Hand-breathe: Non-Contact Monitoring of Breathing Abnormalities from Hand Palm

In post-covid19 world, radio frequency (RF)-based non-contact methods, e.g., software-defined radios (SDR)-based methods have emerged as promising candidates for intelligent remote sensing of human vitals, and could help in containment of contagious viruses like covid19. To this end, this work utilizes the universal software radio peripherals (USRP)-based SDRs along with classical machine learning (ML) methods to design a non-contact method to monitor different breathing abnormalities. Under our proposed method, a subject rests his/her hand on a table in between the transmit and receive antennas, while an orthogonal frequency division multiplexing (OFDM) signal passes through the hand. Subsequently, the receiver extracts the channel frequency response (basically, fine-grained wireless channel state information), and feeds it to various ML algorithms which eventually classify between different breathing abnormalities. Among all classifiers, linear SVM classifier resulted in a maximum accuracy of 88.1\%. To train the ML classifiers in a supervised manner, data was collected by doing real-time experiments on 4 subjects in a lab environment. For label generation purpose, the breathing of the subjects was classified into three classes: normal, fast, and slow breathing. Furthermore, in addition to our proposed method (where only a hand is exposed to RF signals), we also implemented and tested the state-of-the-art method (where full chest is exposed to RF radiation). The performance comparison of the two methods reveals a trade-off, i.e., the accuracy of our proposed method is slightly inferior but our method results in minimal body exposure to RF radiation, compared to the benchmark method

Energy Disaggregation & Appliance Identification in a Smart Home: Transfer Learning enables Edge Computing

Non-intrusive load monitoring (NILM) or energy disaggregation aims to extract the load profiles of individual consumer electronic appliances, given an aggregate load profile of the mains of a smart home. This work proposes a novel deep-learning and edge computing approach to solve the NILM problem and a few related problems as follows. 1) We build upon the reputed seq2-point convolutional neural network (CNN) model to come up with the proposed seq2-[3]-point CNN model to solve the (home) NILM problem and site-NILM problem (basically, NILM at a smaller scale). 2) We solve the related problem of appliance identification by building upon the state-of-the-art (pre-trained) 2D-CNN models, i.e., AlexNet, ResNet-18, and DenseNet-121, which are fine-tuned two custom datasets that consist of Wavelets and short-time Fourier transform (STFT)-based 2D electrical signatures of the appliances. 3) Finally, we do some basic qualitative inference about an individual appliance's health by comparing the power consumption of the same appliance across multiple homes. Low-frequency REDD dataset is used for all problems, except site-NILM where REFIT dataset has been used. As for the results, we achieve a maximum accuracy of 94.6\% for home-NILM, 81\% for site-NILM, and 88.9\% for appliance identification (with Resnet-based model).Comment: 10 pages, 4 figures, 3 tables, under review with a journa

Biochemical screening of intellectually disabled patients: A stepping stone to initiate a newborn screening program in Pakistan

Inborn errors of metabolism (IEMs) are rare group of genetic disorders comprising of more than 1,000 different types. Around 200 of IEMs are potentially treatable through diet, pharmacological and other therapies, if diagnosed earlier in life. IEMs can be diagnosed early through newborn screening (NBS) programs, which are in place in most of the developed countries. However, establishing a NBS in a developing country is a challenging task due to scarcity of disease related data, large population size, poor economy, and burden of other common disorders. Since, not enough data is available for the prevalence of IEMs in Pakistan; therefore, in this study, we set out to find the prevalence of various treatable IEMs in a cohort of intellectually disabled patients suspected for IEMs, which will help us to initiate a NBS program for the most frequent IEMs in Pakistan. Therefore, a total of 429 intellectually disabled (IQ < 70) patient samples were collected from Pakistan. A subset of 113 patient samples was selected based on the clinical information for the detailed biochemical screening. Advance analytical techniques like, Amino Acid Analyzer, GC-MS, UHPLC-MS, and MS/MS were used to screen for different treatable IEMs like aminoacidopathies, fatty acid β-oxidation disorders and mucopolysaccharidoses (MPS) etc. A total of 14 patients were diagnosed with an IEM i.e., 9 with homocystinuria, 2 with MPS, 2 with Guanidinoacetate methyltransferase (GAMT) deficiency and 1 with sitosterolemia. These IEMs are found frequent in the collected patient samples from Pakistan. Thus, present study can help to take an initiative step to start a NBS program in Pakistan, especially for the homocystinuria having highest incidence among aminoacidopathies in the studied patients, and which is amenable to treatment. This endeavor will pave the way for a healthier life of affected patients and will lessen the burden on their families and society

