{
  "abstract": "The purpose of this study was to use the meta-analytic approach to investigate the ability of Inertial Measurement Unit-based commercial system measured gait variability and asymmetry in distinguishing individuals with Parkinson’s disease (PD) from healthy controls (HC). Cross-sectional studies included using commercial IMU-based systems measuring gait variability or asymmetry at any stage of PD patients and healthy adults were included. Studies were determined by searching for four electronic databases and cross-referencing. Dual selection and data abstraction of studies were conducted. Hedges’ g standardized mean difference was calculated for each variable and pooled using inverse heterogeneity mode. Statistically significant was determined by two tailed z-alpha values ≤0.05 and non-overlapping 95% CI. Heterogeneity was estimated using Q and I2 with alpha values ≤0.10 for Q considered statistically significant. Small-study effects were examined using doi plots and LFK index. A total of 1,725 studies were screened. Eventually, 9 studies representing up to 571 PD patients and 470 HC met the inclusion criteria. Overall gait variability was significantly greater in individuals with PD than in HC (Hedges’ g = 0.368, 95% CI 0.139–0.597). The multi-IMU subgroup also showed significantly greater gait variability (Hedges’ g = 0.397, 95% CI 0.221–0.574), whereas the one-IMU subgroup did not. However, the between-subgroup difference was not statistically significant, and the multi-IMU prediction interval included null. The primary analysis detected no statistically significant overall difference in gait asymmetry (Hedges’ g = 0.180, 95% CI −0.012–0.373). These findings provide preliminary evidence of an average group-level difference in gait variability but hard to establish individual-level discrimination, clinical utility, or the superiority of multi-IMU systems.",
  "abstract_shown": true,
  "affiliations": [
    "Biomechanics & Neurorehabilitation Lab, Department of Physical Education, Xinjiang Normal University, Urumqi, Xinjiang, China",
    "Department of Kinesiology and Health Education, The University of Texas at Austin, Austin, Texas, United States of America"
  ],
  "article_type": "Research Article",
  "arxiv": null,
  "author_total": 2,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Jiahao Pan"
    },
    {
      "affs": [
        1
      ],
      "name": "Hui Tang"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/7n9gh8s9p3g5e.bib",
  "cited_by": 0,
  "doi": "10.1371/journal.pone.0360793",
  "fulltext_url": null,
  "id": "7n9gh8s9p3g5e",
  "issns": [
    "1932-6203"
  ],
  "landing_url": "https://doi.org/10.1371/journal.pone.0360793",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "3612|Balance, Gait, and Falls Prevention"
    ],
    [
      "plos",
      "/Biology and life sciences/Physiology/Biological locomotion/Gait analysis"
    ],
    [
      "plos",
      "/Biology and life sciences/Physiology/Biological locomotion/Walking"
    ],
    [
      "plos",
      "/Medicine and health sciences/Epidemiology/Medical risk factors"
    ],
    [
      "plos",
      "/Medicine and health sciences/Medical conditions/Neurodegenerative diseases/Movement disorders/Parkinson disease"
    ],
    [
      "plos",
      "/Medicine and health sciences/Neurology/Neurodegenerative diseases/Movement disorders/Parkinson disease"
    ],
    [
      "plos",
      "/Physical sciences/Mathematics/Statistics/Statistical methods/Metaanalysis"
    ],
    [
      "plos",
      "/Research and analysis methods/Database and informatics methods/Database searching"
    ],
    [
      "plos",
      "/Research and analysis methods/Mathematical and statistical techniques/Statistical methods/Metaanalysis"
    ],
    [
      "plos",
      "/Research and analysis methods/Research assessment/Systematic reviews"
    ],
    [
      "plos",
      "/Research and analysis methods/Research design/Cross-sectional studies"
    ]
  ],
  "openalex": "W7222276920",
  "pdf_url": "https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0360793&type=printable",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-15",
  "publisher": "Public Library of Science",
  "ris": "https://research.draconitic.com/paper/7n9gh8s9p3g5e.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:23Z",
      "native_id": "10.1371/journal.pone.0360793",
      "source": "plos",
      "url": "https://doi.org/10.1371/journal.pone.0360793"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "plos:statistical methods",
      "subfield": "statistics"
    },
    {
      "field": "medicine",
      "origin": "plos:epidemiology",
      "subfield": "epidemiology-public-health"
    },
    {
      "field": "medicine",
      "origin": "plos:physiology",
      "subfield": "physiology"
    }
  ],
  "title": "The ability of the commercial inertial measurement unit-based gait system in determining Parkinson’s disease: A systematic review with meta-analysis of cross-sectional studies",
  "title_text": "The ability of the commercial inertial measurement unit-based gait system in determining Parkinson’s disease: A systematic review with meta-analysis of cross-sectional studies",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:17:23Z",
  "url": "https://research.draconitic.com/paper/7n9gh8s9p3g5e",
  "venue": "PLOS One",
  "versions": []
}