Technical and clinical view on ambulatory assessment in Parkinson's disease

Acta Neurol Scand. 2014 Sep;130(3):139-47. doi: 10.1111/ane.12248. Epub 2014 Apr 1.


With the progress of technologies of recent years, methods have become available that use wearable sensors and ambulatory systems to measure aspects of--particular axial--motor function. As Parkinson's disease (PD) can be considered a model disorder for motor impairment, a significant number of studies have already been performed with these patients using such techniques. In general, motion sensors such as accelerometers and gyroscopes are used, in combination with lightweight electronics that do not interfere with normal human motion. A fundamental advantage in comparison with usual clinical assessment is that these sensors allow a more quantitative, objective, and reliable evaluation of symptoms; they have also significant advantages compared to in-lab technologies (e.g., optoelectronic motion capture) as they allow long-term monitoring under real-life conditions. In addition, based on recent findings particularly from studies using functional imaging, we learned that non-motor symptoms, specifically cognitive aspects, may be at least indirectly assessable. It is hypothesized that ambulatory quantitative assessment strategies will allow users, clinicians, and scientists in the future to gain more quantitative, unobtrusive, and everyday relevant data out of their clinical evaluation and can also be designed as pervasive (everywhere) and intensive (anytime) tools for ambulatory assessment and even rehabilitation of motor and (partly) non-motor symptoms in PD.

Keywords: Parkinson's disease; ambulatory systems; gait analysis; motor symptoms; motor-cognitive interaction; sway analysis; wearable sensors.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Accelerometry / methods*
  • Humans
  • Middle Aged
  • Motion
  • Parkinson Disease / diagnosis*
  • Parkinson Disease / physiopathology
  • Physical Examination / methods*