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.
Highlights
A basic component of everyday human motor repertoire, the reaching movement refers to the movement of the hand from an initial to a target position according to a motivation-based trajectory generated by the brain by taking distance and direction into account
This paper proposes a spatiotemporal parameterization method to evaluate human reaching movements based on the time base generator (TBG) [17]
The features of the velocity waveform during the reaching movement can be quantitatively acquired by fitting a reaching trajectory generation model based on the TBG [17] to the measured reaching data and subsequently estimating the parameters
Summary
A basic component of everyday human motor repertoire, the reaching movement refers to the movement of the hand from an initial to a target position according to a motivation-based trajectory generated by the brain by taking distance and direction into account. Reaching movements have been evaluated by investigators to help improve motor function in rehabilitation and to inform the design of user interfaces [1]–[5]. Have been used to evaluate the reaching movement [5]–[7]. Standardized protocols (e.g., data collection, processing, and analysis) to evaluate upper limb movements remain lacking [5], [6]. Defining the reaching movement time is difficult, as various methods have been used to determine reaching movement time based on the available data, such as extracting at a rate of 5%–20% of the peak velocity, and no one definition of this index exists. Few studies have focused on the analysis and evaluation of individual differences in the shape of the velocity waveform during a reaching movement [8]–[10]
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