Abstract
A study on force-feedback interaction with a model of a neural oscillator provides insight into enhanced human-robot interactions for controlling musical sound. We provide differential equations and discrete-time computable equations for the core oscillator model developed by Edward Large for simulating rhythm perception. Using a mechanical analog parameterization, we derive a force-feedback model structure that enables a human to share control of a virtual percussion instrument with a "robotic" neural oscillator. A formal human subject test indicated that strong coupling (STRNG) between the force-feedback device and the neural oscillator provided subjects with the best control. Overall, the human subjects predominantly found the interaction to be "enjoyable" and "fun" or "entertaining." However, there were indications that some subjects preferred a medium-strength coupling (MED), presumably because they were unaccustomed to such strong force-feedback interaction with an external agent. With related models, test subjects performed better when they could synchronize their input in phase with a dominant sensory feedback modality. In contrast, subjects tended to perform worse when an optimal strategy was to move the force-feedback device with a 90° phase lag. Our results suggest an extension of dynamic pattern theory to force-feedback tasks. In closing, we provide an overview of how a similar force-feedback scenario could be used in a more complex musical robotics setting.
Highlights
1.1 Interactive music any perceivable sound can be synthesized by a digital computer [1], most sounds are generally considered not to be musically interesting, and many are even unpleasant to hear [2]
We were aware that the task of stopping the bouncing could be challenging, so we presented the models to the test subjects always in the following order during the training phase: no force-feedback model (NF)-HINT to immediately provide insight into an optimal strategy, Position followed by NF, medium-strength coupling (MED), weak force-feedback (WEAK), and strong coupling (STRNG)
Building upon ideas inherited from human studies of neural oscillators, we presented an explicitly computable expression for the Large neural oscillator, and we introduced its mechanical analog
Summary
1.1 Interactive music any perceivable sound can be synthesized by a digital computer [1], most sounds are generally considered not to be musically interesting, and many are even unpleasant to hear [2]. They could follow the green ball with a 0° phase lag, which is much more stable from the dynamic patterns perspective This result showed that a theory from visual-only human coordination experiments could be extended to situations involving auditory feedback: non-physical visual feedback could enable a subject to complete an otherwise impossible or very difficult task, if the visualization revealed an inner state or otherwise unseen strategy that provided a human test subject with assistance [18]. Our own perception of the models, and the subject test we carried out, allowed us to state that force-feedback interaction with a neural oscillator enabled innovative coupling for exploring a new middle ground between intuitiveness and strangeness
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