Evidence map›Paper›PMID 37779198›Full record

ReviewArthroplasty (London, England)2023

Advances in the application of wearable sensors for gait analysis after total knee arthroplasty: a systematic review.

Yuguo Feng, Yu Liu, Yuan Fang, Jin Chang, Fei Deng, Jin Liu, Yan Xiong

Registry-linked trialOpen access · diamondAbstract readReview
In one paragraph

Review in Arthroplasty (London, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07367789 (Prediction of Patient-reported Outcome Measure and Performance-based Measure After Total Knee Arthroplasty Using Instrumented Insoles and Deep Neural Networks), which is not on this map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
7.3field-weighted citation impact, top 2% 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.

NCT07367789 recruitingnot on this map

Prediction of Patient-reported Outcome Measure and Performance-based Measure After Total Knee Arthroplasty Using Instrumented Insoles and Deep Neural Networks

TypeobservationalSponsorYonsei UniversityRan2021 to 2026Enrolled200ConditionsKnee Osteoarthritis, Total Knee ArthroplastyArmsInstrumented Insole Gait Assessment
3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 23 citations in OpenAlex.

  1. Observational
  2. Review
  3. Article
  4. Article
  5. Review
  6. Monitoring Gait Recovery After Total Knee Arthroplasty Using Wearable Sensors: Responsiveness of Gait Accelerations.Journal of orthopaedic research : official publication of the Orthopaedic Research Society · 2025
    Observational
  7. Article
  8. Review
  9. Review
  10. Article
  11. Review
  12. Article
  13. [The potential of wearable technology in knee arthroplasty].Orthopadie (Heidelberg, Germany) · 2024
    Review
  14. [Postoperative rehabilitation after knee arthroplasty].Orthopadie (Heidelberg, Germany) · 2024
    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

7 authors at 3 institutions in 1 country.

Yuguo FengCollege of Art and Design, Xihua University, Chengdu, 610039, China.
Yu LiuChongqing Brace Technology Co., Ltd., Chongqing, 401120, China.
Yuan FangChongqing Brace Technology Co., Ltd., Chongqing, 401120, China.
Jin ChangChongqing Brace Technology Co., Ltd., Chongqing, 401120, China.
Fei DengChongqing Brace Technology Co., Ltd., Chongqing, 401120, China.
Jin LiuAffiliated Experimental School of Sichuan Normal University, Chengdu, 610000, China.
Yan XiongDepartment of Orthopaedics, Daping Hospital, Army Medical University, Chongqing, 400042, China. xiongyandoctor@163.com.ORCID http://orcid.org/0000-0001-6653-5356
Army Medical University · CNSichuan Normal University · CNXihua University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWearable sensors have become a complementary means for evaluation of body function and gait in lower limb osteoarthritis. This study aimed to review the applications of wearable sensors for gait analysis after total knee arthroplasty (TKA).

methodsFive databases, including Web of Science Core Collection, Embase, Cochrane, Medline, and PubMed, were searched for articles published between January 2010 and March 2023, using predetermined search terms that focused on wearable sensors, TKA, and gait analysis as broad areas of interest.

resultsA total of 25 articles were identified, involving 823 TKA patients. Methodologies varied widely across the articles, with inconsistencies found in reported patient characteristics, sensor data and experimental protocols. Patient-reported outcome measures (PROMs) and gait variables showed various recovery times from 1 week postoperatively to 5 years postoperatively. Gait analysis using wearable sensors and PROMs showed differences in controlled environments, daily life, and when comparing different surgeries.

conclusionWearable sensors offered the potential to remotely monitor the gait function post-TKA in both controlled environments and patients' daily life, and covered more aspects than PROMs. More cohort longitudinal studies are warranted to further confirm the benefits of this remote technology in clinical practice.

Indexed as

Gait analysisReviewTotal knee arthroplastyWalkingWearable sensors

Identifiers

PMID37779198
PMCPMC10544450
OpenAlexW4387235061

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.