Paper Info
Title
Experimental Recording And Assessing Gait Phases Using Mobile Phone Sensors And Eeg
Abstract
Human manner of walking characterized by kinematic parameters measure posture-gait control characterizing the dynamic changes in body parts with the involvement of multi-sensory patterns processed by different parts of the brain. In this study, low-cost sensors have been used to collect gait signals and identify the features responsible for differentiating the gait phases (swing/stance). Dataset was obtained for a total of 160 trails with 5 gait cycles per trail from healthy volunteers (n=20). Torque involved during progressive gait was also estimated to model regulation of the body for maintaining balance in gait and posture. Additionally, we also investigated EEG and gait correlates by identifying the brain regions that are active during movement initiation and during stance and swing (a progressive gait) using electroencephalography. While identifying key biomarkers relevant for posture control and gait, this could enhance lowcost detection of movement related diseases in technically challenged regions.
Year
DOI
Venue
2018
10.1109/ICACCI.2018.8554790
2018 INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING, COMMUNICATIONS AND INFORMATICS (ICACCI)
Keywords
Field
DocType
gait, mobile phone sensors, electroencephalography, movement
Kinematics,Torque,Gait,Computer science,Control theory,Model regulation,Physical medicine and rehabilitation,Mobile phone,Electroencephalography,Swing
Conference
Citations 
PageRank 
References 
0
0.34
0
Authors
5
Name
Order
Citations
PageRank
Abhijith Balachandran100.34
Chaitanya Nutakki222.08
Sandeep Bodda300.34
Bipin Nair42614.21
Shyam Diwakar54418.20