A Survey Study of the Current Challenges and Opportunities of Deploying the ECG Biometric Authentication Method in IoT and 5G Environments

The environment prototype of the Internet of Things (IoT) has opened the horizon for researchers to utilize such environments in deploying useful new techniques and methods in different fields and areas. The deployment process takes place when numerous IoT devices are utilized in the implementation phase for new techniques and methods. With the wide use of IoT devices in our daily lives in many fields, personal identification is becoming increasingly important for our society. This survey aims to demonstrate various aspects related to the implementation of biometric authentication in healthcare monitoring systems based on acquiring vital ECG signals via designated wearable devices that are compatible with 5G technology. The nature of ECG signals and current ongoing research related to ECG authentication are investigated in this survey along with the factors that may affect the signal acquisition process. In addition, the survey addresses the psycho-physiological factors that pose a challenge to the usage of ECG signals as a biometric trait in biometric authentication systems along with other challenges that must be addressed and resolved in any future related research.

Connected healthcare: Improving patient care using digital health technologies

Now more than ever, traditional healthcare models are being overhauled with digital technologies of Healthcare 4.0 being increasingly adopted. Worldwide, digital devices are improving every stage of the patient care pathway. For one, sensors are being used to monitor patient metrics 24/7, permitting swift diagnosis and interventions. At the treatment stage, 3D printers are currently being investigated for the concept of personalised medicine by allowing patients access to on-demand, customisable therapeutics. Robots are also being explored for treatment, by empowering precision surgery or targeted drug delivery. Within medical logistics, drones are being leveraged to deliver critical treatments to remote areas, collect samples, and even provide emergency aid. To enable seamless integration within healthcare, the Internet of Things technology is being exploited to form closed-loop systems that remotely communicate with one another. This review outlines the most promising healthcare technologies and devices, their strengths, drawbacks, and scopes for clinical adoption

Multimedia sensors embedded in smartphones for ambient assisted living and e-health

The final publication is available at link.springer.com[EN] Nowadays, it is widely extended the use of smartphones to make human life more comfortable. Moreover, there is a special interest on Ambient Assisted Living (AAL) and e-Health applications. The sensor technology is growing and amount of embedded sensors in the smartphones can be very useful for AAL and e-Health. While some sensors like the accelerometer, gyroscope or light sensor are very used in applications such as motion detection or light meter, there are other ones, like the microphone and camera which can be used as multimedia sensors. This paper reviews the published papers focused on showing proposals, designs and deployments of that make use of multimedia sensors for AAL and e-health. We have classified them as a function of their main use. They are the sound gathered by the microphone and image recorded by the camera. We also include a comparative table and analyze the gathered information.Parra-Boronat, L.; Sendra, S.; Jimenez, JM.; Lloret, J. (2016). Multimedia sensors embedded in smartphones for ambient assisted living and e-health. Multimedia Tools and Applications. 75(21):13271-13297. doi:10.1007/s11042-015-2745-8S13271132977521Acampora G, Cook DJ, Rashidi P, Vasilakos AV (2013) A survey on ambient intelligence in healthcare. Proc IEEE 101(12):2470–2494Al-Attas R, Yassine A, Shirmohammadi S (2012) Tele-Medical Applications in Home-Based Health Care. In proceeding of the 2012 I.E. International Conference on Multimedia and Expo Workshops (ICMEW 2012). Jul. 9–13, 2012. Melbourne, Australia. (pp. 441–446)Alemdar H, Ersoy C (2010) Wireless sensor networks for healthcare: a survey. Comput Netw 54(15):2688–2710Alqassim S, Ganesh M, Khoja S, Zaidi M, Aloul F, Sagahyroon A (2012) Sleep apnea monitoring using mobile phones. 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Addressing training data sparsity and interpretability challenges in AI based cellular networks

