Automated Detection of Symptomatic Autonomic Dysreflexia Through Multimodal Sensing
Automated Detection of Symptomatic Autonomic Dysreflexia Through Multimodal Sensing
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DOI：
10.1109/jtehm.2019.2955947
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发表时间：
2020-01-01
影响因子：
3.4
通讯作者：
Duerstock, Bradley S.
中科院分区：
文献类型：
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作者：
Suresh, Shruthi;Duerstock, Bradley S.
目的：自主神经反射障碍（AD）是一种潜在的危及生命的综合征，发生在高水平脊髓损伤（SCI）患者中。阿尔茨海默病是由触发因素引起的，它可以导致病理生理反应的快速升级，如果不消除触发因素，阿尔茨海默病可能是致命的。目前还没有客观、无创、准确的监测系统可以在非临床环境中实时自动检测AD症状的发生。技术或方法：我们开发了一种独立于用户的实时AD症状检测方法，使用可穿戴生理遥测系统（PTS）和机器学习模型，使用11名SCI参与者的数据。结果：PTS检测AD症状的平均准确率为94.10%，假阴性率为4.89%。结论：PTS检测AD症状的发生具有较高的敏感性和特异性，可帮助SCIs患者预防AD的发生。这将使具有高级社会科学能力的人能够更加独立，从事职业活动，同时给予持续的医疗监督。临床影响：PTS可以作为现有解决方案的补充工具，用于检测AD的发作，并使新受伤的个体为AD发作做好准备。此外，它可以转化为一个系统，鼓励个人实践更好的医疗管理，以防止未来发生。
Objective: Autonomic Dysreflexia (AD) is a potentially life-threatening syndrome which occurs in individuals with higher level spinal cord injuries (SCI). AD is caused by triggers which can lead to rapid escalation of pathophysiological responses and if the trigger is not removed, AD can be fatal. There is currently no objective, non-invasive and accurate monitoring system available to automatically detect the onset of AD symptoms in real time in a non-clinical setting. Technology or Method: We developed a user-independent method of symptomatic AD detection in real time with a wearable physiological telemetry system (PTS) and a machine learning model using data from eleven participants with SCI. Results: The PTS could detect onset of AD symptoms with an average accuracy of 94.10% and a false negative rate of 4.89%. Conclusions: The PTS can detect the onset of the symptoms AD with high sensitivity and specificity to assist people with SCIs in preventing the occurrence of AD. It would enable persons with high level SCIs to be more independent and pursue vocational activities while granting continuous medical oversight. Clinical Impact: The PTS could serve as a supplementary tool to current solutions to detect the onset of AD and prepare individuals who are newly injured to be better prepared for AD episodes. Moreover, it could be translated into a system to encourage individuals to practice better healthcare management to prevent future occurrences.