| NSF Org: |
IIS Division of Information & Intelligent Systems |
| Recipient: |
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| Initial Amendment Date: | September 22, 2015 |
| Latest Amendment Date: | September 22, 2015 |
| Award Number: | 1555408 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Phillip Regalia
pregalia@nsf.gov (703)292-2981 IIS Division of Information & Intelligent Systems CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | October 1, 2015 |
| End Date: | September 30, 2018 (Estimated) |
| Total Intended Award Amount: | $300,000.00 |
| Total Awarded Amount to Date: | $300,000.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
3 RUTGERS PLZ NEW BRUNSWICK NJ US 08901-8559 (848)932-0150 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
96 Frelinghuysen Rd Piscataway NJ US 08854-8018 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): |
Info Integration & Informatics, Smart and Connected Health |
| Primary Program Source: |
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| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
Overview: Computers and Internet use have dramatically transformed our life style and exposed us to many significant occupational health hazards including neck and shoulder pains and low back pain associated with long-time sitting. These hazards have become a significant public health problem both in the US and the rest of the world. Although many lifestyle-related risk factors have been identified, effective monitoring and management is lacking to prevent the occurrence of these diseases in long term. The aim of this project, in partnership with Liberty Mutual Research Institute for Safety, is develop a first smart active chair to prevent injuries and improve office safety.
Keywords: ergonomics, sensor fusion, visual tracking, proactive intervention.
Intellectual Merit: The intellectual merit of this proposed exploratory research is that our research leads to a new paradigm of proactive preventing unhealthy lifestyle based on multimodal sensing research and technology. The investigators develop a novel method to predict neck, back and shoulder joint loading and muscle forces in real-time and to develop a personalized and real-time intervention system to automatically reconfigure the workstation and chair to reduce the injury/disorder risk.
Broad Impacts: The broader Impact is that our project achieves substantial reduction in office-related health disorders, such as lower back pain, promoting improved lifestyle quality in the office and in our homes. The proposed research results in a unique and diverse generation of undergraduate and graduate researchers capable to address this new class of multidisciplinary problems and encourages active participation of women and underrepresented.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
As computers have become ubiquitous in the our lives, many of us have developed debilitating symptoms such as neck and shoulder pain, carpal tunnel syndrome, and lower back pain, due to prolonged sitting and computer use. These occupational health hazards are becoming a significant public health problem in the US. Improving health and safety in the computer use environment is of great importance due to the high incidence of these disorders and the potential increased mortality risk associated with extensive computer use. Although efforts to prevent these occupational health hazards such as ergonomic modifications have received increased attention, the incidence of disorders is expected to increase due to the increasing prevalence of computers. There is an urgent need to provide effective interventions to directly address health hazard prevention for the computer use environment.
This project will focus on modeling of human-seat interaction and developing a novel system, the Smart Active Chair, to revolutionize the current hazard intervention in the computer use environment, and limit the adverse effects of computer usage on health and wellbeing.
In this project, we have developed Smart chair prototypes, which can automatically adjust their configuration to adapt to the users’ posture. We have been developing the deep learning methods for predicting the posture and understanding the critical joint behaviors. We have proposed a deep multi-task and task-specific feature learning network for robust shape preserved joint segmentation. We have also developed a novel deep-learning effective 3D bone extraction method using low-contrast and high-shape-variability MR data and applied for shoulder bones.
We have proposed machine learning and deep learning approaches to estimate the human posture. We have been also developed image-based methods for assessing joint morphology and joint kinematics.
Based on our work, we have published numerous top journal and conference papers. Some papers have been published as a cover story and some received best paper awards.
The novel chair system will, we hope, make a contribution alleviating the adverse effects of computer usage on health and wellbeing analysis. A wide variety of other applications, with the potential to improve the lives of the people with musculoskeletal disorders, could also benefit from the advances made through this project.
Through this project, many undergraduate and graduate students have had the opportunity to participate in human movement analysis, product design, and image analysis research. This results in a unique generation of under-graduate and graduate researchers with a comprehensive knowledge of computational sciences, occupational medicine, and product design.
Last Modified: 02/13/2019
Modified by: Kang Li
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