Med Biol Eng Comput - Inertial sensors in estimating walking speed and inclination: an evaluation of sensor error models.

Tópicos

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Resumo

With the increasing interest of using inertial measurement units (IMU) in human biomechanics studies, methods dealing with inertial sensor measurement errors become more and more important. Pre-test calibration and in-test error compensation are commonly used to minimize the sensor errors and improve the accuracy of the walking speed estimation results. However, the performance of a given sensor error compensation method does not only depend on the accuracy of the calibration or the sensor error evaluation, but also strongly relies on the selected sensor error model. The best performance could be achieved only when the essential components of sensor errors are included and compensated. Two new sensor error models, with the concerns about sensor acceleration measurement biases and sensor attachment misalignment, have been developed. The performance of these two error models were evaluated in the shank-mounted IMU-based walking speed/inclination estimation algorithm with a comparison of an existing error model. The treadmill walking experiment, conducted at both level and incline conditions, demonstrated the importance of sensor error model selection on the spatio-temporal gait parameter estimation performance. Accurate walking inclination estimation was made possible with a newly developed sensor error model.

Resumo Limpo

increas interest use inerti measur unit imu human biomechan studi method deal inerti sensor measur error becom import pretest calibr intest error compens common use minim sensor error improv accuraci walk speed estim result howev perform given sensor error compens method depend accuraci calibr sensor error evalu also strong reli select sensor error model best perform achiev essenti compon sensor error includ compens two new sensor error model concern sensor acceler measur bias sensor attach misalign develop perform two error model evalu shankmount imubas walk speedinclin estim algorithm comparison exist error model treadmil walk experi conduct level inclin condit demonstr import sensor error model select spatiotempor gait paramet estim perform accur walk inclin estim made possibl newli develop sensor error model

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