Stride time estimation: Realtime peak detection implemented on an 8-bit, portable microcontroller
Falls are a threat of great magnitude for the aging population. Methods, and the pursuit thereof to improve anticipatory prediction of falls, could reduce incidence of injury thereby lowering associated costs of healthcare. Gait monitoring is seen as a reliable area to help decipher potential warning signs as precursors to falls. Stride time is one such parameter, in particular to monitor a patient and recognize variation between stride times. Demographic trends show increasing numbers of older adults. Prevention and avoidance of injurious falls is a key area to impact sustained vigour and quality of life for seniors. Couple this with prolonged ability to maintain autonomy and remain living at home. This combination can profoundly extend distribution of healthcare resources. A portable, inexpensive, low power 8-bit microcontroller in conjunction with an accelerometer and gyroscope is used to implement an algorithm on the microcontroller board to perform peak detection and calculate the gait parameter, stride time, of a patient in real time. This information then transmits via Bluetooth®.
|Keywords||Accelerometer, Algorithm, Ambulatory Monitoring, Biomedical Signal Processing, Falls, Gait, Home Monitoring, Microcontrollers, Mobile Monitoring, Open source software, Peak Detection, Remote Monitoring, Wellness|
|Conference||2012 IEEE Symposium on Medical Measurements and Applications, MeMeA 2012|
Russell, L. (Luke), Steele, A, & Goubran, R. (2012). Stride time estimation: Realtime peak detection implemented on an 8-bit, portable microcontroller. Presented at the 2012 IEEE Symposium on Medical Measurements and Applications, MeMeA 2012. doi:10.1109/MeMeA.2012.6226657