Purpose Lip prints are unique and have potential for use as a human identifier. The purpose of this study was to observe possible cheiloscopy differences of individuals with and without parafunctional oral habits such as smoking, vaping, playing a wind instrument or using an asthma inhaler.Methods This IRB approved blinded cross-sectional observation pilot study collected lip prints from sixty-six individuals, three of which were excluded. Participants cleansed their lips, then lipstick was applied to the vermillion zones of the upper and lower lips. Adhesive tape was applied to the lips and prints were transferred to white bond paper for viewing purposes. Each set of included lip prints was divided into quadrants and dichotomized into a group of those with an oral parafunctional habit or with no such habits. Each quadrant sample was then manually analyzed and classed according to the gold standard Suzuki and Tsuchihashi system.Results A total of 252 dichotomized lip print quadrants (with habits n=76, 30.2%, and without habits n=176, 69.8%) were analyzed. Type II patterns were the most common for examined quadrant samples; however, no statistically significant differences (Pearson\'s chi-squared test, p=0.366) were observed between pattern classifications of samples with and without parafunctional oral habits.Conclusion There is no statistically significant difference of lip print patterns between individuals with and without parafunctional oral habits. Further research on populational variations is needed for cheiloscopy to aid in human identifications.

In low-and middle-income countries, many infants and children remain unregistered in both civil registration and healthcare records, limiting their access to essential rights-based services, including healthcare. A novel biometric registration prototype, applying a non-touch platform using smart phones and tablets to capture physical characteristics of infants and children for electronic registration, was tested in rural Mozambique. This study assessed acceptability and perceived barriers and facilitators to the usability of this biometric registration prototype in Manhiça district, southern Mozambique. The study followed a qualitative design consisting of 5 semi-structured interviews with healthcare providers, 7 focus group discussions with caregivers of infants aged between 0 and 5 years old, and 2 focus group discussions with data collectors involved in the implementation of the biometric registration pilot project. Data were thematically analysed. The results of this study show that there is wide acceptability of the biometric registration prototype among healthcare providers and caregivers. Participants were aware of the benefits of the biometric registration prototype. The perceived benefits included that the biometric registration prototype would solve the inefficiency of paper-based registration, and the perception of biometric registration as \"healthcare norm\". Perceived potential barriers to the implementation of the biometric registration prototype included: myths and taboos, lack of information, lack of time, lack of father\'s consent, and potential workload among healthcare providers. In conclusion, the biometric prototype was widely accepted due to its perceived usefulness. However, there is a need to address the perceived barriers, and involvement of children\'s fathers and/or other relevant family members in the process of biometric registration.

A partnership between the University of Antwerp and the University of Kinshasa implemented the EBOVAC3 clinical trial with an Ebola vaccine regimen administered to health care provider participants in Tshuapa Province, Democratic Republic of the Congo. This randomized controlled trial was part of an Ebola outbreak preparedness initiative financed through Innovative Medicines Initiative-European Union. The EBOVAC3 clinical trial used iris scan technology to identify all health care provider participants enrolled in the vaccine trial, to ensure that the right participant received the right vaccine at the right visit.
We aimed to assess the acceptability, accuracy, and feasibility of iris scan technology as an identification method within a population of health care provider participants in a vaccine trial in a remote setting.
We used a mixed methods study. The acceptability was assessed prior to the trial through 12 focus group discussions (FGDs) and was assessed at enrollment. Feasibility and accuracy research was conducted using a longitudinal trial study design, where iris scanning was compared with the unique study ID card to identify health care provider participants at enrollment and at their follow-up visits.
During the FGDs, health care provider participants were mainly concerned about the iris scan technology causing physical problems to their eyes or exposing them to spiritual problems through sorcery. However, 99% (85/86; 95% CI 97.1-100.0) of health care provider participants in the FGDs agreed to be identified by the iris scan. Also, at enrollment, 99.0% (692/699; 95% CI 98.2-99.7) of health care provider participants accepted to be identified by iris scan. Iris scan technology correctly identified 93.1% (636/683; 95% CI 91.2-95.0) of the participants returning for scheduled follow-up visits. The iris scanning operation lasted 2 minutes or less for 96.0% (656/683; 95% CI 94.6-97.5), and 1 attempt was enough to identify the majority of study participants (475/683, 69.5%; 95% CI 66.1-73.0).
Iris scans are highly acceptable as an identification tool in a clinical trial for health care provider participants in a remote setting. Its operationalization during the trial demonstrated a high level of accuracy that can reliably identify individuals. Iris scanning is found to be feasible in clinical trials but requires a trained operator to reduce the duration and the number of attempts to identify a participant.
ClinicalTrials.gov NCT04186000; https://clinicaltrials.gov/ct2/show/NCT04186000.

