一种适用于单片机的老人跌倒检测算法研究

摘要

针对单片机的计算能力和检测系统的实时性,设计了一种可穿戴的老人跌倒检测装置.利用六轴陀螺仪加速度计进行原始信号的采集,将合成加速度和姿态角作为特征量,设计一种基于二叉树支持向量机分类思想的三级检测算法.首先,以合成加速度是否超出阈值作为分类条件,识别样本是否属于剧烈运动;其次,则以合成加速度是否呈现周期性变化和人体是否处于类静止状态(合成加速度在0.8~1.2g)将样本进一步细分;最后,则通过判断人体的姿态确定老人是否跌倒.当检测到老人跌倒后,利用GPS对老人进行定位,同时利用GSM模块发送报警信息.实验证明算法准确率高、实时性好.同时能够准确定位,并将信息发送出去.%In allusion to the computation capability of the single chip microcomputer and the real-time performance of the detection system,a wearable fallen elder detection device is designed. The original signal is collected by the six-axis gyroscope accelerometer,and with the synthetic acceleration and attitude angle as the characteristic quantities,a three-level detection algo-rithm based on binary-tree support vector machine(BT-SVM)classification is designed. First,whether the synthetic accelera-tion has exceeded the threshold is taken as the classification condition to identify whether the sample is in strenuous motion.Second, the sample is further classified according to whether the synthetic acceleration(0.8~1.2 g)is changing periodically and whether the human body is in static state. Finally,whether the elder has fallen or not is judged according to his attitude. When a fallen elder is detected,his location will be determined by GPS,and the alarm information will be sent by the GSM module at the same time. The experimental results show that the algorithm has high accuracy and good real-time performance,and can locate the fallen elder accurately and send information out.