GR-29 Wrist Intent Recognition for Stroke Rehabilitation

Abstract Hand mentor robotic device is beneficial for stroke patients . This is rehabilitation technique used in stroke therapy. It strengthens and improves the range of motion which ultimately improves the quality of life for severely impaired stroke patients. It is easy to use without assistance and most importantly stroke survivors able to use independently. Usage of hand mentor device is quite expensive for stroke patients on hourly basis . Coming up with most efficient deep learning algorithm for sensor data is motivation to cut down the cost and easy availability usage for stroke patients. EMG signal is recorded using relevant sensors which provides useful information to infer muscle movement. In this study, we utilized publicly available EMG signal datasets recorded from upper limb of human subjects to develop a neural network based model for the prediction of wrist motion intention. Research Question or Motivation The Motivation of this study is to train a simple neural network model to accurately predict three basic wrist motions (extension, flexion and no motion) using optimum number of EMG sensors. This model can be further deployed to augment the capabilities of commercially available robotic-assistive rehabilitation devices. Materials and Methods Sensor-based continuous hand gesture recognition activity requires profound knowledge about gesture activities from multitudes of low-level sensor readings. There are two ways to provide the solutions either to go by handcrafted features from sensor data or use deep learning techniques. The advantage of using deep learning technique is to utilize the automatic high-level feature extraction with outstanding performance. However, sensor data requires signal pre-or post-processing such as feature selection, dimension reduction, denoising, etc. Based on the literature review of many research papers, we found that 1D Convolutional Neural Network have recently become the state-of-the-art technique for crucial signal processing applications. 1D CNN is very effective when we aim to extract features from fixed-length segments of the overall dataset and where the location of the feature within the segment is not of high relevance. In addition to this, real-time and low-cost hardware implementation is feasible using 1D CNN. After a successful literature review on 1D CNN knowing its advantages and benefits of using over signal. We decided to use 1D CNN on raw EMG signal data. Preliminary results: Since it is an application-based project, we planned to work in phases to achieve the long-term goal of benefitting stroke patients using deep learning techniques. In this initial phase of the study, we utilized publicly available EMG dataset for hand gestures from UCI Machine Learning Repository to test the performance of the 1D CNN algorithm on gesture classification. We used only 3 labels (hand at rest, wrist flexion, wrist extension) out of 8 labels in the dataset for our particular application requirement. This dataset contains 8 EMG channels collected from commercial MYO Thalmic bracelet device. We first performed an initial analysis to investigate the optimum number of sensor/channels based on the highest gesture classification accuracy using KNN, Decision Tree and Naïve Bayes algorithms. As a result of this analysis, we obtained the optimum channel combination (Ch1, Ch4, Ch5, Ch8) data which generates the best classification accuracy. We used these 4 sensor datasets to train a 1D CNN with 78/22 train/test split. Dataset contains total 36 subjects. Data with subject number less than or equal to 28 is considered as training set and data with subject number greater than 28 is considered as test set. We also performed an optimization study on finding the optimum time signal window and overlap sizes of 100 ms and 50 ms . We achieved test accuracy of 97% for the classification accuracy of 3 gestures (hand at rest, wrist flexion, wrist extension).Advisors(s): Supervisor : Dr. Coskun Tekes Email id : [email protected](s): Artificial IntelligenceCS799

Understanding the degeneracies in NOν\nuA data

The combined analysis of $\nu_\mu$ disappearance and $\nu_e$ appearance data of NO$\nu$A experiment leads to three nearly degenerate solutions. This degeneracy can be understood in terms of deviations in $\nu_e$ appearance signal, caused by unknown effects, with respect to the signal expected for a reference set of oscillations parameters. We define the reference set to be vacuum oscillations in the limit of maximal $\theta_{23}$ and no CP-violation. We then calculate the deviations induced in the $\nu_e$ appearance signal event rate by three unknown effects: (a) matter effects, due to normal or inverted hierarchy (b) octant effects, due to $\theta_{23}$ being in higher or lower octant and (c) CP-violation, whether $\delta_{CP} \sim - \pi/2$ or $\delta_{CP} \sim \pi/2$. We find that the deviation caused by each of these effects is the same for NO$\nu$A. The observed number of $\nu_e$ events in NO$\nu$A is equivalent to the increase caused by one of the effects. Therefore, the observed number of $\nu_e$ appearance events of NO$\nu$A is the net result of the increase caused by two of the unknown effects and the decrease caused by the third. Thus we get the three degenerate solutions. We also find that further data by NO$\nu$A can not distinguish between these degenerate solutions but addition of one year of neutrino run of DUNE can make a distinction between all three solutions. The distinction between the two NH solutions and the IH solution becomes possible because of the larger matter effect in DUNE. The distinction between the two NH solutions with different octants is a result of the synergy between the anti-neutrino data of NO$\nu$A and the neutrino data of DUNE.Comment: Published version v2; with minor changes to v

