关键词: Biomechanical modeling IPC Machine learning Peripheral vascular disease Personalized therapy

Mesh : Humans Foot / blood supply physiology Male Female Intermittent Pneumatic Compression Devices Middle Aged Regional Blood Flow / physiology Adult Skin / blood supply Leg / blood supply Aged

来  源:   DOI:10.1016/j.jbiomech.2023.111820

Abstract:
Intermittent pneumatic compression (IPC) therapy has been adopted in prevention and treatment of ischemic-related peripheral vascular diseases. The aim of this study is to provide an approach to personalize the compression strategy of IPC therapy for maximizing foot skin blood flow. In this study, we presented a method to predict the optimized compression mode (OCM) for each subject based on biomechanical features extracted from experimental data tested with multiple IPC modes. First, to demonstrate the blood flow enhancing effect by applying the personalized OCM, four IPC modes of different frequency settings were tested on a total of 24 subjects. The frequency settings were adjusted by deflating-waiting time, which was defined as the total time length from the start of cuff deflation to the start of next compression. The foot skin blood perfusion and IPC air cuff pressure were monitored during the experiments. The personalized OCM was defined as the certain IPC mode that has the highest blood perfusion augmentation (BPA). Compared with the rest stage blood perfusion, the personalized OCM settings resulted in >50% of augmentation for 75% of healthy subjects (maximum augmentation at 244%) and >20% augmentation for 75% of patients with diabetes (maximum augmentation at 180%). Second, for predicting the OCM, we establish a random forest model based on the features extracted from the experimental data. The binary classification resulted in acceptable prediction performance (AUC > 0.7). This study might inspire new IPC strategies for improving foot microcirculation.
摘要:
间歇性充气压缩(IPC)疗法已被用于预防和治疗缺血性相关的外周血管疾病。这项研究的目的是提供一种方法来个性化IPC治疗的压缩策略,以最大程度地提高足部皮肤血流量。在这项研究中,我们提出了一种方法来预测优化压缩模式(OCM)为每个受试者的基础上提取的实验数据与多种IPC模式测试的生物力学特征。首先,通过应用个性化OCM来展示血流增强效果,在总共24名受试者中测试了四种不同频率设置的IPC模式.通过放气等待时间调整频率设置,定义为从袖带放气开始到下一次压缩开始的总时间长度。在实验过程中监测足部皮肤血液灌注和IPC空气袖带压力。个性化OCM被定义为具有最高血液灌注增强(BPA)的特定IPC模式。与静息期血液灌流相比,个性化OCM设置导致75%的健康受试者增加>50%(最大增加为244%),75%的糖尿病患者增加>20%(最大增加为180%).第二,为了预测OCM,根据实验数据提取的特征建立随机森林模型。二元分类导致可接受的预测性能(AUC>0.7)。这项研究可能会激发新的IPC策略来改善足部微循环。
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