**6. Future directions**

Our study was just started with myoelectrical analysis on the forearm muscles and finger motion. Proposed technique was applied to the hand game called "rock-paper-scissors." But it was configured so as to verify the validity of the method rather than to demonstrate its usefulness.

We are planning to improve the technique to human-robot interface system. The advanced input device for computers is one of the applications, which is more intuitive than the dataglove. Such versatile system is neccesary to distinguish many finger motions based on vague myoelectric information.

This paper evaluated the myoelectric signals processed simply by statistic evaluation for noise reduction or feature extraction. Higher performance may be expected by introducing some meta-heuristic method or intelligent method, e. g. neural networks, or suppot vector machine.

The muscle activity was determined on the basis of dualistic taxology according to the criterion established beforehand in this paper. It is necessary to determine the criterion adaptively to the measument conditions to apply to realtime robotic systems.

Practical systems will be realized by integrated measurement method combined with the other perceptual devices.

The proposed technique will be improved not only to the engineering applications but the medical ones, such as the bio-feedback system in rehabilitation or the phyisical support system for handicapped persons.
