Published on in Vol 8 , No 3 (2019) :March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/12808, first published .
Identification of Motor Symptoms Related to Parkinson Disease Using Motion-Tracking Sensors at Home (KÄVELI): Protocol for an Observational Case-Control Study

Identification of Motor Symptoms Related to Parkinson Disease Using Motion-Tracking Sensors at Home (KÄVELI): Protocol for an Observational Case-Control Study

Identification of Motor Symptoms Related to Parkinson Disease Using Motion-Tracking Sensors at Home (KÄVELI): Protocol for an Observational Case-Control Study

Journals

  1. Rashidisabet H, Thomas P, Ajilore O, Zulueta J, Moore R, Leow A. A systems biology approach to the digital behaviorome. Current Opinion in Systems Biology 2020;20:8 View
  2. Juutinen M, Wang C, Zhu J, Haladjian J, Ruokolainen J, Puustinen J, Vehkaoja A, Dimitriadis S. Parkinson’s disease detection from 20-step walking tests using inertial sensors of a smartphone: Machine learning approach based on an observational case-control study. PLOS ONE 2020;15(7):e0236258 View
  3. Lu R, Xu Y, Li X, Fan Y, Zeng W, Tan Y, Ren K, Chen W, Cao X. Evaluation of Wearable Sensor Devices in Parkinson’s Disease: A Review of Current Status and Future Prospects. Parkinson's Disease 2020;2020:1 View
  4. Jung S, Michaud M, Oudre L, Dorveaux E, Gorintin L, Vayatis N, Ricard D. The Use of Inertial Measurement Units for the Study of Free Living Environment Activity Assessment: A Literature Review. Sensors 2020;20(19):5625 View