Title :
A new smart fall-down detector for senior healthcare system using inertial microsensors
Author :
Yongkun Sui ; Chanmin Ahn ; Ahn, Chong H.
Author_Institution :
Dept. of Electr. Eng. & Comput. Syst., Univ. of Cincinnati, Cincinnati, OH, USA
Abstract :
A new smart fall-down detector for senior healthcare system using inertial microsensors and Wi-Fi technology has been designed, prototyped and characterized in this work. The detector can reduce the risk of severe injury or death caused by falling down with minimum false alarm rate. The different patterns of motion are sensed by a set of inertial sensors composed of a tri-axial accelerometer and a tri-axial gyroscope. The signals of motion are sampled and processed by a microcontroller with integrated algorithms. The smart algorithm integrated with machine learning can be customized according to different habits of different seniors to reduce false alarms. The fall-down signal is transmitted through Wi-Fi to the client via Internet.
Keywords :
Internet; accelerometers; biomedical communication; geriatrics; gyroscopes; health care; intelligent sensors; learning (artificial intelligence); medical signal detection; medical signal processing; microcontrollers; microsensors; signal sampling; wireless LAN; Internet; Wi-Fi technology; fall-down signal; false alarm rate; inertial microsensors; integrated algorithms; machine learning; microcontroller; motion signal processing; motion signal sampling; senior healthcare system; severe injury risk; smart algorithm; smart fall-down detector; triaxial accelerometer; triaxial gyroscope; Acceleration; Accelerometers; Detectors; Feature extraction; Gyroscopes; Microcontrollers;
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE
Conference_Location :
Chicago, IL
DOI :
10.1109/EMBC.2014.6943660