To meet the diverse and stringent communication requirements for emerging networks use cases, zero-touch arti cial intelligence (AI) based deep automation in cellular networks is envisioned. However, the full potential of AI in cellular networks remains hindered by two key challenges: (i) training data is not as freely available in cellular networks as in other fields where AI has made a profound impact and (ii) current AI models tend to have black box behavior making operators reluctant to entrust the operation of multibillion mission critical networks to a black box AI engine, which allow little insights and discovery of relationships between the configuration and optimization parameters and key performance indicators. This dissertation systematically addresses and proposes solutions to these two key problems faced by emerging networks. A framework towards addressing the training data sparsity challenge in cellular networks is developed, that can assist network operators and researchers in choosing the optimal data enrichment technique for different network scenarios, based on the available information. The framework encompasses classical interpolation techniques, like inverse distance weighted and kriging to more advanced ML-based methods, like transfer learning and generative adversarial networks, several new techniques, such as matrix completion theory and leveraging different types of network geometries, and simulators and testbeds, among others. The proposed framework will lead to more accurate ML models, that rely on sufficient amount of representative training data. Moreover, solutions are proposed to address the data sparsity challenge specifically in Minimization of drive test (MDT) based automation approaches. MDT allows coverage to be estimated at the base station by exploiting measurement reports gathered by the user equipment without the need for drive tests. Thus, MDT is a key enabling feature for data and artificial intelligence driven autonomous operation and optimization in current and emerging cellular networks. However, to date, the utility of MDT feature remains thwarted by issues such as sparsity of user reports and user positioning inaccuracy. For the first time, this dissertation reveals the existence of an optimal bin width for coverage estimation in the presence of inaccurate user positioning, scarcity of user reports and quantization error. The presented framework can enable network operators to configure the bin size for given positioning accuracy and user density that results in the most accurate MDT based coverage estimation. The lack of interpretability in AI-enabled networks is addressed by proposing a first of its kind novel neural network architecture leveraging analytical modeling, domain knowledge, big data and machine learning to turn black box machine learning models into more interpretable models. The proposed approach combines analytical modeling and domain knowledge to custom design machine learning models with the aim of moving towards interpretable machine learning models, that not only require a lesser training time, but can also deal with issues such as sparsity of training data and determination of model hyperparameters. The approach is tested using both simulated data and real data and results show that the proposed approach outperforms existing mathematical models, while also remaining interpretable when compared with black-box ML models. Thus, the proposed approach can be used to derive better mathematical models of complex systems. The findings from this dissertation can help solve the challenges in emerging AI-based cellular networks and thus aid in their design, operation and optimization

Contributory studies to the development, validation and field use of a telemetry system to monitor ventilation and trophic activity in wild Brown Trout

This work was performed as part of a major research project into the evaluation of the ecology of lake dwelling Brown Trout, Salmo trutta L. using ultrasonic biotelemetry techniques. The supplementary research results. leading up to and after the execution of a program of experiments involving the telemetry of feeding and ventilatory rhythms are described: 1. The presence of red (slow) fibres in the adductor mandibulae muscle of Brown Trout was confirmed to be as previously described in the Rainbow Trout, Sälmo gairdneri Richardson and other salmonids. 2. By electromyographic (EMG) and pharmacological means, the red fibres in the a. mandibulae were shown to be active during ventilation and the mosaic fibres comprising the bulk of the muscle were recruited during more dynamic events such as feeding and coughing. Observations were made on the innervation of the red fibres. 3. Comparative investigations made at sea on large deep sea Squaloid and Galeoid sharks (which have a simple adductor muscle like the Trout) showed an identical functional differentiation as obtained in the Trout. 4. The presence of a migratory 'pace setter potential' was found for the first time in Fish. Its use as an indicator of feeding activity by telemetry was rejected on practical grounds. ýýY NO 5. An ultrasonic transmitter was developed to telemeter an analogue of the adductor mandibulae EMG from wild Brown Trout, using a novel electrode design. Four fish were so equipped and released into Airthrey Loch, University of Stirling and tracked for up to 24 hours (following a 24 hr allowance for post-anaesthetic recovery). Feeding and ventilatory periodicity, linear and angular movement patterns and photoperiod were intercorrelated. Angle of turn and subsequent step length were positively correlated and feeding activity was marked by a preference for dextral turning. 'Area restricted searching' and 'area avoided searching' were the probable causes of the movement patterns seen in this and previous investigations at Airthrey Loch. A depth preference and orientation of the fish to topography was demonstrated. Following analysis of the angle of turn and step length data, it was concluded that the larger transmitter package and more severe surgery materially affected the fishes' behaviour relative to data previously obtained at Airthrey Loch using smaller transmitters. 6. Due to difficulties experienced in 5 above due to an unsuspected effect on the a. mandibulae EMG detectable up to 24 hrs post-anaesthesia, a frequency analysis was made of the a. mandibulae EMG of the Brown Trout and several other species. This disclosed that the EMG from red fibres has a frequency spectrum considerably lower than that of 'standard' mammalian muscle. The progressive failure of the EMG transmitter with time was due to a combination of the anaesthetic effect and the frequency spectrum relative to certain design features. (vii, In the light of these observations, subsequent designs of the EMG transmitter were able to take this into account

Advances in Computer Recognition, Image Processing and Communications, Selected Papers from CORES 2021 and IP&C 2021

As almost all human activities have been moved online due to the pandemic, novel robust and efficient approaches and further research have been in higher demand in the field of computer science and telecommunication. Therefore, this (reprint) book contains 13 high-quality papers presenting advancements in theoretical and practical aspects of computer recognition, pattern recognition, image processing and machine learning (shallow and deep), including, in particular, novel implementations of these techniques in the areas of modern telecommunications and cybersecurity

