Evidence map›Paper›PMID 32095745›Full record

ArticleDigital biomarkers

Multiple Wearable Sensors in Parkinson and Huntington Disease Individuals: A Pilot Study in Clinic and at Home.

Jamie L Adams, Karthik Dinesh, Mulin Xiong, Christopher G Tarolli, Saloni Sharma, Nirav Sheth, A J Aranyosi, William Zhu, Steven Goldenthal, Kevin M Biglan and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Digital biomarkers. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed, 5 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

45 citing papers in PubMed, 5 syntheses or guidelines pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Jamie L AdamsDepartment of Neurology, University of Rochester Medical Center, Rochester, New York, USA.
Karthik DineshDepartment of Electrical and Computer Engineering, University of Rochester Medical Center, Rochester, New York, USA.
Mulin XiongCenter for Health and Technology, University of Rochester Medical Center, Rochester, New York, USA.
Christopher G TarolliDepartment of Neurology, University of Rochester Medical Center, Rochester, New York, USA.
Saloni SharmaCenter for Health and Technology, University of Rochester Medical Center, Rochester, New York, USA.
Nirav ShethMC10 Inc., Lexington, Massachusetts, USA.
A J AranyosiMC10 Inc., Lexington, Massachusetts, USA.
William ZhuCenter for Health and Technology, University of Rochester Medical Center, Rochester, New York, USA.
Steven GoldenthalCenter for Health and Technology, University of Rochester Medical Center, Rochester, New York, USA.
Kevin M BiglanDepartment of Neurology, University of Rochester Medical Center, Rochester, New York, USA.
E Ray DorseyDepartment of Neurology, University of Rochester Medical Center, Rochester, New York, USA.
Gaurav SharmaDepartment of Electrical and Computer Engineering, University of Rochester Medical Center, Rochester, New York, USA.

Funding

EXPERIMENTAL THERAPEUTICS IN NEUROLOGICAL DISEASET32NS007338 · NINDS · UNIVERSITY OF ROCHESTER · PI ROBERT G. HOLLOWAY, Michael P McDermott · 1990 to 2026
$6.4M
NINDS NIH HHS T32 NS007338
6 · The paper itself

Abstract

backgroundClinician rating scales and patient-reported outcomes are the principal means of assessing motor symptoms in Parkinson disease and Huntington disease. However, these assessments are subjective and generally limited to episodic in-person visits. Wearable sensors can objectively and continuously measure motor features and could be valuable in clinical research and care.

methodsWe recruited participants with Parkinson disease, Huntington disease, and prodromal Huntington disease (individuals who carry the genetic marker but do not yet exhibit symptoms of the disease), and controls to wear 5 accelerometer-based sensors on their chest and limbs for standardized in-clinic assessments and for 2 days at home. The study's aims were to assess the feasibility of use of wearable sensors, to determine the activity (lying, sitting, standing, walking) of participants, and to survey participants on their experience.

resultsFifty-six individuals (16 with Parkinson disease, 15 with Huntington disease, 5 with prodromal Huntington disease, and 20 controls) were enrolled in the study. Data were successfully obtained from 99.3% (278/280) of sensors dispatched. On average, individuals with Huntington disease spent over 50% of the total time lying down, substantially more than individuals with prodromal Huntington disease (33%,

conclusionsAmong individuals with movement disorders, the use of wearable sensors in clinic and at home was feasible and well-received. These sensors can identify statistically significant differences in activity profiles between individuals with movement disorders and those without. In addition, continuous, objective monitoring can reveal disease characteristics not observed in clinic.

Indexed as

Ambulatory patientsClinical studyGaitHuntington diseaseMonitoringMovement disordersParkinson diseaseRemote sensing technologyTechnology

Identifiers

PMID32095745
PMCPMC7015372

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.