I. MOTIVATION AND STATE OF THE ART Multiple sclerosis (MS) is a neurological disease of autoimmune nature that leads to motor impairment and progressing disability. For evaluation of disease progression and/or the success of a treatment the grade of motor deficits is a major readout. Current MS research focuses on the development of new anti-inflammatory compounds. Drug testing often involves non-human primates e.g. common marmosets (Callithrix jacchus) to overcome the limitations of rodent studies regarding complex brain function and drug safety. A widely used MS model is the experimental autoimmune encephalomyelitis (EAE) which mimics key pathological and clinical features of MS such as inflammatory demyelinating lesions and severe neurological deficits. Longitudinal monitoring of disease progression and treatment effects is assessed either by neurological examination and or behavioral testing. These tests are not only significantly influenced by errors but also lack sensitivity regarding the detection of fine-motor movements and subtle motor deficits. Therefore, a strong interest exists in the automation and objective analysis of motor behavior using highsensitive motion caption technology. Motion capture systems using infrared cameras and retroreflective balls as markers for body limbs are disadvantageous when applied to laboratory animals. First, the markers may be removed by the animals or hidden by objects. Furthermore, this system works only in a spatially limited environment. Alternatively, animal behavior may be assessed simply by observation. However, manual analysis of video recordings is a time and cost-expensive approach. Another possibility is to measure motoric function with inertial sensors mounted on the animals. To date one-axis acceleration sensors are already used for measuring the activity [1]. More over the sensor log the acceleration value every time period (adjustable from 2sec till 1min). These acceleration values are accumulated over the measurement period therefore the data can be not used for a detailed movement study. Our new approach is using a new sensor based on a Inertial Measurement Unit (IMU) which consist of a three-axis accelerometer, three-axis gyroscope and three-axis magnetometer sensor. With the sensor technology a detailed movement observation is possible. For human tracking inertial sensors can be also integrated into clothes or shoes [2]. Therefore the IMUs can extend the functionality of pedometers by full 3D location information. Even more complex tasks like full-body human motion capture have
been addressed using inertial sensors. However, due to their size, weight and power consumption [3], commercially available IMUs are not ideally suited for the motion capture application in animals. The practical size dimensions and weight which is not disturbing the natural movement of the animal are important. Therefore a small movement sensor based on IMUs was developed for movement detection and due to its light weight can be easily attached to test animals. The new sensor is completely wireless or can be read out later. There are no requirements to illumination and no restrictions to the environment where the measurement takes place