Establishing accelerometer cut-points to classify walking speed in people post stroke

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dc.contributor.authorConradsson, David Moulaee
dc.contributor.authorBezuidenhout, Lucian John-Ross
dc.date.accessioned2022-07-14T09:14:11Z
dc.date.available2022-07-14T09:14:11Z
dc.date.issued2022
dc.description.abstractWhile accelerometers could be used to monitor important domains of walking in daily living (e.g., walking speed), the interpretation of accelerometer data often relies on validation studies performed with healthy participants. The aim of this study was to develop cut-points for waistand ankle-worn accelerometers to differentiate non-ambulation from walking and different walking speeds in people post stroke. Forty-two post-stroke persons wore waist and ankle accelerometers (ActiGraph GT3x+, AG) while performing three non-ambulation activities (i.e., sitting, setting the table and washing dishes) and while walking in self-selected and brisk speeds. Receiver operating characteristic (ROC) curve analysis was used to define AG cut-points for non-ambulation and different walking speeds (0.41–0.8 m/s, 0.81–1.2 m/s and >1.2 m/s) by considering sensor placement, axis, filter setting and epoch length. Optimal data input and sensor placements for measuring walking were a vector magnitude at 15 s epochs for waist- and ankle-worn AG accelerometers, respectively.en_US
dc.identifier.citationConradsson, D. M., & Bezuidenhout, L. J. R. (2022). Establishing accelerometer cut-points to classify walking speed in people post stroke. Sensors , 22(11), 4080. https://doi.org/10.3390/s22114080en_US
dc.identifier.issn1424-8220
dc.identifier.urihttps://doi.org/10.3390/s22114080
dc.identifier.urihttp://hdl.handle.net/10566/7594
dc.language.isoenen_US
dc.publisherMDPIen_US
dc.subjectStrokeen_US
dc.subjectMortalityen_US
dc.subjectHealth scienceen_US
dc.subjectAccelerometersen_US
dc.titleEstablishing accelerometer cut-points to classify walking speed in people post strokeen_US
dc.typeArticleen_US

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