Camera-based objective measures of Parkinson’s disease gait features

Jannis van Kersbergen, Karen Otte, Nienke M. de Vries, Bastiaan R. Bloem, Hanna Rohling, Sebastian Mansow-Model, Nicolien M. van der Kolk, Sebastiaan Overeem, Sveta Zinger, Merel M. van Gilst (Corresponding author)

Research output: Contribution to journalArticleAcademicpeer-review

2 Citations (Scopus)
25 Downloads (Pure)


Parkinson’s disease is a common, age-related, neurodegenerative disease, affecting gait and other motor functions. Technological developments in consumer imaging are starting to provide high-quality, affordable tools for home-based diagnosis and monitoring. This pilot study aims to investigate whether a consumer depth camera can capture changes in gait features of Parkinson’s patients. The dataset consisted of 19 patients (tested in both a practically defined OFF phase and ON phase) and 8 controls, who performed the “Timed-Up-and-Go” test multiple times while being recorded with the Microsoft Kinect V2 sensor. Camera-derived features were step length, average walking speed and mediolateral sway. Motor signs were assessed clinically using the Movement Disorder Society Unified Parkinson’s Disease Rating Scale.

We found significant group differences between patients and controls for step length and average walking speed, showing the ability to detect Parkinson’s features. However, there were no differences between the ON and OFF medication state, so further developments are needed to allow for detection of small intra-individual changes in symptom severity.
Original languageEnglish
Article number329
Number of pages6
JournalBMC Research Notes
Publication statusPublished - 26 Aug 2021


  • Gait
  • Gait Disorders, Neurologic
  • Humans
  • Neurodegenerative Diseases
  • Parkinson Disease/diagnosis
  • Pilot Projects
  • Walking Speed
  • Kinect TUG-test
  • Movement disorders
  • Parkinson’s disease


Dive into the research topics of 'Camera-based objective measures of Parkinson’s disease gait features'. Together they form a unique fingerprint.

Cite this