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1.
Cogn Res Princ Implic ; 7(1): 29, 2022 Apr 01.
Article in English | MEDLINE | ID: covidwho-1785174

ABSTRACT

Previous research has mostly approached face recognition and target identification by focusing on face perception mechanisms, but memory mechanisms also appear to play a role. Here, we examined how the presence of a mask interferes with the memory mechanisms involved in face recognition, focusing on the dynamic interplay between encoding and recognition processes. We approach two known memory effects: (a) matching study and test conditions effects (i.e., by presenting masked and/or unmasked faces) and (b) testing expectation effects (i.e., knowing in advance that a mask could be put on or taken off). Across three experiments using a yes/no recognition paradigm, the presence of a mask was orthogonally manipulated at the study and the test phases. All data showed no evidence of matching effects. In Experiment 1, the presence of masks either at study or test impaired the correct identification of a target. But in Experiments 2 and 3, in which the presence of masks at study or test was manipulated within participants, only masks presented at test-only impaired face identification. In these conditions, test expectations led participants to use similar encoding strategies to process masked and unmasked faces. Across all studies, participants were more liberal (i.e., used a more lenient criterion) when identifying masked faces presented at the test. We discuss these results and propose that to better understand how people may identify a face wearing a mask, researchers should take into account that memory is an active process of discrimination, in which expectations regarding test conditions may induce an encoding strategy that enables overcoming perceptual deficits.


Subject(s)
DiGeorge Syndrome , Facial Recognition , Face , Head , Humans , Recognition, Psychology
2.
Sensors (Basel) ; 22(2)2022 Jan 17.
Article in English | MEDLINE | ID: covidwho-1634795

ABSTRACT

Remote photoplethysmography (rPPG) is a video-based non-contact heart rate measurement technology. It is a fact that most existing rPPG methods fail to deal with the spatiotemporal features of the video, which is significant for the extraction of the rPPG signal. In this paper, we propose a 3D central difference convolutional network (CDCA-rPPGNet) to measure heart rate, with an attention mechanism to combine spatial and temporal features. First, we crop and stitch the region of interest together through facial landmarks. Next, the high-quality regions of interest are fed to CDCA-rPPGNet based on a central difference convolution, which can enhance the spatiotemporal representation and capture rich relevant time contexts by collecting time difference information. In addition, we integrate the attention module into the neural network, aiming to strengthen the ability of the neural network to extract video channels and spatial features, so as to obtain more accurate rPPG signals. In summary, the three main contributions of this paper are as follows: (1) the proposed network base on central difference convolution could better capture the subtle color changes to recover the rPPG signals; (2) the proposed ROI extraction method provides high-quality input to the network; (3) the attention module is used to strengthen the ability of the network to extract features. Extensive experiments are conducted on two public datasets-the PURE dataset and the UBFC-rPPG dataset. In terms of the experiment results, our proposed method achieves 0.46 MAE (bpm), 0.90 RMSE (bpm) and 0.99 R value of Pearson's correlation coefficient on the PURE dataset, and 0.60 MAE (bpm), 1.38 RMSE (bpm) and 0.99 R value of Pearson's correlation coefficient on the UBFC dataset, which proves the effectiveness of our proposed approach.


Subject(s)
Algorithms , Signal Processing, Computer-Assisted , Face , Heart Rate , Photoplethysmography
3.
J Laryngol Otol ; 136(3): 197-207, 2022 Mar.
Article in English | MEDLINE | ID: covidwho-1586114

ABSTRACT

OBJECTIVES: The coronavirus disease 2019 pandemic has led to a need for alternative teaching methods in facial plastics. This systematic review aimed to identify facial plastics simulation models, and assess their validity and efficacy as training tools. METHODS: Literature searches were performed. The Beckman scale was used for validity. The McGaghie Modified Translational Outcomes of Simulation-Based Mastery Learning score was used to evaluate effectiveness. RESULTS: Overall, 29 studies were selected. These simulated local skin flaps (n = 9), microtia frameworks (n = 5), pinnaplasty (n = 1), facial nerve anastomosis (n = 1), oculoplastic procedures (n = 5), and endoscopic septoplasty and septorhinoplasty simulators (n = 10). Of these models, 14 were deemed to be high-fidelity, 13 low-fidelity and 2 mixed-fidelity. None of the studies published common outcome measures. CONCLUSION: Simulators in facial plastic surgical training are important. These models may have some training benefits, but most could benefit from further assessment of validity.


