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

Autor:	Liu Y; Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA., Zhang G; Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA., 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., Hristov R; Emerald Innovations Inc., Cambridge, MA 02142, USA., 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., 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., 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., 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., 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., 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., Yang Y; Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA., Nordahl T; Department of Physical Therapy & Athletic Training, Center for Neurorehabilitation, Boston University College of Health and Rehabilitation: Sargent College, Boston, MA 02215, USA., 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., 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., 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., 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., Ellis T; Department of Physical Therapy & Athletic Training, Center for Neurorehabilitation, Boston University College of Health and Rehabilitation: Sargent College, Boston, MA 02215, USA., 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., Katabi D; Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.; Emerald Innovations Inc., Cambridge, MA 02142, USA.
Jazyk:	angličtina
Zdroj:	Science translational medicine [Sci Transl Med] 2022 Sep 21; Vol. 14 (663), pp. eadc9669. Date of Electronic Publication: 2022 Sep 21.
DOI:	10.1126/scitranslmed.adc9669
Abstrakt:	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.
Databáze:	MEDLINE
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