Gait partitioning methods: A systematic review

Juri Taborri, Eduardo Palermo, Stefano Rossi, Paolo Cappa

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Article number66
JournalSensors (Switzerland)
Volume16
Issue number1
DOIs
Publication statusPublished - Jan 6 2016

Keywords

  • Electromyography (EMG)
  • Footswitches
  • Force platform
  • Gait pattern
  • Gait phase partitioning
  • Inertial measurements units (IMU)
  • Opto-electronic system
  • Wearable sensors

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Atomic and Molecular Physics, and Optics
  • Analytical Chemistry
  • Biochemistry

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