Neurological diseases associated with pathological movements (NDPMs) such as Parkinson’s disease, stroke, and multiple sclerosis affect millions of people worldwide. The evaluation of these diseases is typically performed by medical professionals in a clinic or doctor’s practice using qualitative or, at best, semi-quantitative approaches.
Two quantitative movement assessment techniques have already found their way into clinical research and, at least with pilot systems, into clinical management: complex stationary lab assessments and inertial measurement units (IMUs). Complex stationary lab assessments are extremely accurate and allow detailed, timesynchronized, comprehensive analyses of movement patterns. Disadvantages are high cost and relatively inflexible and time-consuming assessments. In contrast, IMUs, most often based on acceleration assessment with accelerometry and angular measurement with gyroscopes, have the advantage of flexible application. Disadvantages are data synchronization difficulties and time-related signal drift. Moreover, these techniques do not provide a comprehensive picture of body movements, neither in a global coordinate system nor in relation to a specific part of the body, e.g. the lower back.
We propose here an entirely novel movement detection strategy based on magnetoelectric (ME) sensors (combined with IMUs) that has the potential to combine almost all advantages of the movement detection techniques currently in use (e.g. flexible use, relatively cheap, unobtrusive, exact, and objective), while overcoming most of the respective disadvantages (e.g. not bound to a specific environment). This system will substantially add to our general understanding of physiological and pathological human movement under supervised and unsupervised conditions. It will eventually add to the quality of treatment evaluation of NDPMs (significant reduction of drift, improved localization performance).