ABSTRACT
In this paper we use the accelerometer of a smart phone to design and implement a fall monitor with mobility detection function for the user. We not only analyze the change of acceleration but also analyze the four typical actions of humans. These are going upstairs, going downstairs, standing up, sitting down, running and jumping. Then we compare the four actions with the characteristics of a fall. These are weightlessness, impact, immobility and overturning of the body. Because the waist is the center of gravity in the human body, our system is used more effectively when we place the smart phone at the waist. Our system is based on an open source system platform and the accelerometer in the smart phone.
PURPOSE:
This paper deals with the Numerous experiment data indicate it gather accurate information about human body which reflect the truthfully human body motions and this paper is process or transmit it to advanced comprehensively analyzed and this is widely used in such fields are health recovery training, physical exercises, computer games controlling. And here some mathematical calculations about the acceleration component information such as motional track and dynamic process will be gotten for this platform.
PROJECT DESCRIPTION:
Any human body motion, from its beginning to the end, the acceleration of every part of the mobile limbs or other parts of human body is keeping changing. If certain motion is repeated, then its acceleration changing regularity is also very also very close. Therefore if a three-axis acceleration sensor is put on some typical point of measured limbs or other body parts, then the three acceleration components X_Y_Z of that typical point in the motion process can be collected accurately. Then by mathematical calculation about the acceleration components information such as the motional track and dynamic process about that point will be gotten. From comprehensive analysis of the data gathered about several typical points detailed information about the measured human body motions is obtained so that motion information is digitalized.
When the human body falls on the ground the microcontroller will take GPS values and send to the Bluetooth .the Smartphone .
This motion information collection platform uses multi-knot internet technology to collect the acceleration information of multiple typical points simultaneously, and process or transmit it to advanced computers to be comprehensively analyzed, thus this platform can be widely used in such fields as health recovery training, physical exercises, computer games controlling.
BLOCK DIAGRAM:
POWER SUPPLY:
OUTPUT WINDOW:
RECEIVER SECTION:
TECHNOLOGY:
GPS:
GPS (Global Positioning System) technology is used to find the location of any object or vehicle to monitor a child continuously using satellite signals. Three satellite signals are necessary to locate the receiver in 3D space and fourth satellite is used for time accuracy.GPS will give the information of parameters like longitude, latitude and attitude. With the help of these parameters one can easily locate the position of any object. In this GPS technology, the communication takes place between GPS transceiver and GPS satellite.
MEMS:
Microelectronic integrated circuits can be thought of as the “brains” of a system and MEMS augments this decision-making capability with “eyes” and “arms”, to allow Microsystems to sense and control the environment. Sensors gather information from the environment through measuring mechanical, thermal, biological, chemical, optical, and magnetic phenomena. The electronics then process the information derived from the sensors and through some decision making capability direct the actuators to respond by moving, positioning, regulating, pumping, and filtering, thereby controlling the environment for some desired outcome or purpose. Because MEMS devices are manufactured using batch fabrication techniques similar to those used for integrated circuits, unprecedented levels of functionality, reliability, and sophistication can be placed on a small silicon chip at a relatively low cost.
HARDWARE REQUIREMENT:
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- ARM7 Â Â Â LPC2148 MICRO CONTROLLER
- GPS MODEM
- LCD
- MAX232
- BLUETOOTH MODEM
- HUMAN BODY SENSOR
- BUZZER
SOFTWARE:
- EMBEDDED C
- KEIL µVISION4
- FLASH MAGIC
- EXPRESS PCB
RESULT:
In this paper we use four characteristics to determine a fall. In addition we use the fifth state to determine whether the user has lost his mobility or not. Our design is based on the smart phone, so that is can be carried anywhere including out of doors. We can also use the GPS in the smart phone to find out where the fall has taken place. This and the third characteristic of a fall enhance the effect of first aid. In the future we will analyze the acceleration values of X, Y and Z-axis in the static state to recognize the posture in falling
