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

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)...

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Veröffentlicht in:Sensors (Basel, Switzerland) Jg. 20; H. 20; S. 5963
Hauptverfasser: Warmerdam, Elke, Romijnders, Robbin, Welzel, Julius, Hansen, Clint, Schmidt, Gerhard, Maetzler, Walter
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Switzerland MDPI AG 21.10.2020
MDPI
Schlagworte:
Adult
Aged
Algorithms
Arm
Asymmetry
Fitness equipment
Gait
gyroscope
Humans
inertial measurement unit
Letter
Male
Middle Aged
Parkinson Disease - diagnosis
Parkinson's disease
Principal components analysis
Sensors
Velocity
Walking
Wearable Electronic Devices
United States > US
inertial measurement unit
gait
Parkinson’s disease
gyroscope
ISSN:1424-8220, 1424-8220
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Zusammenfassung: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.
Bibliographie:SourceType-Scholarly Journals-1
ObjectType-Correspondence-1
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ISSN:1424-8220
1424-8220
DOI:10.3390/s20205963