2021
DOI: 10.1016/j.gaitpost.2020.11.017
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Validation of a smartphone embedded inertial measurement unit for measuring postural stability in older adults

Abstract: Background. Identifying older adults with increased fall risk due to poor postural control on a large scale is only possible through omnipresent and low cost measuring devices such as the inertial measurement units (IMU) embedded in smartphones. However, the correlation between smartphone measures of postural stability and state-of-the-art force plate measures has never been assessed in a large sample allowing us to take into account age as a covariate.Research question. How reliably can postural stability be … Show more

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Cited by 19 publications
(9 citation statements)
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“…The authors of neither study mentioned validation of their apps against gold standard tools 85,113 . Given the widespread use of smartphones, this may be the most scalable and acceptable option to measure gait, although the variable positioning of smartphones (e.g., in the hand, pocket, or a bag) may pose challenges to signal extraction and data quality 155,156 . Only three studies recorded gait remotely and only one also collected gait data passively while participants carried out their normal daily activities.…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…The authors of neither study mentioned validation of their apps against gold standard tools 85,113 . Given the widespread use of smartphones, this may be the most scalable and acceptable option to measure gait, although the variable positioning of smartphones (e.g., in the hand, pocket, or a bag) may pose challenges to signal extraction and data quality 155,156 . Only three studies recorded gait remotely and only one also collected gait data passively while participants carried out their normal daily activities.…”
Section: Resultsmentioning
confidence: 99%
“…134 Although device transferability in gait is more complex owing to the difficulties caused by the variable smartphone positioning, small wearable sensors that can be temporarily fixed to the body and developments in signal extraction algorithms for smartphone data may in the future provide the means for remote measurement of motoric behaviors of this kind. 155,156 Passive sensing of behaviors has many advantages over active testing, including lower user burden and high ecological validity 28,[159][160][161][162] ;…”
Section: Devicesmentioning
confidence: 99%
“…Control postural: El procedimiento se realizó en bipedestación estática sobre una base estable en condición ojos abiertos (Jiménez, AMF, 2018). Las oscilaciones se midieron a través de un acelerómetro triaxial incorporado en un teléfono inteligente (Samsung Galaxy, prime) (Hsieh et al, 2019;De Groote et al, 2021); posicionado en la vértebra L5 utilizando el protocolo propuesto por (Godfrey et al, 2015). Para el cálculo de las posiciones del centro de presión fueron usados los procesos matemáticos elaborados por Mayagoitia et al, (2002), y para las variables del COP se emplearon las fórmulas sugeridas por Duarte & Freitas, (2010), mediante un script, en lenguaje MATLAB (versión 2020 MathWorks, Inc).…”
Section: Procedimientosunclassified
“…After YOLOv4, the YOLOX object detection network appeared and showed superior performance [ 23 ]. The YOLO series algorithm can accurately extract image feature points after training, as well as it consumes less time and does not require human experience intervention [ 24 , 25 , 26 , 27 ].…”
Section: Introductionmentioning
confidence: 99%