{
  "abstract": "Background: Accurate monitoring of activities of daily living (ADLs) in real‑world environments is essential for preventive care and rehabilitation, yet it remains difficult to achieve outside controlled laboratory settings. Instrumented insoles provide a promising, unobtrusive solution for continuous monitoring. However, the use of multimodal systems integrating plantar pressure and inertial data in naturalistic conditions and larger cohorts is still limited. This study therefore aims to evaluate the accuracy of a wireless instrumented insole (WalkinSense) that fuses pressure and inertial sensor data to classify ADLs within a semi free-living setting. Methods: A total of 99 participants performed a broad set of indoor and outdoor activities. Frame-by-frame performance was compared to ground truth (direct observation) using overall accuracy, Cohen’s Kappa, precision, recall, F1-scores and a normalised confusion matrix. Agreement on total activity duration was assessed using mean absolute percentage error (MAPE) scores and Bland-Altman plots. Results: Activity classification showed almost perfect agreement (mean overall accuracy 0.87, mean Cohen’s Kappa 0.84). Excellent performance (F1 > 0.90) was achieved for sitting, walking with crutches and cycling, while standing, level and non-level walking showed good performance (F1 > 0.80). Most misclassifications occurred between level walking, hill walking and stairs. Duration-based analysis confirmed high accuracy for sitting, walking with crutches and cycling (MAPE ≤ 10%). Bland-Altman plots indicated overestimation of level walking and underestimation of hill and stair walking. Step count was highly accurate (MAPE < 5%), whereas stair count showed only reasonable accuracy (MAPE ≈ 26%). Conclusion: These findings demonstrate the system’s strong potential for real-world monitoring and classification of ADLs while also highlighting the need for improved detection of non-level walking activities.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Precision Health, Luxembourg Institute of Health, Strassen, Luxembourg",
    "Luxembourg Institute of Research in Orthopedics, Sports Medicine and Science, Eich, Luxembourg",
    "IEE S.A., Bissen, Luxembourg",
    "Centre Hospitalier de Luxembourg, Eich, Luxembourg"
  ],
  "article_type": "Research Article",
  "arxiv": null,
  "author_total": 10,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Anne Backes"
    },
    {
      "affs": [
        1
      ],
      "name": "Melanie Eckelt"
    },
    {
      "affs": [
        2
      ],
      "name": "Jennifer Fayad"
    },
    {
      "affs": [
        3
      ],
      "name": "Valeria Serchi"
    },
    {
      "name": "Thomas Solignac"
    },
    {
      "name": "Tobias Meyer"
    },
    {
      "name": "Bernd Grimm"
    },
    {
      "name": "Caroline Mouton"
    },
    {
      "name": "Romain Seil"
    },
    {
      "name": "Laurent Malisoux"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/bkjy527bdc6f6.bib",
  "cited_by": 0,
  "doi": "10.1371/journal.pone.0357961",
  "fulltext_url": null,
  "id": "bkjy527bdc6f6",
  "issns": [
    "1932-6203"
  ],
  "landing_url": "https://doi.org/10.1371/journal.pone.0357961",
  "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",
      "1707|Context-Aware Activity Recognition Systems"
    ],
    [
      "plos",
      "/Biology and life sciences/Physiology/Biological locomotion/Gait analysis"
    ],
    [
      "plos",
      "/Biology and life sciences/Physiology/Biological locomotion/Walking"
    ],
    [
      "plos",
      "/Engineering and technology/Management engineering/Decision analysis/Decision trees"
    ],
    [
      "plos",
      "/Medicine and health sciences/Public and occupational health/Physical activity"
    ],
    [
      "plos",
      "/Medicine and health sciences/Rehabilitation medicine/Gait rehabilitation"
    ],
    [
      "plos",
      "/Physical sciences/Materials science/Materials/Resistors"
    ],
    [
      "plos",
      "/Physical sciences/Physics/Classical mechanics/Motion/Inertia"
    ],
    [
      "plos",
      "/Research and analysis methods/Decision analysis/Decision trees"
    ],
    [
      "plos",
      "/Research and analysis methods/Imaging techniques/Video recording"
    ]
  ],
  "openalex": "W7213406131",
  "pdf_url": "https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0357961&type=printable",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-16",
  "publisher": "Public Library of Science",
  "ris": "https://research.draconitic.com/paper/bkjy527bdc6f6.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:49Z",
      "native_id": "10.1371/journal.pone.0357961",
      "source": "plos",
      "url": "https://doi.org/10.1371/journal.pone.0357961"
    }
  ],
  "subjects": [
    {
      "field": "chemistry",
      "origin": "plos:materials science",
      "subfield": "materials-polymers"
    },
    {
      "field": "medicine",
      "origin": "plos:public and occupational health",
      "subfield": "epidemiology-public-health"
    },
    {
      "field": "medicine",
      "origin": "plos:physiology",
      "subfield": "physiology"
    }
  ],
  "title": "Classification of daily activities using a wireless instrumented insole (WalkinSense) in a semi free-living setting",
  "title_text": "Classification of daily activities using a wireless instrumented insole (WalkinSense) in a semi free-living setting",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:17:49Z",
  "url": "https://research.draconitic.com/paper/bkjy527bdc6f6",
  "venue": "PLOS One",
  "versions": []
}