EAGER: Development of Model-Based Active Chair for Proactive Injury Prevention

EAGER：开发基于模型的主动椅，用于主动预防伤害

• 批准号: 1555408
• 负责人: Kang Li
• 金额: $ 30万
• 依托单位: Rutgers University New Brunswick
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-10-01 至 2018-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1555408&HistoricalAwards=false
• 关键词: EAGER; Development; Model; Based; Active

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.

概述：计算机和互联网的使用极大地改变了我们的生活方式，并使我们面临许多重大的职业健康危害，包括脖子和肩膀疼痛以及与长期坐着相关的腰痛。在美国和世界其他地区，这些危害已成为一个重大的公共卫生问题。尽管已经确定了许多与生活方式相关的风险因素，但缺乏有效的监测和管理以防止长期发生这些疾病。该项目的目的与自由共同研究机构合作，是开发首个明智的主席，以防止伤害并改善办公室的安全性。关键词：人体工程学，传感器融合，视觉跟踪，主动的干预措施。智能优点：这项提出的探索性研究的智力优点，我们的研究是基于新的研究，以防止新型的运动型，并没有任何健康的范围，并且是不健康的范围，并且是不健康的范围，并且是不健康的范围，并且是不健康的范围。 技术。研究人员开发了一种新的方法来实时预测颈部，背部和肩部关节负荷和肌肉力量，并开发一个个性化和实时的干预系统，以自动重新配置工作站和椅子以减少伤害/障碍的风险：更广泛的影响是，我们的项目的影响更大，我们的项目可以实现与办公室相关的健康疾病的大幅度降低，例如较低的后果，例如降低后果，并改善了您的后果，并促进了我们的良好的良好效果，并促进了我们的良好的良好的良好的良好状态。拟议的研究导致独特而多样化的本科生和研究生研究人员能够解决这一新的多学科问题，并鼓励妇女积极参与和代表性不足。

项目成果

A computer vision based method for 3D posture estimation of symmetrical lifting

• DOI: 10.1016/j.jbiomech.2018.01.012
• 发表时间: 2018-03-01
• 期刊: JOURNAL OF BIOMECHANICS
• 影响因子: 2.4
• 作者: Mehrizi, Rahil;Peng, Xi;Li, Kang
• 通讯作者: Li, Kang

Predicting 3-D Lower Back Joint Load in Lifting: A Deep Pose Estimation Approach

• DOI: 10.1109/thms.2018.2884811
• 发表时间: 2019-02-01
• 期刊: IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS
• 影响因子: 3.6
• 作者: Mehrizi, Rahil;Peng, Xi;Li, Kang
• 通讯作者: Li, Kang

A Deep Neural Network-based method for estimation of 3D lifting motions

• DOI: 10.1016/j.jbiomech.2018.12.022
• 发表时间: 2019-02-14
• 期刊: JOURNAL OF BIOMECHANICS
• 影响因子: 2.4
• 作者: Mehrizi, Rahil;Peng, Xi;Li, Kang
• 通讯作者: Li, Kang