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Research Spending & Results

Award Detail

Awardee:UNIVERSITY OF MISSOURI SYSTEM
Doing Business As Name:University of Missouri-Columbia
PD/PI:
  • Marjorie Skubic
  • (573) 882-7766
  • skubicm@missouri.edu
Co-PD(s)/co-PI(s):
  • James M Keller
  • Dominic K.C. Ho
  • Zhihai He
  • Mihail Popescu
Award Date:08/15/2009
Estimated Total Award Amount: $ 1,409,963
Funds Obligated to Date: $ 1,409,963
  • FY 2009=$1,409,963
Start Date:09/01/2009
End Date:08/31/2013
Transaction Type:Grant
Agency:NSF
Awarding Agency Code:4900
Funding Agency Code:4900
CFDA Number:47.070
Primary Program Source:040101 RRA RECOVERY ACT
Award Title or Description:CPS: Medium: Active Heterogeneous Sensing for Fall Detection and Fall Risk Assessment
Federal Award ID Number:0931607
DUNS ID:153890272
Parent DUNS ID:006326904
Program:CPS-Cyber-Physical Systems
Program Officer:
  • Usha Varshney
  • (703) 292-8339
  • uvarshne@nsf.gov

Awardee Location

Street:115 Business Loop 70 W
City:COLUMBIA
State:MO
ZIP:65211-0001
County:Columbia
Country:US
Awardee Cong. District:04

Primary Place of Performance

Organization Name:University of Missouri-Columbia
Street:115 Business Loop 70 W
City:COLUMBIA
State:MO
ZIP:65211-0001
County:Columbia
Country:US
Cong. District:04

Abstract at Time of Award

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5). The objective of this research is to study active sensing and adaptive fusion using vision and acoustic sensors for continuous, reliable fall detection and assessment of fall risk in dynamic and unstructured home environments. The approach is to incorporate active vision with infrared light sources and camera controls, an acoustic array that identifies the sound characteristics and location, and sensor fusion based on the Choquet integral and hierarchical fuzzy logic systems that supports uncertain heterogeneous sensor data at varying time scales, qualitative data, and risk factors. The project will advance the state of the art in (1) active vision sensing for human 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, (4) automatic fall detection and fall risk assessment using non-wearable sensors, and (5) algorithms for cyber physical systems that address the interplay of anomaly detection (falls) and risk factors affecting the likelihood of an anomaly event. The project will impact the health care and quality of life for older adults. New approaches will assist health care providers to identify potential health problems early, offering a model for eldercare technology that keeps seniors independent while reducing health care costs. 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

Publications Produced as a Result of this Research

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Rantz MJ, Skubic M, Abbott C, Galambos C, Pak Y, Ho D, Stone EE, Rui L, Back J & Miller S "In-Home Fall Risk Assessment and Detection Sensor System" Journal of Gerontological Nursing, v.39, 2013, p.18.

Rantz MJ, Skubic M, Miller SJ, Galambos C, Alexander G, Keller J & Popescu M "Sensor Technology to Support Aging in Place" Journal of the American Medical Directors Association, v.14, 2013, p.386.

Li Y, Ho KC & Popescu M "A Microphone Array System for Automatic Fall Detection" IEEE Transactions on Biomedical Engineering, v.59, 2012, p.1291.

Stone E & Skubic M "Evaluation of an Inexpensive Depth Camera for In-Home Gait Assessment" Journal of Ambient Intelligence and Smart Environments, v.3, 2011, p.349.

Stone E & Skubic M "Evaluation of an Inexpensive Depth Camera for In-Home Gait Assessment" Journal of Ambient Intelligence and Smart Environments, v.3(4), 2011, p.349-361.

Wang S, Skubic M & Zhu Y "Activity Density Map Visualization and Dissimilarity Comparison for Eldercare Monitoring" IEEE Journal of Biomedical and Health Informatics, v.16, 2012, p.607.

Alexander GL, Rantz M, Skubic M, Koopman RJ, Phillips LJ, Guevara RD & Miller SJ "Evolution of an Early Illness Warning System to Monitor Frail Elders in Independent Living" Journal of Healthcare Engineering, v.2, 2011, p.259.

Wang F, Stone E, Skubic M, Keller JM & Abbott C "Toward a Passive Low-Cost In-Home Gait Assessment System for Older Adults" IEEE Journal of Biomedical and Health Informatics, v.17, 2013, p.346.

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