• Title/Summary/Keyword: Biometric Data

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Inferring Pedestrians' Emotional States through Physiological Responses to Measure Subjective Walkability Indices

  • Kim, Taeeun;Lee, Meesung;Hwang, Sungjoo
    • International conference on construction engineering and project management
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    • 2022.06a
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    • pp.1245-1246
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    • 2022
  • Walkability is an indicator of how much pedestrians are willing to walk and how well a walking environment is created. As walking can promote pedestrians' mental and physical health, there has been increasing focus on improving walkability in different ways. Thus, plenty of research has been undertaken to measure walkability. When measuring walkability, there are many objective and subjective variables. Subjective variables include a feeling of safety, pleasure, or comfort, which can significantly affect perceived walkability. However, these subjective factors are difficult to measure by making the walkability index more reliant on objective and physical factors. Because many subjective variables are associated with human emotional states, understanding pedestrians' emotional states provides an opportunity to measure the subjective walkability variables more quantitatively. Pedestrians' emotions can be examined through surveys, but there are social and economic difficulties involved when conducting surveys. Recently, an increasing number of studies have employed physiological data to measure pedestrians' stress responses when navigating unpleasant environmental barriers on their walking paths. However, studies investigating the emotional states of pedestrians in the walking environment, including assessing their positive emotions felt, such as pleasure, have rarely been conducted. Using wearable devices, this study examined the various emotional states of pedestrians affected by the walking environment. Specifically, this study aimed to demonstrate the feasibility of monitoring biometric data, such as electrodermal activity (EDA) and heart rate variability (HRV), using wearable devices as an indicator of pedestrians' emotional states-both pleasant-unpleasant and aroused-relaxed states. To this end, various walking environments with different characteristics were set up to collect and analyze the pedestrians' biometric data. Subsequently, the subjects wearing the wearable devices were allowed to walk on the experimental paths as usual. After the experiment, the valence (i.e., pleasant or unpleasant) and arousal (i.e., activated or relaxed) scale of the pedestrians was identified through a bipolar dimension survey. The survey results were compared with many potentially relevant EDA and HRV signal features. The research results revealed the potential for physiological responses to indicate the pedestrians' emotional states, but further investigation is warranted. The research results were expected to provide a method to measure the subjective factors of walkability by measuring emotions and monitoring pedestrians' positive or negative feelings when walking to improve the walking environment. However, due to the lack of samples and other internal and external factors influencing emotions (which need to be studied further), it cannot be comprehensively concluded that the pedestrians' emotional states were affected by the walking environment.

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Mining Biometric Data to Predict Task Difficulty (생체 데이터를 이용한 프로그래머의 프로그램 난이도 예측)

  • Lee, Seolhwa;Lim, Heuiseok
    • 한국어정보학회:학술대회논문집
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    • 2016.10a
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    • pp.231-234
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    • 2016
  • 프로그래머들이 코딩을 할 때 발생하는 빈번한 실수는 많은 시간적 비용을 낭비할 수 있고 작은 실수가 전체 코드에 치명적인 에러를 유발하기도 한다. 이러한 문제점은 프로그래머들이 코드를 작성할 때 전체적인 알고리즘을 얼마나 잘 이해하는지와 이전 코드에 대한 이해력과 연관이 있다. 만약 코드에 대한 이해가 어렵다면 정교하고 간결한 코드를 작성하는데 무리가 있을 것이다. 기존 코드에 대한 난이도를 평가하는 방법은 자가평가 등을 통해 이루어져 왔다. 사람 내부 변화를 직접 측정하면 더 객관적인 평가가 가능할 것이다. 본 논문은 이런 문제들을 해결하고자 동공 추적이 가능한 아이트래커와 뇌파 측정이 가능한 EEG장비를 이용하여 습득한 생체 데이터를 통해 프로그래머들의 프로그램 난이도 예측 모델을 개발하였다.

