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

Pilot studies (ehealth) (266) Attention Deficit Disorder (ADD/ADHD) (78) Development and Evaluation of Research Methods, Instruments and Tools (648) Wearable Devices and Sensors (1011) mHealth for Data Collection and Research (1088) Machine Learning (1765) Formative Evaluation of Digital Health Interventions (2854)

Published on in Vol 6, No 4 (2022): April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/35803, first published .
Objective Measurement of Hyperactivity Using Mobile Sensing and Machine Learning: Pilot Study

Objective Measurement of Hyperactivity Using Mobile Sensing and Machine Learning: Pilot Study

Objective Measurement of Hyperactivity Using Mobile Sensing and Machine Learning: Pilot Study

Authors of this article:

Oliver Lindhiem1 Author Orcid Image ;   Mayank Goel2 Author Orcid Image ;   Sam Shaaban3 Author Orcid Image ;   Kristie J Mak4 Author Orcid Image ;   Prerna Chikersal2 Author Orcid Image ;   Jamie Feldman4 Author Orcid Image ;   Jordan L Harris4 Author Orcid Image
Article Authors Cited by (11) Tweetations (8) Metrics

Journals

  1. Park C, Rouzi M, Atique M, Finco M, Mishra R, Barba-Villalobos G, Crossman E, Amushie C, Nguyen J, Calarge C, Najafi B. Machine Learning-Based Aggression Detection in Children with ADHD Using Sensor-Based Physical Activity Monitoring. Sensors 2023;23(10):4949 View
  2. Arakawa R, Ahuja K, Mak K, Thompson G, Shaaban S, Lindhiem O, Goel M. LemurDx. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2023;7(2):1 View
  3. Bibbo D, De Marchis C, Schmid M, Ranaldi S. Machine learning to detect, stage and classify diseases and their symptoms based on inertial sensor data: a mapping review. Physiological Measurement 2023;44(12):12TR01 View
  4. Salazar de Pablo G, Iniesta R, Bellato A, Caye A, Dobrosavljevic M, Parlatini V, Garcia-Argibay M, Li L, Cabras A, Haider Ali M, Archer L, Meehan A, Suleiman H, Solmi M, Fusar-Poli P, Chang Z, Faraone S, Larsson H, Cortese S. Individualized prediction models in ADHD: a systematic review and meta-regression. Molecular Psychiatry 2024;29(12):3865 View
  5. Cibrian F, Monteiro E, Lakes K. Digital assessments for children and adolescents with ADHD: a scoping review. Frontiers in Digital Health 2024;6 View
  6. Toki E, Zakopoulou V, Tatsis G, Pange J. Automated Detection of Neurodevelopmental Disorders Using Face-to-Face Mobile Technology Among Typically Developing Greek Children: Randomized Controlled Trial. JMIR Formative Research 2024;8:e53465 View
  7. González Barral C, Servais L. Wearable sensors in paediatric neurology. Developmental Medicine & Child Neurology 2025;67(7):834 View
  8. Ul Ain Q, Jawed S, Rauf Subhani A, Haider Butt W, Usman Akram M. Examining AI-Powered ADHD Diagnosis: Current Trends, Key Challenges, and Future Directions in the Field. IEEE Access 2025;13:93148 View

Books/Policy Documents

  1. Basic J, Uusimaa J, Salmi J. Digital Health and Wireless Solutions. View

Conference Proceedings

  1. Hamim M, Tanmoy F, Tasfia O, Juthi F. 2023 14th International Conference on Computing Communication and Networking Technologies (ICCCNT). Attention deficit hyperactivity disorder detection using deep learning approach View
  2. Wang Z, Jiang X, Gao C, Chen Y. 2023 IEEE Smart World Congress (SWC). Interactive Scene-driven Multi-stream Graph Neural Network for ADHD Diagnosis View