Evidence map›Paper›PMID 37545175›Full record

ArticleOrthopaedic surgery2023

Validation of a Wearable System for Lower Extremity Assessment.

Haohua Zhang, Yang Song, Cheng Li, Yong Dou, Dacheng Wang, Yinyue Wu, Xiaoyi Chen, Di Liu

Open access · goldAbstract read
In one paragraph

Article in Orthopaedic surgery, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.2field-weighted citation impact, top 11% 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

7 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
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  6. Accuracy validation of a wearable IMU-based gait analysis in healthy female.BMC sports science, medicine & rehabilitation · 2024
    Article
  7. 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

8 authors at 3 institutions in 1 country.

Haohua ZhangDepartment of Orthopaedic Surgery, Beijing Jishuitan Hospital, Beijing, China.ORCID https://orcid.org/0009-0009-9467-7365
Yang SongDepartment of Orthopaedic Surgery, Beijing Jishuitan Hospital, Beijing, China.
Cheng LiDepartment of Orthopaedic Surgery, Beijing Jishuitan Hospital, Beijing, China.
Yong DouDepartment of Orthopaedic Surgery, Beijing Jishuitan Hospital, Beijing, China.
Dacheng WangDepartment of Orthopaedic Surgery, Beijing Jishuitan Hospital, Beijing, China.
Yinyue WuGuoke Ningbo Life Science Research Institute, Beijing, China.
Xiaoyi ChenGuoke Ningbo Life Science Research Institute, Beijing, China.
Di LiuJiakang Zhongzhi Technology Company, Beijing, China.
Peking University · CNUniversity of Nottingham Ningbo China · CNHongzhiwei Technology (China) · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveRemote assessment and diagnosis of functional impairment caused by osteoarthritis (OA) of the knee can achieve early intervention of patients' functional impairment, prevent the deterioration of OA of the knee, and provide functional remote screening for patients with knee OA. This study introduced an inertial measurement unit (IMU) sensor-based system to assess lower extremity function and perform gait analysis. Then, we compared its accuracy to gold-standard motion capture and gait measurement systems.

methodsNine adults were selected to participate in a comparative study of gait assessment outcomes using an IMU sensor-based wearable system, a gold-standard motion capture system, and a pressure-based gait analysis system. The subject walked on a path that incorporated all three systems. Data analysis was performed on spatiotemporal gait parameters, including velocity, cycle time, cadence, and stride length. This was followed by gait phases, including stance, swing, double stance, and single limb support phases. Data were processed using the data processing software of each system. An independent sample t-test was conducted for inter-group comparison to analyze the data.

resultsThe spatiotemporal gait parameters of the systems demonstrated excellent consistency, and the gait phases showed high consistency. Compared to the gold-standard pressure-based gait analysis system (the GATERite system), the mean gait cycle time results were 1.124 s vs. 1.127 s (p = 0.404); cadence was 93.333 steps/min vs. 94.189 steps/min (p = 0.482); stance phase was 60.89% vs. 63.26% (p < 0.001); swing phase was 39.11% vs. 36.74% (p < 0.001); stride length was 1.404 m vs. 1.420 m (p = 0.743); speed was 1.093 m/s vs. 1.110 m/s (p = 0.725). Compared to the gold-standard video-based motion capture system, the root mean square error was 2.7° for the hip angle and 2.6° for the knee angle.

conclusionsThis IMU-based wearable system delivered precise measuring results to evaluate patients with knee OA. This technology can also be used to guide rehabilitation exercises for patients with knee OA.

Indexed as

Osteoarthritis, KneeWearable Electronic DevicesAdultBiomechanical PhenomenaGaitHumansKnee JointLower ExtremityWalkingGait AnalysisKnee; OsteoarthritisRemote Monitor

Identifiers

PMID37545175
PMCPMC10622265
OpenAlexW4385620808

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.