基于MEMS的帕金森病人体姿态分类监测系统
发布时间：2019-05-24 02:53
【摘要】：帕金森病有较高的患病率和致残率,已成为危害老年人健康的主要疾病之一,针对这种情况,开发了一套人体姿态监测与分类的系统,以便在危险发生时能够及时发现,避免情况进一步恶化。设计了一个便携式人体加速度信息采集装置,通过无线数据传输技术,将采集到的人体加速度信息传送到上位机PC中,根据相应算法,在上位机PC中编写相应的程序,提取不同姿态下的人体特征,然后根据这些姿态特征,实现人体姿态的实时监测,并且将人体姿态分类成平躺、坐、站、行走、起立等。实验结果表明该系统有良好的识别能力。
[Abstract]:Parkinson's disease has a high prevalence and disability rate, and has become one of the main diseases endangering the health of the elderly. In view of this situation, a set of human posture monitoring and classification system has been developed so that it can be detected in time when the risk occurs. Avoid further deterioration of the situation. A portable human acceleration information acquisition device is designed. Through wireless data transmission technology, the collected human acceleration information is transmitted to the upper computer PC. According to the corresponding algorithm, the corresponding program is written in the upper computer PC. The human body features under different postures are extracted, and then the real-time monitoring of human posture is realized according to these posture features, and the human posture is classified into lying, sitting, standing, walking, standing and so on. The experimental results show that the system has good recognition ability.
【作者单位】： 南京理工大学智能弹药技术国防重点学科实验室;
【基金】：国家自然科学基金(61201391)
【分类号】：R742.5;TP391.41
，
本文编号：2484482
[Abstract]:Parkinson's disease has a high prevalence and disability rate, and has become one of the main diseases endangering the health of the elderly. In view of this situation, a set of human posture monitoring and classification system has been developed so that it can be detected in time when the risk occurs. Avoid further deterioration of the situation. A portable human acceleration information acquisition device is designed. Through wireless data transmission technology, the collected human acceleration information is transmitted to the upper computer PC. According to the corresponding algorithm, the corresponding program is written in the upper computer PC. The human body features under different postures are extracted, and then the real-time monitoring of human posture is realized according to these posture features, and the human posture is classified into lying, sitting, standing, walking, standing and so on. The experimental results show that the system has good recognition ability.
【作者单位】： 南京理工大学智能弹药技术国防重点学科实验室;
【基金】：国家自然科学基金(61201391)
【分类号】：R742.5;TP391.41
，
本文编号：2484482
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