Repository logo
Log in(current)
Repository logoMIT Open ScholarshipDSpace@MIT
  1. Home
  2. MIT Open Access Articles
  3. MIT Open Access Articles
  4. Passive Monitoring at Home: A Pilot Study in Parkinson Disease

Passive Monitoring at Home: A Pilot Study in Parkinson Disease

Thumbnail Image
Download
Name

document.pdf

Description
Published version
Size

1.14 MB

Format

Adobe PDF

Checksum (MD5)

00d9f6e7903c1e0f6bc4dbdf78f4d1a2

sword-2020-12-23T16:26:55.original.xml (130 B)
Original SWORD entry document
Author(s)
Kabelac, Zachary E.
•
Tarolli, Christopher G.
•
Snyder, Christopher
•
Feldman, Blake
•
Glidden, Alistair
•
Hsu, Chen-Yu
•
Hristov, Rumen H.
•
Dorsey, E. Ray
•
Katabi, Dina
Date Issued
April 2019
Journal
Digital Biomarkers
Publisher
S. Karger AG
Citation
Kabelac, Zachary et al. "Passive Monitoring at Home: A Pilot Study in Parkinson Disease." Digital Biomarkers 3, 1 (April 2019): 22–30 © 2019 The Author(s)
Version
Final published version
Abstract
We conducted a pilot study using a passive radio-wave-based home monitor in individuals with Parkinson disease (PD) with a focus on gait, home activity, and time in bed. We enrolled 7 ambulatory individuals to have the device installed in the bedroom of their homes over 8 weeks and performed standard PD assessments at baseline. We evaluated the ability of the device to objectively measure gait and time in bed and to generate novel visualizations of home activity. We captured 353 days of monitoring. Mean gait speed (0.39-0.78 m/s), time in bed per day (4.4-12.1 h), and number (1.4-5.9) and duration (15.0-49.8 min) of nightly awakenings varied substantially across and within individuals. Derived gait speed correlated well with the Movement Disorder Society-Unified Parkinson's Disease Rating Scale total (r = -0.88, p = 0.009) and motor sub-score (r = -0.95, p = 0.001). Six of the seven participants agreed that their activity was typical and indicated a willingness to continue monitoring. This technology provided promising new insights into the home activities of those with PD and may be broadly applicable to other chronic conditions.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
Creative Commons Attribution-NonCommercial-NoDerivs License
http://creativecommons.org/licenses/by-nc-nd/4.0/
Persistent DSpace Link
https://hdl.handle.net/1721.1/129463
DOI of Published Version
https://doi.org/10.1159/000498922
Repository logo
PrivacyPermissionsAccessibilityContact us
Repository logo
Notify us about copyright concerns.