Research Article

Blood Pressure Classification Using the Method of the Modular Neural Networks

Table 4

Average results of the MNN with (trainlm).

PersonTimeSystolicDiastolicPulse

Person 100:15:341157367

Person 200:15:341057277

Person 300:15:341147080

Person 400:15:341197172

Person 500:15:341458475

Person 600:15:341046190

Person 700:15:341258796

Person 800:15:341096473

Person 900:15:341297356

Person 1000:15:341227765

Person 1100:15:341366370

Person 1200:15:341368171

Person 1300:15:341207478

Person 1400:15:341106277

Person 1500:15:341196870

Person 1600:15:341318280

Person 1700:15:341257780

Person 1800:15:341066579

Person 1900:15:341106879

Person 2000:15:341237680

Person 2100:15:341157276

Person 2200:15:341127378

Person 2300:15:341227677

Person 2400:15:341176890

Person 2500:15:341217492

Person 2600:15:341308289

Person 2700:15:341216386

Person 2800:15:341127390

Person 2900:15:341238280

Person 3000:15:34956173

Person 3100:15:341086572

Person 3200:15:341107073

Person 3300:15:341166771

Person 3400:15:341308680

Person 3500:15:341177380

Person 3600:15:341175481

Person 3700:15:341137474

Person 3800:15:341328679

Person 3900:15:341288078

Person 4000:15:341318570