Retraining of interjoint arm coordination after stroke using robot-assisted time-independent functional training

We have developed a haptic-based approach for retraining of interjoint coordination following stroke called time-independent functional training (TIFT) and implemented this mode in the ARMin III robotic exoskeleton. The ARMin III robot was developed by Drs. Robert Riener and Tobias Nef at the Swiss Federal Institute of Technology Zurich (Eidgenossische Technische Hochschule Zurich, or ETH Zurich), in Zurich, Switzerland. In the TIFT mode, the robot maintains arm movements within the proper kinematic trajectory via haptic walls at each joint. These arm movements focus training of interjoint coordination with highly intuitive real-time feedback of performance; arm movements advance within the trajectory only if their movement coordination is correct. In initial testing, 37 nondisabled subjects received a single session of learning of a complex pattern. Subjects were randomized to TIFT or visual demonstration or moved along with the robot as it moved though the pattern (time-dependent [TD] training). We examined visual demonstration to separate the effects of action observation on motor learning from the effects of the two haptic guidance methods. During these training trials, TIFT subjects reduced error and interaction forces between the robot and arm, while TD subject performance did not change. All groups showed significant learning of the trajectory during unassisted recall trials, but we observed no difference in learning between groups, possibly because this learning task is dominated by vision. Further testing in stroke populations is warranted.

Eye-head coordination abnormalities in schizophrenia

Eye-movement abnormalities in schizophrenia are a well-established phenomenon that has been observed in many studies. In such studies, visual targets are usually presented in the center of the visual field, and the subject's head remains fixed. However, in every-day life, targets may also appear in the periphery. This study is among the first to investigate eye and head movements in schizophrenia by presenting targets in the periphery of the visual field.

Analysis of eye and head coordination in a visual peripheral recognition task

Coordinated eye and head movements simultaneously occur to scan the visual world for relevant targets. However, measuring both eye and head movements in experiments allowing natural head movements may be challenging. This paper provides an approach to study eye-head coordination: First, we demonstra- te the capabilities and limits of the eye-head tracking system used, and compare it to other technologies. Second, a beha- vioral task is introduced to invoke eye-head coordination. Third, a method is introduced to reconstruct signal loss in video- based oculography caused by cornea reflection artifacts in order to extend the tracking range. Finally, parameters of eye- head coordination are identified using EHCA (eye-head co- ordination analyzer), a MATLAB software which was developed to analyze eye-head shifts. To demonstrate the capabilities of the approach, a study with 11 healthy subjects was performed to investigate motion behavior. The approach presented here is discussed as an instrument to explore eye-head coordination, which may lead to further insights into attentional and motor symptoms of certain neurological or psychiatric diseases, e.g., schizophrenia.

EPA-1380 – Coordinated body-movement reflects psychotherapy outcome

Social interaction is a core aspect of human life that affects individuals’ physical and mental health. Social interaction usually leads to mutual engagement in diverse areas of mental, emotional, physiological and physical activity involving both interacting persons and subsequently impacting the outcome of interactions. A common approach to the analysis of social interaction is the study of the verbal content transmitted between sender and receiver. However, additional important processes and dynamics are occurring in other domains too, for example in the area of nonverbal behaviour: In a series of studies, we have looked at nonverbal synchrony – the coordination of two persons’ movement patterns – and it‘s association with relationship quality and with the outcome of interactions. Using a computer-based algorithm (Motion Energy Analysis, MEA: Ramseyer & Tschacher, 2011), which automatically quantifies a person‘s body-movement, we were able to objectively calculate nonverbal synchrony in a large number of dyads interacting in various settings. In a first step, we showed that the phenomenon of nonverbal synchrony exists at a level that is significantly higher than expected by chance. In a second step, we ascertained that across different settings – including patient-therapist dyads and healthy dyads – more synchronized movement was associated with better relationship quality and better interactional outcomes. The quality of a relationship is thus embodied by the synchronized movement patterns emerging between partners. Our studies suggest that embodied cognition is a valuable approach to research in social interaction, providing important clues for an improved understanding of interaction dynamics.