title: Gait Partitioning Methods: A Systematic 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.
authors.affiliation: Department of Mechanical and Aerospace Engineering, Sapienza University of Roma, Via Eudossiana 18, Roma I-00184, Italy. juri.taborri@uniroma1.it.
authors.forename: Juri
authors.initials: J
authors.lastname: Taborri
authors.affiliation: Department of Mechanical and Aerospace Engineering, Sapienza University of Roma, Via Eudossiana 18, Roma I-00184, Italy. eduardo.palermo@uniroma1.it.
authors.forename: Eduardo
authors.initials: E
authors.lastname: Palermo
authors.affiliation: Department of Economics and Management, Industrial Engineering (DEIM), University of Tuscia, Via del Paradiso 47, Viterbo I-01100, Italy. stefano.rossi@unitus.it.
authors.forename: Stefano
authors.initials: S
authors.lastname: Rossi
authors.affiliation: Department of Mechanical and Aerospace Engineering, Sapienza University of Roma, Via Eudossiana 18, Roma I-00184, Italy. paolo.cappa@uniroma1.it.|MARLab, Movement Analysis and Robotics Laboratory, Neurorehabilitation Division, IRCCS Children's Hospital "Bambino Gesù", Via Torre di Palidoro snc, Fiumicino (RM) I-00050, Italy. paolo.cappa@uniroma1.it.
authors.forename: Paolo
authors.initials: P
authors.lastname: Cappa
mesh_terms: D061725:Accelerometry; D003020:Clothing; D004576:Electromyography; D005684:Gait / Q000502:physiology*; D006801:Humans; D018670:Monitoring, Ambulatory; D012815:Signal Processing, Computer-Assisted
keywords: electromyography (EMG); footswitches; force platform; gait pattern; gait phase partitioning; inertial measurements units (IMU); opto-electronic system; wearable sensors