BACKGROUND: Rotator cuff injury is the most common cause of shoulder dysfunction. Despite the continuous advancement of surgical techniques, the incidence of re-tearing after rotator cuff repair is still high. The main reason is that it is difficult to reconstruct the normal tendon bone interface and the process is slow, and the application of tissue engineering technology can promote tendon and bone healing. This study will evaluate the effect of the bionic double membrane stent on the rotator cuff healing after arthroscopic rotator cuff repair.
METHODS: This is a prospective randomized controlled trial to study the effect of biomimetic double-layer biofilm stent on rotator cuff healing. Approved by the clinical research ethics committee of our hospital. The patients were randomly divided into 1 of 2 treatment options: (A) a biomimetic double-layer biofilm stent group and (B) a non-bionic dual-layer biofilm stent group. Observation indicators include: visual analog scale score, University of California Los Angeles score, American Shoulder & Elbow Surgeons score and Constant-Murley score. Data were analyzed using the statistical software package SPSS version 16.0 (Chicago, IL).
CONCLUSIONS: This study will evaluate and evaluate the effect of the bionic double-layer membrane stent on the rotator cuff healing after arthroscopic rotator cuff repair. The results of this experiment will provide new treatment ideas for promoting rotator cuff tendon bone healing.
UNASSIGNED: DOI 10.17605/OSF.IO/FWKD6.

The risk of personal data exposure through unauthorized access has never been as imminent as today. To counter this, biometric authentication has been proposed: the use of distinctive physiological and behavioral characteristics as a form of identification and access control. One of the recent developments is electroencephalography (EEG)-based authentication. It builds on the subject-specific nature of brain responses which are difficult to recreate artificially. We propose an authentication system based on EEG signals recorded in response to a simple motor paradigm. Authentication is achieved with a novel two-stage decoder. In the first stage, EEG signal features are extracted using an inception- and a VGG-like deep learning neural network (NN) both of which we compare with principal component analysis (PCA). In the second stage, a support vector machine (SVM) is used for binary classification to authenticate the subject based on the extracted features. All decoders are trained on EEG motor-movement data recorded from 105 subjects. We achieved with the VGG-like NN-SVM decoder a false-acceptance rate (FAR) of 2.55% with an overall accuracy of 88.29%, a FAR of 3.33% with an accuracy of 87.47%, and a FAR of 2.89% with an accuracy of 90.68% for 8, 16, and 64 channels, respectively. With the Inception-like NN-SVM decoder we achieved a false-acceptance rate (FAR) of 4.08% with an overall accuracy of 87.29%, a FAR of 3.53% with an accuracy of 85.31%, and a FAR of 1.27% with an accuracy of 93.40% for 8, 16, and 64 channels, respectively. The PCA-SVM decoder achieved accuracies of 92.09%, 92.36%, and 95.64% with FARs of 2.19%, 2.17%, and 1.26% for 8, 16, and 64 channels, respectively.

With the increasing development of internet, the security of personal information becomes more and more important. Thus, variety of personal recognition methods have been introduced to ensure persons\' information security. Traditional recognition methods such as Personal Identification Number (PIN), or Identification tag (ID) are vulnerable to hackers. Then the biometric technology, which uses the unique physiological characteristics of human body to identify user information has been proposed. But the biometrics widely used at present such as human face, fingerprint, iris, and voice can also be forged and falsified. The biometric with living body features such as electromyography (EMG) signal is a good method to achieve aliveness detection and prevent the spoofing attacks. However, there are few studies on personal recognition based on EMG signal. According to the application context, personal recognition system may operate either in identification mode or verification mode. In the personal identification mode, the system recognizes an individual by searching the templates of all the users in the database for a match. While in the personal verification mode, the system validates a person\'s identity by comparing the captured features with her or his own template(s) stored in the system database. In this paper, both EMG-based personal identification method and EMG-based personal verification method are investigated. First, the Myo armband is placed on the right forearm (specifically, the height of the radiohumeral joint) of 21 subjects to collect the surface EMG signal under hand-open gesture. Then, two different methods are proposed for EMG-based personal identification, i.e., personal identification method based on Discrete Wavelet Transform (DWT) and ExtraTreesClassifier, and personal identification method based on Continuous Wavelet Transform (CWT) and Convolutional Neural Networks (CNN). Experiments with 21 subjects show that the identification accuracy of this two methods can achieve 99.206% and 99.203% respectively. Then based on the identification method using CWT and CNN, transfer learning algorithm is adopted to solve the model update problem when new data is added. Finally, an EMG-based personal verification method using CWT and siamese networks is proposed. Experiments show that the verification accuracy of this method can achieve 99.285%.

