wearable Sensor and Mobile App–Based mHealth Approach for Investigating Substance Use and Related Factors in Daily Life: Protocol for an Ecological Momentary Assessment Study. JMIR Research Protocols 2023;12:e44275 View
- 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
- Kim E, Jenness J, Miller A, Halabi R, de Zambotti M, Bagot K, Baker F, Pratap A. Association of Demographic and Socioeconomic Indicators With the Use of Wearable Devices Among Children. JAMA Network Open 2023;6(3):e235681 View
- Wang S, Feng M, Fang Y, Lv L, Sun G, Cheng S, Huang W, Yang S, Guo P, Qian M, Chen H. Effects of chronotype on antidepressant treatment and symptoms in patients with depression: a multicenter, parallel, controlled study. BMC Psychiatry 2023;23(1) View
- Ricka N, Pellegrin G, Fompeyrine D, Lahutte B, Geoffroy P. Predictive biosignature of major depressive disorder derived from physiological measurements of outpatients using machine learning. Scientific Reports 2023;13(1) View
- 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
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- Yeung A, Torkamani A, Butte A, Glicksberg B, Schuller B, Rodriguez B, Ting D, Bates D, Schaden E, Peng H, Willschke H, van der Laak J, Car J, Rahimi K, Celi L, Banach M, Kletecka-Pulker M, Kimberger O, Eils R, Islam S, Wong S, Wong T, Gao W, Brunak S, Atanasov A. The promise of digital healthcare technologies. Frontiers in Public Health 2023;11 View
- Tao Z, Sun N, Yuan Z, Chen Z, Liu J, Wang C, Li S, Ma X, Ji B, Li K. Research on a New Intelligent and Rapid Screening Method for Depression Risk in Young People Based on Eye Tracking Technology. Brain Sciences 2023;13(10):1415 View
- Bertl M, Bignoumba N, Ross P, Yahia S, Draheim D. Evaluation of deep learning-based depression detection using medical claims data. Artificial Intelligence in Medicine 2024;147:102745 View
- Price G, Heinz M, Song S, Nemesure M, Jacobson N. Using digital phenotyping to capture depression symptom variability: detecting naturalistic variability in depression symptoms across one year using passively collected wearable movement and sleep data. Translational Psychiatry 2023;13(1) View
- Piccin J, Viduani A, Buchweitz C, Pereira R, Zimerman A, Amando G, Cosenza V, Ferreira L, McMahon N, Melo R, Richter D, Reckziegel F, Rohrsetzer F, Souza L, Tonon A, Costa-Valle M, Zajkowska Z, Araújo R, Hauser T, van Heerden A, Hidalgo M, Kohrt B, Mondelli V, Swartz J, Fisher H, Kieling C. Prospective Follow-Up of Adolescents With and at Risk for Depression: Protocol and Methods of the Identifying Depression Early in Adolescence Risk Stratified Cohort Longitudinal Assessments. JAACAP Open 2024;2(2):145 View
- Price G, Heinz M, Collins A, Jacobson N. Detecting major depressive disorder presence using passively-collected wearable movement data in a nationally-representative sample. Psychiatry Research 2024;332:115693 View
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- Barata F, Shim J, Wu F, Langer P, Fleisch E. The Bitemporal Lens Model—toward a holistic approach to chronic disease prevention with digital biomarkers. JAMIA Open 2024;7(2) View
- Choo M, Park D, Cho M, Bae S, Kim J, Han D. Exploring a multimodal approach for utilizing digital biomarkers for childhood mental health screening. Frontiers in Psychiatry 2024;15 View
- Dong T, Yu C, Mao Q, Han F, Yang Z, Yang Z, Pires N, Wei X, Jing W, Lin Q, Hu F, Hu X, Zhao L, Jiang Z. Advances in biosensors for major depressive disorder diagnostic biomarkers. Biosensors and Bioelectronics 2024;258:116291 View
- 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
- 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
- Huang J, Wang H, Wu Q, Yin J, Zhou H, He Y. Clinical research on neurological and psychiatric diagnosis and monitoring using wearable devices: A literature review. Interdisciplinary Medicine 2024;2(4) View
- Newby D, Taylor N, Joyce D, Winchester L. Optimising the use of electronic medical records for large scale research in psychiatry. Translational Psychiatry 2024;14(1) View
- Park Y, Park S, Lee M. Effectiveness of artificial intelligence in detecting and managing depressive disorders: Systematic review. Journal of Affective Disorders 2024;361:445 View
- Li B, Guo S, Xu H, Zhou Y, Zhang M, Wang J, Chen Y, Chen H, Song J, Tan S. Abnormal circadian rhythm of heart rate variability and their association with symptoms in patients with major depressive disorder. Journal of Affective Disorders 2024;362:14 View
