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Efficient and Cost-Effective Multimodal System for Pain Management in Low Back Pain

Efficient and Cost-Effective Multimodal System for Pain Management in Low Back Pain
用于腰痛疼痛管理的高效且具有成本效益的多模式系统
批准号:
10319006
负责人:
Zakia Hammal
金额:
$59.82万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2020
资助国家:
美国
项目状态:
未结题
起止时间:
2020-03-16 至 2026-06-30

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中文摘要
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英文摘要
Project Summary/Abstract Pain is among the most pervasive and universal forms of human distress. Pain typically is measured by patient self-report or clinician impressions, either through clinical interview or the visual analog scale. However, self- reported pain is difficult to interpret and in some circumstances not possible to obtain [Hadjistavropoulos et al., 2002]. To improve the standard of care and advance pain assessment, monitoring, and intervention, we propose (1) a savvy technology based on automatic facial, head, and body movement analysis for a reliable and valid assessment of the occurrence and intensity associated with five causes of acute and chronic low back pain (LBP); (2) inform our understanding of psychosocial and behavioral indicators of chronic LBP to develop new means to prevent chronic LBP. Participants' face, head, and body movement will be recorded during clinical assessment using two synchronized high-definition digital video cameras during extension, flexion, and rotation movements. The obtained video-recordings, taken during a first visit to the clinic and 3 follow-up visits after treatment, will be used for the development of automatic measures of the occurrence and intensity of pain. To investigate the generalizability of the proposed automatic measures, we will explicitly train and test the proposed classifiers on five different types of acute and chronic LBP. To do so, face, head, and body movement will be automatically tracked using our fully- automatic methods. The tracking results will be used to train end-to-end deep-leaning based classifiers to automatically measure the occurrence and intensity of LBP. To investigate the validity of the proposed classifiers, we will compare automated measurement to the patient- and clinician- rated visual analog scale, brief pain inventory, and continuous observer ratings of pain intensity from the video recordings. MANOVA will be used to quantify the relationship between the individual modalities and their combination for the measurement of the occurrence and intensity of the five LBP conditions and for chronic and acute conditions. To inform our understanding of how LBP evolves into a chronic form, we will use Ecological Momentary Assessment (EMA) to collect behavioral and contextual information beyond the video-recordings and pain scores' assessments. Participants will be monitored for 6 months after treatment, at a frequency of 7 consecutive days per month (1 week per month), and 4 prompts per day, to identify those who evolved to chronic LBP. EMA measures will be used to investigate whether pain intensity differs by psychosocial and behavioral factors both between and within LBP groups as well as whether psychosocial and behavioral factors are associated with the development of chronic LBP.
期刊论文(3)
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会议论文
Face and Gesture Analysis for Health Informatics.
健康信息学的面部和手势分析。
DOI: 10.1145/3382507.3419747
发表时间: 2020-10
期刊: Proceedings of the ... ACM International Conference on Multimodal Interaction. ICMI (Conference)
影响因子: --
作者: [Hammal Z, Huang D, Bailly K, Chen L, Daoudi M]
通讯作者: Daoudi M
DOI: 10.1145/3461615.3485671
发表时间: 2021-10
期刊: ICMI '21 companion : companion publication of the 2021 International Conference on Multimodal Interaction : October 18th-22, 2021, Montreal, Canada. ICMI (Conference) (23rd : 2021 : Montreal, Quebec; Online)
影响因子: --
作者: []
通讯作者:
Efficient and Cost-Effective Multimodal System for Pain Management in Low Back Pain
  • 批准号:
    9886461
  • 项目类别:
  • 资助金额:
    $48.68万
  • 财政年份:
    2020
  • 负责人:
    Zakia Hammal
  • 依托单位:
Automatic Multimodal Assessment of Pain in Dementia
  • 批准号:
    10288413
  • 项目类别:
  • 资助金额:
    $34.47万
  • 财政年份:
    2020
  • 负责人:
    Zakia Hammal
  • 依托单位:
海外基金