Numerous EEG-based brain-computer interface (BCI) systems that are being developed focus on novel feature extraction algorithms, classification methods and combining existing approaches to create hybrid BCIs. Several recent studies demonstrated various advantages of hybrid BCI systems in terms of an improved accuracy or number of commands available for the user. But still, BCI systems are far from realization for daily use. Having high performance with less number of channels is one of the challenging issues that persists, especially with hybrid BCI systems, where multiple channels are necessary to record information from two or more EEG signal components. Therefore, this work proposes a single-channel (C3 or C4) hybrid BCI system that combines motor imagery (MI) and steady-state visually evoked potential (SSVEP) approaches. This study demonstrates that besides MI features, SSVEP features can also be captured from C3 or C4 channel. The results show that due to rich feature information (MI and SSVEP) at these channels, the proposed hybrid BCI system outperforms both MI- and SSVEP-based systems having an average classification accuracy of 85.6 ± 7.7% in a two-class task.

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This paper introduces an interactive music tempo control with closed-loop heart rate feedback to yield a sportsperson with better physio-psychological states. A total of 23 participants (13 men, 10 women; 16–32 years, mean = 20.04 years) who are professionals or school team members further guide a sportsperson to amend their physical tempo to harmonize their psychological and physical states. The self-tuning mechanism between the surroundings and the human can be amplified using interactive music tempo control. The experiments showed that listening to interactive music had a significant effect on the heart rate and rating of perceived exertion (RPE) of the basketball player compared to those listening to asynchronous music or no music during exercise (p < 0.01). Synchronized interactive music allows athletes to increase their heart rate and decrease RPE during exercise and does not require a multitude of preplanned playlists. All self-selected songs can be converted into sports-oriented music using algorithms. The algorithms of synchronous and asynchronous modes in this study can be adjusted and applied to other sports fields or recovery after exercise. In the future, other musical parameters should be adjusted in real-time based on physiological signals, such as tonality, beats, chords, and orchestration.

NuText is a novel music-encoding technology based on numbered musical notation. This paper outlines the notation principles of numbered musical notation and delineates the conversion relationship and encoding protocol between NuText and numbered musical notation. Furthermore, this study demonstrates NuText's playback software and its practical applications, including digital artwork creation, Non-Fungible Tokens (NFTs), and social use, and identifies opportunities to develop it as a music technology. The encoding method proposed herein was implemented on PCs and mobile devices, and the method has been successfully applied to sports-oriented music. The image steganography method used in digital artwork creation, Non-Fungible Tokens (NFTs), and social use does not destroy images, and it has been implemented on mobile devices. NuText is a note-level encoding method, which has advantages for interpreting music connotations and a great potential in the development of music information retrieval and artificial intelligence composition. In future work, special musical skills may be added, including the modification of each note velocity, and this may be incorporated into the encoding specification to realize sound in virtual reality.