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{ "item_title" : "Human Gait Analysis using Wearable Sensors", "item_author" : [" Hewa Balisane", "Waqar Ahmed", "Peter Twigg "], "item_description" : "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.", "item_img_path" : "https://covers2.booksamillion.com/covers/bam/3/84/655/554/3846555541_b.jpg", "price_data" : { "retail_price" : "63.72", "online_price" : "63.72", "our_price" : "63.72", "club_price" : "63.72", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Human Gait Analysis using Wearable Sensors|Hewa Balisane

Human Gait Analysis using Wearable Sensors

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Overview

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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Details

  • ISBN-13: 9783846555545
  • ISBN-10: 3846555541
  • Publisher: LAP Lambert Academic Publishing
  • Publish Date: January 2012
  • Dimensions: 9 x 6 x 0.36 inches
  • Shipping Weight: 0.52 pounds
  • Page Count: 156

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