• The Journal of Korea Robotics Society
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• v.15 no.3
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• pp.286-292
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• 2020

This paper is about a fall inducement system for guiding like a real fall. Reliable fall data can be used as an essential element in developing effective fall protection devices. We can get this data if the induced fall is very realistic. The proposed system analyzes gait characteristics and determines when to fall based on the pedestrian's biometric data. To estimate the fall inducement time, an active estimation algorithm was proposed using different biometric values for each pedestrian. The proposed algorithm is designed to response actively to the ratio of gait cycle and a stance period. To verify this system, an experimental environment was implemented using a multi-rail treadmill equipped with a ground reaction force measurement device. An experiment was conducted to induce falls to pedestrians using a fall inducement system. By comparing the experimental scene to the video of the actual fall, it has been confirmed that the proposed system can induce a reliable fall.

• ETRI Journal
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• v.45 no.4
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• pp.603-614
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• 2023

Advancements in remote medical technologies and smart devices have led to expectations of contactless rehabilitation. Conventionally, rehabilitation requires clinicians to perform routine muscle function assessments with patients. However, assessment results are difficult to cross-reference owing to the lack of a gold standard. Thus, the application of remote smart rehabilitation systems is significantly hindered. This study analyzes the factors affecting the real-time evaluation of muscle function based on biometric sensor data so that we can provide a basis for a remote system. We acquired real clinical stroke patient data to identify the meaningful features associated with normal and abnormal musculature. We provide a system based on these emerging features that assesses muscle functionality in real time via streamed biometric signal data. A system view based on the amount of data, data processing speed, and feature proportions is provided to support the production of a rudimentary remote smart rehabilitation system.

• Journal of Digital Convergence
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• v.12 no.4
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• pp.319-326
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• 2014

According to the increasing mobile security users who have experienced authentication failure by forgetting passwords, user names, or a response to a knowledge-based question have preference for biological information such as hand geometry, fingerprints, voice in personal identification and authentication. Therefore biometric verification of personal identification and authentication for mobile security provides assurance to both the customer and the seller in the internet. Our study focuses on human hand biometric information recognition system for personal identification and personal Authentication, including its shape, palm features and the lengths and widths of the fingers taken from mobile phone photographs such as iPhone4 and galaxy s2. Our hand biometric information recognition system consists of six steps processing: image acquisition, preprocessing, removing noises, extracting standard hand feature extraction, individual feature pattern extraction, hand biometric information recognition for personal identification and authentication from input images. The validity of the proposed system from mobile phone image is demonstrated through 93.5% of the sucessful recognition rate for 250 experimental data of hand shape images and palm information images from 50 subjects.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.5
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• pp.632-639
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• 2007

This paper presents a wavelet-based watermarking algorithm to securely hide biometric features such as face and fingerprint and effectively extract them with less distortion of the concealed data. To hide the biometric features, we proposed a determination method of insert location based on wavelet transform and adaptive weight method according to the image characteristics. The hidden features are effectively extracted by applying the inverse wavelet transform to the watermarked image. To show the effectiveness, we analyze the various performance such as PSNR and correlation of watermark features before and after applying watermarking. Also, we evaluate the effect of watermaking algorithm with respect to biometric system such as recognition rate. Recognition rate shows 98.67% for multimodal biometric systems consisted of face and fingerprint. From these, we confirm that the proposed method makes it possible to effectively hide and extract the biometric features without lowering recognition rate.

• Journal of KIISE
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• v.42 no.4
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• pp.419-426
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• 2015

This paper proposes a fingerprint verification system on a fuzzy vault with steganography for a smartphone. While biometric-based authentication can provide strong security, the biometric data must be handled carefully as it cannot be re-enrolled when it is revealed to other people. When the transformed data is used for authentication, the original biometric data can be protected. In this paper, we combine a fingerprint verification system with a fuzzy vault scheme to protect the fingerprint data of a smartphone user. In addition, the transformed data using a fuzzy vault scheme increases the security as it is concealed by the steganography scheme. The result of the experiment using fingerprint databases shows that the proposed scheme provides a high level of convenience and security for authentication of a smartphone having with a fingerprint sensor.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.41-43
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• 2022

