Evidence map›Paper›PMID 41024673›Full record

SynthesisNeurodegenerative disease management

Gait assessment using wearable technologies in neurological disorders: a rapid umbrella.

Prajakta P Masurkar, Sagar Rikame

Abstract readSystematic Review
In one paragraph

Synthesis in Neurodegenerative disease management. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–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

4 citing papers in PubMed.

  1. Walking as a Window to the Brain: Redefining Gait in Neurology.Medical sciences (Basel, Switzerland) · 2026
    Review
  2. Review
  3. Article
  4. 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

2 authors.

Prajakta P MasurkarDepartment of Pharmaceutical Health Outcomes and Policy, University of Houston, Houston, TX, USA.ORCID 0000-0002-1417-9764
Sagar RikameDepartment of Computer Science, SUNY Binghamton, Binghamton, NY, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGait analysis is essential tool for tracking neurological disorders-Parkinson's disease (PD), stroke, Alzheimer's disease (AD), and multiple sclerosis (MS). Wearable technologies enable continuous, noninvasive gait tracking beyond clinical settings but face challenges in accuracy and adoption. This review investigates wearable gait assessment, identifying patterns and future needs.

methodsThis rapid umbrella review was conducted, synthesizing systematic reviews and meta-analyses of wearable technologies for gait assessment in PD, stroke, AD, and MS. Following PRISMA guidelines two reviewers screened, extracted data on gait outcomes, and assessed quality using AMSTAR-2.

resultsSeventeen reviews (13systematic, 4meta-analyses) encompassing 308 primary studies were included. Most focused-on PD (

conclusionsLack of standardization, validation, and usability limits clinical adoption. Future efforts must prioritize real-world testing and user-centered design.

Indexed as

Gait AnalysisGait Disorders, NeurologicNervous System DiseasesWearable Electronic DevicesHumansMultiple SclerosisParkinson Diseasealzheimer’s diseasedigital healthGaitmultiple sclerosisneurological disordersparkinson’s diseasestrokewearables

Identifiers

PMID41024673
PMCPMC13248496

What OpenQuestion holds

Textmetadata
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.