Beet-ing Muscle Dysfunction and Exercise Intolerance in Pulmonary Hypertension

Indiana University-Purdue University Indianapolis (IUPUI)Background: Pulmonary Hypertension (PH) is a devastating disease characterized by pulmonary arterial remodeling, right ventricular dysfunction and ultimately right heart failure. Increased emphasis has been given to skeletal muscle dysfunction in PH, and to its implication in the severe exercise intolerance that is a hallmark of the condition. In this dissertation, skeletal muscle blood flow was measured via the microsphere technique at rest and during exercise (Aim 1), with an acute dose of dietary nitrate via beetroot juice (BRJ) gavage used to determine if supplementation could improve muscle blood flow and alter energetics (Aim 2). VO2max, voluntary running and grip strength tests were used to determine the effect of disease on performance, and to test for an ergogenic effect of BRJ vs. placebo (PL) in healthy and PH rats (Aim 3). Methods: A prospective, randomized, counterbalanced, placebo-controlled trial was used to examine the aforementioned aims across four groups; PH rats (induced with monocrotaline, MCT, 60mg/kg, s.q., 4 weeks) supplemented with BRJ (MCT BRJ, n=9); PH rats supplemented with placebo (MCT PL, n=9); healthy control rats (vehicle, s.q.) supplemented with BRJ (CON BRJ, n=8); healthy control rats supplemented with placebo (CON PL, n=9). Results: Monocrotaline induced a severe PH phenotype evidenced by increased RV wall thickness, RV hypertrophy, RVSP and reduced cardiac output and stroke volume compared to controls (p=<0.001). MCT rats demonstrated lower muscle blood flow at rest, and more prominently during exercise compared to controls (p=0.007-0.047), regardless of supplementation. MCT rats displayed a greater reliance on anaerobic metabolism, demonstrated by increased blood lactate accumulation (p=<0.001), and this was significantly related to reduced blood flow during exercise (r=-0.5879, p=0.001). BRJ supplementation resulted in increased plasma nitrate and nitrite compared to PL (p=<0.001), but at the skeletal muscle level, only nitrate was increased after BRJ. BRJ did not have a significant effect on blood flow, with no improvement during exercise shown vs. PL. Similarly, BRJ did not significantly improve exercise function in MCT or CON rats. Conclusion: MCT rats demonstrated a reduction in muscle blood flow, with BRJ supplementation not resulting in improved flow or exercise performance

Intelligent Circuits and Systems

ICICS-2020 is the third conference initiated by the School of Electronics and Electrical Engineering at Lovely Professional University that explored recent innovations of researchers working for the development of smart and green technologies in the fields of Energy, Electronics, Communications, Computers, and Control. ICICS provides innovators to identify new opportunities for the social and economic benefits of society.　 This conference bridges the gap between academics and R&D institutions, social visionaries, and experts from all strata of society to present their ongoing research activities and foster research relations between them. It provides opportunities for the exchange of new ideas, applications, and experiences in the field of smart technologies and finding global partners for future collaboration. The ICICS-2020 was conducted in two broad categories, Intelligent Circuits & Intelligent Systems and Emerging Technologies in Electrical Engineering