Subject(s)
Models, Anatomic , Reconstructive Surgical Procedures/education , Simulation Training , Face , Humans
4.
Sci Rep ; 11(1): 24183, 2021 12 17.
Article in English | MEDLINE | ID: covidwho-1585792

ABSTRACT

COVID-19 has restricted singing in communal worship. We sought to understand variations in droplet transmission and the impact of wearing face masks. Using rapid laser planar imaging, we measured droplets while participants exhaled, said 'hello' or 'snake', sang a note or 'Happy Birthday', with and without surgical face masks. We measured mean velocity magnitude (MVM), time averaged droplet number (TADN) and maximum droplet number (MDN). Multilevel regression models were used. In 20 participants, sound intensity was 71 dB for speaking and 85 dB for singing (p < 0.001). MVM was similar for all tasks with no clear hierarchy between vocal tasks or people and > 85% reduction wearing face masks. Droplet transmission varied widely, particularly for singing. Masks decreased TADN by 99% (p < 0.001) and MDN by 98% (p < 0.001) for singing and 86-97% for other tasks. Masks reduced variance by up to 48%. When wearing a mask, neither singing task transmitted more droplets than exhaling. In conclusion, wide variation exists for droplet production. This significantly reduced when wearing face masks. Singing during religious worship wearing a face mask appears as safe as exhaling or talking. This has implications for UK public health guidance during the COVID-19 pandemic.


Subject(s)
COVID-19/transmission , Disease Transmission, Infectious/prevention & control , Face , Masks , Singing/physiology , Adult , COVID-19/epidemiology , COVID-19/virology , Cross-Sectional Studies , Exhalation/physiology , Female , Humans , Male , Pandemics/prevention & control , Risk Factors , SARS-CoV-2/physiology , Virus Shedding/physiology
5.
PLoS One ; 16(3): e0247575, 2021.
Article in English | MEDLINE | ID: covidwho-1573727

ABSTRACT

INTRODUCTION: The COVID-19 pandemic has led to widespread shortages of N95 respirators and other personal protective equipment (PPE). An effective, reusable, locally-manufactured respirator can mitigate this problem. We describe the development, manufacture, and preliminary testing of an open-hardware-licensed device, the "simple silicone mask" (SSM). METHODS: A multidisciplinary team developed a reusable silicone half facepiece respirator over 9 prototype iterations. The manufacturing process consisted of 3D printing and silicone casting. Prototypes were assessed for comfort and breathability. Filtration was assessed by user seal checks and quantitative fit-testing according to CSA Z94.4-18. RESULTS: The respirator originally included a cartridge for holding filter material; this was modified to connect to standard heat-moisture exchange (HME) filters (N95 or greater) after the cartridge showed poor filtration performance due to flow acceleration around the filter edges, which was exacerbated by high filter resistance. All 8 HME-based iterations provided an adequate seal by user seal checks and achieved a pass rate of 87.5% (N = 8) on quantitative testing, with all failures occurring in the first iteration. The overall median fit-factor was 1662 (100 = pass). Estimated unit cost for a production run of 1000 using distributed manufacturing techniques is CAD $15 in materials and 20 minutes of labor. CONCLUSION: Small-scale manufacturing of an effective, reusable N95 respirator during a pandemic is feasible and cost-effective. Required quantities of reusables are more predictable and less vulnerable to supply chain disruption than disposables. With further evaluation, such devices may be an alternative to disposable respirators during public health emergencies. The respirator described above is an investigational device and requires further evaluation and regulatory requirements before clinical deployment. The authors and affiliates do not endorse the use of this device at present.


