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專利授權區
專利名稱(中)	基於步態分析的個人身分識別方法及系統
專利名稱(英)	Gait Analysis-Based Personal Identity recognition method and system
專利家族	中華民國：I812235 美國：US2023/0376567A1(公開號)
專利權人	國立清華大學 100.00%
發明人	李昀儒
技術領域	工業工程,資訊工程

專利摘要(中)
一種基於步態分析的個人身分識別方法利用電腦系統實施並包含：獲取特定人員在慣性感測板上行走多步期間感測其震動所獲得的多筆訓練特徵資料；將該等筆訓練特徵資料以每次兩筆的輸入方式來訓練孿生神經網路並調整其共用的權重，以建立步態相似度估測模型；根據受測者在該慣性感測板上行走一步期間產生的慣性感測資料獲得一筆特徵資料；及根據該步態相似度估測模型估測出該筆特徵資料分別與該等筆訓練特徵資料的多個相似度值及預定閾值，辨識該受測者是否為該特定人員。

專利摘要(中)

一種基於步態分析的個人身分識別方法利用電腦系統實施並包含：獲取特定人員在慣性感測板上行走多步期間感測其震動所獲得的多筆訓練特徵資料；將該等筆訓練特徵資料以每次兩筆的輸入方式來訓練孿生神經網路並調整其共用的權重，以建立步態相似度估測模型；根據受測者在該慣性感測板上行走一步期間產生的慣性感測資料獲得一筆特徵資料；及根據該步態相似度估測模型估測出該筆特徵資料分別與該等筆訓練特徵資料的多個相似度值及預定閾值，辨識該受測者是否為該特定人員。

專利摘要(英)
A gait analysis-based personal identity recognition method is implemented by a computer system, and includes: acquiring multiple pieces of training feature data obtained by sensing vibration of an inertial sensing board while a specific person walks on the inertial sensing board for multiple steps; training a Siamese neural network based on the pieces of training feature data in an input manner that two piece of training feature data are inputted to the Siamese neural network each time and adjusting its shared weights to establish a gait similarity estimation model; obtaining feature data based on inertial sensing data that is generated by sensing the inertial sensing board while a subject walks on the inertial sensing board for one step; and identifying whether the subject is the specific person based on a predetermined threshold, and on a plurality of similarity values each associated with the feature data and a corresponding one of the piece of training feature data and estimated by the gait similarity estimation model.

專利摘要(英)

A gait analysis-based personal identity recognition method is implemented by a computer system, and includes: acquiring multiple pieces of training feature data obtained by sensing vibration of an inertial sensing board while a specific person walks on the inertial sensing board for multiple steps; training a Siamese neural network based on the pieces of training feature data in an input manner that two piece of training feature data are inputted to the Siamese neural network each time and adjusting its shared weights to establish a gait similarity estimation model; obtaining feature data based on inertial sensing data that is generated by sensing the inertial sensing board while a subject walks on the inertial sensing board for one step; and identifying whether the subject is the specific person based on a predetermined threshold, and on a plurality of similarity values each associated with the feature data and a corresponding one of the piece of training feature data and estimated by the gait similarity estimation model.

聯絡資訊
承辦人姓名	李佳玲
承辦人電話	03-5715131 #62300
承辦人Email	cl.lee@mx.nthu.edu.tw