Mobile authentication/identification has grown into a priority issue nowadays because of its existing outdated mechanisms, such as PINs or passwords. In this paper, we introduce gait recognition by using a mobile accelerometer as not only effective but also as an implicit identification model. Unlike previous works, the gait recognition only performs well with a particular mobile specification ...

Biometric gait recognition is a well suited method for authentication on mobile devices as it is unobtrusive and concurrent. Hence, in contrast to PIN authentication it is no extra-effort for the user. The characteristic gait of a subject can be recorded using accelerometers which are nowadays already contained in many mobile devices. From this data biometric feature vectors can be extracted an...

OBJECTIVE To explore the strength of the association between gait speed and community ambulation and whether this association is significantly distorted by other variables. DESIGN Cross-sectional study conducted 3 years after stroke. SUBJECTS A total of 102 patients after first-ever stroke following inpatient rehabilitation who are now living in the community. METHODS Community ambulation...

BACKGROUND Freezing of gait (FOG) remains one of the most common debilitating aspects of Parkinson's disease and has been linked to injuries, falls and reduced quality of life. Although commercially available portable cueing devices exist claiming to assist with overcoming freezing; their immediate effectiveness in overcoming gait initiation failure is currently unknown. This study investigated...

Accelerometer-based gait recognition for mobile healthcare systems has became an attractive research topic in the past years. However, a major bottleneck of such system is it requires continuous sampling of accelerometer, which reduces battery life of wearable sensors. In this paper, we present KEHGait, which advocates use of output voltage signal from kinetic energy harvester (KEH) as the sour...

This paper describes a decision tree (DT) based pedometer algorithm and its implementation on Android. The DTbased pedometer can classify 3 gait patterns, including walking on level ground (WLG), up stairs (WUS) and down stairs (WDS). It can discard irrelevant motion and count user’s steps accurately. The overall classification accuracy is 89.4%. Accelerometer, gyroscope and magnetic field sens...

Assessment of physical activity in morbidly obese subjects is important especially in bariatric surgery. We examined the validity of Intelligent Device for Energy Expenditure and Activity (IDEEA) for measuring physical activity and sedentary behavior in morbidly obese women. Activity types, gait counts, and speed detected by the IDEEA monitor were compared to those reported by an observer. The ...