Title :
Quantitative Assessment of Upper Limb Motion in Neurorehabilitation Utilizing Inertial Sensors
Author :
Lu Bai ; Pepper, Matthew G. ; Yong Yan ; Spurgeon, Sarah K. ; Sakel, Mohamed ; Phillips, Malcolm
Author_Institution :
Sch. of Eng. & Digital Arts, Univ. of Kent, Canterbury, UK
Abstract :
Two inertial sensor systems were developed for 3-D tracking of upper limb movement. One utilizes four sensors and a kinematic model to track the positions of all four upper limb segments/joints and the other uses one sensor and a dead reckoning algorithm to track a single upper limb segment/joint. Initial evaluation indicates that the system using the kinematic model is able to track orientation to 1 degree and position to within 0.1 cm over a distance of 10 cm. The dead reckoning system combined with the “zero velocity update” correction can reduce errors introduced through double integration of errors in the estimate in offsets of the acceleration from several meters to 0.8% of the total movement distance. Preliminary evaluation of the systems has been carried out on ten healthy volunteers and the kinematic system has also been evaluated on one patient undergoing neurorehabilitation over a period of ten weeks. The initial evaluation of the two systems also shows that they can monitor dynamic information of joint rotation and position and assess rehabilitation process in an objective way, providing additional clinical insight into the rehabilitation process.
Keywords :
biomechanics; kinematics; motion estimation; neurophysiology; patient rehabilitation; sensors; 3D upper limb movement tracking; 3D upper limb position tracking; acceleration offsets; dead reckoning algorithm; distance 10 cm; inertial sensor systems; kinematic system; neurorehabilitation; time 10 week; zero velocity update correction; Acceleration; Joints; Kinematics; Sensor systems; Shoulder; Tracking; 3-D motion tracking; Dead reckoning; inertial sensors; kinematic modelling; motion monitoring; upper limb motion; zero velocity update;
Journal_Title :
Neural Systems and Rehabilitation Engineering, IEEE Transactions on
DOI :
10.1109/TNSRE.2014.2369740