Contactless privacy-preserving head movement recognition using deep learning for driver fatigue detection

Head movement holds significant importance in con-veying body language, expressing specific gestures, and reflecting emotional and character aspects. The detection of head movement in smart or assistive driving applications can play an important role in preventing major accidents and potentially saving lives. Additionally, it aids in identifying driver fatigue, a significant contributor to deadly road accidents worldwide. However, most existing head movement detection systems rely on cameras, which raise privacy concerns, face challenges with lighting conditions, and require complex training with long video sequences. This novel privacy-preserving system utilizes UWB-radar technology and leverages Deep Learning (DL) techniques to address the mentioned issues. The system focuses on classifying the five most common head gestures: Head 45L (HL45), Head 45R (HR45), Head 90L (HL90), Head 90R (HR90), and Head Down (HD). By processing the recorded data as spectrograms and leveraging the advanced DL model VGG16, the proposed system accurately detects these head gestures, achieving a maximum classification accuracy of 84.00% across all classes. This study presents a proof of concept for an effective and privacy-conscious approach to head position classification.</p

Wi-fi and radar fusion for head movement sensing through walls leveraging deep learning

The detection of head movement plays a crucial role in human–computer interaction systems. These systems depend on control signals to operate a range of assistive and augmented technologies, including wheelchairs for Quadriplegics, as well as virtual/augmented reality and assistive driving. Driver drowsiness detection and alert systems aided by head movement detection can prevent major accidents and save lives. Wearable devices, such as MagTrack consist of magnetic tags and magnetic eyeglasses clips and are intrusive. Vision-based systems suffer from ambient lighting, line of sight, and privacy issues. Contactless sensing has become an essential part of next-generation sensing and detection technologies. Wi-Fi and radar provide contactless sensing, however, in assistive driving they need to be inside enclosures or dashboards, which for all practical purposes in this article have been considered as through walls. In this study, we propose a contactless system to detect human head movement with and without walls. We used ultra-wideband (UWB) radar and Wi-Fi signals, leveraging machine and deep learning (DL) techniques. Our study analyzes the six common head gestures: right, left, up, and down movements. Time-frequency multiresolution analysis based on wavelet scalograms is used to obtain features from channel state information values, along with spectrograms from radar signals for head movement detection. Feature fusion of both radar and Wi-Fi signals is performed with state-of-the-art DL models. A high classification accuracy of 83.33% and 91.8% is achieved overall with the fusion of VGG16 and InceptionV3 model features trained on radar and Wi-Fi time–frequency maps with and without the walls, respectively

Comparative Neurological and Behavioral Assessment of Central and Peripheral Stimulation Technologies for Induced Pain and Cognitive Tasks

Pain is a multifaceted, multisystem disorder that adversely affects neuro-psychological processes. This study compares the effectiveness of central stimulation (transcranial direct current stimulation—tDCS over F3/F4) and peripheral stimulation (transcutaneous electrical nerve stimulation—TENS over the median nerve) in pain inhibition during a cognitive task in healthy volunteers and to observe potential neuro-cognitive improvements. Eighty healthy participants underwent a comprehensive experimental protocol, including cognitive assessments, the Cold Pressor Test (CPT) for pain induction, and tDCS/TENS administration. EEG recordings were conducted pre- and post-intervention across all conditions. The protocol for this study was categorized into four groups: G1 (control), G2 (TENS), G3 (anodal-tDCS), and G4 (cathodal-tDCS). Paired t-tests (p &lt; 0.05) were conducted to compare Pre-Stage, Post-Stage, and neuromodulation conditions, with t-values providing insights into effect magnitudes. The result showed a reduction in pain intensity with TENS (p = 0.002, t-value = −5.34) and cathodal-tDCS (p = 0.023, t-value = −5.08) and increased pain tolerance with TENS (p = 0.009, t-value = 4.98) and cathodal-tDCS (p = 0.001, t-value = 5.78). Anodal-tDCS (p = 0.041, t-value = 4.86) improved cognitive performance. The EEG analysis revealed distinct neural oscillatory patterns across the groups. Specifically, G2 and G4 showed delta-power reductions, while G3 observed an increase. Moreover, G2 exhibited increased theta-power in the occipital region during CPT and Post-Stages. In the alpha-band, G2, G3, and G4 had reductions Post-Stage, while G1 and G3 increased. Additionally, beta-power increased in the frontal region for G2 and G3, contrasting with a reduction in G4. Furthermore, gamma-power globally increased during CPT1, with G1, G2, and G3 showing reductions Post-Stage, while G4 displayed a global decrease. The findings confirm the efficacy of TENS and tDCS as possible non-drug therapeutic alternatives for cognition with alleviation from pain

