Signer-Independent Arabic Sign Language Recognition System Using Deep Learning Model

Every one of us has a unique manner of communicating to explore the world, and such communication helps to interpret life. Sign language is the popular language of communication for hearing and speech-disabled people. When a sign language user interacts with a non-sign language user, it becomes difficult for a signer to express themselves to another person. A sign language recognition system can help a signer to interpret the sign of a non-sign language user. This study presents a sign language recognition system that is capable of recognizing Arabic Sign Language from recorded RGB videos. To achieve this, two datasets were considered, such as (1) the raw dataset and (2) the face-hand region-based segmented dataset produced from the raw dataset. Moreover, operational layer-based multi-layer perceptron "SelfMLP" is proposed in this study to build CNN-LSTM-SelfMLP models for Arabic Sign Language recognition. MobileNetV2 and ResNet18-based CNN backbones and three SelfMLPs were used to construct six different models of CNN-LSTM-SelfMLP architecture for performance comparison of Arabic Sign Language recognition. This study examined the signer-independent mode to deal with real-time application circumstances. As a result, MobileNetV2-LSTM-SelfMLP on the segmented dataset achieved the best accuracy of 87.69% with 88.57% precision, 87.69% recall, 87.72% F1 score, and 99.75% specificity. Overall, face-hand region-based segmentation and SelfMLP-infused MobileNetV2-LSTM-SelfMLP surpassed the previous findings on Arabic Sign Language recognition by 10.970% accuracy.

Multi-Modal Portable Respiratory Rate Monitoring Device for Childhood Pneumonia Detection

Accurate assessment of Respiratory Rate (RR) is the most important mechanism in detecting pneumonia in low-resource settings. Pneumonia is a disease with one of the highest mortality rates among young children under five. However, the diagnosis of pneumonia for infants remains challenging, especially in low- and middle-income countries (LMIC). In such situations, RR is most often measured manually with visual inspection. Accurate RR measurement requires the child to remain calm without any stress for a few minutes. The difficulty in achieving this with a sick child in a clinical environment can result in errors and misdiagnosis, even more so when the child is crying and non-cooperating around unfamiliar adults. Therefore, we propose an automated novel RR monitoring device built with textile glove and dry electrodes which can make use of the relaxed posture when the child is resting on the carer's lap. This portable system is non-invasive and made with affordable instrumentation integrated on customized textile glove. The glove has multi-modal automated RR detection mechanism that simultaneously uses bio-impedance and accelerometer data. This novel textile glove with dry electrodes can easily be worn by a parent/carer and is washable. The real-time display on a mobile app shows the raw data and the RR value, allowing a healthcare professional to monitor the results from afar. The prototype device has been tested on 10 volunteers with age variation of 3 years to 33 years, including male and female. The maximum variation of measured RR with the proposed system is ±2 compared to the traditional manual counting method. It does not create any discomfort for either the child or the carer and can be used up to 60 to 70 sessions/day before recharging.

Bangla Sign Language (BdSL) Alphabets and Numerals Classification Using a Deep Learning Model

A real-time Bangla Sign Language interpreter can enable more than 200 k hearing and speech-impaired people to the mainstream workforce in Bangladesh. Bangla Sign Language (BdSL) recognition and detection is a challenging topic in computer vision and deep learning research because sign language recognition accuracy may vary on the skin tone, hand orientation, and background. This research has used deep machine learning models for accurate and reliable BdSL Alphabets and Numerals using two well-suited and robust datasets. The dataset prepared in this study comprises of the largest image database for BdSL Alphabets and Numerals in order to reduce inter-class similarity while dealing with diverse image data, which comprises various backgrounds and skin tones. The papers compared classification with and without background images to determine the best working model for BdSL Alphabets and Numerals interpretation. The CNN model trained with the images that had a background was found to be more effective than without background. The hand detection portion in the segmentation approach must be more accurate in the hand detection process to boost the overall accuracy in the sign recognition. It was found that ResNet18 performed best with 99.99% accuracy, precision, F1 score, sensitivity, and 100% specificity, which outperforms the works in the literature for BdSL Alphabets and Numerals recognition. This dataset is made publicly available for researchers to support and encourage further research on Bangla Sign Language Interpretation so that the hearing and speech-impaired individuals can benefit from this research.

