Biometrics' new identity—measuring more physical and biological traits

Rinaldi, Andrea C.

doi:10.15252/embr.201541677

Cited by 14 publications

(8 citation statements)

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“…Limitations with UPIs and matching algorithms have led to the exploration of other add-on technologies including biometric identification technologies. Such approaches include fingerprints, palm vein scanning, iris scanning, and facial recognition 41 . Biometric identification technologies are advantageous because biometrics data is more difficult to “steal, exchange or forget” 25 .…”

Section: Resultsmentioning

confidence: 99%

Patient Identification Techniques – Approaches, Implications, and Findings

2020

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Objectives: To identify current patient identification techniques and approaches used worldwide in today’s healthcare environment. To identify challenges associated with improper patient identification. Methods: A literature review of relevant peer-reviewed and grey literature published from January 2015 to October 2019 was conducted to inform the paper. The focus was on: 1) patient identification techniques and 2) unintended consequences and ramifications of unresolved patient identification issues. Results: The literature review showed six common patient identification techniques implemented worldwide ranging from unique patient identifiers, algorithmic approaches, referential matching software, biometrics, radio frequency identification device (RFID) systems, and hybrid models. The review revealed three themes associated with unresolved patient identification: 1) treatment, care delivery, and patient safety errors, 2) cost and resource considerations, and 3) data sharing and interoperability challenges. Conclusions: Errors in patient identification have implications for patient care and safety, payment, as well as data sharing and interoperability. Different patient identification techniques ranging from unique patient identifiers and algorithms to hybrid models have been implemented worldwide. However, no current patient identification techniques have resulted in a 100% match rate. Optimizing algorithmic matching through data standardization and referential matching software should be studied further to identify opportunities to enhance patient identification techniques and approaches. Further efforts to improve patient identity management include adoption of patients’ photos at registration, naming conventions, and standardized processes for recording patients’ demographic data attributes.

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Section: Resultsmentioning

confidence: 99%

Patient Identification Techniques – Approaches, Implications, and Findings

2020

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“…photos) or even remotely via technology (e.g. social media) without necessarily gaining the express permission of an individual (Arigbabu et al, 2014; Rinaldi, 2016).…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Al-enabled biometrics in recruiting: Insights from marketers for managers

Esch

Black²,

Franklin

et al. 2020

Australasian Marketing Journal

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Both researchers and practitioners are only in the early stages of examining and understanding the application of artificial intelligence (AI) in terms of marketing themselves as employers or the open jobs they have. AI has the potential to significantly affect how firms reach, identify, attract, and select human capital. We examine factors that can influence a job candidate's intent to complete AI-enabled recruiting processes, especially the influence of a firm's use of biometrics in that process. The results show that (1) social media can increase technology use motivation and AI-enabled recruiting with (2) trendiness as a first stage boundary condition and (3) biometrics as a second stage boundary condition. We contribute to marketing knowledge by identifying that for managers wanting to influence job seekers’ technology use motivation in order to increase their participation in AI-enabled recruiting; they must focus on the indirect effects of trendiness, biometrics, and their social media usage.

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“…The NHS lists patient misidentification as serious patient safety incidents that should not occur. 61 EEG is an important tool for the assessment of brain development in newborns. [62][63][64][65] It has been found that coherent EEG activity during sleep may provide unique insight into maturation processes of brain functional connectivity.…”

Section: Possible Application Areas and Future Workmentioning

confidence: 99%

Feature Extraction with GMDH-Type Neural Networks for EEG-Based Person Identification

Schetinin

Jakaite

Nyah

et al. 2018

Int. J. Neur. Syst.

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The brain activity observed on EEG electrodes is influenced by volume conduction and functional connectivity of a person performing a task. When the task is a biometric test the EEG signals represent the unique "brain print", which is defined by the functional connectivity that is represented by the interactions between electrodes, whilst the conduction components cause trivial correlations. Orthogonalization using autoregressive modeling minimizes the conduction components, and then the residuals are related to features correlated with the functional connectivity. However, the orthogonalization can be unreliable for high-dimensional EEG data. We have found that the dimensionality can be significantly reduced if the baselines required for estimating the residuals can be modeled by using relevant electrodes. In our approach, the required models are learnt by a Group Method of Data Handling (GMDH) algorithm which we have made capable of discovering reliable models from multidimensional EEG data. In our experiments on the EEG-MMI benchmark data which include 109 participants, the proposed method has correctly identified all the subjects and provided a statistically significant ([Formula: see text]) improvement of the identification accuracy. The experiments have shown that the proposed GMDH method can learn new features from multi-electrode EEG data, which are capable to improve the accuracy of biometric identification.

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Biometrics' new identity—measuring more physical and biological traits

Cited by 14 publications

References 10 publications

Patient Identification Techniques – Approaches, Implications, and Findings

Patient Identification Techniques – Approaches, Implications, and Findings

Al-enabled biometrics in recruiting: Insights from marketers for managers

Feature Extraction with GMDH-Type Neural Networks for EEG-Based Person Identification

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