Physical therapy is crucial to rehabilitating hand function needed for activities of daily living after neurological traumas such as traumatic brain injury (TBI). Virtual reality (VR) can motivate participation in motor rehabilitation therapies. This study examines how multimodal feedback in VR to train grasp-and-place function will impact the neurological and motor responses in TBI participants ( = 7) compared to neurotypicals ( = 13). We newly incorporated VR with our existing intelligent glove system to seamlessly enhance the augmented visual and audio feedback to inform participants about grasp security. We then assessed how multimodal feedback (audio plus visual cues) impacted electroencephalography (EEG) power, grasp-and-place task performance (motion pathlength, completion time), and electromyography (EMG) measures. After training with multimodal feedback, electroencephalography (EEG) alpha power significantly increased for TBI and neurotypical groups. However, only the TBI group demonstrated significantly improved performance or significant shifts in EMG activity. These results suggest that the effectiveness of motor training with augmented sensory feedback will depend on the nature of the feedback and the presence of neurological dysfunction. Specifically, adding sensory cues may better consolidate early motor learning when neurological dysfunction is present. Computerized interfaces such as virtual reality offer a powerful platform to personalize rehabilitative training and improve functional outcomes based on neuropathology.
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http://dx.doi.org/10.3389/frobt.2023.1230086 | 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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