Research Assistant (1 year) T150-01201 BE-FIT SEC

In collaboration with the Woodlands Health (WH) and the National Health Group (NHG), the Rehabilitation Research Institute of Singapore (RRIS), the Nanyang Technological University (NTU), and SingHealth, SEC is undertaking a research programme on "Built Environment and physical activity in Falls and Arthritis study (BE-FIT)". It addresses imminent health challenge on moving away from “sickcare” and pivoting towards preventive healthcare as part of the nationwide effort on Healthier SG. Within BE-FIT we envision motivating vulnerable older adults to engage in healthy behavior by providing recommendations on improving accessibility (as well as preception thereof), in urban environment for uptake of physical activity. A deeper understanding of the interactions and interplay between BE and the high burden of falls and OA as proposed within the BE-FIT is crucial towards informing data-driven decisions on urban design and how the mobility-impaired elderly interact with their physical environment.

Falls result in severe physical as well as psychological impact among older adults. Beyond physical implications on injury-related trauma and in severe cases death, the psychosocial impact of falling can also be excruciating. Fear of falling can result in vicious cycles of decreased activity as well social isolation. These in turn lead to lower muscle strength and higher risk of future falls. In a similar manner, osteo-arthritis (OA) can lead to fear of movement (kinesiophobia) resulting in reduction of physical activity levels. Within Work package 3 (WP3) of the BE-FIT study, we investigate movement patterns and features of walking outdoors and in the neighbourhoods among vulnerable older adults (suffering from OA as well as at high risk of falling). We will acquire these movement patterns and features using the state-of-the-art inertial measurement units (wearables such as ZurichMOVE or Axivity) sensors. These sensors are equipped with triaxial accelerometers and gyrospcopes and provide assessment of aspects such as impact and swing behaviour during different movements. Specifically, we will be addressing the following research questions:

1. What are the kinematic characteristics of walking among older adults with OA and/or previous falls under ecological settings (neighbourhoods etc)?
2. Do the kinematic characteristics of naturalistic walking predict physical activity rates?
3. Does the design of walkways (including overall layout, e.g. design of curbs, pathways etc and accessibility features e.g. size of the curbs, or height of side walk, ramps vs stairs) impact overall levels of physical activity as well as specifics of walking quality?

As a Research Assistant in the BE-FIT, you will be responsible to:

• Design, implement, and test the measurement protocol on long term monitoring using the state-of-the-art inertial measurement unit sensors.
• Assist project management for BE-FIT research activities at SEC including project planning activities, effort estimates, and on-site and remote exchange with several research partners, especially at the CNRS, RRIS and WH.
• Conduct research for the BE-FIT long-term monitoring within the Work package 3,including participant recruitment and scheduling of measurements, but also communication with participants on replacement of sensors and battery charging, and finally storage of data collection.
• Interact with end users as well as researchers at SEC, ETH Zurich, and local partners

• A university or applied science degree in Nursing and Physiotherapy, but also Psychology, Cognitive or Behavioural Science, Neuroscience, Rehabilitation Science, Biomedical Engineering, or a related field/equivalent work experience
• Experience with research methods, study design, project management, handling patients, especially older adults
• Good “people skills” when interacting with participants, patients, and colleagues
• Interested in working with and developing protocols for acquiring data using technological tools and equipment particularly in the field, e.g. remote sensing, etc.

The following competencies will be advantageous:

• Be proactive, communicative and show personal responsibility, initiative and enjoy technology and interdisciplinary teamwork
• Can work autonomously and with a self-starter attitude
• Good communication skills orally and in writing
• Previous experience with health-related data and protocols

The Singapore-ETH-Centre is an equal opportunity and family-friendly employer. All candidates will be evaluated on their merits and qualifications, without regards to gender, race, age or religion.