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http://dx.doi.org/10.6109/jicce.2017.15.4.244

Seafarers Walking on an Unstable Platform: Comparisons of Time and Frequency Domain Analyses for Gait Event Detection  

Youn, Ik-Hyun (Department of Computer Science, College of Information Science & Technology, University of Nebraska at Omaha)
Choi, Jungyeon (Department of Computer Science, College of Information Science & Technology, University of Nebraska at Omaha)
Youn, Jong-Hoon (Department of Computer Science, College of Information Science & Technology, University of Nebraska at Omaha)
Publication Information
Journal of information and communication convergence engineering / v.15, no.4, 2017 , pp. 244-249 More about this Journal
Abstract
Wearable sensor-based gait analysis has been widely conducted to analyze various aspects of human ambulation abilities under the free-living condition. However, there have been few research efforts on using wearable sensors to analyze human walking on an unstable surface such as on a ship during a sea voyage. Since the motion of a ship on the unstable sea surface imposes significant differences in walking strategies, investigation is suggested to find better performing wearable sensor-based gait analysis algorithms on this unstable environment. This study aimed to compare two representative gait event algorithms including time domain and frequency domain analyses for detecting heel strike on an unstable platform. As results, although two methods did not miss any heel strike, the frequency domain analysis method perform better when comparing heel strike timing. The finding suggests that the frequency analysis is recommended to efficiently detect gait event in the unstable walking environment.
Keywords
Frequency and time domain analysis; Gait event detection; Unstable surface; Wearable sensor;
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