Altered Dynamic Postural Control during Step Turning in Persons with Early-Stage Parkinson's Disease

Persons with early-stage Parkinson's disease (EPD) do not typically experience marked functional deficits but may have difficulty with turning tasks. Studies evaluating turning have focused on individuals in advanced stages of the disease. The purpose of this study was to compare postural control strategies adopted during turning in persons with EPD to those used by healthy control (HC) subjects. Fifteen persons with EPD, diagnosed within 3 years, and 10 HC participated. Participants walked 4 meters and then turned 90°. Dynamic postural control was quantified as the distance between the center of pressure (COP) and the extrapolated center of mass (eCOM). Individuals with EPD demonstrated significantly shorter COP-eCOM distances compared to HC. These findings suggest that dynamic postural control during turning is altered even in the early stages of PD

Visual SLAM Based Spatial Recognition and Visualization Method for Mobile AR Systems

The simultaneous localization and mapping (SLAM) market is growing rapidly with advances in Machine Learning, Drones, and Augmented Reality (AR) technologies. However, due to the absence of an open source-based SLAM library for developing AR content, most SLAM researchers are required to conduct their own research and development to customize SLAM. In this paper, we propose an open source-based Mobile Markerless AR System by building our own pipeline based on Visual SLAM. To implement the Mobile AR System of this paper, we use ORB-SLAM3 and Unity Engine and experiment with running our system in a real environment and confirming it in the Unity Engine’s Mobile Viewer. Through this experimentation, we can verify that the Unity Engine and the SLAM System are tightly integrated and communicate smoothly. In addition, we expect to accelerate the growth of SLAM technology through this research

Visual SLAM Based Spatial Recognition and Visualization Method for Mobile AR Systems

The simultaneous localization and mapping (SLAM) market is growing rapidly with advances in Machine Learning, Drones, and Augmented Reality (AR) technologies. However, due to the absence of an open source-based SLAM library for developing AR content, most SLAM researchers are required to conduct their own research and development to customize SLAM. In this paper, we propose an open source-based Mobile Markerless AR System by building our own pipeline based on Visual SLAM. To implement the Mobile AR System of this paper, we use ORB-SLAM3 and Unity Engine and experiment with running our system in a real environment and confirming it in the Unity Engine’s Mobile Viewer. Through this experimentation, we can verify that the Unity Engine and the SLAM System are tightly integrated and communicate smoothly. In addition, we expect to accelerate the growth of SLAM technology through this research

Mapping Server Collaboration Architecture Design with OpenVSLAM for Mobile Devices

SLAM technology, which is used for spatial recognition in autonomous driving and robotics, has recently emerged as an important technology to provide high-quality AR contents on mobile devices due to the spread of XR and metaverse technologies. In this paper, we designed, implemented, and verified the SLAM system that can be used on mobile devices. Mobile SLAM is composed of a stand-alone type that directly performs SLAM operation on a mobile device and a mapping server type that additionally configures a mapping server based on FastAPI to perform SLAM operation on the server and transmits data for map visualization to a mobile device. The mobile SLAM system proposed in this paper mixes the two types in order to make SLAM operation and map generation more efficient. The stand-alone type of SLAM system was configured as an Android app by porting the OpenVSLAM library to the Unity engine, and the map generation and performance were evaluated on desktop PCs and mobile devices. The mobile SLAM system in this paper is an open-source project, so it is expected to help develop AR contents based on SLAM in a mobile environment

Review Article Exercise and Motor Training in People with Parkinson’s Disease: A Systematic Review of Participant Characteristics, Intervention Delivery, Retention Rates, Adherence, and Adverse Events in Clinical Trials

Copyright © 2012 Natalie E. Allen et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. There is research evidence that exercise and motor training are beneficial for people with Parkinson’s disease (PD), and clinicians seek to implement optimal programs. This paper summarizes important factors about the nature and reporting of randomized controlled trials of exercise and/or motor training for people with PD which are likely to influence the translation of research into clinical practice. Searches identified 53 relevant trials with 90 interventions conducted for an average duration of 8.3 (SD 4.2) weeks. Most interventions were fully supervised (74%) and conducted at a facility (79%). Retention rates were high with 69 % of interventions retaining ≥85 % of their participants; however adherence was infrequently reported, and 72 % of trials did not report adverse events. Overall, the labor-intensive nature of most interventions tested in these trials and the sparse reporting of adherence and adverse events are likely to pose difficulties for therapists attempting to balance benefits and costs when selecting protocols that translate to sustainable clinical practice for people with PD. 1

A Video Self-Modeling Intervention Using Virtual Reality Plus Physical Practice for Freezing of Gait in Parkinson Disease: Feasibility and Acceptability Study

