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Sensors 2016, 16(1), 66; doi:10.3390/s16010066

Gait Partitioning Methods: A Systematic Review

1
Department of Mechanical and Aerospace Engineering, Sapienza University of Roma, Via Eudossiana 18, Roma I-00184, Italy
2
Department of Economics and Management, Industrial Engineering (DEIM), University of Tuscia, Via del Paradiso 47, Viterbo I-01100, Italy
3
MARLab, Movement Analysis and Robotics Laboratory, Neurorehabilitation Division, IRCCS Children’s Hospital “Bambino Gesù”, Via Torre di Palidoro snc, Fiumicino (RM) I-00050, Italy
*
Author to whom correspondence should be addressed.
Academic Editor: Oliver Amft
Received: 30 November 2015 / Revised: 24 December 2015 / Accepted: 4 January 2016 / Published: 6 January 2016
(This article belongs to the Special Issue Wearable Sensors)
View Full-Text   |   Download PDF [236 KB, uploaded 6 January 2016]

Abstract

In the last years, gait phase partitioning has come to be a challenging research topic due to its impact on several applications related to gait technologies. A variety of sensors can be used to feed algorithms for gait phase partitioning, mainly classifiable as wearable or non-wearable. Among wearable sensors, footswitches or foot pressure insoles are generally considered as the gold standard; however, to overcome some inherent limitations of the former, inertial measurement units have become popular in recent decades. Valuable results have been achieved also though electromyography, electroneurography, and ultrasonic sensors. Non-wearable sensors, such as opto-electronic systems along with force platforms, remain the most accurate system to perform gait analysis in an indoor environment. In the present paper we identify, select, and categorize the available methodologies for gait phase detection, analyzing advantages and disadvantages of each solution. Finally, we comparatively examine the obtainable gait phase granularities, the usable computational methodologies and the optimal sensor placements on the targeted body segments. View Full-Text
Keywords: gait phase partitioning; gait pattern; wearable sensors; footswitches; inertial measurements units (IMU); electromyography (EMG); opto-electronic system; force platform gait phase partitioning; gait pattern; wearable sensors; footswitches; inertial measurements units (IMU); electromyography (EMG); opto-electronic system; force platform
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Taborri, J.; Palermo, E.; Rossi, S.; Cappa, P. Gait Partitioning Methods: A Systematic Review. Sensors 2016, 16, 66.

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