Tensions between the appearance data of T2K and NOvA

The long baseline neutrino experiments, T2K and NOvA, have taken significant amount of data in each of the four channels: (a) $\nu_\mu$ disappearance, (b) $\bar\nu_\mu$ disappearance (c) $\nu_e$ appearance and (d) $\bar\nu_e$ appearance. There is a mild tension between the disappearance and the appearance data sets of T2K. A more serious tension exists between the $\nu_e$ appearance data of T2K and the $\nu_e / \bar\nu_e$ appearance data of NOvA. This tension is significant enough that T2K rules out the best-fit point of NOvA at $95\%$ confidence level whereas NOvA rules out T2K best-fit point at $90\%$ confidence level. We explain the reason why these tensions arise. We also do a combined fit of T2K and NOvA data and comment on the results of this fit.Comment: matches the published versio

Profile of congenital defects in foetuses: incidence and risk factors: a prospective observational study

Background: Perinatal outcome is one of the major indicators of evaluating health care system of a country. Congenital defects form important components of this parameter. The aim of the study was to determine the risk factors associated with congenital malformations in foetuses.Methods: All antenatal mothers whose foetuses were detected to have congenital defects on ultrasonography irrespective of period of gestation were enrolled for the study.Results: Eighty-six pregnant women with prenatally diagnosed fetal anomalies were enrolled for the study, out of which, 87.2% (N=75) belonged to 20-30 years age group. Majority of the subjects were educated till secondary school. Compared to primigravidae, the incidence of malformations was significantly higher in the multigravida group (69.8% vs 30.2% respectively). Thirty-eight (44.2%) mothers with malformed foetuses missed folic acid intake during early pregnancy. Only 40% mothers had prior history of abortions. Smoking was seen in 9% of subjects with malformations. Seven (8.3%) mothers had previous history of malformations and 5 (5.8%) reported a family history of malformations. Consanguineous marriage was observed in 4.7% of couples. Oligohydramnios or anhydramnios was associated with 11.6% foetuses, while polyhydramnios was seen in 53.5%. CNS malformations were seen in 57% of foetus, followed by genitourinary system malformations (9.2%).Conclusions: Tertiary level hospitals need to be upgraded with a dedicated multidisciplinary team of foetal medicine to cater to medical, clinical, surgical, preventive and therapeutic needs of malformed foetuses

Triacylglycerols: Fuelling the Hibernating Mycobacterium tuberculosis

Mycobacterium tuberculosis (Mtb) has the remarkable ability to persist with a modified metabolic status and phenotypic drug tolerance for long periods in the host without producing symptoms of active tuberculosis. These persisters may reactivate to cause active disease when the immune system becomes disrupted or compromised. Thus, the infected hosts with the persisters serve as natural reservoir of the deadly pathogen. Understanding the host and bacterial factors contributing to Mtb persistence is important to devise strategies to tackle the Mtb persisters. Host lipids act as the major source of carbon and energy for Mtb. Fatty acids derived from the host cells are converted to triacylglycerols (triglycerides or TAG) and stored in the bacterial cytoplasm. TAG serves as a dependable, long-term energy source of lesser molecular mass than other storage molecules like glycogen. TAG are found in substantial amounts in the mycobacterial cell wall. This review discusses the production, accumulation and possible roles of TAG in mycobacteria, pointing out the aspects that remain to be explored. Finally, the essentiality of TAG synthesis for Mtb is discussed with implications for identification of intervention strategies

Jaw bone metastasis from Lung cancer as sole primary source : a systematic review

Lung cancer is one of the leading causes of death worldwide. Lung cancer metastasis to oral region is very rare. Very few research work has been conducted till date to analyse the jaw bone metastasis from Lung cancer as the primary source. The goal of th

Role of cytokine in malignant T-cell metabolism and subsequent alternation in T-cell tumor microenvironment

T cells are an important component of adaptive immunity and T-cell-derived lymphomas are very complex due to many functional sub-types and functional elasticity of T-cells. As with other tumors, tissues specific factors are crucial in the development of T-cell lymphomas. In addition to neoplastic cells, T- cell lymphomas consist of a tumor micro-environment composed of normal cells and stroma. Numerous studies established the qualitative and quantitative differences between the tumor microenvironment and normal cell surroundings. Interaction between the various component of the tumor microenvironment is crucial since tumor cells can change the microenvironment and vice versa. In normal T-cell development, T-cells must respond to various stimulants deferentially and during these courses of adaptation. T-cells undergo various metabolic alterations. From the stage of quiescence to attention of fully active form T-cells undergoes various stage in terms of metabolic activity. Predominantly quiescent T-cells have ATP-generating metabolism while during the proliferative stage, their metabolism tilted towards the growth-promoting pathways. In addition to this, a functionally different subset of T-cells requires to activate the different metabolic pathways, and consequently, this regulation of the metabolic pathway control activation and function of T-cells. So, it is obvious that dynamic, and well-regulated metabolic pathways are important for the normal functioning of T-cells and their interaction with the microenvironment. There are various cell signaling mechanisms of metabolism are involved in this regulation and more and more studies have suggested the involvement of additional signaling in the development of the overall metabolic phenotype of T cells. These important signaling mediators include cytokines and hormones. The impact and role of these mediators especially the cytokines on the interplay between T-cell metabolism and the interaction of T-cells with their micro-environments in the context of T-cells lymphomas are discussed in this review article