Development and psychometric validation of pain scales in feline osteoarthritis

L’arthrose féline est détectable sur radiographie, surtout chez l’animal âgé. La rareté antérieure du diagnostic clinique s’explique par ses signes subtils et facilement attribués à d’autres maladies gériatriques ou au processus normal de vieillissement. Ces signes répondent néanmoins au traitement analgésique. Le but de ce projet de recherche était de développer et valider deux grilles de douleur arthrosique (Montreal Instruments for Cat Arthritis Testing), une pour les propriétaires de chats [MI-CAT(C)], et une pour les vétérinaires [MI-CAT(V)]. Le développement était fondé sur une revue de la littérature, notre expertise clinique en douleur et en comportement félin, et un sondage de propriétaires de chats arthrosiques. Des experts internes et externes ont confirmé la validité de contenu des grilles. Ensuite, une étude pilote sur chats de laboratoire a permis une évaluation préliminaire de leur fiabilité et validité. Dans le cadre d’un essai clinique chez des chats arthrosiques, la grille pour propriétaires MI-CAT(C) discriminait les groupes placebo et meloxicam, et ses changements de score corrélaient avec l’activité motrice et l’âge, soutenant sa validité. La grille était généralement facile à comprendre, appuyant de façon préliminaire sa validité de face (l’acceptabilité) et son interprétation. La mesure de fiabilité intra- et inter-observateur préconisait l’évaluation par le propriétaire principal vs. un(e) propriétaire secondaire. La grille MI-CAT(C) était homogène, sans redondance, selon l’évaluation préliminaire de la consistance interne. Une seconde évaluation de la grille vétérinaire MI-CAT(V) a été menée chez des chats de laboratoire (avec ou sans arthrose naturelle). L’évaluation de la fiabilité intra- et inter-observateur démontrait une courbe d’apprentissage pour le nouvel utilisateur de la grille. Seules les sous-catégories Gait (démarche) et Posture (allure) avaient une tendance (non-significative) à détecter le statut arthrosique; la palpation et la manipulation des articulations n’avait aucune sensibilité du même genre. Gait et Posture corrélaient avec une mesure objective, la force verticale d’appui au sol. Une analyse vidéo a ensuite été faite pour améliorer la sensibilité de la grille MI-CAT(V) à l’arthrose. La grille révisée a été soumise à des étapes successives de validation et de raffinement, via trois études thérapeutiques (utilisant la gabapentine, le tramadol, et le meloxicam sous forme orale transmuqueuse par vaporisateur). Sa fiabilité intra- et inter-observateur, et l’évaluation préliminaire de la consistance interne étaient bonnes à excellentes, et elle fut capable de détecter le statut arthrosique. Cependant, elle ne détecta pas les effets thérapeutiques démontrés par d’autres mesures objectives. Des recherches ultérieures devront confirmer que la grille pour propriétaires MI-CAT(C) distingue le statut arthrosique, et évaluer sa réponse, vs. placébo, à d’autres traitements que le meloxicam. La grille vétérinaire MI-CAT(V) requerra une confirmation de sa fiabilité et validité chez des chats de propriétaires ; elle nécessitera encore des raffinements pour détecter les effets de traitement. L’établissement de seuils (p. ex. : distinction arthrosique/non-arthrosique, différence minimale significative) pour les deux grilles est conseillé pour faciliter leur utilisation clinique, ainsi qu’une évaluation de leur faisabilité et utilité clinique, ainsi qu’une réévaluation de leur structure interne et de leur compréhension.Radiographic signs of osteoarthritis are prevalent in cats, becoming more common with age. Historically, the rate of diagnosis has tended to be low, suggesting that signs are subtle and/or tend to be attributed to normal age-related changes or to other geriatric diseases. However, cats with osteoarthritis display signs that are responsive to analgesic treatment. This project aimed to develop and validate rating scales for detection and measurement of feline osteoarthritis pain and related disability (the Montreal Instruments for Cat Arthritis Testing). Two such scales, one for use by caretakers/owners [MI-CAT(C)], and one for use by veterinarians [MI-CAT(V)], were developed based on a review of the literature, expert opinion, and a survey study of owners of cats with a diagnosis of osteoarthritis. The content validity (via expert review) was excellent for both scales. A pilot study in a colony of laboratory cats with naturally-occurring osteoarthritis evaluated reliability and ability to detect osteoarthritis status, for both scales; preliminary revisions were made based on the results. The MI-CAT(C) owner scale subsequently underwent validation in a clinical trial of meloxicam in client-owned osteoarthritic cats. Evidence for validity included the ability to distinguish placebo from active treatment, and correlations with objectively measured activity and age. Owners found most scale items clear/easy to understand, preliminarily supporting comprehensibility and face validity (acceptability). Evaluation of intra- and inter-rater reliability suggested that secondary owners varied substantially in their ability to complete the scale, compared to primary owners. A preliminary assessment of internal consistency reliability supported homogeneity, without redundancy, of the scale. The MI-CAT(V) veterinary scale was evaluated in a study of laboratory cats with and without naturally-occurring osteoarthritis. Intra- and inter-rater reliability assessments suggested that a naïve user’s ability to use the scale was influenced by experience with it. The scale was unable to distinguish osteoarthritic and non-osteoarthritic cats, but the subcategories Gait and Posture were somewhat promising based on a non-significant tendency to detect osteoarthritis status, and correlations with an objective measure of osteoarthritis pain, peak vertical force. Palpation of the limbs did not detect osteoarthritis status. A video analysis was performed to increase MI-CAT(V) scale sensitivity to osteoarthritis. Subsequent evaluation and refinements based on three therapeutic trials (involving gabapentin, tramadol, and oral transmucosal meloxicam treatments) in laboratory cats with and without naturally-occurring osteoarthritis resulted in good to excellent intra- and inter-rater reliability, and ability to detect osteoarthritis status. Preliminary evidence supported scale internal consistency. Therapeutic response detected by objective outcome measures was not demonstrable using the scale. It is recommended that the MI-CAT(C) owner scale be evaluated for ability to distinguish osteoarthritic from non-osteoarthritic cats. The MI-CAT(V) veterinary scale requires testing in client-owned cats, and potentially further refinements to permit detection of treatment effects, if it is to be used as more than a disease screening tool. Both scales require additional investigation of internal structure and comprehensibility, and determination of cut-points to guide clinical use (e.g., minimally important difference, and thresholds for classification of cats as osteoarthritic vs. non-osteoarthritic), and evaluation of their feasibility and clinical utility