Subject(s)
COVID-19/prevention & control , Equipment Design/instrumentation , Filtration/instrumentation , Pandemics/prevention & control , Personal Protective Equipment , Respiratory Protective Devices , Ventilators, Mechanical , Equipment Reuse , Face , Humans , Materials Testing/instrumentation , N95 Respirators , Occupational Exposure/prevention & control , Printing, Three-Dimensional/instrumentation , SARS-CoV-2/pathogenicity
6.
Appl Physiol Nutr Metab ; 46(7): 753-762, 2021 Jul.
Article in English | MEDLINE | ID: covidwho-1571437

ABSTRACT

We sought to determine the impact of wearing cloth or surgical masks on the cardiopulmonary responses to moderate-intensity exercise. Twelve subjects (n = 5 females) completed three, 8-min cycling trials while breathing through a non-rebreathing valve (laboratory control), cloth, or surgical mask. Heart rate (HR), oxyhemoglobin saturation (SpO2), breathing frequency, mouth pressure, partial pressure of end-tidal carbon dioxide (PetCO2) and oxygen (PetO2), dyspnea were measured throughout exercise. A subset of n = 6 subjects completed an additional exercise bout without a mask (ecological control). There were no differences in breathing frequency, HR or SpO2 across conditions (all p > 0.05). Compared with the laboratory control (4.7 ± 0.9 cmH2O [mean ± SD]), mouth pressure swings were smaller with the surgical mask (0.9 ± 0.7; p < 0.0001), but similar with the cloth mask (3.6 ± 4.8 cmH2O; p = 0.66). Wearing a cloth mask decreased PetO2 (-3.5 ± 3.7 mm Hg) and increased PetCO2 (+2.0 ± 1.3 mm Hg) relative to the ecological control (both p < 0.05). There were no differences in end-tidal gases between mask conditions and laboratory control (both p > 0.05). Dyspnea was similar between the control conditions and the surgical mask (p > 0.05) but was greater with the cloth mask compared with laboratory (+0.9 ± 1.2) and ecological (+1.5 ± 1.3) control conditions (both p < 0.05). Wearing a mask during short-term moderate-intensity exercise may increase dyspnea but has minimal impact on the cardiopulmonary response. Novelty: Wearing surgical or cloth masks during exercise has no impact on breathing frequency, tidal volume, oxygenation, and heart rate However, there are some changes in inspired and expired gas fractions that are physiologically irrelevant. In young healthy individuals, wearing surgical or cloth masks during submaximal exercise has few physiological consequences.


Subject(s)
Exercise/physiology , Heart Rate , Masks , Oxyhemoglobins/metabolism , Respiratory Rate , Adult , COVID-19/prevention & control , Carbon Dioxide/physiology , Dyspnea/physiopathology , Equipment Design , Exercise Test , Face , Female , Humans , Male , Mouth/physiology , Oxygen/physiology , Partial Pressure , Pressure , Skin Temperature , Tidal Volume , Young Adult
9.
Sci Rep ; 11(1): 21449, 2021 11 02.
Article in English | MEDLINE | ID: covidwho-1500502

ABSTRACT

The World Health Organisation has called for a 40% increase in personal protective equipment manufacturing worldwide, recognising that frontline workers need effective protection during the COVID-19 pandemic. Current devices suffer from high fit-failure rates leaving significant proportions of users exposed to risk of viral infection. Driven by non-contact, portable, and widely available 3D scanning technologies, a workflow is presented whereby a user's face is rapidly categorised using relevant facial parameters. Device design is then directed down either a semi-customised or fully-customised route. Semi-customised designs use the extracted eye-to-chin distance to categorise users in to pre-determined size brackets established via a cohort of 200 participants encompassing 87.5% of the cohort. The user's nasal profile is approximated to a Gaussian curve to further refine the selection in to one of three subsets. Flexible silicone provides the facial interface accommodating minor mismatches between true nasal profile and the approximation, maintaining a good seal in this challenging region. Critically, users with outlying facial parameters are flagged for the fully-customised route whereby the silicone interface is mapped to 3D scan data. These two approaches allow for large scale manufacture of a limited number of design variations, currently nine through the semi-customised approach, whilst ensuring effective device fit. Furthermore, labour-intensive fully-customised designs are targeted as those users who will most greatly benefit. By encompassing both approaches, the presented workflow balances manufacturing scale-up feasibility with the diverse range of users to provide well-fitting devices as widely as possible. Novel flow visualisation on a model face is presented alongside qualitative fit-testing of prototype devices to support the workflow methodology.


