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In psychophysics, the response to a stimulus is usually limited to a single value during some time interval. Moreover, the response is usually quantified, e.g., binary (yes or no). Such data is very limited information for parameter estimation. A particular example is the response to a sensory stimulus where we vary one stimulus profile around a threshold. Instead of the psychophysical threshold we aim to estimate parameters of a neurophysiological model, given the input-output data using different experimental profile settings.

Tremor and bradykinesia are two prominent features of Parkinson's disease (PD). This paper presents the PD monitor, a measurement system using accelerometry to quantify tremor and bradykinesia. A correlation analysis of the physician's scores and the PD monitor demonstrated that the system accurately measured the severity of tremor and bradykinesia whilts assessing a broad spectrum of aspects related to both symptoms. In conclusion the PD monitor can be used for a detailed evaluation of the PD monitor symptoms in order to optimize treatment.

Deep Brain Stimulation (DBS) in subthalamic nucleus (STN) has substantially improved the suppression of symptoms in Parkinson's disease (PD). However, a quantitative understanding of the high-frequency stimulation opn the neuronal elements surrounding the electrode and the resulting effects for the different symptoms for upper and lower extremities is missing. The aim of the study is to investigate if there is a somatotopic organisation of the STN.

An important part in the analysis of human activity video data is the silhouette segmentation. The results of segmentation are greatly affected by imaging environment, thus posing a problem for the extraction of the region in the image containing a subject of interest. In this paper we propose a human motion analysis method based on nonparametric clustering of monocular color images. Motivated by the need to automatically extract human silhouettes for kinematic gait analysis, without spurious segmentations naturally occurring in other segmentation methods, we have developed and applied adaptive mesh-based color clustering which can be combined with motion segmentation. The advantage of our method is that it is controlled by few intuitive parameters allowing the method to be adjusted to different capturing environments. The usage of color is not sensitive to illumination variations, or to different color distributions of different cameras, as the color distribution is compared between different regions of the same frame. To provide a qualitative evaluation of our method, our results are compared with the Gaussian Mixture model, a standard vision-based human subject extraction method based on background segmentation techniques.

Rehabilitation robots can support the training of patients with neurological gait disorders. Classical control approaches permit patients to remain passive during the robot-assisted training. We hypothesize that promoting active participation of patients will improve training efficacy. In this paper, we evaluate the combination of two existing patient-cooperative control strategies. These strategies are applicable to robotic exoskeletons that assist a patient walking on a treadmill. The first strategy, Automatic treadmill speed adaptation, detects the patient’s desired walking speed and accelerates the treadmill accordingly. The second strategy, Path control, provides spatial guidance of the legs via the rehabilitation robot while the patient controls the timing of his/her movements. We demonstrate that both strategies can be successfully combined towards an approach that allows subjects to walk on their own with the support of a robot instead of being passively moved.

In this paper, a virtual instrument for bio-impedance measurements in oral cavity is described and characterized. The instrument is realized by using general purpose USB data acquisition device and LabVIEW. The flexibility of the virtual instrument allows the evaluation of different values and indices, in order to determine most suitable measurement parameter. The realized instrument was tested on electrical models with known impedance values and during in-vivo measurements.

Robotic gait rehabilitation faces many challenges regarding ankle assistance, body weight support and physical human-robot interaction. This paper reports on the development of a gait rehabilitation exoskeleton prototype intended as a platform for the evaluation of design and control concepts in view of improved physical human-robot interaction. The performance of proxy-based sliding mode control as a "robot-in-charge" control strategy is evaluated both in simulation and in experiments on a test setup. Compared to PID control, test results indicate good tracking performance and in particular safe system behavior.