Development of a Diagnosis and Evaluation System for Hemiplegic Patients Post-Stroke Based on Motion Recognition Tracking and Analysis of Wrist Joint Kinematics

4D dynamic system for visual-motor integration analysis

It is very important to evaluate visual-motor integration (VMI), as it is used as an index to evaluate cognitive abilities. However, it is difficult to use the existing paper-based tests to evaluate the dynamic process, including spatial and depth perception abilities. Therefore, this study aims to extract kinematic and dynamic features for dynamic assessment for VMI. We propose a 4D dynamic analysis system that implements a VMI test in a virtual space using Leap motion controller and Unity3D and acquires the time-series data of hand joints and traces. We selected three categories of features: postural control ability, spatial and depth perception ability, and 4D analysis. The degree and patterns of postural maintenance differed between subjects in the VMI and MC tests. In addition, the personal patterns were identified with dynamic features, including their fluency and hesitation in relation to the task figures of the VMI test tool. As such, this system enables dynamic feature extraction and analysis which were previously impossible and presents performance results for healthy adults.

Analysis of the Leap Motion Controller's Performance in Measuring Wrist Rehabilitation Tasks Using an Industrial Robot Arm Reference

The Leap Motion Controller (LMC) is a low-cost markerless optical sensor that performs measurements of various parameters of the hands that has been investigated for a wide range of different applications. Research attention still needs to focus on the evaluation of its precision and accuracy to fully understand its limitations and widen its range of applications. This paper presents the experimental validation of the LMC device to verify the feasibility of its use in assessing and tailoring wrist rehabilitation therapy for the treatment of physical disabilities through continuous exercises and integration with serious gaming environments. An experimental set up and analysis is proposed using an industrial robot as motion reference. The high repeatability of the selected robot is used for comparisons with the measurements obtained via a leap motion controller while performing the basic movements needed for rehabilitation exercises of the human wrist. Experimental tests are analyzed and discussed to demonstrate the feasibility of using the leap motion controller for wrist rehabilitation.

Leap Motion Controller Video Game-Based Therapy for Upper Extremity Motor Recovery in Patients with Central Nervous System Diseases. A Systematic Review with Meta-Analysis

Leap Motion Controller (LMC) is a virtual reality device that can be used in the rehabilitation of central nervous system disease (CNSD) motor impairments. This review aimed to evaluate the effect of video game-based therapy with LMC on the recovery of upper extremity (UE) motor function in patients with CNSD. A systematic review with meta-analysis was performed in PubMed Medline, Web of Science, Scopus, CINAHL, and PEDro. We included five randomized controlled trials (RCTs) of patients with CNSD in which LMC was used as experimental therapy compared to conventional therapy (CT) to restore UE motor function. Pooled effects were estimated with Cohen's standardized mean difference (SMD) and its 95% confidence interval (95% CI). At first, in patients with stroke, LMC showed low-quality evidence of a large effect on UE mobility (SMD = 0.96; 95% CI = 0.47, 1.45). In combination with CT, LMC showed very low-quality evidence of a large effect on UE mobility (SMD = 1.34; 95% CI = 0.49, 2.19) and the UE mobility-oriented task (SMD = 1.26; 95% CI = 0.42, 2.10). Second, in patients with non-acute CNSD (cerebral palsy, multiple sclerosis, and Parkinson's disease), LMC showed low-quality evidence of a medium effect on grip strength (GS) (SMD = 0.47; 95% CI = 0.03, 0.90) and on gross motor dexterity (GMD) (SMD = 0.73; 95% CI = 0.28, 1.17) in the most affected UE. In combination with CT, LMC showed very low-quality evidence of a high effect in the most affected UE on GMD (SMD = 0.80; 95% CI = 0.06, 1.15) and fine motor dexterity (FMD) (SMD = 0.82; 95% CI = 0.07, 1.57). In stroke, LMC improved UE mobility and UE mobility-oriented tasks, and in non-acute CNSD, LMC improved the GS and GMD of the most affected UE and FMD when it was used with CT.

Comparison of the Performance of the Leap Motion ControllerTM with a Standard Marker-Based Motion Capture System

Over the last few years, the Leap Motion Controller™ (LMC) has been increasingly used in clinical environments to track hand, wrist and forearm positions as an alternative to the gold-standard motion capture systems. Since the LMC is marker-less, portable, easy-to-use and low-cost, it is rapidly being adopted in healthcare services. This paper demonstrates the comparison of finger kinematic data between the LMC and a gold-standard marker-based motion capture system, Qualisys Track Manager (QTM). Both systems were time synchronised, and the participants performed abduction/adduction of the thumb and flexion/extension movements of all fingers. The LMC and QTM were compared in both static measuring finger segment lengths and dynamic flexion movements of all fingers. A Bland–Altman plot was used to demonstrate the performance of the LMC versus QTM with Pearson’s correlation (r) to demonstrate trends in the data. Only the proximal interphalangeal joint (PIP) joint of the middle and ring finger during flexion/extension demonstrated acceptable agreement (r = 0.9062; r = 0.8978), but with a high mean bias. In conclusion, the study shows that currently, the LMC is not suitable to replace gold-standard motion capture systems in clinical settings. Further studies should be conducted to validate the performance of the LMC as it is updated and upgraded.