ArticlePloS one2021
Parkinson's disease medication state and severity assessment based on coordination during walking.
Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 20 citations in OpenAlex.
- Using an unbiased symbolic movement representation to characterize Parkinson's disease states.Scientific reports · 2020Trial
- Validation of IMU-Based Insoles (LUBU) for the Estimation of Gait Spatio-Temporal Parameters.Sensors (Basel, Switzerland) · 2026Article
- A Smart Shoe System for Gait Analysis and Remote Monitoring in Parkinson's Disease-A Validation Study.Sensors (Basel, Switzerland) · 2026Article
- Systematic review of wearables assessing medication effect on motor function and symptoms in Parkinson's disease.NPJ Parkinson's disease · 2025Article
- Comparison of feetme insoles with a motion capture system coupled to force plates for assessing gait and posture.Scientific reports · 2025Article
- The impact of Parkinson's Disease on interlimb coordination: a scoping review of gait adaptability.Frontiers in psychology · 2025Review
- Medication Management Initiatives Using Wearable Devices: Scoping Review.JMIR human factors · 2024Article
- Instrumented timed up and go test and machine learning-based levodopa response evaluation: a pilot study.Journal of neuroengineering and rehabilitation · 2024Article
- Inter-joint coordination with and without dopaminergic medication in Parkinson's disease: a case-control study.Journal of neuroengineering and rehabilitation · 2024Article
- Evaluation of the Validity and Reliability of Connected Insoles to Measure Gait Parameters in Healthy Adults.Sensors (Basel, Switzerland) · 2021Article
- Reliability of IMU-Derived Static Balance Parameters in Neurological Diseases.International journal of environmental research and public health · 2021Article
- Combining Multimodal Behavioral Data of Gait, Speech, and Drawing for Classification of Alzheimer's Disease and Mild Cognitive Impairment.Journal of Alzheimer's disease : JAD · 2021Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Walking is a complex motor function requiring coordination of all body parts. Parkinson's disease (PD) motor signs such as rigidity, bradykinesia, and impaired balance affect movements including walking. Here, we propose a computational method to objectively assess the effects of Parkinson's disease pathology on coordination between trunk, shoulder and limbs during the gait cycle to assess medication state and disease severity. Movements during a scripted walking task were extracted from wearable devices placed at six different body locations in participants with PD and healthy participants. Three-axis accelerometer data from each device was synchronized at the beginning of either left or right steps. Canonical templates of movements were then extracted from each body location. Movements projected on those templates created a reduced dimensionality space, where complex movements are represented as discrete values. These projections enabled us to relate the body coordination in people with PD to disease severity. Our results show that the velocity profile of the right wrist and right foot during right steps correlated with the participant's total score on the gold standard Unified Parkinson's Disease Rating Scale (UPRDS) with an r2 up to 0.46. Left-right symmetry of feet, trunk and wrists also correlated with the total UPDRS score with an r2 up to 0.3. In addition, we demonstrate that binary dopamine replacement therapy medication states (self-reported 'ON' or 'OFF') can be discriminated in PD participants. In conclusion, we showed that during walking, the movement of body parts individually and in coordination with one another changes in predictable ways that vary with disease severity and medication state.
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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.