Monitoring gait at home with radio waves in Parkinson's disease: A marker of severity, progression, and medication response.


Journal

Science translational medicine
ISSN: 1946-6242
Titre abrégé: Sci Transl Med
Pays: United States
ID NLM: 101505086

Informations de publication

Date de publication:
21 09 2022
Historique:
entrez: 21 9 2022
pubmed: 22 9 2022
medline: 24 9 2022
Statut: ppublish

Résumé

Parkinson's disease (PD) is the fastest-growing neurological disease in the world. A key challenge in PD is tracking disease severity, progression, and medication response. Existing methods are semisubjective and require visiting the clinic. In this work, we demonstrate an effective approach for assessing PD severity, progression, and medication response at home, in an objective manner. We used a radio device located in the background of the home. The device detected and analyzed the radio waves that bounce off people's bodies and inferred their movements and gait speed. We continuously monitored 50 participants, with and without PD, in their homes for up to 1 year. We collected over 200,000 gait speed measurements. Cross-sectional analysis of the data shows that at-home gait speed strongly correlates with gold-standard PD assessments, as evaluated by the Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS) part III subscore and total score. At-home gait speed also provides a more sensitive marker for tracking disease progression over time than the widely used MDS-UPDRS. Further, the monitored gait speed was able to capture symptom fluctuations in response to medications and their impact on patients' daily functioning. Our study shows the feasibility of continuous, objective, sensitive, and passive assessment of PD at home and hence has the potential of improving clinical care and drug clinical trials.

Identifiants

pubmed: 36130014
doi: 10.1126/scitranslmed.adc9669
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

eadc9669

Subventions

Organisme : NINDS NIH HHS
ID : P50 NS108676
Pays : United States

Auteurs

Yingcheng Liu (Y)

Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.

Guo Zhang (G)

Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.

Christopher G Tarolli (CG)

Department of Neurology, University of Rochester Medical Center, Rochester, NY 14642, USA.
Center for Health + Technology, University of Rochester Medical Center, Rochester, NY 14642, USA.

Rumen Hristov (R)

Emerald Innovations Inc., Cambridge, MA 02142, USA.

Stella Jensen-Roberts (S)

Department of Neurology, University of Rochester Medical Center, Rochester, NY 14642, USA.
Center for Health + Technology, University of Rochester Medical Center, Rochester, NY 14642, USA.

Emma M Waddell (EM)

Department of Neurology, University of Rochester Medical Center, Rochester, NY 14642, USA.
Center for Health + Technology, University of Rochester Medical Center, Rochester, NY 14642, USA.

Taylor L Myers (TL)

Department of Neurology, University of Rochester Medical Center, Rochester, NY 14642, USA.
Center for Health + Technology, University of Rochester Medical Center, Rochester, NY 14642, USA.

Meghan E Pawlik (ME)

Department of Neurology, University of Rochester Medical Center, Rochester, NY 14642, USA.
Center for Health + Technology, University of Rochester Medical Center, Rochester, NY 14642, USA.

Julia M Soto (JM)

Department of Neurology, University of Rochester Medical Center, Rochester, NY 14642, USA.
Center for Health + Technology, University of Rochester Medical Center, Rochester, NY 14642, USA.

Renee M Wilson (RM)

Department of Neurology, University of Rochester Medical Center, Rochester, NY 14642, USA.
Center for Health + Technology, University of Rochester Medical Center, Rochester, NY 14642, USA.

Yuzhe Yang (Y)

Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.

Timothy Nordahl (T)

Department of Physical Therapy & Athletic Training, Center for Neurorehabilitation, Boston University College of Health and Rehabilitation: Sargent College, Boston, MA 02215, USA.

Karlo J Lizarraga (KJ)

Department of Neurology, University of Rochester Medical Center, Rochester, NY 14642, USA.
Center for Health + Technology, University of Rochester Medical Center, Rochester, NY 14642, USA.

Jamie L Adams (JL)

Department of Neurology, University of Rochester Medical Center, Rochester, NY 14642, USA.
Center for Health + Technology, University of Rochester Medical Center, Rochester, NY 14642, USA.

Ruth B Schneider (RB)

Department of Neurology, University of Rochester Medical Center, Rochester, NY 14642, USA.
Center for Health + Technology, University of Rochester Medical Center, Rochester, NY 14642, USA.

Karl Kieburtz (K)

Department of Neurology, University of Rochester Medical Center, Rochester, NY 14642, USA.
Center for Health + Technology, University of Rochester Medical Center, Rochester, NY 14642, USA.

Terry Ellis (T)

Department of Physical Therapy & Athletic Training, Center for Neurorehabilitation, Boston University College of Health and Rehabilitation: Sargent College, Boston, MA 02215, USA.

E Ray Dorsey (ER)

Department of Neurology, University of Rochester Medical Center, Rochester, NY 14642, USA.
Center for Health + Technology, University of Rochester Medical Center, Rochester, NY 14642, USA.

Dina Katabi (D)

Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Emerald Innovations Inc., Cambridge, MA 02142, USA.

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Classifications MeSH