疼痛的自动评估:前景,进展和前进的道路
Kenneth Prkachin1, Zakia Hammal2
1University of Northern British Columbia.
概括
使用计算机视觉的自动化疼痛评估显示,它有望改善疼痛测量,超出传统的口头报告. 为了在疼痛科学和临床环境中广泛使用,需要进一步开发.
科学领域:
- 疼痛研究 疼痛研究
- 医学技术 医学技术 医学技术
- 行为科学是一种行为科学.
背景情况:
- 精确的疼痛测量对于促进疼痛控制至关重要.
- 目前的疼痛评估严重依赖于主观的口头报告,这些报告有局限性.
- 需要对疼痛相关行为的客观测量,如面部表情,但现有的技术往往是繁的.
研究的目的:
- 探索使用计算机视觉和机器学习进行自动化疼痛评估的可行性.
- 识别挑战,并建议开发客观疼痛测量工具的方向.
主要方法:
- 应用计算机视觉和机器学习技术来分析与疼痛相关的面部表情.
- 对疼痛行为自动评估的潜力的评估.
主要成果:
- 计算机视觉和机器学习已经在评估与疼痛相关的面部表情方面取得了成功.
- 通过当前的技术,对疼痛行为进行自动评估似乎是可行的.
结论:
- 通过面部表情分析进行自动疼痛评估是客观疼痛测量的一个有希望的途径.
- 需要进一步的研究和开发来克服目前的局限性,并使疼痛科学和临床实践的更广泛实施成为可能.
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