Published on in Vol 20, No 3 (2018): March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/9462, first published .
Detecting Motor Impairment in Early Parkinson’s Disease via Natural Typing Interaction With Keyboards: Validation of the neuroQWERTY Approach in an Uncontrolled At-Home Setting

Detecting Motor Impairment in Early Parkinson’s Disease via Natural Typing Interaction With Keyboards: Validation of the neuroQWERTY Approach in an Uncontrolled At-Home Setting

Detecting Motor Impairment in Early Parkinson’s Disease via Natural Typing Interaction With Keyboards: Validation of the neuroQWERTY Approach in an Uncontrolled At-Home Setting

Journals

  1. López-Blanco R, Velasco M, Méndez-Guerrero A, Romero J, del Castillo M, Serrano J, Rocon E, Benito-León J. Smartwatch for the analysis of rest tremor in patients with Parkinson's disease. Journal of the Neurological Sciences 2019;401:37 View
  2. Taib R, Berkovsky S. Modeling humans via physiological and behavioral signals. Interactions 2020;27(3):30 View
  3. Belić M, Bobić V, Badža M, Šolaja N, Đurić-Jovičić M, Kostić V. Artificial intelligence for assisting diagnostics and assessment of Parkinson’s disease—A review. Clinical Neurology and Neurosurgery 2019;184:105442 View
  4. Matarazzo M, Arroyo‐Gallego T, Montero P, Puertas‐Martín V, Butterworth I, Mendoza C, Ledesma‐Carbayo M, Catalán M, Molina J, Bermejo‐Pareja F, Martínez‐Castrillo J, López‐Manzanares L, Alonso‐Cánovas A, Rodríguez J, Obeso I, Martínez‐Martín P, Martínez‐Ávila J, Cámara A, Gray M, Obeso J, Giancardo L, Sánchez‐Ferro Á. Remote Monitoring of Treatment Response in Parkinson's Disease: The Habit of Typing on a Computer. Movement Disorders 2019;34(10):1488 View
  5. Iakovakis D, Chaudhuri K, Klingelhoefer L, Bostantjopoulou S, Katsarou Z, Trivedi D, Reichmann H, Hadjidimitriou S, Charisis V, Hadjileontiadis L. Screening of Parkinsonian subtle fine-motor impairment from touchscreen typing via deep learning. Scientific Reports 2020;10(1) View
  6. Morgan C, Rolinski M, McNaney R, Jones B, Rochester L, Maetzler W, Craddock I, Whone A. Systematic Review Looking at the Use of Technology to Measure Free-Living Symptom and Activity Outcomes in Parkinson’s Disease in the Home or a Home-like Environment. Journal of Parkinson's Disease 2020;10(2):429 View
  7. Piri S. Missing care: A framework to address the issue of frequent missing values;The case of a clinical decision support system for Parkinson's disease. Decision Support Systems 2020;136:113339 View
  8. Sanderson J, Yu J, Liu D, Amaya D, Lauro P, D'Abreu A, Akbar U, Lee S, Asaad W. Multi-Dimensional, Short-Timescale Quantification of Parkinson's Disease and Essential Tremor Motor Dysfunction. Frontiers in Neurology 2020;11 View
  9. Monje M, Foffani G, Obeso J, Sánchez-Ferro Á. New Sensor and Wearable Technologies to Aid in the Diagnosis and Treatment Monitoring of Parkinson's Disease. Annual Review of Biomedical Engineering 2019;21(1):111 View
  10. Iakovakis D, Hadjidimitriou S, Charisis V, Bostantjopoulou S, Katsarou Z, Klingelhoefer L, Reichmann H, Dias S, Diniz J, Trivedi D, Chaudhuri K, Hadjileontiadis L. Motor Impairment Estimates via Touchscreen Typing Dynamics Toward Parkinson's Disease Detection From Data Harvested In-the-Wild. Frontiers in ICT 2018;5 View
  11. Warmerdam E, Hausdorff J, Atrsaei A, Zhou Y, Mirelman A, Aminian K, Espay A, Hansen C, Evers L, Keller A, Lamoth C, Pilotto A, Rochester L, Schmidt G, Bloem B, Maetzler W. Long-term unsupervised mobility assessment in movement disorders. The Lancet Neurology 2020;19(5):462 View
  12. Estrada-Galiñanes V, Wac K, Hoehndorf R. Collecting, exploring and sharing personal data: Why, how and where. Data Science 2020;3(2):79 View
  13. Mirelman A, Ray Dorsey E, Brundin P, Bloem B. Using Technology to Reshape Clinical Care and Research in Parkinson’s disease. Journal of Parkinson's Disease 2021:1 View