文中的研究目的是针对当前医疗监护系统不能个性化地反映监护对象身体状况变化等问题。提出一种个性化家庭远程医疗监护系统,对不同年龄、性别、体质的监护对象建立因人而异的监护报警模型。文中的研究方法为通过实时采集人体的体温、心率、血压和血氧饱和度等生理数据,利用支持向量机建立监护对象的生理模型进行诊断。结果显示该模型准确地反映监护对象的身体状况,自动识别出因为传感器误差和监护对象移动所产生的错误报警,同时准确判断出由于生理异常而产生的报警,提高医疗监护系统的诊断效率和准确性。
The purpose is for the current health care system can not reflect the change of care.object' s physical condition,present a per- sonalized family remote monitoring system, which can build individual alarm model by people' s age, gender and physique. The research method utilizes support vector machine to build object' s physical model through real-time acquisition of people' s temperature, heart rate, blood pressure and blood oxygen saturation. The results show that the model can reflect object' s physical condition correctly and au- tomatically identify those false alarms generated by the sensor error and the moving of objects and accurately determine the physiological abnormalities alarm, which improves efficiency and accuracy of diagnosis for the system.