In many low and middle-income countries (LMICs), difficulties in patient identification are a major obstacle to the delivery of longitudinal care. In absence of unique identifiers, biometrics have emerged as an attractive solution to the identification problem. We developed an mHealth App for subject identification using pattern recognition around ear morphology (Project SEARCH (Scanning EARS for Child Health). Early field work with the SEARCH App revealed that image stabilization would be required for optimum performance.
To improve image capture, we designed and tested a device (the \'Donut\'), which standardizes distance, angle, rotation and lighting. We then ran an experimental trial with 194 participants to measure the impact of the Donut on identification rates. Images of the participant\'s left ear were taken both with and without use of the Donut, then processed by the SEARCH algorithm, measuring the top one and top ten most likely matches.
With the Donut, the top one identification rate and top ten identification rates were 99.5 and 99.5%, respectively, vs. 38.4 and 24.1%, respectively, without the Donut (P < 0.0001 for each comparison). In sensitivity analyses, crop technique during pre-processing of images had a powerful impact on identification rates, but this too was facilitated through the Donut.
By standardizing lighting, angle and spatial location of the ear, the Donut achieved near perfect identification rates on a cohort of 194 participants, proving the feasibility and effectiveness of using the ear as a biometric identifier.
This study did not include a medical intervention or assess a medical outcome, and therefore did not meet the definition of a human subjects research study as defined by FDAAA. We did not register our study under clinicaltrials.gov .

Palmprints are often encountered on the scene of crime. It can play a key role in sex determination (male or female), which may help in the process of elimination and hence in narrowing down the suspect pool during forensic investigation. In the present study, 300 bilateral palmprints collected from 150 healthy consenting adults (75 males and 75 females) belonging to heterogeneous population of central India were examined. The distance between the palmar tri-radii (deltas) \'a\', \'b\', \'c\', \'d\' to the axial tri-radius \'t\' were studied individually as well as combined. Applying t-test, the results were found to be statistically significant (p < 0.05). Probability densities for men and women derived from the frequency distribution were used to calculate the likelihood ratio and posterior probabilities of sex designation for the given combined abcd-t distance for subjects using Baye\'s theorem. For left as well as right palmprint, a combined distance of ≤30 cm will have a higher probability of belonging to a female donor (p = 0.99) while, a combined distance of ≥32.5 cm will be more indicative of the print belonging to a male donor (p = 0.99).

Every year thousands of migrants die during the endeavour to reach the Italian coasts, making the Mediterranean the theatre of one of the greatest tragedies of mankind. Over 60% of these victims is buried unidentified: one of the reasons behind this is related to the specific difficulties and lack of strategies concerning AM and PM data collection. The present article describes how Italy is trying to face the problem of migrant identification, thanks to the collaboration between government, the Italian national police and universities. In particular, this is the first pilot study carried out to identify the victims of the second greatest tragedy of its kind off the Italian coast, near Lampedusa, on October 3rd 2013, which caused 366 victims. The present article shows the strategies conceived to collect postmortem and especially antemortem data and to compare them to identify matches, using medicolegal, anthropological, odontological and genetic approaches. Thirty-one victims out of 53 missing sought by relatives were identified (58.5%). The type and the quality of antemortem data available, generally photos and videos, pinpoints the importance of the face and the body for identification when the bodies are well preserved and how DNA analyses may at times present difficulties. In fact, critical points emerged concerning especially the lack of genetic information of the populations to which the victims belonged, the number of genetic markers needed to reach a statistical support for the identification and the need to adopt lineage markers such as mitochondrial DNA and Y-chromosome polymorphisms to identify parental relationships. This pilot study however has proven that families continue to seek their relatives and that it is possible, as well as mandatory, to identify migrant victims in spite of the difficulties in the collection of antemortem and postmortem data. In addition, considering the peculiar scenario, novel strategies for positive identification have to be defined in each field (anthropological, odontological and genetic) as well as in combination.

Portable polysomnography is often too complex and encumbering for recording sleep at home. We recorded sleep using a biometric shirt (electrocardiogram sensors, respiratory inductance plethysmography bands and an accelerometer) in 21 healthy young adults recorded in a sleep laboratory for two consecutive nights, together with standard polysomnography. Polysomnographic recordings were scored using standard methods. An algorithm was developed to classify the biometric shirt recordings into rapid eye movement sleep, non-rapid eye movement sleep and wake. The algorithm was based on breathing rate and heart rate variability, body movement, and included a correction for sleep onset and offset. The overall mean percentage of agreement between the two sets of recordings was 77.4%; when non-rapid eye movement and rapid eye movement sleep epochs were grouped together, it increased to 90.8%. The overall kappa coefficient was 0.53. Five of the seven sleep variables were significantly correlated. The findings of this pilot study indicate that this simple portable system could be used to estimate the general sleep pattern of young healthy adults.