Transport time to trauma facilities in Karachi: an exploratory study

Background: Rapid urban growth in developing countries has outpaced the development of health infrastructure, including trauma centers, leading to potential delays in trauma care. This study was conducted in Karachi, a city of 16 million people in Pakistan. Aims: Our aim was to determine the time taken to reach the nearest 24-h emergency care facility (ECF) and the government-designated trauma center (TC). We also sought to determine the availability of supplies and equipment required for basic trauma care at these centers.Methods:We selected five towns in Karachi that had the highest number of road traffic injuries (RTIs) (as identified through medicolegal records). We then measured the time taken to reach the nearest ECF and the government-designated TC from four compass points within each town. We also asked about the equipment and supplies used in basic trauma care.Results: All three TCs in Karachi were located in the selected towns and were within 5.0-10.5 km of each other. The transport times to the 3 TCs were an average of 13.3 min (+/- 7.1) and to the 16 ECFs an average of 4.7 min (+/- 2.4) (p value \u3c 0.00). Most ECFs did not have all equipment and supplies necessary for basic trauma care, 90% had the basic equipment for management of airway, oxygen, and IV fluids, 70% had morphine, and 45% had C-spine collars. Conclusions: Vital time is lost in reaching a government-designated TC. ECFs might be an alternative option, but are not fully equipped and funded to provide adequate trauma care to all

Pushing the limits of remote RF sensing by reading lips under the face mask

The problem of Lip-reading has become an important research challenge in recent years. The goal is to recognise speech from lip movements. Most of the Lip-reading technologies developed so far are camera-based, which require video recording of the target. However, these technologies have well-known limitations of occlusion and ambient lighting with serious privacy concerns. Furthermore, vision-based technologies are not useful for multi-modal hearing aids in the coronavirus (COVID-19) environment, where face masks have become a norm. This paper aims to solve the fundamental limitations of camera-based systems by proposing a radio frequency (RF) based Lip-reading framework, having an ability to read lips under face masks. The framework employs Wi-Fi and radar technologies as enablers of RF sensing based Lip-reading. A dataset comprising of vowels A, E, I, O, U and empty (static/closed lips) is collected using both technologies, with a face mask. The collected data is used to train machine learning (ML) and deep learning (DL) models. A high classification accuracy of 95% is achieved on the Wi-Fi data utilising neural network (NN) models. Moreover, similar accuracy is achieved by VGG16 deep learning model on the collected radar-based dataset

Mortality from gastrointestinal congenital anomalies at 264 hospitals in 74 low-income, middle-income, and high-income countries: a multicentre, international, prospective cohort study

