Identifying people from gait pattern with accelerometers

Abstract

Protecting portable devices is becoming more important, not only because of the value of the devices themselves, but for the value of the data in them and their capability for transactions, including m-commerce and m-banking. An unobtrusive and natural method for identifying the carrier of portable devices is presented. The method uses acceleration signals produced by sensors embedded in the portable device. When the user carries the device, the acceleration signal is compared with the stored template signal. The method consists of finding individual steps, normalizing and averaging them, aligning them with the template and computing cross-correlation, which is used as a measure of similarity. Equal Error Rate of 6.4% is achieved in tentative experiments with 36 test subjects.

Smartphone User Identity Verification Using Gait Characteristics

“…Ailisto et al [10] propose the gait authentication based on wearable accelerometer. Acceleration data were analyzed to find individual steps, normalize, and align them with the template.…”

Biometric Gait Recognition Based on Machine Learning Algorithms

“…Furthermore, for any biometric system to be more adequate by overall public, it is desirable to be a nonintrusive system. Gait recognition that was first introduced by Ailisto et al (2005) is particularly considered as it enables the identification at a distance using standard cameras in any conditions. Henceforward, it is applicable to unfavorable far observation in banks, airports, military departments and homeland security.…”

Orientation-Compensative Signal Registration for Owner Authentication Using an Accelerometer

“…In detail, the sensor-orientation variation of sensor attachment does not actually make any temporal distortion but rotates the signals so that they cannot be matched properly. A solution to avoid Copyright c 2014 The Institute of Electronics, Information and Communication Engineers this problem is to fix the sensor on the owner's body as most existing methods [7], [18]- [29], [31], [32] do. However, it is undesirable and unnatural in real applications (e.g.…”

“…There are many existing methods for recognizing a person carrying a sensor based on the gait signals of an inertial sensor, such as identification [7], [18]- [20] or authentication [21]- [26], which showed a promising application of inertial sensors for biometric recognition. Because the human gait is a periodic motion, there are several approaches for gait-based owner recognition: gait model-based, frequency analysis-based, and period detection-based approaches.…”

“…In the frequency analysis-based methods, a histogram of signal intensity [7], [29] or a vector of coefficients of Fourier, wavelet transform [19], [30] are used as a gait pattern. In the period detection-based methods [18]- [26], [31], [32], a gait period (two consecutive steps) is first detected, and the signal segment of the gait period is used as a gait pattern.…”