Evidence map›Paper›PMID 40125472›Full record

ReviewPragmatic and observational research2025

Better Understanding Rehabilitation of Motor Symptoms: Insights from the Use of Wearables.

Yunus Celik, Conor Wall, Jason Moore, Alan Godfrey

Abstract readReview
In one paragraph

Review in Pragmatic and observational research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Article
  3. Walking as a Window to the Brain: Redefining Gait in Neurology.Medical sciences (Basel, Switzerland) · 2026
    Review
  4. Review
  5. Article
  6. 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

4 authors.

Yunus CelikDepartment of Computer and Information Sciences, Northumbria University, Newcastle upon Tyne, NE1 8ST, UK.
Conor WallDepartment of Computer and Information Sciences, Northumbria University, Newcastle upon Tyne, NE1 8ST, UK.
Jason MooreDepartment of Computer and Information Sciences, Northumbria University, Newcastle upon Tyne, NE1 8ST, UK.
Alan GodfreyDepartment of Computer and Information Sciences, Northumbria University, Newcastle upon Tyne, NE1 8ST, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Movement disorders present a substantial challenge by adversely affecting daily routines and overall well-being through a diverse spectrum of motor symptoms. Traditionally, motor symptoms have been evaluated through manual observational methods and patient-reported outcomes. While those approaches are valuable, they are limited by their subjectivity. In contrast, wearable technologies (wearables) provide objective assessments while actively supporting rehabilitation through continuous tracking, real-time feedback, and personalized physical therapy-based interventions. The aim of this literature review is to examine current research on the use of wearables in the rehabilitation of motor symptoms, focusing on their features, applications, and impact on improving motor function. By exploring research protocols, metrics, and study findings, this review aims to provide a comprehensive overview of how wearables are being used to support and optimize rehabilitation outcomes. To achieve that aim, a systematic search of the literature was conducted. Findings reveal that gait disturbance and postural balance are the primary motor symptoms extensively studied with tremor and freezing of gait (FoG) also receiving attention. Wearable sensing ranges from bespoke inertial and/or electromyography to commercial units such as personal devices (ie, smartwatch). Interactive (virtual reality, VR and augmented reality, AR) and immersive technologies (headphones), along with wearable robotic systems (exoskeletons), have proven to be effective in improving motor skills. Auditory cueing (via smartwatches or headphones), aids gait training with rhythmic feedback, while visual cues (via VR and AR glasses) enhance balance exercises through real-time feedback. The development of treatment protocols that incorporate personalized cues via wearables could enhance adherence and engagement to potentially lead to long-term improvements. However, evidence on the sustained effectiveness of wearable-based interventions remains limited.

Indexed as

motor symptomsmovement disordersrehabilitationwearable technology

Identifiers

PMID40125472
PMCPMC11930022

What OpenQuestion holds

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LicenceCC BY-NC
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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.