Probing Deep Lung Regions using a New 6-electrode Tetrapolar Impedance Method

Probing deep regions of the lung using electrical impedance is very important considering the need for a low cost and simple technique, particularly for the low and medium income countries. Because of complexity and cost, Electrical Impedance Tomography is not suitable for this envisaged application. The simple Tetrapolar Impedance Measurement (TPIM) technique employing four electrodes is the age old technique for bioelectrical measurements. However, it has its limitations in respect of organ localisation and depth sensitivity using skin surface electrodes. Recently, a new 6-electrode TPIM with two current electrodes but two pairs of appropriately connected potential electrodes positioned on the front and back of the thorax, proposed by one of the authors, came with a promise. However, this work gave a qualitative proposal based on concepts of physics and lacked a quantitative evaluation. In order to evaluate the method quantitatively, the present work employed finite element method based COMSOL Multiphysics software and carried out simulation studies using this new 6-electrode TPIM and compared the results with those from 4-electrode TPIM, with electrodes applied either on the front or at the back of the thorax for the latter. Initially, it carried out a sensitivity distribution study using a simple rectangular volume conductor which showed that the 6-electrode TPIM gives better depth sensitivity throughout the lung region. Next it used a near life like thorax model developed by another of the authors earlier. Using this model, extensive studies were carried out to quantify the overall sensitivity over a target lung region, the contribution of the target lung to the total measured impedance, and several other parameters. Through these studies, the 6-electrode TPIM was established on a stronger footing for probing deep regions of the lungs.

A Multi-Frequency Focused Impedance Measurement System Based on Analogue Synchronous Peak Detection

Monitoring of anatomical structures and physiological processes by electrical impedance has attracted scientists as it is noninvasive, nonionizing and the instrumentation is relatively simple. Focused Impedance Method (FIM) is attractive in this context, as it has enhanced sensitivity at the central region directly beneath the electrode configuration minimizing contribution from neighboring regions. FIM essentially adds or averages two concentric and orthogonal combinations of conventional Tetrapolar Impedance Measurements (TPIM) and has three versions with 4, 6, and 8 electrodes. This paper describes the design and testing of a multi-frequency FIM (MFFIM) system capable of measuring all three versions of FIM at 8 frequencies in the range 10 kHz—1 MHz. A microcontroller based multi-frequency signal generator and a balanced Howland current source with high output impedance (476 kΩ at 10 kHz and 58.3 kΩ at 1 MHz) were implemented for driving currents into biological tissues with an error <1%. The measurements were carried out at each frequency sequentially. The peak values of the amplified voltage signals were measured using a novel analogue synchronous peak detection technique from which the transfer impedances were obtained. The developed system was tested using TPIM measurements on a passive RC Cole network placed between two RC networks, the latter representing skin-electrode contact impedances. Overall accuracy of the measurement was very good (error <4% at all frequencies except 1 MHz, with error 6%) and the resolution was 0.1 Ω. The designed MFFIM system had a sampling rate of >45 frames per second which was deemed adequate for noninvasive real-time impedance measurements on biological tissues.

Video based non-contact monitoring of respiratory rate and chest indrawing in children with pneumonia

OBJECTIVE

Pneumonia is the single largest cause of death in children worldwide due to infectious diseases. According to WHO guidelines, fast breathing and chest indrawing are the key indicators of pneumonia in children requiring antibiotic treatments. The aim of this study was to develop a video-based novel method for simultaneous monitoring of respiratory rate and chest indrawing without upsetting babies.

APPROACH

Respiratory signals, corresponding to periodic movements of chest-abdominal walls during breathing, were extracted by analyzing RGB (red, green, blue) components in video frames captured by a smartphone camera. Respiratory rate was then obtained by applying fast fourier transform on the de-noised respiratory signal. Chest indrawing was detected by analysing relative phases of regional chest-abdominal wall mobility. The performance of the developed algorithm was evaluated on both healthy and pneumonia children.

MAIN RESULTS

The proposed method can measure respiratory rate with an overall mean absolute error of 1.8 bpm in the range 18-105 bpm. Phase difference between regional chest wall movements in the chest indrawing (pneumonia) cases was found to be 143±23.9 degrees, which was significantly higher than that in the healthy cases 52.3 ±32.6 degrees (p<0.001).

SIGNIFICANCE

Being non-intrusive and non-subjective, this computer-aided method can be useful in the monitoring for respiratory rate and chest indrawing for the diagnosis of pneumonia and its severity in children.

Physical activity attitudes among adolescents in Bangladesh

OBJECTIVES

The purpose of this study was to examine physical activity (PA) attitudes among adolescents in Bangladesh and their associations with sociodemographic, lifestyle and activity-related factors.

STUDY DESIGN

Cross-sectional study.

METHODS

A total of 781 students (52% female; mean age 14.3 years, SD 1.1) from eight secondary schools in Dhaka, Bangladesh, completed a written questionnaire. Exploratory factor analysis was used to derive positive and negative PA attitude measures. Generalized estimating equations were used to examine the associations.