Subject(s)
Face/physiology , Personal Protective Equipment , Photogrammetry/methods , COVID-19/prevention & control , COVID-19/virology , Computer-Aided Design , Equipment Design , Face/anatomy & histology , Humans , Printing, Three-Dimensional , SARS-CoV-2/isolation & purification
10.
Facial Plast Surg ; 37(5): 688-690, 2021 Oct.
Article in English | MEDLINE | ID: covidwho-1462057
11.
Sensors (Basel) ; 21(19)2021 Sep 30.
Article in English | MEDLINE | ID: covidwho-1444303

ABSTRACT

Frequent spontaneous facial self-touches, predominantly during outbreaks, have the theoretical potential to be a mechanism of contracting and transmitting diseases. Despite the recent advent of vaccines, behavioral approaches remain an integral part of reducing the spread of COVID-19 and other respiratory illnesses. The aim of this study was to utilize the functionality and the spread of smartwatches to develop a smartwatch application to identify motion signatures that are mapped accurately to face touching. Participants (n = 10, five women, aged 20-83) performed 10 physical activities classified into face touching (FT) and non-face touching (NFT) categories in a standardized laboratory setting. We developed a smartwatch application on Samsung Galaxy Watch to collect raw accelerometer data from participants. Data features were extracted from consecutive non-overlapping windows varying from 2 to 16 s. We examined the performance of state-of-the-art machine learning methods on face-touching movement recognition (FT vs. NFT) and individual activity recognition (IAR): logistic regression, support vector machine, decision trees, and random forest. While all machine learning models were accurate in recognizing FT categories, logistic regression achieved the best performance across all metrics (accuracy: 0.93 ± 0.08, recall: 0.89 ± 0.16, precision: 0.93 ± 0.08, F1-score: 0.90 ± 0.11, AUC: 0.95 ± 0.07) at the window size of 5 s. IAR models resulted in lower performance, where the random forest classifier achieved the best performance across all metrics (accuracy: 0.70 ± 0.14, recall: 0.70 ± 0.14, precision: 0.70 ± 0.16, F1-score: 0.67 ± 0.15) at the window size of 9 s. In conclusion, wearable devices, powered by machine learning, are effective in detecting facial touches. This is highly significant during respiratory infection outbreaks as it has the potential to limit face touching as a transmission vector.


Subject(s)
COVID-19 , Face , Female , Humans , Machine Learning , SARS-CoV-2 , Support Vector Machine
12.
Acta Biomed ; 92(4): e2021379, 2021 09 02.
Article in English | MEDLINE | ID: covidwho-1395636

ABSTRACT

NA.


Subject(s)
COVID-19 Vaccines , COVID-19 , Face , Humans , SARS-CoV-2 , Vaccination
14.
IEEE Trans Image Process ; 30: 7636-7648, 2021.
Article in English | MEDLINE | ID: covidwho-1381078

ABSTRACT

Convolutional neural networks are capable of extracting powerful representations for face recognition. However, they tend to suffer from poor generalization due to imbalanced data distributions where a small number of classes are over-represented (e.g. frontal or non-occluded faces) and some of the remaining rarely appear (e.g. profile or heavily occluded faces). This is the reason why the performance is dramatically degraded in minority classes. For example, this issue is serious for recognizing masked faces in the scenario of ongoing pandemic of the COVID-19. In this work, we propose an Attention Augmented Network, called AAN-Face, to handle this issue. First, an attention erasing (AE) scheme is proposed to randomly erase units in attention maps. This well prepares models towards occlusions or pose variations. Second, an attention center loss (ACL) is proposed to learn a center for each attention map, so that the same attention map focuses on the same facial part. Consequently, discriminative facial regions are emphasized, while useless or noisy ones are suppressed. Third, the AE and the ACL are incorporated to form the AAN-Face. Since the discriminative parts are randomly removed by the AE, the ACL is encouraged to learn different attention centers, leading to the localization of diverse and complementary facial parts. Comprehensive experiments on various test datasets, especially on masked faces, demonstrate that our AAN-Face models outperform the state-of-the-art methods, showing the importance and effectiveness.