BackgroundDespite optimal medical and surgical intervention, freezing of gait commonly occurs in people with Parkinson disease. Action observation via video self-modeling, combined with physical practice, has potential as a noninvasive intervention to reduce freezing of gait. ObjectiveThe aim of this study is to determine the feasibility and acceptability of a home-based, personalized video self-modeling intervention delivered via a virtual reality head-mounted display (HMD) to reduce freezing of gait in people with Parkinson disease. The secondary aim is to investigate the potential effect of this intervention on freezing of gait, mobility, and anxiety. MethodsThe study was a single-group pre-post mixed methods pilot trial for which 10 participants with Parkinson disease and freezing of gait were recruited. A physiotherapist assessed the participants in their homes to identify person-specific triggers of freezing and developed individualized movement strategies to overcome freezing of gait. 180° videos of the participants successfully performing their movement strategies were created. Participants watched their videos using a virtual reality HMD, followed by physical practice of their strategies in their own homes over a 6-week intervention period. The primary outcome measures included the feasibility and acceptability of the intervention. Secondary outcome measures included freezing of gait physical tests and questionnaires, including the Timed Up and Go Test, 10-meter walk test, Goal Attainment Scale, and Parkinson Anxiety Scale. ResultsThe recruitment rate was 24% (10/42), and the retention rate was 90% (9/10). Adherence to the intervention was high, with participants completing a mean of 84% (SD 49%) for the prescribed video viewing and a mean of 100% (SD 56%) for the prescribed physical practice. One participant used the virtual reality HMD for 1 week and completed the rest of the intervention using a flat-screen device because of a gradual worsening of his motion sickness. No other adverse events occurred during the intervention or assessment. Most of the participants found using the HMD to view their videos interesting and enjoyable and would choose to use this intervention to manage their freezing of gait in the future. Five themes were constructed from the interview data: reflections when seeing myself, my experience of using the virtual reality system, the role of the virtual reality system in supporting my learning, developing a deeper understanding of how to manage my freezing of gait, and the impact of the intervention on my daily activities. Overall, there were minimal changes to the freezing of gait, mobility, or anxiety measures from baseline to postintervention, although there was substantial variability between participants. The intervention showed potential in reducing anxiety in participants with high levels of anxiety. ConclusionsVideo self-modeling using an immersive virtual reality HMD plus physical practice of personalized movement strategies is a feasible and acceptable method of addressing freezing of gait in people with Parkinson disease

Home-based step training using videogame technology in people with Parkinson’s disease: a single-blinded randomised controlled trial

Objectives: To determine whether 12-week home-based exergame step training can improve stepping performance, gait and complementary physical and neuropsychological measures associated with falls in Parkinson’s disease. Design: A single-blinded randomised controlled trial Setting: Community (experimental intervention), university laboratory (outcome measures). Subjects: Sixty community-dwelling people with Parkinson’s disease. Interventions: Home-based step training using videogame technology Main measures: The primary outcomes were the choice stepping reaction time test and Functional Gait Assessment. Secondary outcomes included physical and neuropsychological measures associated with falls in Parkinson’s disease, number of falls over sixmonths and self-reported mobility and balance. Results: Post intervention, there were no differences between the intervention (n=28) and control (n=25) groups in the primary or secondary outcomes except for the Timed Up and Go test, where there was a significant difference in favour of the control group (P=0.02). Intervention participants reported mobility improvement, whereas control participants reported mobility deterioration—between-group difference on an 11-point scale=0.9 (95% confidence interval: −1.8 to −0.1, P=0.03). Interaction effects between intervention and disease severity on physical function measures were observed (P=0.01 to P=0.08) with seemingly positive effects for the low-severity group and potentially negative effects for the high-severity group. Conclusion: Overall, home-based exergame step training was not effective in improving the outcomes assessed. However, the improved physical function in the lower disease severity intervention participants as well as the self-reported improved mobility in the intervention group suggest home-based exergame step training may have benefits for some people with Parkinson’s disease

Exercise for falls prevention in Parkinson disease : a randomized controlled trial

Objective: To determine whether falls can be prevented with minimally supervised exercise targeting potentially remediable fall risk factors, i.e., poor balance, reduced leg muscle strength, and freezing of gait, in people with Parkinson disease. Methods: Two hundred thirty-one people with Parkinson disease were randomized into exercise or usual-care control groups. Exercises were practiced for 40 to 60 minutes, 3 times weekly for 6 months. Primary outcomes were fall rates and proportion of fallers during the intervention period. Secondary outcomes were physical (balance, mobility, freezing of gait, habitual physical activity), psychological (fear of falling, affect), and quality-of-life measures. Results: There was no significant difference between groups in the rate of falls (incidence rate ratio [IRR] = 0.73, 95% confidence interval [CI] 0.45–1.17, p = 0.18) or proportion of fallers (p = 0.45). Preplanned subgroup analysis revealed a significant interaction for disease severity (p < 0.001). In the lower disease severity subgroup, there were fewer falls in the exercise group compared with controls (IRR = 0.31, 95% CI 0.15–0.62, p < 0.001), while in the higher disease severity subgroup, there was a trend toward more falls in the exercise group (IRR = 1.61, 95% CI 0.86–3.03, p = 0.13). Postintervention, the exercise group scored significantly (p < 0.05) better than controls on the Short Physical Performance Battery, sit-to-stand, fear of falling, affect, and quality of life, after adjusting for baseline performance. Conclusions: An exercise program targeting balance, leg strength, and freezing of gait did not reduce falls but improved physical and psychological health. Falls were reduced in people with milder disease but not in those with more severe Parkinson disease.9 page(s