Capturing nighttime symptoms in Parkinson disease: Technical development and experimental verification of inertial sensors for nocturnal hypokinesia

J Rehabil Res Dev. 2016;53(4):487-98. doi: 10.1682/JRRD.2015.04.0062.

Abstract

Although nocturnal hypokinesia represents one of the most common nocturnal disabilities in Parkinson disease (PD), it is often a neglected problem in daily clinical practice. We have developed a portable ambulatory motion recorder (the NIGHT-Recorder), which consists of 16-bit triaxial integrated microelectromechanical system inertial sensors that are specifically designed to measure movements, register the position of the body with respect to gravity, and provide information on rotations on the longitudinal axis while lying in bed. The signal processing uses the forward derivative method to identify rolling over and getting out of bed as primary indicators. The prototype was tested on six PD pairs to measure their movements for one night. Using predetermined definitions, 134 movements were captured consisting of rolling over 115 times and getting out of bed 19 times. Patients with PD rolled over significantly fewer times than their spouses (p = 0.03), and the position change was significantly smaller in patients with PD (p = 0.03). Patients with PD rolled over at a significantly slower speed (p = 0.03) and acceleration (p = 0.03) than their spouses. In contrast, patients with PD got out of bed significantly more often than their spouses (p = 0.02). It is technically feasible to develop an easy-to-use, portable, and accurate device that can assist physicians in the assessment of nocturnal movements of patients with PD.

Keywords: Parkinson disease; accelerometers; ambulatory monitoring; getting out of bed; inertial sensors; nocturia; nocturnal akinesia; nocturnal hypokinesia; quality of life; rolling over; sleep.

MeSH terms

  • Acceleration
  • Aged
  • Equipment Design
  • Humans
  • Hypokinesia / diagnosis*
  • Hypokinesia / etiology
  • Male
  • Middle Aged
  • Movement
  • Parkinson Disease / physiopathology*
  • Signal Processing, Computer-Assisted*
  • Sleep