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Letter

Quantification of Arm Swing during Walking in Healthy Adults and Parkinson’s Disease Patients: Wearable Sensor-Based Algorithm Development and Validation

1
Department of Neurology, Kiel University, Arnold-Heller-Straße 3, 24105 Kiel, Germany
2
Faculty of Engineering, Kiel University, Kaiserstraße 2, 24143 Kiel, Germany
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(20), 5963; https://doi.org/10.3390/s20205963
Received: 15 September 2020 / Revised: 12 October 2020 / Accepted: 20 October 2020 / Published: 21 October 2020
(This article belongs to the Special Issue Wearable Sensors for Movement Analysis)
Neurological pathologies can alter the swinging movement of the arms during walking. The quantification of arm swings has therefore a high clinical relevance. This study developed and validated a wearable sensor-based arm swing algorithm for healthy adults and patients with Parkinson’s disease (PwP). Arm swings of 15 healthy adults and 13 PwP were evaluated (i) with wearable sensors on each wrist while walking on a treadmill, and (ii) with reflective markers for optical motion capture fixed on top of the respective sensor for validation purposes. The gyroscope data from the wearable sensors were used to calculate several arm swing parameters, including amplitude and peak angular velocity. Arm swing amplitude and peak angular velocity were extracted with systematic errors ranging from 0.1 to 0.5° and from −0.3 to 0.3°/s, respectively. These extracted parameters were significantly different between healthy adults and PwP as expected based on the literature. An accurate algorithm was developed that can be used in both clinical and daily-living situations. This algorithm provides the basis for the use of wearable sensor-extracted arm swing parameters in healthy adults and patients with movement disorders such as Parkinson’s disease. View Full-Text
Keywords: gait; gyroscope; inertial measurement unit; Parkinson’s disease gait; gyroscope; inertial measurement unit; Parkinson’s disease
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MDPI and ACS Style

Warmerdam, E.; Romijnders, R.; Welzel, J.; Hansen, C.; Schmidt, G.; Maetzler, W. Quantification of Arm Swing during Walking in Healthy Adults and Parkinson’s Disease Patients: Wearable Sensor-Based Algorithm Development and Validation. Sensors 2020, 20, 5963. https://doi.org/10.3390/s20205963

AMA Style

Warmerdam E, Romijnders R, Welzel J, Hansen C, Schmidt G, Maetzler W. Quantification of Arm Swing during Walking in Healthy Adults and Parkinson’s Disease Patients: Wearable Sensor-Based Algorithm Development and Validation. Sensors. 2020; 20(20):5963. https://doi.org/10.3390/s20205963

Chicago/Turabian Style

Warmerdam, Elke, Robbin Romijnders, Julius Welzel, Clint Hansen, Gerhard Schmidt, and Walter Maetzler. 2020. "Quantification of Arm Swing during Walking in Healthy Adults and Parkinson’s Disease Patients: Wearable Sensor-Based Algorithm Development and Validation" Sensors 20, no. 20: 5963. https://doi.org/10.3390/s20205963

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