Remote health monitoring: fall detection

Abstract

Urgency of the research. Falling is a serious health issue among the elderly population; it can result in critical injuries like hip fractures. Immobilization caused by injury or unconsciousness means that the victim cannot summon help themselves. Target setting. The target of this paper is to design and create a fall detection system. The system consists of a monitoring device that links wirelessly with a laptop. The device is able to accurately distinguish between fall and non-fall. Actual scientific researches and issues analysis. Healthcare systems in the world have undergone tremendous evolution in the last 50 years. In the early 1960s, we had computers in the form of mainframes being incorporated into healthcare systems. However, there were some problems met from their usage. These mainframes were very few, expensive, large in size and consumed a lot of electrical power and as a result, they had to be shared by several hospitals since independent ownership wasn’t feasible an idea to be considered at all. Uninvestigated parts of general matters defining. Despite all of the changes, there was still the issue of affordability of the treatments offered by the hospitals from the patients’ point of view. This had a negative impact on both the hospitals & patients. Hospitals were not getting that large enough a number of patients for treatment while patients were opting for alternatively cheaper treatment plans. The research objective. The scope of this paper is limited to fall detection and remote viewing of the collected data. Fall detection algorithm is developed and implemented through programming on Arduino Uno board. Remote viewing of the data is done on a laptop after having fall detection data wirelessly transmitted to it. The statement of basic materials. To detect fall along an axis, the acceleration magnitude is considered. With the accelerometer output data, the angle change can also be calculated using the dot product. In the event of falling, one experiences a momentary free-fall then a large spike in acceleration. For wireless data transmission, we choose the HC‐05 module which is an easy to use Blue-tooth SPP (Serial Port Protocol) module, designed for transparent wireless serial connection setup. For appropriate fall detection, we choose an accelerometer. The Bluetooth module receives fall detection data from the micro-controller and transmits the same to a laptop computer where we realize remote viewing of the data. Conclusions. The objective of this paper was to design a fall detection system that links wirelessly with a laptop computer (where we have remote viewing of the collected data). By the conclusion of this paper, we had achieved the primary goal of creating a working system able to recognize falls from non-falls, while wirelessly synched with a laptop.