Introduction

Abstract

Today, hospitals are full of advanced technology, ranging from large machines such as MRI scanners, to tiny devices such as implantable electrodes. In addition, patient information systems and wireless communication technologies help doctors provide the best care for their patients. Although most technology is operated by specially trained personnel, medical doctors also transform technical results into clinically relevant knowledge themselves. One of the tasks of engineers is to provide a link from medical techniques to clinical practice, by optimally designing technological devices and software for the hospital environment and advising physicians in their use of technology. Thus, both for physicians and engineers it is important to bridge the gap between technology and medicine. Clinical neuroengineering is one of the fields providing such a bridge between technology and – in this case – neurology. Clinical neuroengineering strives to advance the clinical neurosciences by employing mathematical, physical, and engineering principles. An essential principle of clinical neuroengineering is that inspiration and challenges are provided by clinical neurological practice. After finding a solution for these challenges using mathematical, physical, and engineering methods, this solution is made available to the neurologist. Thus, clinical neuroengineering approaches proceed “from neurology to methodology and back.” Important fields in clinical neuroengineering are neurodiagnostics and neurotherapy. Neurodiagnostics is the study and recording of physiological signals reflecting brain, nerve, and muscle activity to determine the function of these systems or to diagnose a neurological disease.