Kinematic and Kinetic Comparisons of Arm and Hand Reaching Movements with Mild and Moderate Gravity-Supported, Computer-Enhanced Armeo®spring: A Case Study - (:unkn) unknown (My University, 2013)
Background: Stroke has been recognized as a leading cause of serious long-term disability in the United States (U.S.) with 795,000 people experience a new or recurrent stroke each year (Roger et al., 2011). The most apparent defect after stroke is motor impairments (Masiero, Armani, & Rosati, 2011). Statistically, half of stroke survivors suffer from upper extremity hemiparesis and approximately one quarter become dependent in activities of daily living (Sanchez et al., 2006). There is strong evidence that intensity and task specificity are the main drivers in an effective treatment program after stroke. In addition, this training should be repetitive, functional, meaningful, and challenging for a patient (Van Peppen et al., 2004). The use of robotic systems to complement standard poststroke multidisciplinary programs is a recent approach that looks very promising. Robotic devices can provide high-intensity, repetitive, task-specific, interactive treatment of the impaired limb and can monitor patients' motor progress objectively and reliably, measuring changes in quantitative movement kinematics and forces (Masiero, Armani, & Rosati, 2011). Objective: The purpose of this study was to examine the role of Armeo®Spring (Hocoma, Inc.), a gravity-supported, computer-enhanced robotic devise, on reaching movements while using two different gravity-support levels (mild and moderate weight support) on individuals with stroke. Methods: One stroke subject and one gender-matched healthy control participated in this study after gaining their informed consent. Both subjects performed a computer-based game (picking apples successfully and placing them in a shopping cart) under two gravity weight-support conditions (mild and moderate) provided by the Armeo®Spring device. The game tasks were described as a reaching cycle which consisted of five phases (initiation, reaching, grasping, transporting, and releasing). Joint angles for the glenohumeral and elbow joints throughout the reaching cycle were found. Three kinematic parameters (completion time, moving velocity, acceleration) and one kinetic parameter (vertical force acting on the forearm) was calculated for various instances and phases of the reaching motion. In addition, the muscle activation patterns for anterior deltoid, middle deltoid, biceps, triceps, extensor digitorum, flexor digitorum, and brachioradialis were found and the mean magnitude of the electromyography (EMG) signal during each phase of the reaching cycle was found as a percentage of the subject's maximum voluntary contraction (MVC). Results: Within the healthy control subject, results demonstrated no significant differences in mean completion time, moving velocity, or acceleration between mild to moderate gravity-support levels during all phases of the cycle. The stroke subject results revealed a significant decrease in the cycle mean completion time (p= 0.042) between the two gravity-support levels, specifically in mean completion time of the grasping phase. A significant increase was found in the initiation phase moving velocity (p=0.039) and a significant decrease was found in the grasping phase (p=0.048) between two gravity-support levels in the stroke subject. Between subjects, significant increase in the cycle mean completion time was found under both mild and moderate conditions (p Conclusion: The significant differences in movement performance between mild and moderate physical weight support suggested a preliminary result that the gravity-supported mechanism provides a mean to facilitate functional upper limb motor performance in individuals with stroke. Future studies should examine such effects with larger sample sizes.
Keywords: Armeospring; Gravity Compensation; Rehabilitation Robot; Stroke; Stroke Rehabilitation; Weight Compensation