Identification of three novel pathogenic mutations in cystathionine beta-synthase gene of Pakistani intellectually disabled patients

Background: Classical homocystinuria (HCU) is an autosomal recessive inborn error of metabolism, which is caused by the cystathionine-β-synthase (CBS: encoded by CBS) deficiency. Symptoms of untreated classical HCU patients include intellectual disability (ID), ectopia lentis and long limbs, along with elevated plasma methionine, and homocysteine.Methods: A total of 429 ID patients (age range: 1.6-23 years) were sampled from Northern areas of Punjab, Pakistan. Biochemical and genetic analyses were performed to find classical HCU disease in ID patients.Results: Biochemically, nine patients from seven unrelated families were identified with high levels of plasma methionine and homocysteine. Targeted exonic analysis of CBS confirmed seven causative homozygous mutations; of which three were novel missense mutations (c.451G\u3eT; p.Gly151Trp, c.975G\u3eC; p.Lys325Asn and c.1039 + 1G\u3eT splicing), and four were recurrent variants (c.451 + 1G\u3eA; IVS4 + 1 splicing, c.770C\u3eT; p.Thr257Met, c.808_810del GAG; p.Glu270del and c.752T\u3eC; p.Leu251Pro). Treatment of patients was initiated without further delay with pyridoxine, folic acid, cobalamin, and betaine as well as dietary protein restriction. The immediate impact was noticed in behavioral improvement, decreased irritability, improved black hair color, and socialization. Overall, health outcomes in this disorder depend on the age and symptomatology at the time of treatment initiation.Conclusions: With personalized treatment and care, such patients can reach their full potential of living as healthy a life as possible. This screening study is one of the pioneering initiatives in Pakistan which would help to minimize the burden of such treatable inborn errors of metabolism in the intellectually disabled patients

Adult GAMT deficiency: A literature review and report of two siblings

Guanidinoacetate methyltransferase (GAMT) deficiency is a creatine deficiency disorder and an inborn error of metabolism presenting with progressive intellectual and neurological deterioration. As most cases are identified and treated in early childhood, adult phenotypes that can help in understanding the natural history of the disorder are rare. We describe two adult cases of GAMT deficiency from a consanguineous family in Pakistan that presented with a history of global developmental delay, cognitive impairments, excessive drooling, behavioral abnormalities, contractures and apparent bone deformities initially presumed to be the reason for abnormal gait. Exome sequencing identified a homozygous nonsense variant in GAMT: NM_000156.5:c.134G>A (p.Trp45*). We also performed a literature review and compiled the genetic and clinical characteristics of all adult cases of GAMT deficiency reported to date. When compared to the adult cases previously reported, the musculoskeletal phenotype and the rapidly progressive nature of neurological and motor decline seen in our patients is striking. This study presents an opportunity to gain insights into the adult presentation of GAMT deficiency and highlights the need for in-depth evaluation and reporting of clinical features to expand our understanding of the phenotypic spectrum

Novel mutations in natriuretic peptide receptor-2 gene underlie acromesomelic dysplasia, type maroteaux

<p>Abstract</p> <p>Background</p> <p>Natriuretic peptides (NPs) are peptide hormones that exert their biological actions by binding to three types of cell surface natriuretic peptide receptors (NPRs). The receptor NPR-B binding C-type natriuretic peptide (CNP) acts locally as a paracrine and/or autocrine regulator in a wide variety of tissues. Mutations in the gene <it>NPR2</it> have been shown to cause acromesomelic dysplasia-type Maroteaux (AMDM), an autosomal recessive skeletal disproportionate dwarfism disorder in humans.</p> <p>Methods</p> <p>In the study, presented here, genotyping of six consanguineous families of Pakistani origin with AMDM was carried out using polymorphic microsatellite markers, which are closely linked to the gene <it>NPR2</it> on chromosome 9p21-p12. To screen for mutations in the gene <it>NPR2</it>, all of its coding exons and splice junction sites were PCR amplified from genomic DNA of affected and unaffected individuals of the families and sequenced.</p> <p>Results</p> <p>Sequence analysis of the gene <it>NPR2</it> identified a novel missence mutation (p.T907M) in five families, and a splice donor site mutation c.2986 + 2 T > G in the other family.</p> <p>Conclusion</p> <p>We have described two novel mutations in the gene <it>NPR2.</it> The presence of the same mutation (p.T907M) and haplotype in five families (A, B, C, D, E) is suggestive of a founder effect.</p