Published on in Vol 9, No 3 (2022): Jul-Sep

This is a member publication of University of Bristol (Jisc)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/36370, first published .
Acceptability of an In-home Multimodal Sensor Platform for Parkinson Disease: Nonrandomized Qualitative Study

Acceptability of an In-home Multimodal Sensor Platform for Parkinson Disease: Nonrandomized Qualitative Study

Acceptability of an In-home Multimodal Sensor Platform for Parkinson Disease: Nonrandomized Qualitative Study

Journals

  1. Morgan C, Jameson J, Craddock I, Tonkin E, Oikonomou G, Isotalus H, Heidarivincheh F, McConville R, Tourte G, Kinnunen K, Whone A. Understanding how people with Parkinson's disease turn in gait from a real-world in-home dataset. Parkinsonism & Related Disorders 2022;105:114 View
  2. Morgan C, Tonkin E, Masullo A, Jovan F, Sikdar A, Khaire P, Mirmehdi M, McConville R, Tourte G, Whone A, Craddock I. A multimodal dataset of real world mobility activities in Parkinson’s disease. Scientific Data 2023;10(1) View
  3. Morgan C, Masullo A, Mirmehdi M, Isotalus H, Jovan F, McConville R, Tonkin E, Whone A, Craddock I. Automated Real-World Video Analysis of Sit-to-Stand Transitions Predicts Parkinson’s Disease Severity. Digital Biomarkers 2023:92 View
  4. Khoo L, Lim M, Chong C, McNaney R. Machine Learning for Multimodal Mental Health Detection: A Systematic Review of Passive Sensing Approaches. Sensors 2024;24(2):348 View
  5. Popp Z, Low S, Igwe A, Rahman M, Kim M, Khan R, Oh E, Kumar A, De Anda‐Duran I, Ding H, Hwang P, Sunderaraman P, Shih L, Lin H, Kolachalama V, Au R. Shifting From Active to Passive Monitoring of Alzheimer Disease: The State of the Research. Journal of the American Heart Association 2024;13(2) View

Books/Policy Documents

  1. Rochester L, Del Din S, Hu M, Morgan C, Carroll C. Digital Technologies in Movement Disorders. View