Objective: The purpose of this study was to investigate the effects of virtual reality (VR) on postural control, posture, and kinesiophobia in patients with chronic neck pain (CNP).
Methods: Forty-one participants with CNP were randomly allocated to the VR and control groups. The VR group experienced VR with glasses for 20 minutes and then performed motor control (MC) exercises for 20 minutes. The control group received only MC exercises for 40 minutes. Both groups received 18 sessions over 6 weeks. Computerized dynamic posturography outcomes, including sensory organization test (SOT), limits of stability, and unilateral stance tests, gait speed, forward head posture (FHP), shoulder protraction (SP), cervical lordosis angle, kinesiophobia, and exercise compliance were recorded.
Results: The VR group had more effects regarding composite equilibrium (Cohen's d = 1.20) of SOT and kinesiophobia (Cohen's d = -0.96), P < .05). Also, the VR group was more effective in exercise compliance (P < .05). Contrary to these results, the control group was more effective in correcting FHP and SP (Cohen's d > 0.7, P < .05).
Conclusion: Virtual reality seemed to have an effect on postural control, posture, and kinesiophobia in patients with chronic neck pain.
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http://dx.doi.org/10.1016/j.jmpt.2024.02.006 | DOI Listing |
Exp Brain Res
January 2025
Institute for Experimental Psychology, Heinrich Heine University Düsseldorf, 40225, Düsseldorf, Germany.
When we touch ourselves, the pressure appears weaker compared to when someone else touches us, an effect known as sensory attenuation. Sensory attenuation is spatially tuned and does only occur if the positions of the touching and the touched body-party spatially coincide. Here, we ask about the contribution of visual or proprioceptive signals to determine self-touch.
View Article and Find Full Text PDFJ Clin Med
December 2024
Department of Public Health and Sport Sciences, Faculty of Health and Life Sciences, Medical School, University of Exeter, Exeter EX1 2LU, UK.
: To summarize the impact of various telerehabilitation interventions on motor function, balance, gait, activities of daily living (ADLs), and quality of life (QoL) among patients with stroke and to determine the existing telerehabilitation interventions for delivering physiotherapy sessions in clinical practice. : Six electronic databases were searched to identify relevant quantitative systematic reviews (SRs). Due to substantial heterogeneity, the data were analysed narratively.
View Article and Find Full Text PDFJ Clin Med
December 2024
Department of Oral Pathobiological Science and Surgery, Tokyo Dental College, 2-9-18 Kandamisaki-cho, Chiyoda-ku, Tokyo 101-0061, Japan.
Mandibular gingival squamous cell carcinoma (SCC) is the second most common oral cancer after tongue cancer. As these carcinomas often invade the mandible early, accurately defining the resection extent is important. This report highlights the use of preoperative virtual surgery data, computer-aided design and manufacturing (CAD/CAM) technology, surgical guidance, and extended reality (XR) support in achieving highly accurate marginal mandibulectomy without recurrence or metastasis.
View Article and Find Full Text PDFSensors (Basel)
January 2025
University-Industrial Cooperation Corps of HiVE Center, Wonkwang Health Science University, 514, Iksan-daero, Iksan-si 54538, Republic of Korea.
Virtual reality (VR) technology has gained popularity across various fields; however, its use often induces cybersickness, characterized by symptoms such as dizziness, nausea, and eye strain. This study investigated the differences in cybersickness levels and head movement patterns under three distinct VR viewing conditions: dynamic VR (DVR), static VR (SVR), and a control condition (CON) using a simulator. Thirty healthy adults participated, and their head movements were recorded using the Meta Quest 2 VR headset and analyzed using Python.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Shanxi Key Laboratory of Machine Vision and Virtual Reality, North University of China, Taiyuan 030051, China.
Automatic crack detection is challenging, owing to the complex and thin topologies, diversity, and background noises of cracks. Inspired by the wavelet theory, we present an instance normalization wavelet (INW) layer and embed the layer into the deep model for segmentation. The proposed layer employs prior knowledge in the wavelets to capture the crack features and filter the high-frequency noises simultaneously, accelerating the convergence of model training.
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