DocumentCode
1985085
Title
VRACK: Measuring pedal kinematics during stationary bike cycling
Author
Farjadian, Amir B. ; Kong, Qing-Jie ; Gade, Venkata K. ; Deutsch, Judith E. ; Mavroidis, Constantinos
Author_Institution
Dept. of Mech. & Ind. Eng., Northeastern Univ., Boston, MA, USA
fYear
2013
fDate
24-26 June 2013
Firstpage
1
Lastpage
6
Abstract
Ankle impairment and lower limb asymmetries in strength and coordination are common symptoms for individuals with selected musculoskeletal and neurological impairments. The virtual reality augmented cycling kit (VRACK) was designed as a compact mechatronics system for lower limb and mobility rehabilitation. The system measures interaction forces and cardiac activity during cycling in a virtual environment. The kinematics measurement was added to the system. Due to the constrained problem definition, the combination of inertial measurement unit (IMU) and Kalman filtering was recruited to compute the optimal pedal angular displacement during dynamic cycling exercise. Using a novel benchmarking method the accuracy of IMU-based kinematics measurement was evaluated. Relatively accurate angular measurements were achieved. The enhanced VRACK system can serve as a rehabilitation device to monitor biomechanical and physiological variables during cycling on a stationary bike.
Keywords
Kalman filters; augmented reality; benchmark testing; biomechanics; biomedical equipment; biomedical measurement; cardiology; force measurement; kinematics; mechatronics; medical disorders; medical signal processing; neurophysiology; patient rehabilitation; Kalman filtering; VRACK; accurate angular measurements; ankle impairment; biomechanical variables; cardiac activity; compact mechatronics system; constrained problem definition; dynamic cycling exercise; inertial measurement unit; interaction force measurement; lower limb asymmetries; mobility rehabilitation; musculoskeletal impairments; neurological impairments; novel benchmarking method; optimal pedal angular displacement; pedal kinematics measurement; physiological variables; rehabilitation device; stationary bike cycling; virtual environment; virtual reality augmented cycling kit; Acceleration; Accuracy; Biomedical monitoring; Kalman filters; Kinematics; Monitoring; Virtual reality; Inertial measurement unit; Kalman Filter; Kinematics measurement; Lower limb rehabilitation;
fLanguage
English
Publisher
ieee
Conference_Titel
Rehabilitation Robotics (ICORR), 2013 IEEE International Conference on
Conference_Location
Seattle, WA
ISSN
1945-7898
Print_ISBN
978-1-4673-6022-7
Type
conf
DOI
10.1109/ICORR.2013.6650453
Filename
6650453
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