Ulster University Logo

Ulster Institutional Repository

Feasibility study on iPhone accelerometer for gait detection

Biomedical Sciences Research Institute Computer Science Research Institute Environmental Sciences Research Institute Nanotechnology & Advanced Materials Research Institute

Chan, Herman K.Y., Zheng, Huiru, Wang, HY, Gawley, Richeal, Yang, Mingjing and Sterritt, Roy (2011) Feasibility study on iPhone accelerometer for gait detection. In: Pervasive Computing Technologies for Healthcare (PervasiveHealth), 2011 5th International Conference on, Dublin. IEEE. 4 pp. [Conference contribution]

Full text not available from this repository.

URL: http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=6038786

Abstract

Falls amongst the elderly is becoming a major problem with over 50% of elderly hospitalizations due to injury from fall related accidents. Healthcare expenses are dramatically rising due to growing elderly population. Many current technologies for gait analysis are laboratory-based and can incur substantial costs for the healthcare sector for treatment of falls. However utilization of alternative commercially available technologies can potentially reduce costs. Accelerometers are one such option, being ambulatory motion sensors for the detection of orientation and movement. Smart mobile devices are considered as non-invasive and increasingly contain accelerometers for detecting device orientation. This study looks at the capabilities of the accelerometer within a smart mobile device, namely the iPhone, for identification of gait events from walking along a flat surface. The results prove that it is possible to extract features from the accelerometer of an iPhone such as step detection, stride time and cadence.

Item Type:Conference contribution (Paper)
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Mathematics
Research Institutes and Groups:Computer Science Research Institute
Computer Science Research Institute > Artificial Intelligence and Applications
Computer Science Research Institute > Smart Environments
ID Code:21024
Deposited By:Dr Huiru Zheng
Deposited On:10 Feb 2012 09:23
Last Modified:10 Feb 2012 09:23

Repository Staff Only: item control page