The Validity and Reliability of the Microsoft Kinect for Measuring Trunk Compensation during Reaching.

Compensatory movements at the trunk are commonly utilized during reaching by persons with motor impairments due to neurological injury such as stroke. Recent low-cost motion sensors may be able to measure trunk compensation, but their validity and reliability for this application are unknown. The purpose of this study was to compare the first (K1) and second (K2) generations of the Microsoft Kinect to a video motion capture system (VMC) for measuring trunk compensation during reaching. Healthy participants (n = 5) performed reaching movements designed to simulate trunk compensation in three different directions and on two different days while being measured by all three sensors simultaneously. Kinematic variables related to reaching range of motion (ROM), planar reach distance, trunk flexion and lateral flexion, shoulder flexion and lateral flexion, and elbow flexion were calculated. Validity and reliability were analyzed using repeated-measures ANOVA, paired t-tests, Pearson's correlations, and Bland-Altman limits of agreement. Results show that the K2 was closer in magnitude to the VMC, more valid, and more reliable for measuring trunk flexion and lateral flexion during extended reaches than the K1. Both sensors were highly valid and reliable for reaching ROM, planar reach distance, and elbow flexion for all conditions. Results for shoulder flexion and abduction were mixed. The K2 was more valid and reliable for measuring trunk compensation during reaching and therefore might be prioritized for future development applications. Future analyses should include a more heterogeneous clinical population such as persons with chronic hemiparetic stroke.

A virtual reality tool for measuring and shaping trunk compensation for persons with stroke: Design and initial feasibility testing.

Background: Compensatory movement, such as flexing the trunk during reaching, may negatively affect motor improvement during task-based practice for persons with stroke. Shaping, or incrementally decreasing, the amount of compensation used during rehabilitation may be a viable strategy with methods using virtual reality. Methods: A virtual reality tool was designed to (1) monitor upper extremity movement kinematics with an off-the-shelf motion sensor (Microsoft Kinect V2), (2) convert movements into control of widely available computer games, and (3) provide real-time feedback to shape trunk compensation. This system was tested for feasibility by a small cohort of participants with chronic stroke (n = 5) during a 1-h session involving 40 min of virtual reality interaction. Outcomes related to repetitions, compensation, movement kinematics, usability, motivation, and sense of presence were collected. Results: Participants achieved a very high dose of reaching repetitions (461 ± 184), with an average of 81% being successful and 19% involving compensatory trunk flexion. Participants rated the system as highly usable, motivating, engaging, and safe. Conclusions: VRShape is feasible to use as a tool for increasing repetition rates, measuring and shaping compensation, and enhancing motivation for upper extremity therapy. Future research should focus on software improvements and investigation of efficacy during a virtual reality-based motor intervention.

Upper extremity movement reliability and validity of the Kinect version 2.

PURPOSE: Studies have shown that marker-less motion detection systems, such as the first generation Kinect (Kinect 1), have good reliability and potential for clinical application. Studies of the second generation Kinect (Kinect 2) have shown a large range of accuracy relative to balance and joint localization; however, few studies have investigated the validity and reliability of the Kinect 2 for upper extremity motion. This investigation compared reliability and validity among the Kinect 1, Kinect 2 and a video motion capture (VMC) system for upper extremity movements. DESIGN: One healthy, adult male performed six upper extremity movements during two separate sessions. All movements were recorded on the Kinect 1, Kinect 2 and VMC simultaneously. Data were analyzed using MATLAB (Natick, MA), Microsoft Excel (Redmond, WA), and SPSS (Armonk, NY). RESULTS: Results indicated good reliability for both Kinects within a day; results between days were inconclusive for both devices due to the inability to exactly repeat the desired movements. Range of motion (ROM) magnitudes for both Kinects were different from the VMC, yet patterns of motion were very highly correlated for both devices. CONCLUSION: Simple transformations of Kinect data could bring magnitudes in line with those of the VMC, allowing the Kinects to be used in a clinical setting. Implications for Rehabilitation The clinical implications of the investigation support the notion that the Kinects could be used in the clinical setting if an understanding of their limitations exists. Using the Kinects to make assessments with a given data collection session is acceptable. Using the Kinects to make comparisons across different days such as before or after an intervention should be approached with caution. The Kinect 2 provides a more cost effective option compared to the VMC. Additionally, the Kinect is more portable, requires less time to set-up, and takes up less space, thus increasing its overall usability compared to the VMC.

Development of a novel virtual reality gait intervention.

INTRODUCTION: Improving gait speed and kinematics can be a time consuming and tiresome process. We hypothesize that incorporating virtual reality videogame play into variable improvement goals will improve levels of enjoyment and motivation and lead to improved gait performance. PURPOSE: To develop a feasible, engaging, VR gait intervention for improving gait variables. METHODS: Completing this investigation involved four steps: 1) identify gait variables that could be manipulated to improve gait speed and kinematics using the Microsoft Kinect and free software, 2) identify free internet videogames that could successfully manipulate the chosen gait variables, 3) experimentally evaluate the ability of the videogames and software to manipulate the gait variables, and 4) evaluate the enjoyment and motivation from a small sample of persons without disability. RESULTS: The Kinect sensor was able to detect stride length, cadence, and joint angles. FAAST software was able to identify predetermined gait variable thresholds and use the thresholds to play free online videogames. Videogames that involved continuous pressing of a keyboard key were found to be most appropriate for manipulating the gait variables. Five participants without disability evaluated the effectiveness for modifying the gait variables and enjoyment and motivation during play. Participants were able to modify gait variables to permit successful videogame play. Motivation and enjoyment were high. SUMMARY: A clinically feasible and engaging virtual intervention for improving gait speed and kinematics has been developed and initially tested. It may provide an engaging avenue for achieving thousands of repetitions necessary for neural plastic changes and improved gait.

Changes in muscle activation following ankle strength training in children with spastic cerebral palsy: an electromyography feasibility case report.

ABSTRACT Children with cerebral palsy (CP) are likely to experience decreased participation in activities and less competence in activities of daily living. Studies of children with spastic CP have shown that strengthening programs produce positive results in strength, gait, and functional outcomes (measured by the Gross Motor Function Measure). No investigations have analyzed electromyography (EMG) activity before and after strength training to determine whether any changes occur in the GMFM.  This feasibility case report quantified dorsiflexor and plantarflexor muscle activation changes during performance of 3-5 selected GMFM items following a plantarflexor strength training in two children with cerebral palsy. Increased plantarflexor strength and increased ability to selectively activate muscles were found. Little carryover to performance on GMFM items was observed. It is feasible to use EMG during performance on selected GMFM items to evaluate motor control changes following strength training in children with CP.