Falls those leads to fatal injury have become a great challenge that cannot be neglected for elderly people. In the last few years, different kinds of approaches have been proposed in fall detection area, which can be explained and categorized into three types: wearable device based, ambience sensor based and vision based . First of all, wearable devices usually take advantages of embedded sensors to detect the motion and location of the body, such as accelerometer, magnetometer and gyroscope [2, 3]. And the cost of wearable device based approach is quite low, as well as the installation and operation is not complicated for the elderly. Secondly, ambience based approach always use pressure sensors to detect and track body. This solution is also cost-effective and easy-deployment [4, 5]. However, the possibility of sensing objects other than human bodies posts a remarkable challenge to the detection accuracy of this approach. Last but not least, vision based solution makes full use of deployed cameras to monitor all the objects within the range, including human bodies [6, 7]. There is less intrusion into people’s daily life than the above two approaches, while the observation space is limited and ubiquitous monitoring can’t be achieved.
Featured Adafruit Product!
ADXL345 – Triple-Axis Accelerometer (+-2g/4g/8g/16g) w/ I2C/SPI: Filling out our accelerometer offerings, we now have the really lovely digital ADXL345 from Analog Devices, a triple-axis accelerometer with digital I2C and SPI interface breakout. We added an on-board 3.3V regulator and logic-level shifting circuitry, making it a perfect choice for interfacing with any 3V or 5V microcontroller such as the Arduino. (read more)
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