RESULTS

The most frequent positive attitudes were PA would 'get or keep me in shape' (81%) and 'be fun' (73%). Common negative attitudes were PA 'would make me hot and sweaty' (51%) and 'is hard work' (42%). Multivariable analysis showed that positive PA attitudes were more likely among adolescents who had physical education classes, adolescents involved in school sports, adolescents who ate fresh fruit and vegetables daily, and adolescents who had breakfast regularly. Negative PA attitudes were more likely among girls, adolescents who slept ≤8 h/night, and adolescents who were overweight or obese; and were less common among adolescents who ate fresh fruit and vegetables daily.

CONCLUSIONS

This study suggests that PA interventions for adolescents should highlight benefits for being in shape and having fun as key components of positive PA attitudes; and address negative attitudes of PA being hot and hard work. Specific strategies may be needed to address negative PA attitudes among girls, adolescents who are overweight or obese, and adolescents with insufficient sleep.

Chemical and antibacterial data of synthesized thioureido derivatives

This paper provided comprehensive data on spectroscopic and antibacterial activities of thioureido compounds which are relevant with research article entitled “Synthesis, Spectroscopic Studies and Antibacterial Activity of New Lauroyl Thiourea Amino Acid Derivatives” [1]. Based on the reported study, four new thioureido derivatives, namely 3-(3-dodecanoyl-thioureido)propionic acid (R1), 2-(3-dodecanoyl-thioureido)-3-methyl butyric acid (R2), (3-dodecanoyl-thioureido)acetic acid (R3) and 2-(3-dodecanoyl-thioureido)-3-phenyl propionic acid (R4) were characterized by elemental analysis, Fourier Transform Infrared (FTIR), ¹H Nuclear Magnetic Resonance (¹H NMR) and ¹³C Nuclear Magnetic Resonance (¹³C NMR), and Ultraviolet Visible spectroscopy (UV-Vis). The preliminary results from antibacterial assay which were tested against Gram-positive bacteria such as Bacillus subtilis, Staphylococcus epidermidis, Staphylococcus aureus and Gram-negative bacteria such as Escherichia coli, Salmonella typhimurium are also described.

Probing for Stomach using the Focused Impedance Method (FIM)

For probing deep organs of the body using electrical impedance, the conventional method is to use Electrical Impedance Tomography (EIT). However, this would be a sophisticated machine and will be very expensive when a full 3D EIT is developed in the future. Furthermore, for most low income countries such expensive devices may not deliver the benefits to a large number of people. Therefore, this paper suggests the use of simpler techniques like Tetrapolar Impedance Measurement (TPIM) or Focused Impedance Method (FIM) in probing deeper organs. Following a method suggested earlier by one of the authors, this paper studies the possibility of using TPIM and FIM for the stomach. Using a simplified model of the human trunk with an embedded stomach, a finite element simulation package, COMSOL, was used to obtain transfer impedance values and percentage contribution of the stomach region in the total impedance. For this work, judicious placement of electrodes through qualitative visualizations based on point sensitivity equations and equipotential concepts were made, which showed that reasonable contribution of the stomach region is possible through the use of TPIM and FIM. The contributions were a little over 20% which is of similar order of the cross-sectional area percentage of the stomach with respect to that of the trunk. For the case where the conductivity of the stomach region was assumed about 4 times higher, the contributions increased to about 38%. Through further studies this proposed methods may contribute greatly in the study of deeper organs of the body.

Use of a Conical Conducting Layer with an Electrical Impedance Probe to Enhance Sensitivity in Epithelial Tissues

Tetra-polar electrical impedance measurement (TPIM) with a square geometry of electrodes is useful in the characterization of epithelial tissues, especially in the detection of cervical cancer at precancerous stages. However, in TPIM, the peak planar sensitivity just below the electrode surface is almost zero and increases to a peak value at a depth of about one third to one half of the electrode separation. To get high sensitivity for the epithelial layer, having thicknesses of 200 μm to 300 μm, the electrode separation needed is less than 1 mm, which is difficult to achieve in practical probes. This work proposes a conical conducting layer in front of a pencil like probe with a square geometry of TPIM electrodes to create virtual electrodes with much smaller separation at the body surface, thus increasing the sensitivity of the epithelial tissues. To understand the improvements, if any, 3D sensitivity distribution and transfer impedance were simulated using COMSOL Multiphysics software for a simplified body tissue model containing a 300 μm epithelial layer. It has been shown that fractional contribution of an epithelial layer can be increased several times placing a cylindrical conducting layer in between the tissue surface and the electrodes, which can further be enhanced using a conical conducting layer. The results presented in this paper can be used to choose an appropriate electrode separation, conducting layer height and cone parameters for enhanced sensitivity in the epithelial layer.