- Janssen Daalen J, van den Bergh R, Prins E, Moghadam M, van den Heuvel R, Veen J, Mathur S, Meijerink H, Mirelman A, Darweesh S, Evers L, Bloem B. Digital biomarkers for non-motor symptoms in Parkinson’s disease: the state of the art. npj Digital Medicine 2024;7(1) View
- Rykov Y, Ng K, Patterson M, Gangwar B, Kandiah N. Predicting the severity of mood and neuropsychiatric symptoms from digital biomarkers using wearable physiological data and deep learning. Computers in Biology and Medicine 2024;180:108959 View
- Shin D, Kim H, Lee S, Cho Y, Jung W. Using Large Language Models to Detect Depression From User-Generated Diary Text Data as a Novel Approach in Digital Mental Health Screening: Instrument Validation Study. Journal of Medical Internet Research 2024;26:e54617 View
- Kume Y, Kodama A, Arai S, Nagaoka M, Sato A, Saito A, Ota H, Ando H. Improvement of social frailty is associated with stability of nonparametric characteristics of the rest-activity rhythm and improvement of the usual walking ability in the elderly. Chronobiology International 2024;41(9):1239 View
- dos Santos M, Heckler W, Bavaresco R, Barbosa J. Machine learning applied to digital phenotyping: A systematic literature review and taxonomy. Computers in Human Behavior 2024;161:108422 View
- 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
- Hackett K, Xu S, McKniff M, Paglia L, Barnett I, Giovannetti T. Mobility-Based Smartphone Digital Phenotypes for Unobtrusively Capturing Everyday Cognition, Mood, and Community Life-Space in Older Adults: Feasibility, Acceptability, and Preliminary Validity Study. JMIR Human Factors 2024;11:e59974 View
- Ni W, Nassikas N, Fiffer M, Synn A, Baker N, Coull B, Kang C, Koutrakis P, Rice M. Associations of Personal Hourly Exposures to Air Temperature and Pollution with Resting Heart Rate in Chronic Obstructive Pulmonary Disease. Environmental Science & Technology 2024;58(41):18145 View
- Lee J, Kim J, Ory M. The impact of immersive virtual reality meditation for depression and anxiety among inpatients with major depressive and generalized anxiety disorders. Frontiers in Psychology 2024;15 View
- Lim D, Jeong J, Song Y, Cho C, Yeom J, Lee T, Lee J, Lee H, Kim J. Accurately predicting mood episodes in mood disorder patients using wearable sleep and circadian rhythm features. npj Digital Medicine 2024;7(1) View
- Minaeva O, Riese H, Booij S, Lamers F, Giltay E, Scheer F, Hu K. Fractal motor activity during wakefulness and sleep: a window into depression recency and symptom recurrence. Psychological Medicine 2024;54(15):4429 View
- Sameh A, Rostami M, Oussalah M, Korpelainen R, Farrahi V. Digital phenotypes and digital biomarkers for health and diseases: a systematic review of machine learning approaches utilizing passive non-invasive signals collected via wearable devices and smartphones. Artificial Intelligence Review 2024;58(2) View
- Lee H, Otero-Leon D, Dong H, Stringfellow E, Jalali M. Uncovering Patterns in Overdose Deaths: An Analysis of Spike Identification in Fatal Drug Overdose Data in Massachusetts, 2017-2023. Public Health Reports® 2024 View
- Ramesh J, Solatidehkordi Z, Sagahyroon A, Aloul F. Multimodal Neural Network Analysis of Single-Night Sleep Stages for Screening Obstructive Sleep Apnea. Applied Sciences 2025;15(3):1035 View
- Yeom J, Kim H, Pack S, Lee H, Cheong T, Cho C. Exploring the Psychological and Physiological Insights Through Digital Phenotyping by Analyzing the Discrepancies Between Subjective Insomnia Severity and Activity-Based Objective Sleep Measures: Observational Cohort Study. JMIR Mental Health 2025;12:e67478 View
- Jin Y, Huang Y. Long-Term Vital Sign Tracking Study of Depression Patients Based on Wearable Devices. International Journal of Crowd Science 2025;9(1):56 View
- Yang L, Zhang M, Jia L, Yan Z, Yin Q. Understanding digital therapeutics in disease self-management: A systematic literature review. Technology in Society 2025;81:102831 View
- Um J, Park J, Lee D, Ahn J, Baek J. Machine Learning Models to Identify Individuals With Imminent Suicide Risk Using a Wearable Device: A Pilot Study. Psychiatry Investigation 2025;22(2):156 View
- Woll S, Birkenmaier D, Biri G, Nissen R, Lutz L, Schroth M, Ebner-Priemer U, Giurgiu M. Applying AI in the Context of the Association Between Device-Based Assessment of Physical Activity and Mental Health: Systematic Review. JMIR mHealth and uHealth 2025;13:e59660 View