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Biometric authentication using fingerprint of overlap data using moiré pattern and multi-fingerprint recognition (무아레 현상을 이용한 지문의 오버랩 데이터와 다중 지문인식을 사용한 생체인증)

  • Park, Eun-Jin;Kang, Hyeok;Jeon, You-Boo;Lee, Keun-Ho
    • Proceedings of the Korea Information Processing Society Conference
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    • 2017.11a
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    • pp.336-338
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    • 2017
  • 지문인식을 통한 생체인증 방식은 스마트 기기의 인증방법들 중 가장 보편화된 인증 방식이다. 하지만 사용자를 구별하는 유일한 인증 방식으로 발전하기에는 완벽한 생체인증 수단이라고 단정 지을 수 없다. 다수의 손가락을 등록함으로 인한 보안성의 하락이나 지문의 손상으로 인한 정확성을 보장할 수 없기 때문이다. 본 논문은 DFS(Display Fingerprint Solution) 기술이 적용된 터치스크린만으로도 지문 인식이 가능한 멀티 핑거 인증 방법 대해 제안한다. 무엇보다 사용자의 복잡한 지문이미지를 획득하고 이를 중첩시킨 후 간섭무늬를 발생시킨 후, 이를 통해 보안 이미지나 무늬를 획득해 사용자를 구별하는 보다 강화된 인증 방식을 제안한다. 본 논문이 제안하고자 하는 방안은 기존의 단순한 지문 이미지 획득보다 고차원적인 데이터를 생성할 수 있는 점을 중심으로 이루어진다.

An EEG Encryption Scheme for Authentication System based on Brain Wave (뇌파 기반의 인증시스템을 위한 EEG 암호화 기법)

  • Kim, Jung-Sook;Chung, Jang-Young
    • Journal of Korea Multimedia Society
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    • v.18 no.3
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    • pp.330-338
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    • 2015
  • Gradually increasing the value of the technology, the techniques of the various security systems to protect the core technology have been developed. The proposed security scheme, which uses both a Password and the various devices, is always open by malicious user. In order to solve that problem, the biometric authentication systems are introduced but they have a problem which is the secondary damage to the user. So, the authentication methods using EEG(Electroencephalography) signals were developed. However, the size of EEG signals is big and it cause a lot of problems for the real-time authentication. And the encryption method is necessary. In this paper, we proposed an efficient real-time authentication system applied encryption scheme with junk data using chaos map on the EEG signals.

Boundary Stitching Algorithm for Fusion of Vein Pattern (정맥패턴 융합을 위한 Boundary Stitching Algorithm)

  • Lim, Young-Kyu;Jang, Kyung-Sik
    • Proceedings of the Korea Information Processing Society Conference
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    • 2005.05a
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    • pp.521-524
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    • 2005
  • This paper proposes a fusion algorithm which merges multiple vein pattern images into a single image, larger than those images. As a preprocessing step of template matching, during the verification of biometric data such as fingerprint image, vein pattern image of hand, etc., the fusion technique is used to make reference image larger than the candidate images in order to enhance the matching performance. In this paper, a new algorithm, called BSA (Boundary Stitching Algorithm) is proposed, in which the boundary rectilinear parts extracted from the candidate images are stitched to the reference image in order to enlarge its matching space. By applying BSA to practical vein pattern verification system, its verification rate was increased by about 10%.

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RFID Tag Protection using Face Feature

  • Park, Sung-Hyun;Rhee, Sang-Burm
    • Journal of the Semiconductor & Display Technology
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    • v.6 no.2 s.19
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    • pp.59-63
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    • 2007
  • Radio Frequency Identification (RFID) is a common term for technologies using micro chips that are able to communicate over short-range radio and that can be used for identifying physical objects. RFID technology already has several application areas and more are being envisioned all the time. While it has the potential of becoming a really ubiquitous part of the information society over time, there are many security and privacy concerns related to RFID that need to be solved. This paper proposes a method which could protect private information and ensure RFID's identification effectively storing face feature information on RFID tag. This method improved linear discriminant analysis has reduced the dimension of feature information which has large size of data. Therefore, face feature information can be stored in small memory field of RFID tag. The proposed algorithm in comparison with other previous methods shows better stability and elevated detection rate and also can be applied to the entrance control management system, digital identification card and others.

