With the aging of the society, it is expected that the proportion of elderly families in the empty nest will reach 90% by 2030, when the elderly families in China will be empty. According to statistics, more than one-third of the elderly in the 65-year-old population have a fall experience, and 2/3 elderly people are accidentally killed by falls, and this proportion is more than 75 years old. Up to 70%. Fall detection is an implementation of home terminals in remote health monitoring systems, involving multiple fields, including signal acquisition and processing, signal feature extraction, and data transmission. There are many fall detection techniques. Classification from the channels of signal acquisition can be divided into three categories: fall detection based on video images. The disadvantage of this method is that it cannot guarantee the privacy of users and the quality of video images is affected. Light and other environmental impacts are large; the fall detection based on acoustic signals is complicated to install and the initial investment is relatively large; the fall detection based on the wearable device is more prominent than the previous two methods in the applicable environment and the degree of interference to the user. advantage. Comprehensive comparison of various detection methods, based on wearable detection methods for remote monitoring of the health of the elderly is more suitable. The fall detection module is mainly composed of an acceleration collecting unit, a microprocessor unit, a wireless communication unit, and a remote fall monitoring background, and the whole module is performed by a lithium battery. The system collects the acceleration by the acceleration acquisition unit, and preprocesses the signal through the microprocessor unit. The suspicious data extracted by the preprocessing is transmitted to the remote fall monitoring background through the wireless communication unit for final analysis and processing, and the system is detected when the fall is detected. Ability to automatically trigger an alert item. During the fall of the human body, the three vectors of acceleration, velocity and displacement of the object in all directions will change. In fact, it is difficult to fully distinguish the fall action based on only the change in acceleration in the directions of the parties. The acceleration (v) is obtained by performing an integral on the acceleration in the time domain, and the displacement (s) is obtained by two integrations to improve the accuracy of the system. The acceleration collected by the acceleration sensor includes both the acceleration of the Earth's gravity and the acceleration caused by human motion, and both parts exist at the same time. Based on the acceleration of human body motion, a three-dimensional motion model of the human body is established [6], and a three-dimensional coordinate system can be established according to the three orthogonal measurement directions of the acceleration sensor. Usually, when the device is properly worn, the acceleration in the Y direction is expressed as gravitational acceleration (g) and the acceleration in the horizontal direction is 0 when the object is in a stationary or horizontal motion. When the object falls, if only the change of the acceleration value of the initial state is considered, the longitudinal variation ranges from 1g to 0g, and the horizontal component (x or z) changes from 0g to 1g. A fall detection module based on a three-dimensional acceleration sensor, a microprocessor and a wireless communication module is constructed, which can better distinguish daily activities and fall events. Siren Alarm,Outdoor Siren,Wireless Siren,Home Alarm Siren NINGBO SANCO ELECTRONICS CO., LTD. , https://www.sancobuzzer.com
