Kolloquium WiSe 2019/20

The fast-growing costs of acute care are pushing the healthcare systems worldwide to a limit. Globally, we are coming to realize that we cannot afford to provide everybody with access to unlimited healthcare services in the light of current demographic changes. An alternative approach is emerging that focuses on “keeping people healthy” through primary and secondary prevention in all phases of life. This paradigm shift in the healthcare systems is demanding research in ambient, sensor-enhanced assistive technologies that “keep people outside of the hospital”. Therefore, a fast-growing interest exists for wearable and pervasive computing systems and ambient assistive technology that aim at ubiquitous health support for individuals in the home and community settings.

The talk will present research projects (c.f. Fig. 1) where we implemented ambient sensors for physiological and biomechanical data recording, used pervasive computing systems for monitoring and signal processing, and employed machine learning algorithms and simulation models in order to provide accurate information to patients and caregivers in neurological and musculoskeletal movement disorders with the aim of promoting quality of life of patients and improving health care.

As a model disease for technology development, Parkinson’s disease (PD) will be presented. Routinely assessed by observation, the disease’s symptoms are rated as part of semiquantitative clinical scores. In an alliance between medicine and engineering, a sensor based gait analysis system that objectively assesses gait patterns in PD was developed.  The system provides spatiotemporal gait parameters and was evaluated in PD patients (n=190) and age-matched controls (n=101). Cross-sectional analysis revealed altered gait parameters and variations represented by short steps, shuffling gait, and postural instability in PD patients that were specific for different disease stages. In addition, gait parameters reflecting the progressive nature of PD corresponded to physician ratings of gait impairment over time. These data demonstrated the feasibility and applicability of more objective sensor-based gait measurement in PD for clinical studies and individual patient care.

The outlook of the presentation will focus on future research directions that aim at contributing to the above mentioned paradigm shift in global healthcare systems by the use of wearable and pervasive computing for ubiquitous health support.