In order to prevent and block infectious diseases caused by the recent COVID-19 pandemic, non-contact biometric information acquisition and analysis technology is attracting attention. The invasive and attached biometric information acquisition method accurately has the advantage of measuring biometric information, but has a risk of increasing contagious diseases due to the close contact. To solve these problems, the non-contact method of extracting biometric information such as human fingerprints, faces, iris, veins, voice, and signatures with automated devices is increasing in various industries as data processing speed increases and recognition accuracy increases. However, although the accuracy of the non-contact biometric data acquisition technology is improved, the non-contact method is greatly influenced by the surrounding environment of the object to be measured, which is resulting in distortion of measurement information and poor accuracy. In this paper, we propose a context-based bio-signal modeling technique for the interpretation of personalized information (image, signal, etc.) for bio-information analysis. Context-based biometric information modeling techniques present a model that considers contextual and user information in biometric information measurement in order to improve performance. The proposed model analyzes signal information based on the feature probability distribution through context-based signal analysis that can maximize the predicted value probability.

• Journal of Digital Convergence
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• v.11 no.11
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• pp.389-395
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• 2013

As fusing IT and medical technique, the number of patients who adhere medical equipment inside of them is increasing. However there is a problem of for the third person to tap or modulate the patient's biometric data viciously. This paper suggests quantum encryption-based key distribution model to share key for the third person not to tap or modulate the patient's biometric data between patient and hospital staff. The proposed model uses one-time pad key that shares key sending random bits not direct sending message of quantum data. Also, it guarantees patient's anonymity because the biometric data of injected-device in the body doesn't be exposed unnecessarily.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.6
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• pp.1427-1437
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• 2018

While biometric authentication system has been in general use, research is ongoing to apply biometric data to public key infrastructure. It is a significant task to generate a cryptographic key from biometrics in setting up a public key of Bio-PKI. Methods for generating the key by quantization of feature vector can cause data loss and degrade the performance of key extraction. In this paper, we suggest a new method for generating a cryptographic key from classification results of biometric data using multiple classifying models. Our proposal does not cause data loss of feature vector so it showed better performance in key extraction. Also, it uses the multiple models to generate key blocks which produce sufficient length of the key.

• Journal of Internet of Things and Convergence
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• v.7 no.3
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• pp.69-74
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• 2021

With the recent development of biometric authentication technology, the user authentication techniques using biometric authentication are increasing. Various problems arised in certification techniques that use various existing methods such as ID/PW. Therefore, recently, a method of improving security by introducing biometric authentication as secondary authentication has been used. In this thesis, proposal of the user authentication system that can detect user identification and anomalies using ECGs that are extremely difficult to falsify through the electrical biometric signals from the heart among various biometric authentication devices is studied. The system detects user anomalies by comparing ECG data received from a wrist-mounted wearable device-type ECG measurement tool with identification and ECG data stored in blockchain form on the database and identifying the user's location through a beacon system.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.36 no.5
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• pp.83-91
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• 2020

Environmental conditions are known to impact human health and behavior, emotions such as pleasure, anxiety, and depression, and reduce stress. Interior design that elevates emotional comfort and satisfaction can help improve mental health and well-being. This study is a systematic review that analyzed previous empirical studies that explored the effect of interior design elements on the user's emotional response which is quantitatively evaluated by bio-signal and qualitatively evaluated through self-reported questionnaire surveys. This paper aims to derive the attributes of interior design and biometric indicators that affect the user's positive emotion through the synthesis of previous studies and to confirm the feasibility of measuring bio-signals as an objective evaluation tool for architectural design and as a quantitative research method. As a result of the review, the biometric data from EEG, fMRI, ECG, EMG, GSR, and eye-tracking were used to measure the participants' emotional responses, which were manifested as positive or negative depending on certain attributes of interior design such as the form, color, lighting, material and furniture. The attributes of interior design related to the positive emotional response were the curved shape, high ceiling, openness of space, and subdued tone colors. Standard lighting conditions and wooden spaces were related to stress reduction in terms of comfort and relaxation. The free arrangement of furniture was related to the user's positive emotions. On the other hand, consistent experimental protocols could not be found, and although the sample sizes of the studies were small, the studies have demonstrated the feasibility of the emotional response measurement by using the biometric data. Therefore this method can be a useful objective tool in the measurement of human-centric data in architectural design, and to develop the evidence-based design to induce positive emotions and minimize stress.