Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Human Gait Analysis using Wearable Sensors

Human Gait Analysis using Wearable Sensors

Balisane, Hewa
Twigg, Peter
Ahmed, Waqar

Paperback

General Mathematics

ISBN10: 3846555541
ISBN13: 9783846555545
Publisher: Lap Lambert Academic Pub
Published: Jan 6 2012
Pages: 156
Weight: 0.52
Height: 0.36 Width: 6.00 Depth: 9.00
Language: English
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.

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