Roman Kuster

I am a movement scientist with a PhD in Medical Science from Karolinska Institutet, currently working as Senior Scientist at the Lake Lucerne Institute (Therapy Science Lab) in Switzerland. In parallel, I hold research appointments at the University of Zurich (Department of Neurology) and here at the Division of Physiotherapy.

My work integrates movement science, medicine, and data science to research digital health technologies for objective, patient-centred monitoring, therapy design, and treatment planning. I specialize in translating clinical and physiological research questions into actionable data-driven approaches using wearable sensors, virtual reality, and artificial intelligence. My current work spans both remote monitoring and technology-enabled neurorehabilitation, including the development of personalised approaches for stroke rehabilitation.

I have more than a decade of experience spanning academic, clinical, and industrial R&D, including several years at my own start-up, rotavis AG, and at F. Hoffmann-La Roche Ltd., where I contributed to digital biomarker development for neurological conditions. I am the (co-)author of more than twenty peer-reviewed scientific publications, and my research has led to two European patents for sensor-based medical technologies.

My overall goal is to advance how digital health technologies and data can be used to understand patients in everyday life, personalise treatment, support clinical decision-making, and improve rehabilitation outcomes for individuals living with neurological and musculoskeletal conditions.

My research is driven by the ambition to make digital health technologies valid, clinically meaningful, and useful for personalised care. I investigate how data from wearable sensors, clinical assessments, and digital rehabilitation technologies can be translated into better monitoring, therapy design, and treatment planning.

My work therefore spans the continuum from measuring human movement and behaviour to using these data to personalise rehabilitation.

Current research topics include:

• Digital Health & Wearable Sensors – Development and validation of methods and algorithms for passive monitoring of physical activity, posture, and movement in neurological populations, including step counting and energy expenditure.
• Personalised Neurorehabilitation & Virtual Reality – Development and evaluation of adaptive digital therapies that tailor rehabilitation to the individual. Current doctoral projects investigate VR-based trunk and upper-limb training in stroke survivors, including approaches to adapt task difficulty and therapy content automatically to patient performance.
• Data-Driven Therapy Design & Planning – Investigation of how patient characteristics, clinical assessments, treatment data, and individual responses to therapy can be used to select, adapt, and plan rehabilitation interventions.
• Usability & Human Factors Research – Investigation of how patients and healthcare professionals interact with wearable devices, virtual reality systems, mobile applications, and software-as-a-medical-device, with the aim of developing technologies that can be successfully integrated into clinical practice and daily life.

Past projects include the development of POPAI, the Posture and Physical Activity Index, the first valid single-sensor method to measure sedentary behaviour and active sitting in daily life, and the development of an mHealth application for monitoring bulbar and respiratory function in people with spinal muscular atrophy.

Across these areas, I aim to bridge measurement, data, and rehabilitation science so that digital technologies not only quantify patients' behaviour and function accurately, but also help determine what therapy should be delivered, how it should be adapted, and how treatment decisions can be better individualised.

I teach and mentor students across disciplines and educational levels. Over the past years, I have taught at PhD, Master, and Bachelor level at Karolinska Institutet, Lake Lucerne Institute, Zurich University of Applied Sciences, ETH Zurich, and the University of Bern, covering topics including:

• Biomechanics and physiology
• Artificial intelligence, data analysis, and biostatistics
• Scientific writing and research methodology

I have supervised more than 15 Bachelor's and Master's students and contribute to the supervision of PhD students in biomedical engineering, movement science, physiotherapy, and neurorehabilitation. I currently supervise two PhD students investigating VR-based rehabilitation after stroke, with projects focusing on trunk and upper-limb therapy.

My teaching approach combines conceptual understanding with hands-on data analysis and critical thinking to prepare students to work across disciplinary boundaries in health and rehabilitation research.

In addition, I contribute to academic governance and scientific community development as a former member of the Doctoral Education Committee at Karolinska Institutet and as a reviewer for international journals in physical activity, digital health, rehabilitation, and human factors.