Using Biosensors to Detect and Map Language Areas in the Brain for Individuals with Traumatic Brain Injury

The application of biosensors in neurolinguistics has significantly advanced the detection and mapping of language areas in the brain, particularly for individuals with brain trauma. This study explores the role of biosensors in this domain and proposes a conceptual model to guide their use in research and clinical practice. The researchers explored the integration of biosensors in language and brain function studies, identified trends in research, and developed a conceptual model based on cluster and thematic analyses. Using a mixed-methods approach, we conducted cluster and thematic analyses on data curated from Web of Science, Scopus, and SciSpace, encompassing 392 articles. This dual analysis facilitated the identification of research trends and thematic insights within the field. The cluster analysis highlighted Functional Magnetic Resonance Imaging (fMRI) dominance and the importance of neuroplasticity in language recovery. Biosensors such as the Magnes 2500 watt-hour (WH) neuromagnetometer and microwire-based sensors are reliable for real-time monitoring, despite methodological challenges. The proposed model synthesizes these findings, emphasizing biosensors' potential in preoperative assessments and therapeutic customization. Biosensors are vital for non-invasive, precise mapping of language areas, with fMRI and repetitive Transcranial Magnetic Stimulation (rTMS) playing pivotal roles. The conceptual model serves as a strategic framework for employing biosensors and improving neurolinguistic interventions. This research may enhance surgical planning, optimize recovery therapies, and encourage technological advancements in biosensor precision and application protocols.