Summary Background Congenital anomalies are the fifth leading cause of mortality in children younger than 5 years globally. Many gastrointestinal congenital anomalies are fatal without timely access to neonatal surgical care, but few studies have been done on these conditions in low-income and middle-income countries (LMICs). We compared outcomes of the seven most common gastrointestinal congenital anomalies in low-income, middle-income, and high-income countries globally, and identified factors associated with mortality. Methods We did a multicentre, international prospective cohort study of patients younger than 16 years, presenting to hospital for the first time with oesophageal atresia, congenital diaphragmatic hernia, intestinal atresia, gastroschisis, exomphalos, anorectal malformation, and Hirschsprung’s disease. Recruitment was of consecutive patients for a minimum of 1 month between October, 2018, and April, 2019. We collected data on patient demographics, clinical status, interventions, and outcomes using the REDCap platform. Patients were followed up for 30 days after primary intervention, or 30 days after admission if they did not receive an intervention. The primary outcome was all-cause, in-hospital mortality for all conditions combined and each condition individually, stratified by country income status. We did a complete case analysis. Findings We included 3849 patients with 3975 study conditions (560 with oesophageal atresia, 448 with congenital diaphragmatic hernia, 681 with intestinal atresia, 453 with gastroschisis, 325 with exomphalos, 991 with anorectal malformation, and 517 with Hirschsprung’s disease) from 264 hospitals (89 in high-income countries, 166 in middleincome countries, and nine in low-income countries) in 74 countries. Of the 3849 patients, 2231 (58·0%) were male. Median gestational age at birth was 38 weeks (IQR 36–39) and median bodyweight at presentation was 2·8 kg (2·3–3·3). Mortality among all patients was 37 (39·8%) of 93 in low-income countries, 583 (20·4%) of 2860 in middle-income countries, and 50 (5·6%) of 896 in high-income countries (p<0·0001 between all country income groups). Gastroschisis had the greatest difference in mortality between country income strata (nine [90·0%] of ten in lowincome countries, 97 [31·9%] of 304 in middle-income countries, and two [1·4%] of 139 in high-income countries; p≤0·0001 between all country income groups). Factors significantly associated with higher mortality for all patients combined included country income status (low-income vs high-income countries, risk ratio 2·78 [95% CI 1·88–4·11], p<0·0001; middle-income vs high-income countries, 2·11 [1·59–2·79], p<0·0001), sepsis at presentation (1·20 [1·04–1·40], p=0·016), higher American Society of Anesthesiologists (ASA) score at primary intervention (ASA 4–5 vs ASA 1–2, 1·82 [1·40–2·35], p<0·0001; ASA 3 vs ASA 1–2, 1·58, [1·30–1·92], p<0·0001]), surgical safety checklist not used (1·39 [1·02–1·90], p=0·035), and ventilation or parenteral nutrition unavailable when needed (ventilation 1·96, [1·41–2·71], p=0·0001; parenteral nutrition 1·35, [1·05–1·74], p=0·018). Administration of parenteral nutrition (0·61, [0·47–0·79], p=0·0002) and use of a peripherally inserted central catheter (0·65 [0·50–0·86], p=0·0024) or percutaneous central line (0·69 [0·48–1·00], p=0·049) were associated with lower mortality. Interpretation Unacceptable differences in mortality exist for gastrointestinal congenital anomalies between lowincome, middle-income, and high-income countries. Improving access to quality neonatal surgical care in LMICs will be vital to achieve Sustainable Development Goal 3.2 of ending preventable deaths in neonates and children younger than 5 years by 2030

Induction de la sénescence endothéliale auriculaire par l'angiotensine II et la thrombine : rôle du stress oxydant et caractérisation du phénotype pro-thrombotique, pro-adhésif, protéolytique et pro-fibrotique

Many studies documented strong relationship between ageing and development of atrial fibrillation (AF). Moreover, it has been found that senescence and senescence-associated- secretory-phenotype play an important role in development of overall atrial inflammation which can ultimately ends up in atrial structural remodeling paving the way to AF perpetuation and maintenance. Moreover, it has been known for decades that AF has been associated with the activation of local and circulating coagulation factors. However, little is known about the impact of coagulation-derived factors, in particular thrombin, on the onset of AF. The aim of the present study was to determine the link between atrial endothelial cells (AECs) senescence and the induction of pro-inflammatory, pro-adhesive, pro-fibrotic and pro-remodelling AECs patterns and also to evaluate the contribution of coagulation derived-factors such as thrombin.De nombreuses études soulignent une relation directe entre la prévalence de la fibrillation auriculaire (FA) et le vieillissement. La senescence cellulaire et le phénotype sécrétoire associé semblent jouer un rôle central dans le développement de l'inflammation auriculaire. Cette inflammation est à l’origine d’un remodelage auriculaire délétère (stress oxydant, fibrose) favorable à la perpétuation et au maintien de la FA. Par ailleurs, il est connu que la FA favorise la coagulation locale et systémique. Cependant, l'impact des facteurs de la coagulation, notamment la thrombine, sur la FA est peu connu. L’objectif de cette étude était de déterminer le lien entre la sénescence des cellules endothéliales atriales et le phénotype pro-inflammatoire et pro-adhésif, la fibrose et le remodelage auriculaire tout en évaluant l’impact de la coagulation, et en particulier le rôle de la thrombine

