Evidence map›Paper›PMID 36494721›Full record

SynthesisJournal of neuroengineering and rehabilitation2022

Technology-assisted assessment of spasticity: a systematic review.

Xinliang Guo, Rebecca Wallace, Ying Tan, Denny Oetomo, Marlena Klaic, Vincent Crocher

Open access · goldAbstract readSystematic Review
In one paragraph

Synthesis in Journal of neuroengineering and rehabilitation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
3.4field-weighted citation impact, top 6% 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

11 citing papers in PubMed, 31 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Ultrasound-Derived Stretch Reflex Threshold Estimation Using Tendon-to-Bone Distance During Tendon Tapping in Post-Stroke Spasticity.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2026
    Article
  5. Article
  6. Article
  7. Article
  8. A portable system to measure knee extensor spasticity after spinal cord injury.Journal of neuroengineering and rehabilitation · 2024
    Article
  9. Article
  10. Article
  11. Review
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

6 authors at 2 institutions in 1 country.

Xinliang GuoUoM and Fourier Intelligence Joint Robotics Laboratory, Mechanical Engineering Department, The University of Melbourne, Melbourne, Australia.
Rebecca WallaceAllied Health Department, The Royal Melbourne Hospital, Melbourne, Australia.
Ying TanUoM and Fourier Intelligence Joint Robotics Laboratory, Mechanical Engineering Department, The University of Melbourne, Melbourne, Australia.
Denny OetomoUoM and Fourier Intelligence Joint Robotics Laboratory, Mechanical Engineering Department, The University of Melbourne, Melbourne, Australia.
Marlena KlaicSchool of Health Sciences, The University of Melbourne, Melbourne, Australia.
Vincent CrocherUoM and Fourier Intelligence Joint Robotics Laboratory, Mechanical Engineering Department, The University of Melbourne, Melbourne, Australia. vcrocher@unimelb.edu.au.
University of Melbourne · AUThe Royal Melbourne Hospital · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSpasticity is defined as "a motor disorder characterised by a velocity dependent increase in tonic stretch reflexes (muscle tone) with exaggerated tendon jerks". It is a highly prevalent condition following stroke and other neurological conditions. Clinical assessment of spasticity relies predominantly on manual, non-instrumented, clinical scales. Technology based solutions have been developed in the last decades to offer more specific, sensitive and accurate alternatives but no consensus exists on these different approaches.

methodA systematic review of literature of technology-based methods aiming at the assessment of spasticity was performed. The approaches taken in the studies were classified based on the method used as well as their outcome measures. The psychometric properties and usability of the methods and outcome measures reported were evaluated.

results124 studies were included in the analysis. 78 different outcome measures were identified, among which seven were used in more than 10 different studies each. The different methods rely on a wide range of different equipment (from robotic systems to simple goniometers) affecting their cost and usability. Studies equivalently applied to the lower and upper limbs (48% and 52%, respectively). A majority of studies applied to a stroke population (N = 79). More than half the papers did not report thoroughly the psychometric properties of the measures. Analysis identified that only 54 studies used measures specific to spasticity. Repeatability and discriminant validity were found to be of good quality in respectively 25 and 42 studies but were most often not evaluated (N = 95 and N = 78). Clinical validity was commonly assessed only against clinical scales (N = 33). Sensitivity of the measure was assessed in only three studies.

conclusionThe development of a large diversity of assessment approaches appears to be done at the expense of their careful evaluation. Still, among the well validated approaches, the ones based on manual stretching and measuring a muscle activity reaction and the ones leveraging controlled stretches while isolating the stretch-reflex torque component appear as the two promising practical alternatives to clinical scales. These methods should be further evaluated, including on their sensitivity, to fully inform on their potential.

Indexed as

StrokeStroke RehabilitationHumansMuscle SpasticityReflex, StretchTechnologyMuscle toneNeurological disordersNeuro-rehabilitationOutcome measureSpasticity

Identifiers

PMID36494721
PMCPMC9733065
OpenAlexW4311674733

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.