Predicting muscle forces of individuals with hemiparesis following stroke

<p>Abstract</p> <p>Background</p> <p>Functional electrical stimulation (FES) has been used to improve function in individuals with hemiparesis following stroke. An ideal functional electrical stimulation (FES) system needs an accurate mathematical model capable of designing subject and task-specific stimulation patterns. Such a model was previously developed in our laboratory and shown to predict the isometric forces produced by the quadriceps femoris muscles of able-bodied individuals and individuals with spinal cord injury in response to a wide range of clinically relevant stimulation frequencies and patterns. The aim of this study was to test our isometric muscle force model on the quadriceps femoris, ankle dorsiflexor, and ankle plantar-flexor muscles of individuals with post-stroke hemiparesis.</p> <p>Methods</p> <p>Subjects were seated on a force dynamometer and isometric forces were measured in response to a range of stimulation frequencies (10 to 80-Hz) and 3 different patterns. Subject-specific model parameter values were obtained by fitting the measured force responses from 2 stimulation trains. The model parameters thus obtained were then used to obtain predicted forces for a range of frequencies and patterns. Predicted and measured forces were compared using intra-class correlation coefficients, r²values, and model error relative to the physiological error (variability of measured forces).</p> <p>Results</p> <p>Results showed excellent agreement between measured and predicted force-time responses (r²>0.80), peak forces (ICCs>0.84), and force-time integrals (ICCs>0.82) for the quadriceps, dorsiflexor, and plantar-fexor muscles. The <it>model error </it>was within or below the +95% confidence interval of the <it>physiological error </it>for >88% comparisons between measured and predicted forces.</p> <p>Conclusion</p> <p>Our results show that the model has potential to be incorporated as a feed-forward controller for predicting subject-specific stimulation patterns during FES.</p

A Case of Neglected Bilateral Anterior Shoulder Dislocation: A Rare Entity with Unusual Mechanism of Injury

Bilateral shoulder dislocations are rare, and if they occurred, posterior type of dislocations is common. Bilateral anterior shoulder dislocations are very rare and occur due to trauma with unique mechanism of injury. We report a case of unreduced simultaneous bilateral anterior dislocations of shoulder without associated fractures in a forty-year-old man following a unique mechanism of injury; both hands of the patient were pulled from either side. To the best of our knowledge, this unusual mechanism of injury has not been reported in the literature

Prevalence of Severe Anxiety among Elective Caesarean Section Mothers and their Perceived Complications of Anaesthesia in Malaysia

Introduction: Many women experience psychological problems during pregnancy. One of the major psychological problems is anxiety. Pregnancy related anxiety can lead to various negative effects not only on mother’s health, but also on their socio-dynamic factors as well as the infant’s development. Preoperative anxiety among obstetric patients is known to be much higher compared to other surgical patients. Aim: In this study we assessed the prevalence of severe anxiety among elective caesarean section mothers and their perceived complications of anaesthesia in Malaysia. Method: This study was conducted among 280 pregnant women in the obstetrics and gynaecology department in a tertiary hospital in Malaysia. The pregnant women’s level of anxiety was assessed using the 20-item S-anxiety scale, preoperative and postoperative. Results: Pre-operative, out of the 280 respondents, 70 (25%) were classified as having severe anxiety. Among those with previous SVD, 41.7% had severe level of anxiety compared to only 21.2% among those with previous LSCS (p=0.008). At post-operative assessment, 27 (9.6%) were classified as having severe anxiety. Overall, there was a significant reduction in the level of anxiety from pre to post operative (p &lt;0.001). The perceived complications from general anaesthesia were death (34.3%), coma (32.1%) and postoperative pain (30%) and the perceived complications from regional anaesthesia were back pain (27.9%) and paralysis (27.9%). Conclusion: Preoperative anxiety in women undergoing caesarean section is high. Preoperative anxiety should be evaluated for further planning of coping strategies to overcome their anxiety and fear

Development of a mathematical model for predicting electrically elicited quadriceps femoris muscle forces during isovelocity knee joint motion

<p>Abstract</p> <p>Background</p> <p>Direct electrical activation of skeletal muscles of patients with upper motor neuron lesions can restore functional movements, such as standing or walking. Because responses to electrical stimulation are highly nonlinear and time varying, accurate control of muscles to produce functional movements is very difficult. Accurate and predictive mathematical models can facilitate the design of stimulation patterns and control strategies that will produce the desired force and motion. In the present study, we build upon our previous isometric model to capture the effects of constant angular velocity on the forces produced during electrically elicited concentric contractions of healthy human quadriceps femoris muscle. Modelling the isovelocity condition is important because it will enable us to understand how our model behaves under the relatively simple condition of constant velocity and will enable us to better understand the interactions of muscle length, limb velocity, and stimulation pattern on the force produced by the muscle.</p> <p>Methods</p> <p>An additional term was introduced into our previous isometric model to predict the force responses during constant velocity limb motion. Ten healthy subjects were recruited for the study. Using a KinCom dynamometer, isometric and isovelocity force data were collected from the human quadriceps femoris muscle in response to a wide range of stimulation frequencies and patterns. % error, linear regression trend lines, and paired t-tests were used to test how well the model predicted the experimental forces. In addition, sensitivity analysis was performed using Fourier Amplitude Sensitivity Test to obtain a measure of the sensitivity of our model's output to changes in model parameters.</p> <p>Results</p> <p>Percentage RMS errors between modelled and experimental forces determined for each subject at each stimulation pattern and velocity showed that the errors were in general less than 20%. The coefficients of determination between the measured and predicted forces show that the model accounted for ~86% and ~85% of the variances in the measured force-time integrals and peak forces, respectively.</p> <p>Conclusion</p> <p>The range of predictive abilities of the isovelocity model in response to changes in muscle length, velocity, and stimulation frequency for each individual make it ideal for dynamic applications like FES cycling.</p

