Abstract: Assessing the cognitive impact of user interfaces is a shared focus of human-computer interaction researchers and cognitive scientists. Methods of cognitive assessment based on data derived from the system itself, rather than external apparatus, have the potential to be applied in a range of scenarios. The current study applied methods of analyzing kinematics to mouse movements in a computer-based task, alongside the detection response task, a standard workload measure. Sixty-five participants completed a task in which stationary stimuli were tar;geted using a mouse, with a within-subjects factor of task workload based on the number of targets to be hovered over with the mouse (one/two), and a between-subjects factor based on whether both targets (exhaustive) or just one target (minimum-time) needed to be hovered over to complete a trial when two targets were presented. Mouse movement onset times were slower and mouse movement trajectories exhibited more submovements when two targets were presented, than when one target was presented. Responses to the detection response task were also slower in this condition, indicating higher cognitive workload. However, these differences were only found for participants in the exhaustive condition, suggesting those in the minimum-time condition were not affected by the presence of the second target. Mouse movement trajectory results agreed with other measures of workload and task performance. Our findings suggest this analysis can be applied to workload assessments in real-world scenarios.

Abstract: BACKGROUND: Hemiparesis following stroke is often accompanied by spasticity. Spasticity is one factor among the multiple components of the upper motor neuron syndrome that contributes to movement impairment. However, the specific contribution of spasticity is difficult to isolate and quantify. We propose a new method of quantification and evaluation of the impact of spasticity on the quality of movement following stroke. METHODS: Spasticity was assessed using the Tonic Stretch Reflex Threshold (TSRT). TSRT was analyzed in relation to stochastic models of motion to quantify the deviation of the hemiparetic upper limb motion from the normal motion patterns during a reaching task. Specifically, we assessed the impact of spasticity in the elbow flexors on reaching motion patterns using two distinct measures of the 'distance' between pathological and normal movement, (a) the bidirectional Kullback-Liebler divergence (BKLD) and (b) Hellinger's distance (HD). These measures differ in their sensitivity to different confounding variables. Motor impairment was assessed clinically by the Fugl-Meyer assessment scale for the upper extremity (FMA-UE). Forty-two first-event stroke patients in the subacute phase and 13 healthy controls of similar age participated in the study. Elbow motion was analyzed in the context of repeated reach-to-grasp movements towards four differently located targets. Log-BKLD and HD along with movement time, final elbow extension angle, mean elbow velocity, peak elbow velocity, and the number of velocity peaks of the elbow motion were computed. RESULTS: Upper limb kinematics in patients with lower FMA-UE scores (greater impairment) showed greater deviation from normality when the distance between impaired and normal elbow motion was analyzed either with the BKLD or HD measures. The severity of spasticity, reflected by the TSRT, was related to the distance between impaired and normal elbow motion analyzed with either distance measure. Mean elbow velocity differed between targets, however HD was not sensitive to target location. This may point at effects of spasticity on motion quality that go beyond effects on velocity. CONCLUSIONS: The two methods for analyzing pathological movement post-stroke provide new options for studying the relationship between spasticity and movement quality under different spatiotemporal constraints.