Musical Rhythms can be modeled in different ways. Usually the models rely on certain temporal divisions and time discretization. We have proposed a generative model based on Deep Reinforcement Learning (Deep RL) that can ...

This paper introduces and validates a real-time dynamic predictive model based on a neural network approach for soft continuum manipulators. The presented model provides a real-time prediction framework using neural-network-based ...

A microfluidic laminar flow cell (LFC) forms an indispensable component in single-molecule experiments, enabling different substances to be delivered directly to the point under observation and thereby tightly controlling ...

This paper is about creating digital musical instruments where a predictive neural network model is integrated into the interactive system. Rather than predicting symbolic music (e.g., MIDI notes), we suggest that predicting ...

Current practice of assessing mood episodes in affective disorders largely depends on subjective observations combined with semi-structured clinical rating scales. Motor activity is an objective observation of the inner ...

Synchronisation is an important part of collaborative music systems, and with such systems implemented on mobile devices, the implementation of algorithms for synchronisation without central control becomes increasingly ...

We examine how robot movement can help human-robot interaction in the context of a robot helping people over 60-years old at home. Many people are not familiar with a robot moving in their home. We present four movement ...

The paper presents an analysis of the quality of motion data from an iPod Touch (4th gen.). Acceleration and orientation data derived from internal sensors of an iPod is compared to data from a high end optical infrared ...

Changes in motor activity are core symptoms of mood episodes in bipolar disorder. The manic state is characterized by increased variance, augmented complexity and irregular circadian rhythmicity when compared to healthy ...