Studierende finden an der ETH Zürich ein Umfeld, das eigenständiges Denken fördert, Forschende ein Klima, das zu Spitzenleistungen inspiriert.
ETH Zurich is one of the world's leading universities with a strong focus on science and engineering. In 2010 it established the Singapore-ETH Centre (SEC) in collaboration with the National Research Foundation (NRF) to do interdisciplinary research on pressing problems.
In collaboration with the National University of Singapore (NUS), the Nanyang Technological University (NTU), Duke - NUS, the National Health Group (NHG), National University Health System (NUHS), and SingHealth, SEC is undertaking a research program on "Future Health Technologies FHT". In the Early Detection of Health Risks and Prevention research module, we use falls and fractures as a clinical test case due to the high incidence of injurious falls in ageing societies. We develop a holistic concept for large-scale screening that is specific and accurate in identifying individuals with an elevated risk of falling. For these high-risk individuals, the benefits of interventions designed for reducing fall risks at the community level are extremely high.
The global population is rapidly ageing, with the percentage of the population aged 60 years and older predicted to increase dramatically by 2050. Falls and fractures are major health risks to the elderly and preventing them is inherently linked with accurately identifying individuals at risk – those with motor deficits and compromised bone integrity. We propose that an underlying reason for this lack of substantial progress is that fall and fracture risks are approached independently, which ignores the fact that falls and fractures have overlapping aetiologies as well as a synergistic relationship. Our Module within FHT addresses early detection of risks, such that therapies aimed at reducing or preventing injurious falls can be most effective. The aim of the umbrella Project, placed within the Module on early detection of risks, is to provide an assessment of fall risk in a personalised manner via the use of wearable technology. The approach combines the state-of-the-art multipoint wearable sensor systems (ZurichMOVE) with comprehensive neuromuscular model for movement (cNeMo). Walking is one of the most common activities of daily living (ADL). Incidentally, most injurious falls occur during walking. Recent studies show that walking in an effective manner requires coordination of our limbs both spatially and temporally, such that we are able to maintain our balance in a continuous manner. This coordination involves intricate neuromuscular feedback. Age-related decline poses challenges in being able to walk effectively and this burden is further intensified by the individual’s susceptibility to injurious falling. As part of this project, we aim to establish a distribution of gait signatures or features (i.e. coordination, dynamic balance, etc.) during walking in a comprehensive manner for all individuals. Such characterisation will allow us to directly address the age-related decline in task performance and its association with injurious falling.
For the purposes of the project, Singapore is an ideal choice. Its population is highly tech-savvy, its healthcare system is clearly structured and there is a critical mass of accessible patients. Currently, Singapore is facing one of the largest increases in the proportion of elderly in its population. It is likely that Singapore will rank among the top 10 “oldest countries” together with other Asian and European nations. Singapore also happens to be one of the best places to live in Asia. HSBC’s annual survey rates it as the best city in the world to live for ex-pats, while Mercer’s rates it to have the best quality of life in Asia. There are many reasons, but primary factors are efficient public transport, education systems, and a substantial healthcare industry. It is also a very clean and safe city.
The primary task will be to extract features (gait signatures, but also artificial “machine-learned” features) that allow us to assess fall risk in an individualised manner. Crucial aspects are the interpretability and repeatability of these signatures as these aspects will allow clinical uptake, but also form the starting point for the intervention trial aimed at mitigating fall risk. Another important aspect of clinical uptake is the association (via analysis as well as interpretation) of these features to the clinically established gait parameters such as e.g. walking speed, cadence, and even joint angles.
You will have:
The following competence will be advantageous:
Personal: Are you motivated to work on challenging problems? Can you work independently on a project level demonstrating problem solving skills? Do you see yourself fitting in with the team of multinational group of biomechanists, engineers as well as health-care and clinical scientists? Do you have a penchant for collaborating - maintaining channels of communication - with lab/team members in in Switzerland, but also worldwide? If yes, this job might just be for you.
We look forward to receiving your online application including the following documents:
Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.
25-03-2024
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