Digital technologies are creating new opportunities to assess and monitor neurodegenerative disorders beyond traditional clinic-based visits. This talk will explore how smartphones, wearable sensors, mobile applications, and machine learning can be used to capture clinically relevant information about symptoms in everyday environments.

 

Using Parkinson’s disease as the main case study, I will discuss examples of smartphone-based assessments of tremor and finger dexterity, the validation of sensor-derived measures against clinical assessments and wearable devices, and the use of machine learning to estimate symptom severity. The talk will also address an equally important question: whether these technologies are usable, meaningful, and acceptable to the people expected to use them.

 

Finally, I will discuss some of the opportunities and challenges involved in translating digital biomarkers and remote monitoring technologies into clinically useful and patient-centred tools for neurodegenerative disorders.

Dr Gent Ymeri is a computer scientist and digital health researcher with a PhD in Computer Science from Malmö University, Sweden. His research focuses on digital health, mobile and wearable sensing, signal processing, machine learning, and digital biomarkers for remote health assessment. His doctoral research investigated how smartphones and wearable technologies can be used to assess symptoms of Parkinson’s disease in home environments, including tremor, finger dexterity, movement, and voice.

 

He completed his master’s studies at the University of Konstanz, Germany, where he worked with the Data Analysis and Visualization research group. He has also conducted research as a visiting researcher at the University of Applied Sciences and Arts Northwestern Switzerland (FHNW) and the University of Edinburgh, and has collaborated closely with clinicians and researchers at Karolinska Institutet in Sweden. His broader research interests include clinically meaningful, interpretable, and patient-centred digital technologies for healthcare.