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Home > Archives > Volume 20, No 15 (2022) > Article

DOI: 10.14704/NQ.2022.20.15.NQ88007

The Impact of Virtual Reality Training with a Cognitive Load on Falling in Stroke Cases

Ahmed S. Ali 1* Ph.D., Wael S. Shendy Ph.D., Amr Hassan MD, Khaled Atef Abdelmonem MSc., Ayman El Khatib Ph.D.

Abstract

Background: One of the most frequent factors in long-term impairment is stroke. The most prominent, recurrent medical side effect after a stroke is falling, with a prevalence of 14% to 73%. Hip fractures, soft tissue injuries, fear of falling, increased immobility, and disability are all possible outcomes of falling as common medical complications. Aim of the Study: The current academic work seeks to trace and highlight how cognitively demanding virtual reality training decrease the chance of falling in severe stroke cases. Procedures: The study encompassed a sample of thirty stroke cases, males and females, with recurrent falls and a MoCA score higher than 26. The ages of the cases covered a range between 40 to 65 years old, with a medical issue that persisted for more than six months. The control group (CG) and the study group (SG) were randomly sub-categorized into two equal study domains. A typical regime of therapeutic workouts for cases who were at risk of falling was administered to the individuals in the control group. Cases in the study domain underwent the same treatment plan as those in the control domain, in addition to VR balance training and dual-task training utilizing the Nintendo Wii Fit system. Three sessions each week were held during the course of the four-week program. All falling variables were pre-and post-assessed for each case. Both Berg Balance Scale and the 16-item Fall scale were taken into account in the current research. The disparity in Gaming Scores for the Study domain on the International Efficacy Scale (FES-I) was calculated carefully

Keywords

Stroke, Falling, Balance, Berg Balance Scale, Fall efficacy scale, Virtual reality, Nintendo Wii Fit, Dual task training, and Cognitive training

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