Displaying all 11 publications

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  1. Fulltext Ethical challenges of digital health technologies: Aadhaar, India
    Gopichandran V, Ganeshkumar P, Dash S, Ramasamy A
    Bull World Health Organ, 2020 Apr 01;98(4):277-281.
    PMID: 32284652 DOI: 10.2471/BLT.19.237123
    Problem: The proliferation of information and communication technologies in India has enabled the emergence of health-related digital applications, from which important ethical issues arise.

    Approach: The Aadhaar identification system provides each resident in India with a 12-digit unique identification number, linked to demographic and biometric data. Identification by Aadhaar in welfare programmes has the important advantage of ensuring targeted benefits reach the intended recipients.

    Local setting: Some of the major issues faced by the public health sector in India are inadequate funding and inefficient utilization of the funds allocated. The enhancement of currently available digital health records will greatly increase the efficiency of the health care services.

    Relevant changes: The Aadhaar identification system has been linked to several health programmes since 2013. Success was achieved in a programme encouraging pregnant women to undergo delivery at a health facility, as use of Aadhaar number ensured that cash incentives reached the correct recipient. However, interruptions in the treatment of patients with tuberculosis and acquired immunodeficiency syndrome have been reported in other health programmes, due to patients fearing a breach of their confidentiality.

    Lessons learnt: Although the proposed merging of the Aadhaar identification system with digital health care records could enable greater efficiency in monitoring public health and welfare programmes, important ethical issues of privacy and data ownership and use must be considered. In joining the digital revolution, low- and middle-income countries must also develop strict legal regulation to protect data and avoid information technology companies exploiting such databases for profit.