Induction of atrial endothelial senescence by angiotensin II and thrombin : role of oxidative stress and characterization of pro-thrombotic, pro-adhesive, proteolytic and pro-fibrotic phenotype

De nombreuses études soulignent une relation directe entre la prévalence de la fibrillation auriculaire (FA) et le vieillissement. La senescence cellulaire et le phénotype sécrétoire associé semblent jouer un rôle central dans le développement de l'inflammation auriculaire. Cette inflammation est à l’origine d’un remodelage auriculaire délétère (stress oxydant, fibrose) favorable à la perpétuation et au maintien de la FA. Par ailleurs, il est connu que la FA favorise la coagulation locale et systémique. Cependant, l'impact des facteurs de la coagulation, notamment la thrombine, sur la FA est peu connu. L’objectif de cette étude était de déterminer le lien entre la sénescence des cellules endothéliales atriales et le phénotype pro-inflammatoire et pro-adhésif, la fibrose et le remodelage auriculaire tout en évaluant l’impact de la coagulation, et en particulier le rôle de la thrombine.Many studies documented strong relationship between ageing and development of atrial fibrillation (AF). Moreover, it has been found that senescence and senescence-associated- secretory-phenotype play an important role in development of overall atrial inflammation which can ultimately ends up in atrial structural remodeling paving the way to AF perpetuation and maintenance. Moreover, it has been known for decades that AF has been associated with the activation of local and circulating coagulation factors. However, little is known about the impact of coagulation-derived factors, in particular thrombin, on the onset of AF. The aim of the present study was to determine the link between atrial endothelial cells (AECs) senescence and the induction of pro-inflammatory, pro-adhesive, pro-fibrotic and pro-remodelling AECs patterns and also to evaluate the contribution of coagulation derived-factors such as thrombin

Induction of atrial endothelial senescence by angiotensin II and thrombin : role of oxidative stress and characterization of pro-thrombotic, pro-adhesive, proteolytic and pro-fibrotic phenotype

De nombreuses études soulignent une relation directe entre la prévalence de la fibrillation auriculaire (FA) et le vieillissement. La senescence cellulaire et le phénotype sécrétoire associé semblent jouer un rôle central dans le développement de l'inflammation auriculaire. Cette inflammation est à l’origine d’un remodelage auriculaire délétère (stress oxydant, fibrose) favorable à la perpétuation et au maintien de la FA. Par ailleurs, il est connu que la FA favorise la coagulation locale et systémique. Cependant, l'impact des facteurs de la coagulation, notamment la thrombine, sur la FA est peu connu. L’objectif de cette étude était de déterminer le lien entre la sénescence des cellules endothéliales atriales et le phénotype pro-inflammatoire et pro-adhésif, la fibrose et le remodelage auriculaire tout en évaluant l’impact de la coagulation, et en particulier le rôle de la thrombine.Many studies documented strong relationship between ageing and development of atrial fibrillation (AF). Moreover, it has been found that senescence and senescence-associated- secretory-phenotype play an important role in development of overall atrial inflammation which can ultimately ends up in atrial structural remodeling paving the way to AF perpetuation and maintenance. Moreover, it has been known for decades that AF has been associated with the activation of local and circulating coagulation factors. However, little is known about the impact of coagulation-derived factors, in particular thrombin, on the onset of AF. The aim of the present study was to determine the link between atrial endothelial cells (AECs) senescence and the induction of pro-inflammatory, pro-adhesive, pro-fibrotic and pro-remodelling AECs patterns and also to evaluate the contribution of coagulation derived-factors such as thrombin