HIGH-M
Welcome to the Online-Presence of the HIGH-M Project (Human Interaction assessment and Generative segmentation in Health and Music)!
Located at the Institute of Applied Sciences (IFAS) of the Technical University of Applied Sciences Würzburg-Schweinfurt (THWS), we develop an automated tool to analyse autonomy - understood as types of social interaction in line with Kenneth E. Bruscia - of clinical improvisations. To do so, several theories for the analysis of musical improvisations and interaction are being synthesised, formalised, and automated. This tool is being developed for the analysis of clinical improvisations of people with diagnosed depressive disorder.
In development, we have set two aims for the tool. On the one hand, it is supposed to analyse specific dynamics of clinical and musical improvisations. On the other hand, it is also designed as a diagnostic tool in music therapy to analyse and recognise specifics of depressive musical interaction in clinical improvisations.
In our research project, we are being supported by several national and international partners who contribute besides the main data set their expertise in computational analysis, music information retrieval as well as cognitive and music therapeutic background. Furthermore, the THWS is a founding member of the International Music Therapy Assessment Consortium (IMTAC) and contributes to this via HIGH-M.
On the following pages, you can learn more about the structure, the state of our study, our partners, and our publications so far.
For further questions or information feel free to contact us.
Current Issues
16/10/2026 9th Network Meeting of the BayWISS Joint Academic Partnership Health
On 15 October 2026, the HIGH-M team attended the 9th Network Meeting of the BayWISS Joint Academic Partnership Health at the University of Regensburg. Under the title “The Bridge: BayWISS Doctorates between Universities of Applied Sciences and Universities”, doctoral researchers and professors from across Bavaria came together. The panel discussion focused on the synergies that arise from cooperation between universities of applied sciences and universities.
During the subsequent poster session, we had the opportunity to present our poster “Assessing Musical Interaction in Clinical Improvisation: Exploratory Findings of a Machine Learning Method applied to Data from Depression Treatment in Music Therapy”. It was a great chance to situate and represent music therapy within the context of other scientific developments in the health sector – all the more so as the Nuremberg University of Music is the only university of the arts within the BayWISS Health network. We would like to thank the organisers for an inspiring afternoon and many stimulating conversations.
Our Partners