    Matched MeSH terms: Biometric Identification/ethics
  2. Fulltext Estimating body related soft biometric traits in video frames
    Arigbabu OA, Ahmad SM, Adnan WA, Yussof S, Iranmanesh V, Malallah FL
    ScientificWorldJournal, 2014;2014:460973.
    PMID: 25121120 DOI: 10.1155/2014/460973
    Soft biometrics can be used as a prescreening filter, either by using single trait or by combining several traits to aid the performance of recognition systems in an unobtrusive way. In many practical visual surveillance scenarios, facial information becomes difficult to be effectively constructed due to several varying challenges. However, from distance the visual appearance of an object can be efficiently inferred, thereby providing the possibility of estimating body related information. This paper presents an approach for estimating body related soft biometrics; specifically we propose a new approach based on body measurement and artificial neural network for predicting body weight of subjects and incorporate the existing technique on single view metrology for height estimation in videos with low frame rate. Our evaluation on 1120 frame sets of 80 subjects from a newly compiled dataset shows that the mentioned soft biometric information of human subjects can be adequately predicted from set of frames.
    Matched MeSH terms: Biometric Identification/methods*
  3. Person identification in irregular cardiac conditions using electrocardiogram signals
    Sidek KA, Khalil I
    Annu Int Conf IEEE Eng Med Biol Soc, 2011;2011:3772-5.
    PMID: 22255160 DOI: 10.1109/IEMBS.2011.6090644
    This paper presents a person identification mechanism in irregular cardiac conditions using ECG signals. A total of 30 subjects were used in the study from three different public ECG databases containing various abnormal heart conditions from the Paroxysmal Atrial Fibrillation Predicition Challenge database (AFPDB), MIT-BIH Supraventricular Arrthymia database (SVDB) and T-Wave Alternans Challenge database (TWADB). Cross correlation (CC) was used as the biometric matching algorithm with defined threshold values to evaluate the performance. In order to measure the efficiency of this simple yet effective matching algorithm, two biometric performance metrics were used which are false acceptance rate (FAR) and false reject rate (FRR). Our experimentation results suggest that ECG based biometric identification with irregular cardiac condition gives a higher recognition rate of different ECG signals when tested for three different abnormal cardiac databases yielding false acceptance rate (FAR) of 2%, 3% and 2% and false reject rate (FRR) of 1%, 2% and 0% for AFPDB, SVDB and TWADB respectively. These results also indicate the existence of salient biometric characteristics in the ECG morphology within the QRS complex that tends to differentiate individuals.
    Matched MeSH terms: Biometric Identification*
  4. Chemical and Chemometric Methods for Halal Authentication of Gelatin: An Overview
    Hassan N, Ahmad T, Zain NM
    J Food Sci, 2018 Dec;83(12):2903-2911.
    PMID: 30440088 DOI: 10.1111/1750-3841.14370
    The issue of food authenticity has become a concern among religious adherents, particularly Muslims, due to the possible presence of nonhalal ingredients in foods as well as other commercial products. One of the nonhalal ingredients that commonly found in food and pharmaceutical products is gelatin which extracted from porcine source. Bovine and fish gelatin are also becoming the main commercial sources of gelatin. However, unclear information and labeling regarding the actual sources of gelatin in food and pharmaceutical products have become the main concern in halal authenticity issue since porcine consumption is prohibited for Muslims. Hence, numerous analytical methods involving chemical and chemometric analysis have been developed to identify the sources of gelatin. Chemical analysis techniques such as biochemical, chromatography, electrophoretic, and spectroscopic are usually combined with chemometric and mathematical methods such as principal component analysis, cluster, discriminant, and Fourier transform analysis for the gelatin classification. A sample result from Fourier transform infrared spectroscopy analysis, which combines Fourier transform and spectroscopic technique, is included in this paper. This paper presents an overview of chemical and chemometric methods involved in identification of different types of gelatin, which is important for halal authentication purposes.
    Matched MeSH terms: Biometric Identification*
  5. Fulltext Optimal Geometrical Set for Automated Marker Placement to Virtualized Real-Time Facial Emotions
    Maruthapillai V, Murugappan M
    PLoS One, 2016;11(2):e0149003.
    PMID: 26859884 DOI: 10.1371/journal.pone.0149003
    In recent years, real-time face recognition has been a major topic of interest in developing intelligent human-machine interaction systems. Over the past several decades, researchers have proposed different algorithms for facial expression recognition, but there has been little focus on detection in real-time scenarios. The present work proposes a new algorithmic method of automated marker placement used to classify six facial expressions: happiness, sadness, anger, fear, disgust, and surprise. Emotional facial expressions were captured using a webcam, while the proposed algorithm placed a set of eight virtual markers on each subject's face. Facial feature extraction methods, including marker distance (distance between each marker to the center of the face) and change in marker distance (change in distance between the original and new marker positions), were used to extract three statistical features (mean, variance, and root mean square) from the real-time video sequence. The initial position of each marker was subjected to the optical flow algorithm for marker tracking with each emotional facial expression. Finally, the extracted statistical features were mapped into corresponding emotional facial expressions using two simple non-linear classifiers, K-nearest neighbor and probabilistic neural network. The results indicate that the proposed automated marker placement algorithm effectively placed eight virtual markers on each subject's face and gave a maximum mean emotion classification rate of 96.94% using the probabilistic neural network.
    Matched MeSH terms: Biometric Identification/methods*
  6. Fulltext Trusted computing strengthens cloud authentication
    Ghazizadeh E, Zamani M, Ab Manan JL, Alizadeh M
    ScientificWorldJournal, 2014;2014:260187.
    PMID: 24701149 DOI: 10.1155/2014/260187
    Cloud computing is a new generation of technology which is designed to provide the commercial necessities, solve the IT management issues, and run the appropriate applications. Another entry on the list of cloud functions which has been handled internally is Identity Access Management (IAM). Companies encounter IAM as security challenges while adopting more technologies became apparent. Trust Multi-tenancy and trusted computing based on a Trusted Platform Module (TPM) are great technologies for solving the trust and security concerns in the cloud identity environment. Single sign-on (SSO) and OpenID have been released to solve security and privacy problems for cloud identity. This paper proposes the use of trusted computing, Federated Identity Management, and OpenID Web SSO to solve identity theft in the cloud. Besides, this proposed model has been simulated in .Net environment. Security analyzing, simulation, and BLP confidential model are three ways to evaluate and analyze our proposed model.
