Evidence map›Paper›PMID 35897995›Full record

ReviewSensors (Basel, Switzerland)2022

A Systematic Survey of Research Trends in Technology Usage for Parkinson's Disease.

Ranadeep Deb, Sizhe An, Ganapati Bhat, Holly Shill, Umit Y Ogras

Open access · goldAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
4.5field-weighted citation impact, top 4% of its field
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

21 citing papers in PubMed, 1 synthesis or guideline pooled it, 39 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. Review
  20. Article
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

5 authors at 3 institutions in 1 country.

Ranadeep DebAnalog Devices, Raleigh, NC 27603, USA.
Sizhe AnDepartment of Electrical and Computer Engineering, University of Wisconsin-Madison, Madison, WI 53705, USA.ORCID 0000-0002-9211-4886
Ganapati BhatSchool of Electrical Engineering & Computer Science, Washington State University, Pullman, WA 99164, USA.ORCID 0000-0003-1085-2189
Holly ShillLonnie and Muhammad Ali Movement Disorder Center, Phoenix, AZ 85013, USA.
Umit Y OgrasDepartment of Electrical and Computer Engineering, University of Wisconsin-Madison, Madison, WI 53705, USA.ORCID 0000-0002-5045-5535
University of Wisconsin–Madison · USAnalog Devices (United States) · USWashington State University · US

Funding

NSF CAREER award CNS-1651624
6 · The paper itself

Abstract

Parkinson's disease (PD) is a neurological disorder with complicated and disabling motor and non-motor symptoms. The complexity of PD pathology is amplified due to its dependency on patient diaries and the neurologist's subjective assessment of clinical scales. A significant amount of recent research has explored new cost-effective and subjective assessment methods pertaining to PD symptoms to address this challenge. This article analyzes the application areas and use of mobile and wearable technology in PD research using the PRISMA methodology. Based on the published papers, we identify four significant fields of research: diagnosis, prognosis and monitoring, predicting response to treatment, and rehabilitation. Between January 2008 and December 2021, 31,718 articles were published in four databases: PubMed Central, Science Direct, IEEE Xplore, and MDPI. After removing unrelated articles, duplicate entries, non-English publications, and other articles that did not fulfill the selection criteria, we manually investigated 1559 articles in this review. Most of the articles (45%) were published during a recent four-year stretch (2018-2021), and 19% of the articles were published in 2021 alone. This trend reflects the research community's growing interest in assessing PD with wearable devices, particularly in the last four years of the period under study. We conclude that there is a substantial and steady growth in the use of mobile technology in the PD contexts. We share our automated script and the detailed results with the public, making the review reproducible for future publications.

Indexed as

Parkinson DiseaseWearable Electronic DevicesHumansSurveys and QuestionnairesTechnologybiopotential devicesdiagnosisdigital healthParkinson’s diseaseprognosistaxonomywearable devices

Identifiers

PMID35897995
PMCPMC9371095
OpenAlexW4287219767

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.