{
  "abstract": "Drug-induced parkinsonism is a potentially reversible movement disorder that may be subtle and difficult to monitor in residential dementia care. Vision-based machine learning analysis of gait may provide unobtrusive longitudinal monitoring around medication changes. We conducted a two-center cohort study of 61 residents with dementia receiving psychotropic medication. Hallway gait sequences were recorded using ceiling-mounted cameras and converted to three-dimensional body pose. A TabPFN classifier estimated UPDRS-III item 29 gait severity for each walk. We evaluated associations between acute antipsychotic (AP) and antidepressant (AD) dose reduction/cessation (≥50% dose reduction or cessation, 0–21 days after change) and daily mean predicted gait severity using linear mixed-effects models in ever-exposed participants, with complementary equal-weight paired analyses among participants observed in both medication states. In mixed-effects models, acute AP dose reduction/cessation was associated with lower predicted gait severity (β=−0.127, p = 0.022), whereas AD dose reduction/cessation was not (β=−0.060, p = 0.210). Equal-weight paired analyses found no statistically significant participant-average within-person change among paired participants (AP mean change = 0.031, 95% CI [−0.114, 0.176], p = 0.653; AD mean change =−0.021, 95% CI [−0.098, 0.056], p = 0.575), consistent with heterogeneous individual responses. Vision-based monitoring captured within-participant gait variation around psychotropic dose-reduction periods, but findings are associative. Larger prospective studies with documented reasons for medication changes are needed before using such monitoring to guide medication decisions. Author summary: Drug-induced parkinsonism is a movement disorder that can occur when older adults take medications used for psychiatric or behavioral symptoms. It can be difficult to detect because symptoms may be subtle and develop gradually, while clinical assessments are often infrequent. We studied whether a camera-based monitoring system installed in residential-care hallways could help track walking changes after medication dose reductions. The system turns short walking videos into body-pose measurements and uses these measurements to estimate gait severity. In 61 residents with dementia, we found that antipsychotic dose reduction was linked with lower estimated parkinsonism gait severity in a participant-day mixed-effects analysis. However, when we gave each paired participant one equal-weight contrast among participants observed both on medication and after a dose reduction/cessation event, we did not find a clear average improvement, and individual responses varied substantially. Antidepressant dose reduction showed no consistent pattern. Our findings suggest that unobtrusive gait monitoring may help identify people whose walking changes around medication adjustments, but it should not be used alone to guide medication decisions.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Engineering Systems and Services, Delft University of Technology, Delft, the Netherlands",
    "Institute for Health Systems Science, Delft University of Technology, Delft, the Netherlands",
    "KITE Research Institute, University Health Network, Toronto, Ontario, Canada",
    "Vector Institute, Toronto, Ontario, Canada",
    "Department of Computer Science, University of Toronto, Toronto, Ontario, Canada",
    "Institute of Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada"
  ],
  "article_type": "Research Article",
  "arxiv": null,
  "author_total": 6,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Benjamin Filtjens"
    },
    {
      "affs": [
        1
      ],
      "name": "Vida Adeli"
    },
    {
      "affs": [
        2
      ],
      "name": "Soroush Mehraban"
    },
    {
      "affs": [
        3
      ],
      "name": "Andrea Sabo"
    },
    {
      "affs": [
        4
      ],
      "name": "Babak Taati"
    },
    {
      "affs": [
        5
      ],
      "name": "Andrea Iaboni"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/02wyek4n5gvfc.bib",
  "cited_by": 0,
  "doi": "10.1371/journal.pdig.0001780",
  "fulltext_url": "https://journals.plos.org/digitalhealth/article?id=10.1371/journal.pdig.0001780",
  "id": "02wyek4n5gvfc",
  "issns": [
    "2767-3170"
  ],
  "landing_url": "https://journals.plos.org/digitalhealth/article?id=10.1371/journal.pdig.0001780",
  "language": "eng",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "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/Medical conditions/Neurodegenerative diseases/Movement disorders/Parkinson disease"
    ],
    [
      "plos",
      "/Medicine and health sciences/Mental health and psychiatry"
    ],
    [
      "plos",
      "/Medicine and health sciences/Mental health and psychiatry/Dementia"
    ],
    [
      "plos",
      "/Medicine and health sciences/Neurology/Dementia"
    ],
    [
      "plos",
      "/Medicine and health sciences/Neurology/Neurodegenerative diseases/Movement disorders/Parkinson disease"
    ],
    [
      "plos",
      "/Medicine and health sciences/Pharmaceutics/Dose prediction methods"
    ],
    [
      "plos",
      "/Medicine and health sciences/Pharmacology/Drugs/Antidepressants"
    ],
    [
      "plos",
      "/Medicine and health sciences/Pharmacology/Drugs/Antipsychotics"
    ]
  ],
  "openalex": "W7221876886",
  "pdf_url": "https://journals.plos.org/digitalhealth/article/file?id=10.1371/journal.pdig.0001780&type=printable",
  "pmcid": "PMC13671658",
  "pmid": null,
  "published": "2026-10-01",
  "publisher": "Public Library of Science",
  "ris": "https://research.draconitic.com/paper/02wyek4n5gvfc.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:23Z",
      "native_id": "10.1371/journal.pdig.0001780",
      "source": "plos",
      "url": "https://journals.plos.org/digitalhealth/article?id=10.1371/journal.pdig.0001780"
    },
    {
      "first_seen": "2026-10-30T12:18:29Z",
      "native_id": "PMC:PMC13671658",
      "source": "europepmc",
      "url": "https://europepmc.org/article/PMC/PMC13671658"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "plos:neurology",
      "subfield": "neurology"
    },
    {
      "field": "medicine",
      "origin": "plos:physiology",
      "subfield": "physiology"
    },
    {
      "field": "medicine",
      "origin": "plos:mental health and psychiatry",
      "subfield": "psychiatry"
    }
  ],
  "title": "Assessment of change in drug-induced parkinsonism in daily-life gait using vision-based machine learning",
  "title_text": "Assessment of change in drug-induced parkinsonism in daily-life gait using vision-based machine learning",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:18:29Z",
  "url": "https://research.draconitic.com/paper/02wyek4n5gvfc",
  "venue": "PLOS Digital Health",
  "versions": []
}