Evidence map›Paper›PMID 41573397›Full record

ArticleFrontiers in neurology2025

Sensor-based quantification of items used in the MDS-UPDRS-III scale: repetitive lower-limb movements in healthy human participants.

Sven Hunziker, Dorian Vogel, Denise Kalt, Stefanie Feiler, Simone Hemm, Alexander Andrea Tarnutzer

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Article in Frontiers in neurology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Sven HunzikerInstitute for Medical Engineering and Medical Informatics, School of Life Sciences, University of Applied Sciences and Arts Northwestern Switzerland, Muttenz, Switzerland.
Dorian VogelInstitute for Medical Engineering and Medical Informatics, School of Life Sciences, University of Applied Sciences and Arts Northwestern Switzerland, Muttenz, Switzerland.
Denise KaltInstitute for Medical Engineering and Medical Informatics, School of Life Sciences, University of Applied Sciences and Arts Northwestern Switzerland, Muttenz, Switzerland.
Stefanie FeilerDynamics and Statistics of Complex Systems, School of Life Sciences, University of Applied Sciences and Arts Northwestern Switzerland, Muttenz, Switzerland.
Simone HemmInstitute for Medical Engineering and Medical Informatics, School of Life Sciences, University of Applied Sciences and Arts Northwestern Switzerland, Muttenz, Switzerland.
Alexander Andrea TarnutzerNeurology, Cantonal Hospital of Baden, Baden, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) is used as a standardized approach to assess motor function in Parkinson's disease (PD). This assessment is based on the examiner's subjective judgement and is therefore variable. While quantitative approaches have been evaluated for upper-limb movements, data is scarce on lower-limb movements. Thus, our aim was to implement and assess a setup to quantify lower-limb movements as defined in the MDS-UPDRS in healthy participants introducing new parameters for smoothness and acceleration patterns. Methods: Twenty-three participants (age-range = 21-31 years) performed five 20-s trials for both lower-limb movement tasks from the MDS-UPDRS-III, i.e., toe tapping (item 3.7) and leg agility (item 3.8). Foot and leg movements were recorded using four inertial measurement units (two per leg: one mounted on the foot and one on the ankle). Biomarkers such as kinematic parameters (e.g., frequency, angular amplitude, movement smoothness, acceleration-based parameters) were extracted to characterize foot-movement dynamics (dominant vs. non-dominant leg), with statistical analyses including linear mixed-effects models applied to four consecutive, non-overlapping 5-s intervals. Results: A paired Wilcoxon test showed no significant differences in parameters for toe tapping and leg agility based on leg dominance. For toe tapping, the relationship between frequency and angle displayed non-linearity, with a clear decrease in angle with 17.41° -0.83°/interval*t (t = 1-4 time intervals) and no clear decrease in frequency with 2.75 Hz - 0.02 Hz/interval*t. The median frequency and angle for toe tapping were 2.8 Hz and 16° respectively. The median frequency for leg agility was 2.6 Hz. Conclusion: Reference values could be determined for all parameters including smoothness and acceleration patterns. The quantitative assessment of two MDS-UPDRS-III items shows that temporal changes and adaptation-mechanisms significantly influenced leg-movement dynamics. Reducing exercise duration to 10 s and implementing a metronome with defined frequency could enhance measurement accuracy and reliability, offering more precise parameters for future applications in PD-patients.

Indexed as

inertial measurement unitleg agilityMDS-UPDRSParkinson’s diseasequantitative assessmenttoe tapping

Identifiers

PMID41573397
PMCPMC12819309

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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.