Subject(s)
Automated Facial Recognition/methods , Face/anatomy & histology , Image Processing, Computer-Assisted/methods , Neural Networks, Computer , COVID-19 , Humans , Masks
16.
Indian J Ophthalmol ; 69(9): 2554, 2021 09.
Article in English | MEDLINE | ID: covidwho-1371002

Subject(s)
COVID-19 , Neurology , Eye , Face , Humans , SARS-CoV-2
17.
Sci Rep ; 11(1): 16248, 2021 08 10.
Article in English | MEDLINE | ID: covidwho-1351978

ABSTRACT

The use of close-fitting PPE is essential to prevent exposure to dispersed airborne matter, including the COVID-19 virus. The current pandemic has increased pressure on healthcare systems around the world, leading to medical professionals using high-grade PPE for prolonged durations, resulting in device-induced skin injuries. This study focuses on computationally improving the interaction between skin and PPE to reduce the likelihood of discomfort and tissue damage. A finite element model is developed to simulate the movement of PPE against the face during day-to-day tasks. Due to limited available data on skin characteristics and how these vary interpersonally between sexes, races and ages, the main objective of this study was to establish the effects and trends that mask modifications have on the resulting subsurface strain energy density distribution in the skin. These modifications include the material, geometric and interfacial properties. Overall, the results show that skin injury can be reduced by using softer mask materials, whilst friction against the skin should be minimised, e.g. through use of micro-textures, humidity control and topical creams. Furthermore, the contact area between the mask and skin should be maximised, whilst the use of soft materials with incompressible behaviour (e.g. many elastomers) should be avoided.


Subject(s)
Computer Simulation , Masks/adverse effects , Skin Diseases/prevention & control , Face/anatomy & histology , Finite Element Analysis , Friction , Humans , Masks/standards , Skin Diseases/etiology , Skin Physiological Phenomena , User-Centered Design
18.
J Palliat Med ; 24(8): 1252, 2021 08.
Article in English | MEDLINE | ID: covidwho-1343602

Subject(s)
Face , Humans
19.
BMJ Case Rep ; 14(7)2021 Jul 12.
Article in English | MEDLINE | ID: covidwho-1307883

ABSTRACT

Neonatal Schwartz-Jampel syndrome type II is a rare and severe form of genetic disorder. Different from the classical appearance in infancy, neonatal presentation involves respiratory and feeding difficulties, along with characteristic pursed appearance of the mouth, myotonia, skeletal dysplasia and severe fatal hyperthermia. The clinical spectrum of this syndrome is so wide that it easily baffles with more common differentials. In this case report, a neonate born to third-degree consanguineous marriage with previous two abortions presented with respiratory difficulty, severe hyperthermia and feeding difficulty, which were daunting challenges to manage due to being refractory to standard line of management. Severe myotonia and gross dysmorphism were challenging dots to connect. Targeted exome sequencing was a ray of hope, which revealed homozygous mutation in the leukaemia inhibitory factor receptor gene on chromosome 5p13, confirming the genetic diagnosis for a fairly common spectrum of symptoms. The neonate later developed pneumoperitoneum and succumbed to underlying severe neonatal illness.


Subject(s)
Osteochondrodysplasias , Consanguinity , Face , Female , Humans , Infant, Newborn , Muscle Hypertonia/diagnosis , Muscle Hypertonia/genetics , Mutation , Osteochondrodysplasias/complications , Osteochondrodysplasias/diagnosis , Osteochondrodysplasias/genetics , Pregnancy
20.
J Emerg Med ; 61(4): 447-448, 2021 10.
Article in English | MEDLINE | ID: covidwho-1283434

Subject(s)
Face , Head , Humans
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