Diabetes Mellitus affects adults and children, causing changes in lifestyle. The diabetic affected person count has increased drastically worldwide over the last few years; about 425 million people have diabetes. By 2030, it is predicted that diabetic disorder will be the seventh leading cause of human death. Diabetes mellitus is measured invasively. This method has limitations such as patient’s preparation, piercing of the skin, which causes infection and needs for skilled technicians. In order to avoid the limitations of invasive methods, vibrations from the pancreas are acquired using a smartphone accelerometer sensor and detecting the value of diabetes. The human body has a unique energy signature for every organ, which leads to vibrations with different frequencies. The frequency of the vibration signal from the pancreas is proportional to insulin secretion and dynamics. The signals obtained from the accelerometer sensor are trained and analyzed with the Levenberg–Marquardt algorithm for obtaining the relation between the excess insulin secretion and clinical value of the diabetic level of the person. The accelerometer signals and clinical values are modeled with Regression analysis for the diabetic and non-diabetic persons. The results show the correlation between the fluid dynamics of insulin and clinical value at about 95% in prediction.

糖尿病影响成人和儿童，导致生活方式的改变。在过去的几年中，世界范围内糖尿病患者的数量急剧增加。约有4.25亿人患有糖尿病。预计到2030年，糖尿病疾病将成为人类死亡的第七大主要原因。糖尿病是有创测量的。该方法具有局限性，例如患者的准备，皮肤刺穿，这会引起感染并需要熟练的技术人员。为了避免侵入性方法的局限性，使用智能手机加速度传感器并检测糖尿病的值来获取胰腺的振动。人体对每个器官都有独特的能量特征，从而导致不同频率的振动。来自胰腺的振动信号的频率与胰岛素的分泌和动力学成正比。从加速度传感器获得的信号经过Levenberg-Marquardt算法训练和分析，以获取胰岛素分泌过多与患者糖尿病水平的临床价值之间的关系。使用回归分析为糖尿病人和非糖尿病人建模加速度计信号和临床值。结果表明，胰岛素的流体动力学与临床价值之间的相关性约为95％。使用回归分析为糖尿病人和非糖尿病人建模加速度计信号和临床值。结果表明，胰岛素的流体动力学与临床价值之间的相关性约为95％。使用回归分析为糖尿病人和非糖尿病人建模加速度计信号和临床值。结果表明，胰岛素的流体动力学与临床价值之间的相关性约为95％。