SAFETYLIT WEEKLY UPDATE

We compile citations and summaries of about 400 new articles every week.
RSS Feed

HELP: Tutorials | FAQ
CONTACT US: Contact info

Search Results

Journal Article

Citation

Taborri J, Palermo E, Rossi S, Cappa P. Sensors (Basel) 2016; 16(1): s16010066.

Affiliation

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.

Copyright

(Copyright © 2016, MDPI: Multidisciplinary Digital Publishing Institute)

DOI

10.3390/s16010066

PMID

26751449

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.


Language: en

NEW SEARCH


All SafetyLit records are available for automatic download to Zotero & Mendeley
Print