Active Heterogeneous Sensing for Fall Detection and Fall Risk Assessment
Agency: NSF
Funding: $1.4M (CPS Program)
PI: Skubic
Dates: 9/1/2009 to 8/31/2012
Award #: CNS-0931607
MOTIVATION
Americans are living longer and more fulfilling lives. They desire to live as independently as possible, but independent lifestyles come with risks, such as debilitating falls that limit mobility. To address these issues, researchers are developing "smart home" technologies to enhance residents' safety and monitor health conditions using sensors and other devices. In particular, the continuous assessment of physical function is a key indicator of initial decline in health and functional ability. Identifying and assessing problems while they are still small can provide a window of opportunity for interventions that will alleviate the problem areas before they become catastrophic.
PROPOSED RESEARCH
Researchers at the University of Missouri have established an interdisciplinary team dedicated to developing and evaluating technology to keep older adults functioning at high levels and living independently. We will leverage ongoing research at a unique local eldercare facility (TigerPlace) to study active sensing and fusion using vision and acoustic sensors for the continuous assessment of a resident’s risk of falling as well as the reliable detection of falls in the home environment.
Project Objectives:
- Investigate adaptive, active, anonymized vision sensing for monitoring elders in a home setting
- Investigate adaptive acoustic sensing for monitoring elders in a home setting
- Investigate adaptive sensor fusion and intelligent decision making using heterogeneous sensor data collected at varying time scales, including both quantitative and qualitative data, and incorporating risk factors
- Evaluate the effectiveness of the monitoring system in a realistic physical environment with variable conditions
INTELLECTUAL MERIT
The proposed 3-year project will advance the state of the art in (1) active vision sensing for activity recognition in dynamic and unpredictable environments, (2) acoustic sensing in unstructured environments, (3) adaptive sensor fusion and decision making using heterogeneous sensor data in dynamic and unpredictable environments, and (4) automatic fall detection and fall risk assessment using non-wearable sensors. The proposed project offers an example of a cyber physical system in which we will study the interplay of anomaly detection (falls) and the risk factors affecting the likelihood of the anomaly event.
BROADER IMPACTS
The proposed project will impact technology, health care, policy, quality of life for older adults, and peace of mind for their families. Advances in technology have implications for other areas, including fitness and physical rehabilitation. These strides will assist health care providers to identify potential health problems and keep older adults independent longer. This means happier lives for the older adults and their families. Offering a model for eldercare technology may also provide policy makers with information to guide decisions about services for older people. The project will train the next generation of researchers to handle real, cyber-physical systems. Students will be mentored, and research outcomes will be integrated into the classroom. Novel outreach activities are planned to reach the elderly community and the general public.
