Evaluation of supervised classification algorithms for human activity recognition with inertial sensors

The main aim of this work is to compare the performance of different algorithms for human activity recognition by extracting various statistical time domain and frequency domain features from the inertial sensor data. Our results show that Support Vector Machines with quadratic kernel classifier (accuracy: 93.5%) and Ensemble classifier with bagging and boosting (accuracy: 94.6%) outperforms other known activity classification algorithms. A parallel coordinate plot based on visualization of features is used to identify useful features or predictors for separating classes. This enabled exclusion of features that contribute least to classification accuracy in a multi-sensor system (five in our case), made the classifier lightweight in terms of number of useful features, training time and computational load and lends itself to real-time implementation

The effects of binaural spectral resolution mismatch on Mandarin speech perception in simulated electric hearing

This study assessed the effects of binaural spectral resolution mismatch on the intelligibility of Mandarin speech in noise using bilateral cochlear implant simulations. Noise-vocoded Mandarin speech, corrupted by speech-shaped noise at 0 and 5 dB signal-to-noise ratios, were presented unilaterally or bilaterally to normal-hearing listeners with mismatched spectral resolution between ears. Significant binaural benefits for Mandarin speech recognition were observed only with matched spectral resolution between ears. In addition, the performance of tone identification was more robust to noise than that of sentence recognition, suggesting factors other than tone identification might account more for the degraded sentence recognition in noise.published_or_final_versio

Design and implementation of a convolutional neural network on an edge computing smartphone for human activity recognition

Edge computing aims to integrate computing into everyday settings, enabling the system to be context-aware and private to the user. With the increasing success and popularity of deep learning methods, there is an increased demand to leverage these techniques in mobile and wearable computing scenarios. In this paper, we present an assessment of a deep human activity recognition system’s memory and execution time requirements, when implemented on a mid-range smartphone class hardware and the memory implications for embedded hardware. This paper presents the design of a convolutional neural network (CNN) in the context of human activity recognition scenario. Here, layers of CNN automate the feature learning and the influence of various hyper-parameters such as the number of filters and filter size on the performance of CNN. The proposed CNN showed increased robustness with better capability of detecting activities with temporal dependence compared to models using statistical machine learning techniques. The model obtained an accuracy of 96.4% in a five-class static and dynamic activity recognition scenario. We calculated the proposed model memory consumption and execution time requirements needed for using it on a mid-range smartphone. Per-channel quantization of weights and per-layer quantization of activation to 8-bits of precision post-training produces classification accuracy within 2% of floating-point networks for dense, convolutional neural network architecture. Almost all the size and execution time reduction in the optimized model was achieved due to weight quantization. We achieved more than four times reduction in model size when optimized to 8-bit, which ensured a feasible model capable of fast on-device inference

A systematic review of covered balloon-expandable stents for treating aortoiliac occlusive disease

Objective: To evaluate and compare studies reporting the outcomes of the use of covered balloon-expandable (CBE) stents for the treatment of aortoiliac occlusive disease. Methods: A systematic literature search was conducted to identify studies that investigated the use of CBE stents for the treatment of aortoiliac occlusive disease and were published between 2000 and 2019. Baseline demographic data, procedural variables, and long-term outcomes were extracted from publications for analysis. Results: A total of 15 published articles about 14 studies were included in the review. Of these, eight studies were prospective clinical trials and six studies were retrospective real-world studies. The articles included data regarding five different CBE stents, namely, the iCast/Advanta V12, Viabahn VBX, BeGraft, LifeStream, and JOSTENT. Lesion severity was higher in real-world studies, with more TransAtlantic Inter-Society Consensus Classification class D lesions and a higher percentage of occlusions. All studies showed high rates of technical success and patency over the course of 12 months. Long-term data were only available for the iCast/Advanta V12 device, which had a primary patency rate of 74.7% at 5 years. Conclusions: CBE stents are a viable treatment option for patients with complex aortoiliac lesions because of their high rates of technical success and favorable patency across all devices at 12 months. However, long-term data are only available for a single device, the iCast/Advanta V12. The results of using this device were favorable over the course of 5 years

Factors Associated with Klebsiella

Although Klebsiella bacteremia in children is perceived to be associated with fatal consequences, data are scarce on those children presenting with diarrhea. We evaluated the factors associated with Klebsiella bacteremia in such children. In this retrospective chart analysis, data of all diarrheal children was retrieved from electronic medical record system (named as SHEBA) of Dhaka Hospital of International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), from January 1, 2010, to December 31, 2012, who had their blood culture done. This was a study having a case-control design where comparison of clinical and laboratory characteristics was done among children with Klebsiella bacteremia (cases = 30) and those without any bacteraemia (controls = 90). Controls were selected randomly. The cases more often had fatal outcome (p<0.001). In logistic regression analysis, after adjusting for potential confounders such as young age, severe dehydration, severe wasting, abnormal mentation, hypotension, and fast breathing, the cases were independently associated with hospital-acquired infection and positive stool growth (for all, p<0.05). The study highlights the importance of obtaining blood cultures in hospitalized children under five years old with diarrheal illness in the presence of either hospital-acquired infection or positive stool culture to have better outcome

Prevalence of multiple non-communicable diseases risk factors among adolescents in 140 countries:A population-based study

