目前可當作身份認證的生物特徵有很多，本論文以三維空中手寫簽名與肌肉訊號當作個人辨識特徵，資料獲取方式為自製慣性感應器穿戴裝置，裝置於手指部位獲取手指姿態，並使用 Thalmic labs 的 MYO Armband 取得手臂肌肉訊號與手臂姿態，利用三點定位的方式，計算三維空中手寫軌跡作為部分手寫特徵，最後使用循環神經網路訓練身份認證系統。 ;We have lived in a digital life nowadays. We cannot live without computers, smart phone and other information products in our daily life. Those traditional confidentiality and authentication methods, for example cryptographic keys, is too old to cope with the new problems in recent years. Currently, some authentication methods based on biological behavioral characteristics have been widely accepted. Such certification procedures find a new way to help the traditional cryptographic keys which would be copied and forgotten easily.
There are many methods for biometric characteristics. The proposed method uses handwritten signals in a 3D coordinate space and EMG signals as personal identification features. We use an IMU wearable device which is made by ourselves and equiped on fingers to get the pose signals of fingers. Then, we use MYO Armband from Thalmic labs to get EMG and Arm altitude signals and use three-points fix method to calculate handwritten trajetory as part of the features. Finally, we use recurrent neural network with LSTM to train the authentication system.
