Abstract
Accidental falls of patients cannot be completely prevented. However, timely fall detection can help prevent further complications such as blood loss and unconsciousness. In this study, the authors present a cost-effective integrated system designed to remotely detect patient falls in hospitals in addition to classifying non-fall motions into activities of daily living. The proposed system is a wearable device that consists of a camera, gyroscope, and accelerometer that is interfaced with a credit card-sized single board microcomputer. The information received from the camera is used in a visual-based classifier and the sensor data is analysed using the k-Nearest Neighbour and Naïve Bayes' classifiers. Once a fall is detected, an attendant at the hospital is informed. Experimental results showed that the accuracy of the device in classifying fall versus non-fall activity is 95%. Other requirements and specifications are discussed in greater detail.
Highlights
The prime objective of this research project was to design an integrated system that detects patient falls in hospitals, and accurately differentiates between different non-fall motions, which consist of activities of daily living (ADL)
According to the British newspaper ‘The Telegraph’, ∼208,720 falls occurred in National Health Service (NHS) hospitals in England by the end of October 2012, out of which 90 falls resulted in death and >50,000 patients were left injured [1]
The article confirms that 900 of the mentioned cases were classified as severe with patients suffering from hip fractures and brain injuries
Summary
The prime objective of this research project was to design an integrated system that detects patient falls in hospitals, and accurately differentiates between different non-fall motions, which consist of activities of daily living (ADL). The article confirms that 900 of the mentioned cases were classified as severe with patients suffering from hip fractures and brain injuries. It is almost impossible to prevent all falls in hospitals, the timely rescue of the patient can make a difference. The extra cost of taking care of patients who have suffered a fall is an estimated £2.4 billion a year [1]. Accurate and timely fall detection can help save hospital’s resources as well as help patients cope with the physical and emotional consequences of a fall
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
