Quantitative Assessment of Upper Limb Motion in Neurorehabilitation Utilizing Inertial Sensors

Abstract

Abstract-Two inertial sensor systems were developed for 3D 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.

A Pilot Study of Individual Muscle Force Prediction during Elbow Flexion and Extension in the Neurorehabilitation Field

“…A motion monitoring system developed for clinical use should be transportable, easy to set up, and have minimal impact on patients' normal range of movement [6]. To date, optical motion capture is one of the most mature solutions among all existing motion capture methods [32] in the fields of animation production, digital filmmaking, and sports training, etc.…”

“…Assessment scales such as the Fugl-Meyer Assessment (FMA) [3], the Box & Block Test (BBT) [4], and the Action Research Arm Test (ARAT) [5], having been used for years, are all comprehensive and quantitative [6]. As these assessments are viewed and scored by therapists, the evaluation results are often subjective and inaccurate.…”

“…Movement evaluation methods using motion capture systems can provide objective data on the physical movement of the upper limb or how the upper limb moves through space. These precise data may add value in monitoring progress of the patient and the rehabilitation program [6]. However, this method cannot account for neuromuscular characteristics in patients, and the neurological mechanisms used to compensate for the problems associated with their pathology are still unavailable.…”

3D posture estimation of upper limb considering clavicle using inertial sensor

“…Moreover the measurement of the clavicle motion using inertial sensor has not been yet reported. By attaching inertial sensors on scapular, the study about measurement of upper limb was reported (Lu Bai, et al, 2013). However, the accuracy was not inspected.…”

Biological-Signal-Based User-Interface System for Virtual-Reality Applications for Healthcare

“…Although the accuracy and location where movements can be measured vary depending on the number and location of sensors, a technology has been developed lately to the level that user motions can be captured [17]. Research on hands and upper limbs or gait analysis for rehabilitation purposes has been conducted [18,19]. Research on interactive interfaces using gestures for handicapped people has also been carried out.…”