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Acquisition Of Biometric Data To Percept Human Emotion (감성 인식을 위한 생체 정보 수집)

  • Whang Se-Hee;Park Chang-Hyun;Sim Kwee-Bo
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2005.04a
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    • pp.353-356
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    • 2005
  • 감성이란 외부의 여러 가지 감각적인 자극에 대해 직관적이고 반사적으로 발생하는 반응이다. 감성에는 희로애락과 같은 다양한 감정이 포함된다. 감성은 개인과 환경의 영향을 받는 동시에 사회$\cdot$문화적인 영향에 의해 달라지는 종합적이고 복합적인 느낌이기 때문에 명확하게 표현하기 어렵다. 개인적인 차이는 있지만 인간의 감정은 다양한 행동이나 신체적 혹은 생리적인 반응으로 표출되기 때문에 이러한 다양한 반응을 이용해서 인간의 감정을 유추할 수 있다. 행동이나 신체적인 표현은 개인과 환경, 사회$\cdot$문화적인 영향에 따라 다양하게 나타나기 때문에 이를 정량화하기에는 힘든 부분이 있다. 반면 감정 상태에 따른 생리적인 반응은 여러 사람들에게서 공통적인 부분을 찾을 수가 있다. 본 논문에서는 감정에 따라 다양하게 나타나는 인간의 생리적인 반응 정토를 측정하고 이들의 공통점에 따라 생리적 반응을 통해 인간의 감정에 유추할 수 있는 공학적 모델을 제시하고자 한다.

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Mining Biometric Data to Predict Task Difficulty (생체 데이터를 이용한 프로그래머의 프로그램 난이도 예측)

  • Lee, Seolhwa;Lim, Heuiseok
    • Annual Conference on Human and Language Technology
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    • 2016.10a
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    • pp.231-234
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    • 2016
  • 프로그래머들이 코딩을 할 때 발생하는 빈번한 실수는 많은 시간적 비용을 낭비할 수 있고 작은 실수가 전체 코드에 치명적인 에러를 유발하기도 한다. 이러한 문제점은 프로그래머들이 코드를 작성할 때 전체적인 알고리즘을 얼마나 잘 이해하는지와 이전 코드에 대한 이해력과 연관이 있다. 만약 코드에 대한 이해가 어렵다면 정교하고 간결한 코드를 작성하는데 무리가 있을 것이다. 기존 코드에 대한 난이도를 평가하는 방법은 자가평가 등을 통해 이루어져 왔다. 사람 내부 변화를 직접 측정하면 더 객관적인 평가가 가능할 것이다. 본 논문은 이런 문제들을 해결하고자 동공 추적이 가능한 아이트래커와 뇌파 측정이 가능한 EEG장비를 이용하여 습득한 생체 데이터를 통해 프로그래머들의 프로그램 난이도 예측 모델을 개발하였다.

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Development of Electrocardiogram Identification Algorithm using SVM classifier (SVM분류기를 이용한 심전도 개인인식 알고리즘 개발)

  • Lee, Sang-Joon;Lee, Myoung-Ho
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.60 no.3
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    • pp.654-661
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    • 2011
  • This paper is about a personal identification algorithm using an ECG that has been studied by a few researchers recently. Previously published algorithm can be classified as two methods. One is the method that analyzes of ECG features and the other is the morphological analysis of ECG. The main characteristic of proposed algorithm can be classified the method of analysis ECG features. Proposed algorithm adopts DSTW(Down Slope Trace Wave) for extracting ECG features, and applies SVM(Support Vector Machine) to training and testing as a classifier algorithm. We choose 18 ECG files from MIT-BIH Normal Sinus Rhythm Database for estimating of algorithm performance. The algorithm extracts 100 heartbeats from each ECG file, and use 40 heartbeats for training and 60 heartbeats for testing. The proposed algorithm shows clearly superior performance in all ECG data, amounting to 93.89% heartbeat recognition rate and 100% ECG recognition rate.

Iris Recognition Using Ridgelets

  • Birgale, Lenina;Kokare, Manesh
    • Journal of Information Processing Systems
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    • v.8 no.3
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    • pp.445-458
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    • 2012
  • Image feature extraction is one of the basic works for biometric analysis. This paper presents the novel concept of application of ridgelets for iris recognition systems. Ridgelet transforms are the combination of Radon transforms and Wavelet transforms. They are suitable for extracting the abundantly present textural data that is in an iris. The technique proposed here uses the ridgelets to form an iris signature and to represent the iris. This paper contributes towards creating an improved iris recognition system. There is a reduction in the feature vector size, which is 1X4 in size. The False Acceptance Rate (FAR) and False Rejection Rate (FRR) were also reduced and the accuracy increased. The proposed method also avoids the iris normalization process that is traditionally used in iris recognition systems. Experimental results indicate that the proposed method achieves an accuracy of 99.82%, 0.1309% FAR, and 0.0434% FRR.