Gait-cycle segmentation method based on lower-trunk acceleration signals and dynamic time warping

Background: Gait deviations may negatively affect the articular surfaces of the lower extremity joints and lead to some minor degenerative changes. The simplest method for gait evaluation is to assess the symmetry of its parameters, assuming that each undisturbed gait should be symmetrical. This study aims to quantify the degree of asymmetry of kinematic and kinetic parameters caused by the presence of different ankle orthosis settings using Dynamic Time Warping (DTW). Methods: Barefoot gait and gait with four different walker settings were investigated in eighteen healthy persons. Kinematic and kinetic parameters were measured using the Vicon system and Kistler plates. Symmetry was assessed using the DTW method. Results: It was shown that the presence of different ankle orthosis settings significantly disturbs the symmetry of all lower limb kinematic parameters and only knee and hip torques. The highest values of asymmetry were noted for the walker set at 15° of dorsiflexion (15DF). Conclusions: The DTW method allowed us to quantify the degree of asymmetry throughout the gait cycle in relation to barefoot walking. Our results suggest that each orthosis position analysed in this study fulfills its protective function, but gait 15DF can lead to the overload of knee and hip joints.

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SPEED-INDEPENDENT GAIT IDENTIFICATION FOR MOBILE DEVICES

International Journal of Pattern Recognition and Artificial Intelligence ◽

10.1142/s0218001412600130 ◽

2012 ◽

Vol 26 (08) ◽

pp. 1260013 ◽

Cited By ~ 7

Author(s):

GONZALO BAILADOR DEL POZO ◽

CARMEN SÁNCHEZ-ÁVILA ◽

ALBERTO DE-SANTOS-SIERRA ◽

JAVIER GUERRA-CASANOVA

Keyword(s):

Dynamic Time Warping ◽

Euclidean Distance ◽

Identification Problem ◽

Time Warping ◽

Classical Dynamic ◽

Intensive Use ◽

Dynamic Time ◽

Gait Identification ◽

New Generation ◽

Acceleration Signals

Due to the intensive use of mobile phones for different purposes, these devices usually contain confidential information which must not be accessed by another person apart from the owner of the device. Furthermore, the new generation phones commonly incorporate an accelerometer which may be used to capture the acceleration signals produced as a result of owner's gait. Nowadays, gait identification in basis of acceleration signals is being considered as a new biometric technique which allows blocking the device when another person is carrying it. Although distance based approaches as Euclidean distance or dynamic time warping have been applied to solve this identification problem, they show difficulties when dealing with gaits at different speeds. For this reason, in this paper, a method to extract an average template from instances of the gait at different velocities is presented. This method has been tested with the gait signals of 34 subjects while walking at different motion speeds (slow, normal and fast) and it has shown to improve the performance of Euclidean distance and classical dynamic time warping.

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