Spatiotemporal Parameterization of Human Reaching Movements Based on Time Base Generator

Abstract

Human reaching movement is characterized by the invariant features of linearity and the symmetrical bell-shaped velocity profile of the hand trajectory. Reaching movement has been widely evaluated in fields such as rehabilitation and interface design; however, no standardized protocols exist for data collection, processing, or analysis. This paper proposes a spatiotemporal parameterization method that evaluates reaching movements with a trajectory generation model based on a time base generator. The proposed method extracts motion information as a set of model parameters, such as motion duration, distance, and asymmetry of the bell-shaped velocity profile from the reaching data, that are estimated by fitting the model to reaching data with a robust parameter estimation method. The reaching trajectory generation model, for which a straight trajectory in a three-dimensional space is assumed, is also derived from the proposed model. Experiments were conducted using simulated data and real-world three-dimensional and one-dimensional human reaching movement datasets. The results show that the model assuming a straight trajectory in the three-dimensional space is reasonable for evaluating reaching movements. In addition, the model parameters were estimated with relatively greater robustness than were those of the conventional model and were highly correlated with physical features extracted from measured datasets. The results also showed that the parameters representing the asymmetry of the bell-shaped velocity profile differed between individuals. Therefore, the characteristics of reaching movements can be parameterized and evaluated with the proposed method.

Keywords

• Human reaching movements
• time base generator (TBG)
• trajectory generation model
• parameter estimation
• motion parameterization