Biometrics is concerned with measurement and analysis of a universal,
unique and measurable physiological or behavioural characteristic.
Biometric data is taken from individuals, extracting feature sets from
the data and comparing it with the enrolment set in a database. Existing
analyses techniques using wearable sensors are applied to gait analyses
in children for biometric gait recognition. The performance degradation
for children walking compared to adult walking is approximately 100%. A
6.21% Equal Error Rate (EER) for adult gait recognition was reached
compared to 12.69% for children. Carrying an object showed that the
performance actually improved compared to normal walking. However,
faster walking was unstable resulting in a higher Equal Error Rate
(EER). Age and gender differences showed significant variations in EER
values. A coupled approach of statistical time-domain and frequency
domain methods was employed to match biometric gait signals. Using root
mean squared, crest-factor and kurtosis obtained similar matches in gait
signals of children for the ages of 5-16 than for the traditional
methods.