NIHCI
My doctoral dissertation at New York University focuses on the development of NIHCI (Non-Intrusive Human-Computer Interfaces) for handheld musical instruments, with a current emphasis on the trombone. The central aim is to propose a design framework for attachable tangible user interfaces (aTUIs) that are non-invasive, enabling expressive augmentation without compromising traditional playability.
To define the parameters of “invasiveness” in musical performance, I have adopted a mixed-methods approach. This includes an international online survey (n = 128) of professional trombonists - capturing their preferences, experiences, and barriers regarding technological integration - and a series of in-person trials with 20 professional trombonists from the NY/NJ area. After defining the boundaries of the framework, an initial NIHCI prototype was proposed and tested with 10 trombonists to evaluate: 1) the validity of the framework, and 2) to keep fine-tuning the ergonomics, expressiveness, and perceptual intrusiveness aspects.
The current prototype is a fully wireless BLE-MIDI and Wi-Fi-enabled system. It attaches directly to the trombone leadpipe and features two tactile buttons, a gyroscope, and a proximity sensor. The device operates as a Wi-Fi Access Point, serving a browser-based UI for real-time configuration without the need for external software. It translates gestures and switch actions into MIDI CC and/or note messages, allowing easy mapping in any digital audio workstation (DAW).
The project also explores how motion, gesture, and spatial interaction can meaningfully expand trombone performance, beyond sound generation, toward broader interaction with digital systems, including page turning, live processing, and networked performance. Key contributions include proposing criteria for non-invasiveness, articulating design guidelines grounded in performer feedback, and prototyping a sustainable, low-latency, and adaptable interface.
This work is currently being refined in Shanghai as part of the final development phase. The results will form the core of my doctoral dissertation, which I will defend in May 2026.
