Literature DB >> 27533042

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

Roongroj Bhidayasiri1, Jirada Sringean, Poonpak Taechalertpaisarn, Chusak Thanawattano.   

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.

Entities:  

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

Mesh:

Year:  2016        PMID: 27533042     DOI: 10.1682/JRRD.2015.04.0062

Source DB:  PubMed          Journal:  J Rehabil Res Dev        ISSN: 0748-7711


  7 in total

Review 1.  Using wearables to assess bradykinesia and rigidity in patients with Parkinson's disease: a focused, narrative review of the literature.

Authors:  Itay Teshuva; Inbar Hillel; Eran Gazit; Nir Giladi; Anat Mirelman; Jeffrey M Hausdorff
Journal:  J Neural Transm (Vienna)       Date:  2019-05-22       Impact factor: 3.575

Review 2.  Wearables in the home-based assessment of abnormal movements in Parkinson's disease: a systematic review of the literature.

Authors:  Stefania Ancona; Francesca D Faraci; Elina Khatab; Luigi Fiorillo; Oriella Gnarra; Tobias Nef; Claudio L A Bassetti; Panagiotis Bargiotas
Journal:  J Neurol       Date:  2021-01-06       Impact factor: 4.849

3.  Effects of Levodopa on quality of sleep and nocturnal movements in Parkinson's Disease.

Authors:  Eva Schaeffer; Thomas Vaterrodt; Laura Zaunbrecher; Inga Liepelt-Scarfone; Kirsten Emmert; Benjamin Roeben; Morad Elshehabi; Clint Hansen; Sara Becker; Susanne Nussbaum; Jan-Hinrich Busch; Matthis Synofzik; Daniela Berg; Walter Maetzler
Journal:  J Neurol       Date:  2021-02-05       Impact factor: 4.849

4.  Determinants of impaired bed mobility in Parkinson's disease: Impact of hip muscle strength and motor symptoms.

Authors:  Seira Taniguchi; Nicholas D'cruz; Miho Nakagoshi; Toshinori Osaki; Alice Nieuwboer
Journal:  NeuroRehabilitation       Date:  2022       Impact factor: 1.986

5.  Impact of inability to turn in bed assessed by a wearable three-axis accelerometer on patients with Parkinson's disease.

Authors:  Kenji Uchino; Makoto Shiraishi; Keita Tanaka; Masashi Akamatsu; Yasuhiro Hasegawa
Journal:  PLoS One       Date:  2017-11-09       Impact factor: 3.240

6.  Technological evaluation of strategies to get out of bed by people with Parkinson's disease: Insights from multisite wearable sensors.

Authors:  Jirada Sringean; Chusak Thanawattano; Roongroj Bhidayasiri
Journal:  Front Med Technol       Date:  2022-08-25

Review 7.  Shedding Light on Nocturnal Movements in Parkinson's Disease: Evidence from Wearable Technologies.

Authors:  Alessandro Zampogna; Alessandro Manoni; Francesco Asci; Claudio Liguori; Fernanda Irrera; Antonio Suppa
Journal:  Sensors (Basel)       Date:  2020-09-10       Impact factor: 3.576

  7 in total

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