BACKGROUND: Modifiable non-communicable disease (NCD) risk factors are becoming increasingly common among adolescents, with clustering of these risk factors in individuals of particular concern. The aim of this study was to assess global status of clustering of common modifiable NCD risk factors among adolescents. METHODS: We used latest available data from nationally representative survey for 140 countries, namely the Global School-based Student Health Survey, the Health Behaviour in School-Aged Children and the longitudinal study of Australian Children. Weighted mean estimates of prevalence with corresponding 95% confidence intervals of nine NCD risk factors - physical inactivity, sedentary behaviour, insufficient fruits and vegetable consumption, carbonated soft drink consumption, fast food consumption, tobacco use, alcohol consumption and overweight/obesity - were calculated by country, region and sex. FINDINGS: Over 487,565 adolescents, aged 11–17 years, were included in this study. According to trend analysis, prevalence of four or more NCD risk factors increased gradually over time. Prevalence of four or more NCD risk factors was 14.8% in 2003–2007 and increased to 44% in 2013–2017, an approximately three-fold increase (44.0%). Similar trends were also observed for three and two risk factors. Large variation between countries in the prevalence of adolescents with four or more risk factors was found in all regions. The country level range was higher in the South-East Asia Region (minimum Sri Lanka = 8%, maximum Myanmar = 84%) than Western Pacific Region (minimum China = 3%, maximum Niue = 72%), European Region (minimum Sweden = 13.9%, maximum Ireland = 66.0%), African Region (minimum Senegal = 0.8%, maximum Uganda = 82.1%) and Eastern Mediterranean Region (minimum Libya = 0.2%, maximum Lebanon = 80.2%). Insufficient vegetable consumption, insufficient fruit consumption and physically inactivity were three of the four most prevalent risk factors in all regions. INTERPRETATION: Our results suggest a high prevalence of four or more NCD risk factors in adolescents globally, although variation was found between countries. Results from our study indicate that efforts to reduce adolescent NCD risk factors and the associated health burden need to be improved. These findings can assist policy makers to target the rollout of country- specific interventions. FUNDING: None

Effect of 3 Days of Oral Azithromycin on Young Children With Acute Diarrhea in Low-Resource Settings A Randomized Clinical Trial

Importance: World Health Organization (WHO) guidelines do not recommend routine antibiotic use for children with acute watery diarrhea. However, recent studies suggest that a significant proportion of such episodes have a bacterial cause and are associated with mortality and growth impairment, especially among children at high risk of diarrhea-associated mortality. Expanding antibiotic use among dehydrated or undernourished children may reduce diarrhea-associated mortality and improve growth. Objective: To determine whether the addition of azithromycin to standard case management of acute nonbloody watery diarrhea for children aged 2 to 23 months who are dehydrated or undernourished could reduce mortality and improve linear growth. Design, Setting, and Participants: The Antibiotics for Children with Diarrhea (ABCD) trial was a multicountry, randomized, double-blind, clinical trial among 8266 high-risk children aged 2 to 23 months presenting with acute nonbloody diarrhea. Participants were recruited between July 1, 2017, and July 10, 2019, from 36 outpatient hospital departments or community health centers in a mixture of urban and rural settings in Bangladesh, India, Kenya, Malawi, Mali, Pakistan, and Tanzania. Each participant was followed up for 180 days. Primary analysis included all randomized participants by intention to treat. Interventions: Enrolled children were randomly assigned to receive either oral azithromycin, 10 mg/kg, or placebo once daily for 3 days in addition to standard WHO case management protocols for the management of acute watery diarrhea. Main Outcomes and Measures: Primary outcomes included all-cause mortality up to 180 days after enrollment and linear growth faltering 90 days after enrollment. Results: A total of 8266 children (4463 boys [54.0%]; mean [SD] age, 11.6 [5.3] months) were randomized. A total of 20 of 4133 children in the azithromycin group (0.5%) and 28 of 4135 children in the placebo group (0.7%) died (relative risk, 0.72; 95% CI, 0.40-1.27). The mean (SD) change in length-for-age z scores 90 days after enrollment was -0.16 (0.59) in the azithromycin group and -0.19 (0.60) in the placebo group (risk difference, 0.03; 95% CI, 0.01-0.06). Overall mortality was much lower than anticipated, and the trial was stopped for futility at the prespecified interim analysis. Conclusions and Relevance: The study did not detect a survival benefit for children from the addition of azithromycin to standard WHO case management of acute watery diarrhea in low-resource settings. There was a small reduction in linear growth faltering in the azithromycin group, although the magnitude of this effect was not likely to be clinically significant. In low-resource settings, expansion of antibiotic use is not warranted. Adherence to current WHO case management protocols for watery diarrhea remains appropriate and should be encouraged. Trial Registration: ClinicalTrials.gov Identifier: NCT03130114.publishedVersionPeer reviewe

Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BackgroundDisorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021.MethodsWe estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined.FindingsGlobally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer.InterpretationAs the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed

Inertial sensing for gait analysis and the scope for sensor fusion

Conventional gait analysis systems make use of cameras and are therefore bounded to a restricted area. In this work, we focus on developing a low-cost, wearable gait analysis system based on inertial sensors, as a suitable ambulatory alternative to be used in unconstrained locations. The developed system is tailored to study lower body motion in terms of gait parameters and joint kinematics. The main focus is in using the inertial sensors data, e.g. Joint acceleration and quaternion rotation readings, for the reconstruction of visually appealing motion sequences from low-dimensional sensor input. This requires inertial sensor data to be mapped and fused with optical motion capture data. For this purpose, we propose to use a hierarchical skeleton model obtained from an optical motion capture database