    Matched MeSH terms: Biometric Identification/standards; Biometric Identification/trends
  7. Fulltext A modified active appearance model based on an adaptive artificial bee colony
    Abdulameer MH, Sheikh Abdullah SN, Othman ZA
    ScientificWorldJournal, 2014;2014:879031.
    PMID: 25165748 DOI: 10.1155/2014/879031
    Active appearance model (AAM) is one of the most popular model-based approaches that have been extensively used to extract features by highly accurate modeling of human faces under various physical and environmental circumstances. However, in such active appearance model, fitting the model with original image is a challenging task. State of the art shows that optimization method is applicable to resolve this problem. However, another common problem is applying optimization. Hence, in this paper we propose an AAM based face recognition technique, which is capable of resolving the fitting problem of AAM by introducing a new adaptive ABC algorithm. The adaptation increases the efficiency of fitting as against the conventional ABC algorithm. We have used three datasets: CASIA dataset, property 2.5D face dataset, and UBIRIS v1 images dataset in our experiments. The results have revealed that the proposed face recognition technique has performed effectively, in terms of accuracy of face recognition.
    Matched MeSH terms: Biometric Identification/methods*
  8. Based Medical Systems for Patient's Authentication: Towards a New Verification Secure Framework Using CIA Standard
    Mohsin AH, Zaidan AA, Zaidan BB, Albahri OS, Albahri AS, Alsalem MA, et al.
    J Med Syst, 2019 May 22;43(7):192.
    PMID: 31115768 DOI: 10.1007/s10916-019-1264-y
    In medical systems for patient's authentication, keeping biometric data secure is a general problem. Many studies have presented various ways of protecting biometric data especially finger vein biometric data. Thus, It is needs to find better ways of securing this data by applying the three principles of information security aforementioned, and creating a robust verification system with high levels of reliability, privacy and security. Moreover, it is very difficult to replace biometric information and any leakage of biometrics information leads to earnest risks for example replay attacks using the robbed biometric data. In this paper presented criticism and analysis to all attempts as revealed in the literature review and discussion the proposes a novel verification secure framework based confidentiality, integrity and availability (CIA) standard in triplex blockchain-particle swarm optimization (PSO)-advanced encryption standard (AES) techniques for medical systems patient's authentication. Three stages are performed on discussion. Firstly, proposes a new hybrid model pattern in order to increase the randomization based on radio frequency identification (RFID) and finger vein biometrics. To achieve this, proposed a new merge algorithm to combine the RFID features and finger vein features in one hybrid and random pattern. Secondly, how the propose verification secure framework are followed the CIA standard for telemedicine authentication by combination of AES encryption technique, blockchain and PSO in steganography technique based on proposed pattern model. Finally, discussed the validation and evaluation of the proposed verification secure framework.
    Matched MeSH terms: Biometric Identification/instrumentation*
  9. Fulltext Authentication and data hiding using a hybrid ROI-based watermarking scheme for DICOM images
    Al-Qershi OM, Khoo BE
    J Digit Imaging, 2011 Feb;24(1):114-25.
    PMID: 19937363 DOI: 10.1007/s10278-009-9253-1
    Authenticating medical images using watermarking techniques has become a very popular area of research, and some works in this area have been reported worldwide recently. Besides authentication, many data-hiding techniques have been proposed to conceal patient's data into medical images aiming to reduce the cost needed to store data and the time needed to transmit data when required. In this paper, we present a new hybrid watermarking scheme for DICOM images. In our scheme, two well-known techniques are combined to gain the advantages of both and fulfill the requirements of authentication and data hiding. The scheme divides the images into two parts, the region of interest (ROI) and the region of non-interest (RONI). Patient's data are embedded into ROI using a reversible technique based on difference expansion, while tamper detection and recovery data are embedded into RONI using a robust technique based on discrete wavelet transform. The experimental results show the ability of hiding patient's data with a very good visual quality, while ROI, the most important area for diagnosis, is retrieved exactly at the receiver side. The scheme also shows some robustness against certain levels of salt and pepper and cropping noise.
    Matched MeSH terms: Biometric Identification
  10. Ergonomics issues in national identity card for homeland security
    Yeow PH, Yuen YY, Loo WH
    Appl Ergon, 2013 Sep;44(5):719-29.
    PMID: 22841592 DOI: 10.1016/j.apergo.2012.04.017
    Ever since the 9/11 terrorist attack, many countries are considering the use of smart national identity card (SNIC) which has the ability to identify terrorists due to its biometric verification function. However, there are many ergonomics issues in the use of SNIC, e.g. card credibility. This research presents a case study survey of Malaysian users. Although most citizens (>96%) own MyKad (Malaysia SNIC), many do not carry it around and use its applications. This defeats one of its main purposes, i.e. combating terrorism. Thus, the research investigates ergonomics issues affecting the citizens' Intention to Use (ITU) MyKad for homeland security by using an extended technology acceptance model. Five hundred questionnaires were collected and analysed using structural equation modelling. Results show that perceived credibility and performance expectancy are the key issues. The findings provide many countries with insights into methods of addressing ergonomics issues and increasing adoption of SNIC for homeland security.
    Matched MeSH terms: Biometric Identification/instrumentation*
  11. Fulltext 22q11.2 deletion syndrome in diverse populations
    Kruszka P, Addissie YA, McGinn DE, Porras AR, Biggs E, Share M, et al.
    Am J Med Genet A, 2017 Apr;173(4):879-888.
    PMID: 28328118 DOI: 10.1002/ajmg.a.38199
    22q11.2 deletion syndrome (22q11.2 DS) is the most common microdeletion syndrome and is underdiagnosed in diverse populations. This syndrome has a variable phenotype and affects multiple systems, making early recognition imperative. In this study, individuals from diverse populations with 22q11.2 DS were evaluated clinically and by facial analysis technology. Clinical information from 106 individuals and images from 101 were collected from individuals with 22q11.2 DS from 11 countries; average age was 11.7 and 47% were male. Individuals were grouped into categories of African descent (African), Asian, and Latin American. We found that the phenotype of 22q11.2 DS varied across population groups. Only two findings, congenital heart disease and learning problems, were found in greater than 50% of participants. When comparing the clinical features of 22q11.2 DS in each population, the proportion of individuals within each clinical category was statistically different except for learning problems and ear anomalies (P 
    Matched MeSH terms: Biometric Identification/methods*
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