Yusuke Kishishita

Computational Prediction of Subjective Sense of Force Based on Muscle Activity Estimation

We feel the effort during manipulation of a product. The effort takes a key role in the subjective product usability. It is known that muscle activity correlates with the subjective effort. Knowing the muscle activity is useful to predict one’s subjective sense. In this paper, we propose a computational prediction method of subjective sense of force based on the estimation of muscle activity. In this study, we make a hypothesis the subjective sense of force changes according to the amount of the muscle activity. To validate the hypothesis, we developed a three dimensional musculoskeletal model, and estimated the muscle activity during a weight holding task. We also defined the perception change ratio based on the measurement of the relationship between the quantitative applied force and the subjective perceived force. In the experiment, the subjective sense of force was predicted by using the perception change ratio that depends on the muscle activity. The experimental results confirmed the feasibility of the proposed computational prediction method of subjective sense of force.

Human Interface Design Method Based on the Estimation of Muscle Effort by a Musculoskeletal Model

Humans skeletal muscles have sensory systems. Human-machine interfaces that consider muscle effort should improve the usability and manipulability of daily products. This paper presents an interface design method that considers muscle effort and illustrates possible applications. A three-dimensional musculoskeletal model is developed based on the upper extremity model with 29 muscles and 16 joints. Muscle activity is estimated by using the OpenSim. We define the muscle effort as the mean of each muscle activity, and the muscle effort is used to determine the physical design or the physical response of the human interface. We applied the proposed physical design modification method to the design of the key height of a keyboard. The key height is changed proportional to the normalized muscle effort. The estimated muscle effort suggests that users can type every keys of the modified keyboard with a similar muscle effort. We also explore to improve the manipulation feeling of the key touching of mobile devices by changing the feedback response according to the estimated muscle effort when users touch keys. The experimental results indicate that the manipulation feeling can be improved by changing the feedback response according to the muscle effort.

Effort cube: a real-time muscle effort visualization system

Motions of our body are generated by muscle contractions. Effort to move our body can be estimated by knowing the muscle activation to generate the motion. This paper proposes a realtime visualization system of muscle activation by using a database of muscle activation that was built in advance. The muscle activation data in the database are obtained by a linear interpolation of muscle activation calculated by a 3D musculoskeletal model.