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Validation of gait analysis using smartphones: Reliability and validity.
Tao, Shuai; Zhang, Hao; Kong, Liwen; Sun, Yan; Zhao, Jie.
Afiliación
  • Tao S; College of Information Engineering, Dalian University, Dalian, Liaoning, China.
  • Zhang H; College of Information Engineering, Dalian University, Dalian, Liaoning, China.
  • Kong L; College of Information Engineering, Dalian University, Dalian, Liaoning, China.
  • Sun Y; China United Network Communications Co Ltd, Huaian, Jiangsu, China.
  • Zhao J; Affiliated Zhongshan Hospital of Dalian University, Department of Neurology, Dalian, Liaoning, China.
Digit Health ; 10: 20552076241257054, 2024.
Article en En | MEDLINE | ID: mdl-38817844
ABSTRACT

Objective:

This study aims to validate the reliability and validity of gait analysis using smartphones in a controlled environment.

Methods:

Thirty healthy adults attached smartphones to the waist and thigh, while an inertial measurement unit was fixed at the shank as a reference device; each participant was asked to walk six gait cycles at self-selected low, normal, and high speeds. Thirty-five cerebral small vessel disease patients were recruited to attach the smartphone to the thigh, performing single-task (ST), cognitive dual-task (DT1), and physical dual-task walking (DT2) to obtain gait parameters.

Results:

The results from the healthy group indicate that, regardless of whether attached to the thigh or waist, the smartphones calculated gait parameters with good reliability (ICC2,1 > 0.75) across three different walking speeds. There were no significant differences in the gait parameters between the smartphone attached to the thigh and the IMU across all three walking speeds (P > 0.05). However, significant differences were observed between the smartphone at the waist and the IMU during the stance phase, swing phase, stance time, and stride length at high speeds (P < 0.05). At the same time, measurements of other gait parameters were similar (P > 0.05). Patients demonstrated significant differences in the cadence, stride time, stance phase, swing phase, stance time, stride length, and walking speed between ST and DT1 (P < 0.05). Significant differences were observed in the stance phase, swing phase, stride length, and walking speed between ST and DT2 (P < 0.05).

Conclusions:

This study demonstrates the feasibility of using built-in smartphone sensors for gait analysis in a controlled environment.
Palabras clave

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Digit Health Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Digit Health Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Estados Unidos