Network meta-analysis of different virtual reality devices for treating upper limb motor dysfunction after stroke

Abstract

OBJECTIVE: Upper limb dysfunction after stroke is a common complication that seriously affects the quality of life and daily activity of patients. Virtual reality technology, as an emerging rehabilitation method, can effectively promote neural remodeling and functional recovery. This study will systematically evaluate the therapeutic effects of different virtual reality devices on upper limb motor dysfunction in patients with stroke. METHODS: The China National Knowledge Infrastructure (CNKI), WanFang Database, VIP website, PubMed, Web of Science, Embase, and the Cochrane Library were searched to retrieve relevant literature. Relevant data were extracted, and their quality was assessed. The control group received conventional rehabilitation treatment, while the experimental group received virtual reality rehabilitation training in addition to the treatment provided to the control group. Statistical analysis was performed using RevMan 5.4 and Stata 18.0 software. RESULTS: (1) A total of 12 articles and 571 patients were included in the meta-analysis. (2) Meta-analysis results showed that the Fugl-Meyer score of the upper limb in the virtual reality group was 7.29 times that of the conventional group (MD=7.29, 95%CI: 5.60-8.98, P < 0.05); the Action Research Arm Test score in the virtual reality group was 10.69 times that of the conventional group (MD=10.69, 95%CI: 4.96-16.43, P < 0.05); the modified Barthel index score in the virtual reality group was 8.25 times that of the conventional group (MD=8.25, 95%CI: 3.38-13.12, P < 0.05). (3) Subgroup analysis showed that patients aged 50-59 years had better improvement in upper limb Fugl-Meyer score; patients with disease duration within 3 months had better improvement; intervention duration ≥4 weeks had the best improvement. (4) Network meta-analysis showed that smart glove intervention [MD=-1.05, 95%CI(-1.85, -0.24), P < 0.05] was most effective for improving upper limb motor function; Armeo Spring intervention [MD=-1.19, 95%CI(-1.87, -0.51), P < 0.05] was most effective for improving upper limb coordination; Kinect intervention [MD=-0.59, 95%CI(-1.13, -0.06), P < 0.05] was most effective for improving hand dexterity; VREX intervention [MD=-0.76, 95%CI(-1.28, -0.23), P < 0.05] was most effective for improving activities of daily living. CONCLUSION: For improving upper limb motor function, the smart glove system is the first choice; for improving upper limb coordination, the Armeo Spring system is the first choice; for improving hand dexterity, the Kinect system is the first choice; for improving activities of daily living, the VREX system is the first choice. This study has certain limitations, and the above conclusions should be interpreted with caution.

1. Introduction

Stroke is one of the most severe neurological disorders and is listed as the third leading cause of death globally [1]. Data show that approximately 80% of stroke patients have upper limb motor limitations, which persist in half of the survivors [2]. Upper limb motor function includes the ability to precisely grasp and manipulate objects, which is crucial for maintaining daily living activities [3]. Conventional rehabilitation is the main approach to improve upper limb dysfunction after stroke, typically involving repetitive motion training and standardized exercises [4]. However, the training process is often monotonous and boring, leading to patient fatigue and poor adherence [5]. Therefore, providing interesting, functional, diverse, and personalized rehabilitation training has become an urgent issue in clinical rehabilitation.

Virtual reality is a technology that creates a three-dimensional virtual environment through computer technology, allowing users to interact with the virtual environment via visual, auditory, tactile, and other senses [4]. This technology immerses patients in gamified or simulated real-life scenarios, offering various training scenes and tasks such as grasping and placing, target hitting, and puzzle assembly [6], thereby avoiding the monotony of traditional rehabilitation and increasing patient engagement and compliance [7]. It can also tailor virtual reality scenarios to patients' interests and needs, such as designing kitchen scenes for those who enjoy cooking or supermarket scenes for those who like shopping [8]. From commercial video game devices to robotic technology, many types of virtual reality-based rehabilitation devices are currently being developed and used. For example, Xiao Xiang et al. [9] found that Kinect-based somatosensory interaction training can help patients improve the range of motion and motor control of upper limb joints, and patients can learn about their performance through training scores, which aids in rebuilding normal movement patterns. MERIANS et al. [10] used a Cyber Glove instrumented glove to create a virtual piano scene for upper limb training after stroke, observing improvements in finger independence indicators.

Currently, various virtual reality training devices are applied in stroke rehabilitation, such as the BioMaster virtual scenario interactive training system [11], Kinect somatosensory interaction technology [9], smart gloves [12], and others. However, there is a lack of comprehensive comparisons among these devices. This study aims to systematically evaluate the therapeutic effects of different virtual reality devices on upper limb motor dysfunction in stroke patients through a network meta-analysis, providing evidence-based recommendations for clinical practice.