Physiological and behavioral profiling for nociceptive pain estimation using personalized multitask learning
Harvard-MIT Health Sciences and Technology（哈佛-麻省理工学院健康科学与技术）；Affective Computing group, MIT Media Lab, Massachusetts Institute of Technology（麻省理工学院媒体实验室情感计算组）
英文摘要：
Pain is a subjective experience commonly measured through patient's self report. While there exist numerous situations in which automatic pain estimation methods may be preferred, inter-subject variability in physiological and behavioral pain responses has hindered the development of such methods. In this work, we address this problem by introducing a novel personalized multitask machine learning method for pain estimation based on individual physiological and behavioral pain response profiles, and show its advantages in a dataset containing multimodal responses to nociceptive heat pain.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
