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A systematic review of the characteristics and validity of monitoring technologies to assess Parkinson’s disease

Overview of attention for article published in Journal of NeuroEngineering and Rehabilitation, March 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (85th percentile)
  • High Attention Score compared to outputs of the same age and source (86th percentile)

Mentioned by

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1 news outlet
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4 X users
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1 Facebook page

Citations

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182 Dimensions

Readers on

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492 Mendeley
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1 CiteULike
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Title
A systematic review of the characteristics and validity of monitoring technologies to assess Parkinson’s disease
Published in
Journal of NeuroEngineering and Rehabilitation, March 2016
DOI 10.1186/s12984-016-0136-7
Pubmed ID
Authors

Catarina Godinho, Josefa Domingos, Guilherme Cunha, Ana T. Santos, Ricardo M. Fernandes, Daisy Abreu, Nilza Gonçalves, Helen Matthews, Tom Isaacs, Joy Duffen, Ahmed Al-Jawad, Frank Larsen, Artur Serrano, Peter Weber, Andrea Thoms, Stefan Sollinger, Holm Graessner, Walter Maetzler, Joaquim J. Ferreira

Abstract

There is growing interest in having objective assessment of health-related outcomes using technology-based devices that provide unbiased measurements which can be used in clinical practice and scientific research. Many studies have investigated the clinical manifestations of Parkinson's disease using such devices. However, clinimetric properties and clinical validation vary among the different devices. Given such heterogeneity, we sought to perform a systematic review in order to (i) list, (ii) compare and (iii) classify technological-based devices used to measure motor function in individuals with Parkinson's disease into three groups, namely wearable, non-wearable and hybrid devices. A systematic literature search of the PubMed database resulted in the inclusion of 168 studies. These studies were grouped based on the type of device used. For each device we reviewed availability, use, reliability, validity, and sensitivity to change. The devices were then classified as (i) 'recommended', (ii) 'suggested' or (iii) 'listed' based on the following criteria: (1) used in the assessment of Parkinson's disease (yes/no), (2) used in published studies by people other than the developers (yes/no), and (3) successful clinimetric testing (yes/no). Seventy-three devices were identified, 22 were wearable, 38 were non-wearable, and 13 were hybrid devices. In accordance with our classification method, 9 devices were 'recommended', 34 devices were 'suggested', and 30 devices were classified as 'listed'. Within the wearable devices group, the Mobility Lab sensors from Ambulatory Parkinson's Disease Monitoring (APDM), Physilog®, StepWatch 3, TriTrac RT3 Triaxial accelerometer, McRoberts DynaPort, and Axivity (AX3) were classified as 'recommended'. Within the non-wearable devices group, the Nintendo Wii Balance Board and GAITRite® gait analysis system were classified as 'recommended'. Within the hybrid devices group only the Kinesia® system was classified as 'recommended'.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 492 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 <1%
Portugal 2 <1%
Sweden 1 <1%
United Kingdom 1 <1%
Germany 1 <1%
Canada 1 <1%
Libya 1 <1%
Japan 1 <1%
Taiwan 1 <1%
Other 0 0%
Unknown 480 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 72 15%
Student > Master 70 14%
Researcher 57 12%
Student > Bachelor 56 11%
Student > Doctoral Student 44 9%
Other 101 21%
Unknown 92 19%
Readers by discipline Count As %
Medicine and Dentistry 91 18%
Engineering 67 14%
Neuroscience 60 12%
Nursing and Health Professions 50 10%
Computer Science 24 5%
Other 76 15%
Unknown 124 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 12. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 20 August 2016.
All research outputs
#2,863,629
of 25,373,627 outputs
Outputs from Journal of NeuroEngineering and Rehabilitation
#136
of 1,413 outputs
Outputs of similar age
#44,540
of 315,301 outputs
Outputs of similar age from Journal of NeuroEngineering and Rehabilitation
#3
of 23 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,413 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.3. This one has done particularly well, scoring higher than 90% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 315,301 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 85% of its contemporaries.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.