Current Research Areas:

Assistive Technology to Enhance Safety and Autonomy of Dementia Patients at Home:
Most dementia patients have a strong desire to live autonomously in their known environments as long as possible. This often leads to trade-offs between the patient’s desire to live at home and the risks that increase with the progression of the cognitive decline. The risks includes safety issues arising from discontinuous supervision, including a lack of medical compliance, acute medical events (e.g. stroke, heart attack), accidents and other events (e.g. falls), and disorientation (e.g. day/night disturbances, getting lost). We expect that, in combination with existing (i.e. Spitex) and new (i.e. ambulant old-age psychiatry) clinical and social caregiving approaches, assistive technology will play an important role in reducing risks associated with independent living. Numerous technical approaches (e.g. wearable fall sensors, watches with integrated emergency buttons) have been developed to assist independent living for elderly people. In this project, we use existing sensor technology to develop and evaluate an assistive technology system that meets the specific needs of elderly patients with cognitive impairment. One key feature of the envisioned system is that it would not require any active interaction between the system and the supported patient. In collaboration with Damedics GmbH, we have developed a wireless sensor system that measures environmental data (e.g. light distribution, movement patterns). The scientific challenge lies in developing dedicated algorithms to detect unusual situations (e.g. falls, wandering), to estimate the patient’s wellbeing, assess the patient’s ability to cope with activities of daily living, and predict short- and long-term risks.

Cognitive Performance and Driving Behaviour in Older Adults:
The objective of this study is to better understand how cognitive performance and aging influence individual driving behavior and traffic-related risks. We have developed a dynamic, computer-based test to measure driving-relevant cognitive and motivational competences such as processing speed, decision making, anticipation of speed, and motion perception. The test and the human-machine interface are specifically developed for elderly people and the system is intended to serve as a screening tool to assess driving-relevant cognitive performance. In a study of 120 participants, performance in the computer-based test is compared with simulated driving performance. For that purpose, a commercially available driving simulator has been modified to study simulated driving behavior of elderly drivers while measuring neurophysiological parameters (e.g. eye movements, skin conductance). Based on these findings, we intend to derive cognitive training schemes that help elderly to maintain driving relevant cognitive skills as long as possible.

The Age-Dependent Effect of Night Driving on Visual Performance and on Simulated Driving Behaviour:
Both younger and older drivers are challenged by reduced vision in low-light conditions during night driving. Contributing factors are age-related increased glare sensitivity and decreased mesopic visual acuity. We assume that the visual exploration behaviour under mesopic light conditions is an important predictor of driving performance. In this project, the age-dependent influence of mesopic vision, cognition, and comorbidity are evaluated regarding their influence on visual exploration behaviour and on simulated driving performance. In collaboration with Haag-Streit AG (Köniz, Switzerland), we are developing a screening tool for the Octopus 900 perimeter that will support and enhance “fitness-to-drive” assessments and decisions.

Street-Crossing Behaviour of Younger and Older Pedestrians and Car Drivers:
Crossing a street as pedestrian or driver is a challenging task that requires gathering information over a large area. The challenge is to acquire the necessary information for a decision of when to cross within a limited window of time. To better understand how the acquired information leads to a crossing decision, we have modified the driving simulator to study street- and intersection-crossing behaviour.

Outlook:
Besides better understanding the influence of cognitive impairments on mobility and traffic participation, we also aim to develop new means to improve and maintain cognitive performance and prevent cognitive decline as long as possible. In collaboration with other European and Swiss researchers, we plan to develop home-based cognitive and physical training based on both innovative gaming platforms (e.g. Wii and Kinect) and specifically developed serious games. We will place a special focus on adaptive difficulty levels, allowing error-free learning that is expected to increase motivation, fun, and self—confidence.