This research project focuses on developing individualised, explanatory computational models for modulating autonomic responses through music that can be used in digital therapeutics for cardiovascular health, with focus on treatments for raised blood pressure. The scientific approach will be based on studying the interactions between musical prosody (acoustic variations introduced in musical communication) and autonomic parameters such as heart rate, heart rate variability, respiration, and blood pressure. A goal will be to identify the phenotypes, like having a high sympathetic drive, that are more responsive to music interventions.
Cardiovascular disease is the number one cause of death worldwide, and hypertension is the foremost risk factor for cardiovascular disease. Amongst people with raised blood pressure, hypertensive heart disease is the primary cause of death, frequently manifest as atrial fibrillation (a cardiac arrhythmia linked to catastrophic stroke), heart attacks, and heart failure. Pharmacological treatments for high blood pressure work well, but drug compliance is poor due to unpleasant side effects, including arrhythmias.
Music intervention offers a non-invasive, non-pharmacological, and pleasurable way to modulate blood pressure, heart rate, and heart rate variability. However, the links between expressive music structures (the shape of music as it is delivered to listeners) and physiological response are not well understood. Leveraging advances in wearable devices and extensions of music representations to prosodic features, this project aims to bridge the gap between music expressivity and autonomic response. An objective will be to build personalised computational models of music response based on physiological feedback for precision music medicine. A goal will be to find underlying traits that make a person more responsive to music intervention.
The research activities will include literature review, study design, ethics application, data collection, data processing, computational modelling, and analysis, evaluation, and interpretation of results, disseminating results through publications and conference presentations. The student will liaise regularly with the supervision team to discuss research progress, and for guidance and feedback.
The project furthers the United Nation’s Sustainability Development Goal of reducing premature mortality from cardiovascular disease by reducing cardiovascular risk. It also fulfils the World Health Organisation’s global action to reduce avoidable non-communicable disease (NCD) deaths by reducing global prevalence of raised blood pressure and by developing affordable technologies to treat NCDs.
The research activities will be carried out in partnership with the ongoing European Research Council project COSMOS, Computational Shaping and Modeling of Musical Structures (https://cosmos.isd.kcl.ac.uk/), and its accompanying Proof of Concept project HeartFM, Maximizing the Therapeutic Potential of Music through Tailored Therapy with Physiological Feedback in Cardiovascular Disease).
- The candidate should have an undergraduate major in biomedical engineering, computational sciences, music technology, music psychology, or a related discipline.
- Experience in computational or statistical analysis of biosignals and/or music signals or industrial experience is desirable; alternatively, an MSc in a related topic is preferred.
- This scholarship is only available to UK students or to EU students with settled status (students who do not meet this requirement will not be invited for interviews).
To be considered for the position candidates must apply via King’s Apply online application system. Details are available at:
The selection process will involve a pre-selection on documents, if selected this will be followed by an invitation to an interview. If successful at the interview, an offer will be provided in due time.