Classification of breast tumour using electrical impedance and machine learning techniques

When a breast lump is detected through palpation, mammography or ultrasonography, the final test for characterization of the tumour, whether it is malignant or benign, is biopsy. This is invasive and carries hazards associated with any surgical procedures. The present work was undertaken to study the feasibility for such characterization using non-invasive electrical impedance measurements and machine learning techniques. Because of changes in cell morphology of malignant and benign tumours, changes are expected in impedance at a fixed frequency, and versus frequency of measurement. Tetrapolar impedance measurement (TPIM) using four electrodes at the corners of a square region of sides 4 cm was used for zone localization. Data of impedance in two orthogonal directions, measured at 5 and 200 kHz from 19 subjects, and their respective slopes with frequency were subjected to machine learning procedures through the use of feature plots. These patients had single or multiple tumours of various types in one or both breasts, and four of them had malignant tumours, as diagnosed by core biopsy. Although size and depth of the tumours are expected to affect the measurements, this preliminary work ignored these effects. Selecting 12 features from the above measurements, feature plots were drawn for the 19 patients, which displayed considerable overlap between malignant and benign cases. However, based on observed qualitative trend of the measured values, when all the feature values were divided by respective ages, the two types of tumours separated out reasonably well. Using K-NN classification method the results obtained are, positive prediction value: 60%, negative prediction value: 93%, sensitivity: 75%, specificity: 87% and efficacy: 84%, which are very good for such a test on a small sample size. Study on a larger sample is expected to give confidence in this technique, and further improvement of the technique may have the ability to replace biopsy.

Comparative efficacy of combined nebulized salbutamol with ipratropium bromide and nebulized adrenaline to treat children with acute bronchiolitis

As the efficacy of combined nebulized salbutamol & ipratropium bromide as well as L-adrenaline to treat acute bronchiolitis is not well studied among the Bangladeshi infants, this study was carried out to see their efficacy in acute bronchiolitis and to compare their effectiveness. This randomized clinical trial was done among 60 children aged less than 02 years, admitted in the department of Pediatrics, Dhaka Medical College Hospital, during January through December 2005 with acute bronchiolitis. After a quick initial assessment, nebulization were done twice at 6 hours interval with the mentioned drugs, group wise (one group with salbutamol plus ipratropium bromide and other group with L-adrenaline alone) and the outcomes were assessed after 30 minutes of each nebulization in respect to oxygen saturation and clinical modified respiratory distress assessment instrument (MRDAI) scores. The results were analyzed by using SPSS version 10.0 and at a p value of </=0.05, the test was considered significant. The clinical characteristics were similar in both the groups. After 02 doses of nebulizations by the studied drugs, a significant improvement in respect to oxygen saturation and MRDAI score were noted among the children in both the groups, compared to their baseline status (p=0.000). However, L-adrenaline showed more efficacy (MRDAI, p=0.021; SaO2, p=0.034) than combined Salbutamol & Ipratropium bromide. Both L-adrenaline and combined salbutamol & ipratropium bromide were found effective in acute bronchiolitis but L-adrenaline was found more effective. A large multi-centre clinical trial is recommended.

Proliferation Potential of 18-Month-Old Callus ofAnanas comosusL. cv. Moris

Differential effect of plant growth regulators and additives in proliferation of 18-month-old calli of Ananas comosus L. cv. Moris were assessed in vitro. The proliferation of callus relied on the growth regulators and additives. Of the different auxins supplemented in the Murashige and Skoog (MS) media, 32.22 μM α-naphthaleneacetic acid (NAA) gave the highest mean fresh weight of callus (46.817 g). Medium supplemented with 2,4-dichlorophenoxyacetic acid (2,4-D) was inferior to NAA, while b-naphthoxy acetic acid (BNOA) and p-chlorophenoxy acetic acid (4-CPA) were not effective in proliferating 18-months old callus. Addition of casein hydrolysate and coconut water to NAA supplemented medium showed better proliferation and production of callus. However, in terms of callus production, NAA at 32.22 μM was economically better.

Surgical management of cicatricial post-scleromatous sub-glottic stenosis

In Egypt, sub-glottic stenosis is commonly caused by scleromatous affection. The countries in which scleroma is endemic have been reviewed. The incidence of scleroma, laryngeal scleroma, and sub-glottic affection, and their sex ratios have been discussed. Radiological study of the sub-glottic extension has been done. The operative procedures are detailed and the results are presented. The use of the Montgomery T-tube is an essential part of all these operations. The excision of scar tissue from the sub-glottic region was done in children, and this accords with recent trends. Twenty cases have been operated upon, with airway improvement in all of them.