基于蝙蝠算法-随机森林分类算法和脉搏波的精神疲劳检测算法

针对精神疲劳易诱发多种慢性病甚至癌症但却难以精准量化评估的问题,提出了一种基于BA-RFC的光电容积脉搏波信号(photoplethysmographic,PPG)人体精神疲劳检测方法.首先,以高校学生为测试对象,根据其精神疲劳状态进行分组,用PPG仪器测量受试者的脉搏波信号,建立元数据库.接着以蝙蝠算法(bat al...

Pulse wave mental fatigue detection algorithm based on BA-RFC

Mental fatigue is prone to induce chronic diseases and cancer; however, it is difficult to be accurately detected or evaluated. To overcome this problem, we propose mental-fatigue detecting method based on Photoplethysmography (PPG). The fatigue status of mental workers is simulated, their pulsation data acquired and served as metadata. Then, we establish a fatigue-detection model by combining Bat Algorithm (BA) and Random Forest Classification (RFC). In the model, we use BA to optimize the characteristics, such as the number of decision trees and classification. Subsequently, we apply the afore-obtained optimal decision trees and classification features into RFC algorithm to identify the fatigue status. The simulation results show that BA-RFC combined algorithm can screen out the features that are highly correlated with fatigue state, and improve the fatigue recognition accuracy from 93.3% to 96.7%.