The Portable Elderly Health Care System Based On The Detection Of Falls And ECG

With the aging of the increase,the advance of urbanization,a sharp increase in the number of elderly people living alone,elderly care is increasingly becoming a social issue,especially sudden illness care more and more people's attention.This article aims to take advantage of embedded system design a elderly health monitors,displaying ECG,heart rate and real-time detection of falls,fall excursion event of an alarm,from fall to shorten treatment time,reduced from falls accidental cause damage.This study,firstly,designs a waist wearable fall detection system using the MEMS inertial sensors,designs non-standard ECG leads acquisition system using BMD101,data storage and display unit by SD and LCD screen;Secondly,according to the law of fall,proposes a fall detection algorithm based on multi-sensor data fusion,which extracts the body acceleration and its dynamic and static parameter,the body attitude angle,the absolute values of angular velocity.For ECG waveform baseline drift phenomenon,this paper employs morphological filter.Then dispatch the multi-task applying the real-time operating system,design scheduling methods with real-time and safety,the procedures of algorithms are also described.Ultimately,designs fall detection algorithm based on multi-sensor data using the parameters.Then evaluates the algorithm on data recorded from 10 volunteers performing falls and activities of daily living(ADL).Results show that the algorithm based on multi-sensor data fusion is the most suitable method of fall-detection,achieving 96.67% sensitivity and 97% specificity,superior to the algorithm reported by Kagans et al..,and show the ECG waveform after filter.Finally,this paper summarizes the design process of the elderly health care system,pointing out flaws and developing a plan to carry out follow-up work.