Fall Detection FPGA-Based Systems: A Survey

Abdelhedi Sahar
2016 International Journal of Automation and Smart Technology  
Falls can lead to serious injuries, hospitalization and sometimes death, and are considered the number one cause of disabilities among elderly people, making falls a key concern in the healthcare sector. Advances in medical technology and healthcare mechanisms have driven the development of new responses to the healthcare needs of a growing elderly population. Ambulatory accelerometer devices have been applied to develop reliable and robust fall detection systems. This paper assesses fall
more » ... ion systems using Field Programmable Gate Arrays (FPGAs) as a CPU in addition to data transmission. In this paper, we give a survey of the different fall detection systems based on FPGAs in the literature, definition of the main theoretical points of fall detection accelerometers-based systems, existing techniques and algorithms and we give an overview of the main steps to design a fall detection system. A fall detection system is defined as a device that sends out an alert in response to a fall. A miniaturized fall detection device seeks to improve fall detection accuracy while having a minimal impact on the user's daily life. To this end, several attempts [8] [9] have been made to develop a variety of fall detection methods as follows (Fig.1) : Vision based approach This approach uses fixed cameras that monitor all the patient's movements. The recorder video data are then forwarded to a CPU that detects falls following a specific fall pattern recognition algorithm. If a fall is detected, an alarm is triggered automatically [10] . This approach allows for more events to be detected simultaneously, making it less intrusive in the patient's daily life, and the acquired data can also be used for remote verification. Limitations include relatively high cost and implementation complexity, along with privacy concerns. Moreover, a fall can be detected only inside the home in rooms equipped with cameras. Sahar Abdelhedi received the MS degree in Information Technology from University Paris Descartes, Paris, France in 2012. She is currently pursuing the PhD in Microelectronics at the National School of Engineers of Tunis (ENIT), Tunis, Tunisia. From 2013, she is a PhD student working on health monitoring thematic, embedded systems and FPGA technology in collaboration with TELNET innovation department. Her research interest includes the design of a fall detection device implemented on an FPGA for elderly people.
doi:10.5875/ausmt.v6i4.1105 fatcat:rykizqoyfjf3xni4qwuqhsz6qy