Navrag Singh

Navrag Singh received his PhD from the Humboldt University of Berlin, Germany in 2012. During his PhD, he specialised in identifying adaptations that occur with age and muscle fatigue in humans while performing tasks and activities of daily living such as force production, standing and walking. Since 2014, he leads the Neuromuscular Biomechanics research team at the ETH Zurich. Together with his team, Dr Singh implements experimental and statistical methods for thresholding the adaptations, e.g. with age, or pathology as well as task-related perturbations, in performing activities of daily living. Benchmarking behavioural adaptations through these evidence-based approaches will enhance clinical uptake.

His current projects focus on identifying the risk of falling in older adults via the use of wearable sensors to collect motion data while individuals perform activities of daily living. These projects focusses on generalizing existing statistical models by using machine and deep learning approaches to identify features within movement patterns that are precursors to fall risk. Leveraging wearables together with machine learning approaches allows personalized assessment of fall risk in both clinical and read-world settings. In future, such personalization of risk profile will open avenues for development of therapies targeted to the individual.