Genomic-Assisted Enhancement in Stress Tolerance for Productivity Improvement in Sorghum

Sorghum [Sorghum bicolor (L.) Moench], the fifth most important cereal crop in the world after wheat, rice, maize, and barley, is a multipurpose crop widely grown for food, feed, fodder, forage, and fuel, vital to the food security of many of the world’s poorest people living in fragile agroecological zones. Globally, sorghum is grown on ~42 million hectares area in ~100 countries of Africa, Asia, Oceania, and the Americas. Sorghum grain is used mostly as food (~55%), in the form of flat breads and porridges in Asia and Africa, and as feed (~33%) in the Americas. Stover of sorghum is an increasingly important source of dry season fodder for livestock, especially in South Asia. In India, area under sorghum cultivation has been drastically come down to less than one third in the last six decades but with a limited reduction in total production suggesting the high-yield potential of this crop. Sorghum productivity is far lower compared to its genetic potential owing to a limited exploitation of genetic and genomic resources developed in the recent past. Sorghum production is challenged by various abiotic and biotic stresses leading to a significant reduction in yield. Advances in modern genetics and genomics resources and tools could potentially help to further strengthen sorghum production by accelerating the rate of genetic gains and expediting the breeding cycle to develop cultivars with enhanced yield stability under stress. This chapter reviews the advances made in generating the genetic and genomics resources in sorghum and their interventions in improving the yield stability under abiotic and biotic stresses to improve the productivity of this climate-smart cereal

Mapping inequalities in exclusive breastfeeding in low- and middle-income countries, 2000–2018

Exclusive breastfeeding (EBF)—giving infants only breast-milk for the first 6 months of life—is a component of optimal breastfeeding practices effective in preventing child morbidity and mortality. EBF practices are known to vary by population and comparable subnational estimates of prevalence and progress across low- and middle-income countries (LMICs) are required for planning policy and interventions. Here we present a geospatial analysis of EBF prevalence estimates from 2000 to 2018 across 94 LMICs mapped to policy-relevant administrative units (for example, districts), quantify subnational inequalities and their changes over time, and estimate probabilities of meeting the World Health Organization’s Global Nutrition Target (WHO GNT) of ≥70% EBF prevalence by 2030. While six LMICs are projected to meet the WHO GNT of ≥70% EBF prevalence at a national scale, only three are predicted to meet the target in all their district-level units by 2030

Image-based Mangifera Indica Leaf Disease Detection using Transfer Learning for Deep Learning Methods

Mangifera Indica, ordinarily known as mango, comes from a large tree. The leaf of the mango tree has human health benefits; the mango leaf extract is used for curing various diseases, including patients with cancer and diabetes. It also has an anti-oxidant and anti-microbial biological activity. Leaf disease, including fungal disease, is a severe security threat to nourishment and food paramours. Sometimes, it leads to decreased productivity and a huge loss for the farmers. Observing and determining whether a leaf is infected through the naked eye is unreliable and inconsistent. Technology advancement has helped agriculture people in several ways, and deep learning methods are a promising approach to spotting leaf diseases with the best accuracy. A mango leaf disease detection model is developed with the pre-trained model of ResNet18, which is used in transfer learning along with the Fast.ai framework. Around 2000 images were used, including images of healthy and infected leaves. The trained model achieved an accuracy of 99.88% and performed well compared to the existing state-of-the-art methods.Mangifera Indica, ordinarily known as mango, comes from a large tree. The leaf of the mango treehas human health benefits; the mango leaf extract is used for curing various diseases, including patientswith cancer and diabetes. It also has an anti-oxidant and anti-microbial biological activity. Leaf disease,including fungal disease, is a severe security threat to nourishment and food paramours. Sometimes, itleads to decreased productivity and a huge loss for the farmers. Observing and determining whether aleaf is infected through the naked eye is unreliable and inconsistent. Technology advancement has helpedagriculture people in several ways, and deep learning methods are a promising approach to spotting leafdiseases with the best accuracy. A mango leaf disease detection model is developed with the pre-trainedmodel of ResNet18, which is used in transfer learning along with the Fast.ai framework. Around 2000images were used, including images of healthy and infected leaves. The trained model achieved an accuracyof 99.88% and performed well compared to the existing state-of-the-art methods

<span style="font-size:12.0pt;font-family: "Times New Roman";mso-fareast-font-family:"Times New Roman";mso-ansi-language: EN-GB;mso-fareast-language:EN-US;mso-bidi-language:AR-SA" lang="EN-GB">Diethylaminosulfurtrifluoride-catalyzed efficient one-pot three-component aza-Diels-Alder reactions: A facile synthesis of substituted hexahydrofurano[3,2-<i style="mso-bidi-font-style:normal">c</i>]quinolines</span>

553-559The aza-Diels-Alder reactions of anilines in combination with substituted benzaldehydes and electron-rich cyclic alkenes have been investigated. The reactions have been carried out in the presence of catalytic amount of diethylaminosulfurtrifluoride in acetonitrile at room temperature, affording substituted furanoquinolines in 80-95% isolated yields