A novel solution for finding postpartum haemorrhage using fuzzy neural techniques

Postpartum haemorrhage (PPH) is the loss of blood above 500 ml during vaginal or caesarean deliveries. It difficult to find a PPH in an earlier stage, so pregnant women are exposed excess that makes them suffer and die. Antenatal practices help identifying risk factors, modern technology used overcome risk. Still, morbidity rate mortality arise due unpredicted unexpected cause. still significant cause maternal worldwide. The novelty this research work alert medical practitioner about excessive bleeding childbirth. We proposing automation system using wearable devices prevent from PPH. These measure parameters like temperature, pulse rate, pressure, sweat women. Fuzzy neural technique-based rules for each parameter predict developing evaluate performance proposed reducing rates. Our findings experiment carried on metrics HPPH (high-level postpartum haemorrhage), NPPH (normal-level MPPH (medium-level haemorrhage) 15 patients. output value 1 indicates patient state with NPPH, 0 HPPH, values between indicate MPPH. Based sensitivity predicted values, attention taken doctors nurses nearby locations Internet Things infrastructure.