Emerging Technologies in Neurological Disease Diagnosis

The integration of modern technologies has significantly transformed the diagnosis of neurological disorders. With conditions like Parkinson's disease, multiple sclerosis, and Alzheimer's disease affecting millions globally, the need for early and accurate diagnosis has become increasingly important. Emerging technologies, including neuroimaging, artificial intelligence (AI), machine learning (ML), and digital biomarkers, play a significant role in enhancing the precision, speed, accuracy, and accessibility of neurological diagnostics. Neuroimaging methods, including single-photon emission computed tomography (SPECT), functional magnetic resonance imaging (fMRI), and electromyography have become indispensable tools in visualizing the brain's structure and function. These methods allow for the detection of subtle changes in brain activity and anatomy that are indicative of neurological diseases. Furthermore, the advent of ML and AI has enabled the analysis of vast datasets from neuroimaging studies, facilitating the identification of patterns that may not be discernible through traditional analysis methods. Digital biomarkers derived through wearable devices and mobile health technologies facilitate real-time monitoring of neurological activity in patients. Additionally, advances in genomics and precision medicine are enhancing our understanding of the genetic underpinnings of neurological disorders, leading to more precise and customized diagnostic approaches. As these neurotechnologies advance, they hold promise in transforming the landscape of neurological disease diagnosis, enabling early detection, accurate prognoses, and ultimately, better patient outcomes. However, the integration of these technologies into clinical practice requires research, coupled with validation and collaboration, across multidisciplinary teams to ensure their effectiveness and accessibility. In this chapter, we review emerging technologies for diagnosis of neurological conditions, as well as associated ethical considerations.