- Lee Y, Lee J. Real-time monitoring to predict depressive symptoms: study protocol. Frontiers in Psychiatry 2025;15 View
- Kargarandehkordi A, Li S, Lin K, Phillips K, Benzo R, Washington P. Fusing Wearable Biosensors with Artificial Intelligence for Mental Health Monitoring: A Systematic Review. Biosensors 2025;15(4):202 View
- Yang M, Ngai E, Hu X, Hu B, Liu J, Gelenbe E, Leung V. Digital Phenotyping and Feature Extraction on Smartphone Data for Depression Detection. Proceedings of the IEEE 2024;112(12):1773 View
- de Vries H, van der Wal S, Delahaij R, Venrooij W, Kamphuis W. Real-time monitoring of military health and readiness: a perspective on future research. Frontiers in Digital Health 2025;7 View
- Garzón-Partida A, Magaña-Plascencia K, Martínez-Fernández D, García-Estrada J, Luquin S, Fernández-Quezada D. Development of a Cohesive Predictive Model for Substance Use Disorder Rehabilitation Using Passive Digital Biomarkers, Psychological Assessments, and Automated Facial Emotion Recognition: Protocol for a Prospective Cohort Study. JMIR Research Protocols 2025;14:e71374 View
- Maekawa H, Kume Y. Predicting Social Frailty in Older Adults Using Fitbit-Derived Circadian and Heart Rate Biomarkers: Cross-Sectional Study. JMIR Formative Research 2025;9:e71393 View
- Garzón-Partida A, Padilla-Gómez C, Martínez-Fernández D, García-Estrada J, Luquin S, Fernández-Quezada D. The implementation of digital biomarkers in the diagnosis, treatment and monitoring of mood disorders: a narrative review. Frontiers in Digital Health 2025;7 View
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- Kang B, Park M, Kim J, Yoon S, Heo S, Kang C, Lee S, Choi Y, Hong D. Exploring Factors Related to Social Isolation Among Older Adults in the Predementia Stage Using Ecological Momentary Assessments and Actigraphy: Machine Learning Approach. Journal of Medical Internet Research 2025;27:e69379 View
- George S. Chaos to clarity: interpreting time series complexity metrics with an application to depression. Discover Mental Health 2025;5(1) View
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- Zhao X, Lou Z, Shah P, Wu C, Liu R, Xie W, Zhang S. Integration of Multi-Modal Biosensing Approaches for Depression: Current Status, Challenges, and Future Perspectives. Sensors 2025;25(15):4858 View
- McDuff D, Galatzer-Levy I, Thomson S, Barakat A, Heneghan C, Abdel-Ghaffar S, Sunshine J, Poh M, Sunden L, Hernandez J, Jiang A, Liu X, Winbush A, Nelson B, Allen N. Evidence of differences in diurnal electrodermal, temperature and heart rate patterns by mental health status in free-living data. BMJ Mental Health 2025;28(1):e301307 View
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Books/Policy Documents
Conference Proceedings
- Sim S, Paranjpe T, Roberts N, Zhao M. 2022 21st IEEE International Conference on Machine Learning and Applications (ICMLA). Exploring Edge Machine Learning-based Stress Prediction using Wearable Devices View
- Robert K, Takahara T, Sokout H. ETLTC2024 INTERNATIONAL CONFERENCE SERIES ON ICT, ENTERTAINMENT TECHNOLOGIES, AND INTELLIGENT INFORMATION MANAGEMENT IN EDUCATION AND INDUSTRY. Fostering mental wellness: Early detection of depression by using a wearable device View
- Chen Y, Verbert K, Gerling K, Vanden Abeele M, Vanden Abeele V. Proceedings of the 30th International Conference on Intelligent User Interfaces. Will Health Experts Adopt a Clinical Decision Support System for Game-Based Digital Biomarkers? Investigating the Impact of Different Explanations on Perceived Ease-of-Use, Perceived Usefulness, and Trust View
- Karuppannan S, Savarimuthu S. INTERNATIONAL CONFERENCE ON GREEN COMPUTING FOR COMMUNICATION TECHNOLOGIES (ICGCCT – 2024). Machine learning-based classification of depression and schizophrenia from actigraph signals View
- Ouzar Y, Nineuil C, Boualeb F, Pierson E, Amad A, Daoudi M. 2025 IEEE 19th International Conference on Automatic Face and Gesture Recognition (FG). Wearable-Derived Behavioral and Physiological Biomarkers for Classifying Unipolar and Bipolar Depression Severity View
- Shah A, Tomberg V. Proceedings of the 36th Annual Conference of the European Association of Cognitive Ergonomics. Dynamic User Modelling - Leveraging Digital Biomarkers to Infer Psychosocial Factors to Support JITAIs View
