ArticleJMIR mHealth and uHealth2020
Measurement of Step Angle for Quantifying the Gait Impairment of Parkinson's Disease by Wearable Sensors: Controlled Study.
Article in JMIR mHealth and uHealth, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 12 citations in OpenAlex.
- Sensor-Derived Parameters from Standardized Walking Tasks Can Support the Identification of Patients with Parkinson's Disease at Risk of Gait Deterioration.Bioengineering (Basel, Switzerland) · 2026Article
- Instrumented timed up and go test and machine learning-based levodopa response evaluation: a pilot study.Journal of neuroengineering and rehabilitation · 2024Article
- Evaluation of the Parkinson's Remote Interactive Monitoring System in a Clinical Setting: Usability Study.JMIR human factors · 2024Article
- Technology-based therapy-response evaluation of axial motor symptoms under daily drug regimen of patients with Parkinson's disease.Frontiers in aging neuroscience · 2022Article
- A Multi-Sensor Wearable System for the Quantitative Assessment of Parkinson's Disease.Sensors (Basel, Switzerland) · 2020Article
- Development and Initial Validation of the Chinese Version of the Florida Surgical Questionnaire for Parkinson's Disease.Parkinson's disease · 2020Article
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Authors and funding
8 authors at 5 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGait impairments including shuffling gait and hesitation are common in people with Parkinson's disease (PD), and have been linked to increased fall risk and freezing of gait. Nowadays the gait metrics mostly focus on the spatiotemporal characteristics of gait, but less is known of the angular characteristics of the gait, which may provide helpful information pertaining to the functional status and effects of the treatment in PD.
objectiveThis study aimed to quantify the angles of steps during walking, and explore if this novel step angle metric is associated with the severity of PD and the effects of the treatment including the acute levodopa challenge test (ALCT) and deep brain stimulation (DBS).
methodsA total of 18 participants with PD completed the walking test before and after the ALCT, and 25 participants with PD completed the test with the DBS on and off. The walking test was implemented under two conditions: walking normally at a preferred speed (single task) and walking while performing a cognitive serial subtraction task (dual task). A total of 17 age-matched participants without PD also completed this walking test. The angular velocity was measured using wearable sensors on each ankle, and three gait angular metrics were obtained, that is mean step angle, initial step angle, and last step angle. The conventional gait metrics (ie, step time and step number) were also calculated.
resultsThe results showed that compared to the control, the following three step angle metrics were significantly smaller in those with PD: mean step angle (F
conclusionsThis pilot study demonstrated that the gait angular characteristics, as quantified by the step angles, were sensitive to the disease severity of PD and, more importantly, can capture the effects of treatments on the gait, while the traditional metrics cannot. This indicates that these metrics may serve as novel markers to help the assessment of gait in those with PD as well as the rehabilitation of this vulnerable cohort.
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