Modem Myoelectric Control - Is it Time to Change the Algorithmic Focus?

This paper explores the evolving landscape of Electromyogram (EMG) signal analysis, focusing on the growing prominence of deep learning (DL) algorithms for hand, wrist, and finger movement recognition. Such algorithms often come with high computational costs, potentially limiting the clinical translation on resource-limited devices and igniting more research on reduced complexity models. This prompts the question: is it time to shift the algorithmic focus in EMG pattern recognition, given the reported performance of some light-weight traditional or hybrid methods emphasizing synergy between different EMG signals? A comparative study is implemented between state-of-the-art deep learning extension for time series classification, denoted as Random Convolutional Kernel Transform (ROCKET), and simple, yet effective pattern recognition methods tailored to exploit basic forms of EMG signal synergies- Waveform Length Phasors (WLPHASOR), Root-Mean-Squared Phasor (RMSPHASOR), and the proposed novel Multi-Signal Waveform Length (MSWL).

An Efficient Deep Transfer Learning Network for Characterization of Stroke Patients' Motor Execution from Multi-Channel EEG-Recordings.

Recent advances in stroke rehabilitation technology have been focused on developing Intelligent Rehabilitation Robots (IRR) that can effectively engage post-stroke patients (PSP) in intuitive motor training for full function recovery. Most existing rehabilitation robots incorporate functionalities that are passive in nature, constraining PSP to predetermined trajectories that often deviate from patients' limb movement intentions, consequently hindering recovery. To resolve this issue, a robust deep-transfer learning driven network (DTLN) is developed to adequately characterize PSP's motion intention signatures from neural oscillations towards achieving intuitive and active training.

Adaptive Stepwise Feature Selection Approach for EEG-Based Epileptic Seizure Classification.

Recent advancements in feature selection (FS) optimization algorithms have influenced the field of epileptic seizure classification. However, integrating these optimization algorithms into machine learning (ML) models often creates time complexity, limiting their clinical deployment. To address this issue, we propose an innovative adaptive stepwise FS method tailored for epileptic seizure detection (ESD).

Predictors of willingness of HPV vaccine uptake across Eight States in Nigeria.

Background: The Nigerian Federal Government planned to launch the Human Papillomavirus (HPV) vaccine on September 25, 2023. We therefore aimed to assess caregiver awareness and willingness regarding HPV vaccine uptake for girls aged 9-14 across eight states (Abia, Adamawa, Bayelsa, Benue, Enugu, FCT, Jigawa, and Taraba), evaluating public readiness for the vaccine rollout.

Methods: A cross-sectional telephone survey was conducted in the eight states using a structured questionnaire.

ANN-ANFIS model for optimising methylic composite biodiesel from neem and castor oil and predicting emissions of the biodiesel blend.

Researchers and stakeholders have shown interest in heterogeneous composite biodiesel (HCB) due to its enhanced fuel properties and environmental friendliness (EF). The lack of high viscosity datasets for parent hybrid oils has hindered their commercialisation. Reliable models are lacking to optimise the transesterification parameters for developing HCB, and the scarcity of predictive models has affected climate researchers and environmental experts.

Roles of mobile teams in tracing lost to follow-up clients: evidence from the optimization of COVID-19 vaccination uptake and routine immunization in Ekiti State.

Background: Evidence from literature has established that tracing lost to follow-up clients is an effective strategy for complementing other mechanisms for infectious disease control like human immunodeficiency virus (HIV), tuberculosis, and other diseases such as Ebola. As a long-standing successful public health method of optimizing acceptance and/or adherence to infectious disease treatment tracing lost to follow-up clients is usually carried out by manually investigating individuals who absconded or are absent from treatments designed to manage and/or promote their health status. This study seeks to explore the role of mobile teams in tracing clients lost to follow-up for immunization.

Rabies knowledge and prevention practices in Gombe state, Nigeria: a community-based comparative cross-sectional study of rabies hotspot and non-hotspot areas.

Background: Rabies remains a significant public health concern in Nigeria, particularly in rural areas with limited awareness and resources. Gombe State is recognized as a rabies hotspot, facing challenges in controlling the spread of the disease. This study aimed to assess and compare the knowledge and prevention practices related to rabies among community members in hotspot and non-hotspot areas of Gombe State.

Optimizing pre-eclampsia prevention: Embracing low-dose calcium in sub-Saharan Africa.

Pre-eclampsia remains a significant health challenge in sub-Saharan Africa, contributing substantially to maternal and neonatal mortality rates. This paper explores the potential of low-dose calcium supplementation as an alternative strategy to the conventional high-dose regimen in preventing pre-eclampsia. A consistent association between low serum calcium levels and an increased risk of pre-eclampsia is established based on studies spanning Ghana, Nigeria, and Ethiopia.

Assessment of the differences in Mean Age at Menarche (MAM) among adolescent girls in rural and urban Nigeria: a systematic review.

Introduction: Globally, there has been a decline in the age of menarche; the decline is higher in poorer countries than in richer ones. The measurement of the decline was based on the reported mean age at menarche (MAM) across the countries. There is a significant knowledge gap in investigating the generational decline in MAM in low- and median-income countries (LMC).

Machine learning based tuberculosis (ML-TB) health predictor model: early TB health disease prediction with ML models for prevention in developing countries.

Background: Tuberculosis (TB) remains one of the top infectious killers in the world and a prominent fatal disease in developing countries. This study proposes a prototypical solution to early prevention of TB based on its primary symptoms, signs, and risk factors, implemented by means of machine learning (ML) predictive algorithms. Further novelty of the study lies in the uniqueness of patient dataset collected from three top-ranked hospitals of Sindh, Pakistan, a self-administered survey patient-records that comprises a set of questions asked by the doctors treating TB patients in real-time.

Partnership coordination for optimized COVID-19 vaccination: a case study of Benue and Niger states.

Background: Developing countries have partnered with non-governmental and development organizations to ensure universal health coverage and promote equity in accessing health services. This study was motivated by the timely and relevant collaborative partnership among the National Primary Health Care Development Agency (NPHCDA), Sydani Consulting, and other implementing partners at the sub-national level. There is also no evidence of a study on partnership coordination vis-à-vis COVID-19 vaccine optimization.

Understanding the Challenges of Advocacy Communication, Social Mobilization, and Operationalization for COVID-19 and Routine Immunization in Nigeria.

The primary goal of program communication in public health is to influence behaviors. It also aims to raise awareness and ultimately improve health outcomes. Under the umbrella of program communication exist three interconnected, interrelated, and mutually supportive communication aspects: advocacy, communication, and social mobilization (ACSM).

Comprehensive Comparative Study of the Durability Wear Assessment of a Diesel Engine Fuelled with Seed Oil and Diesel Fuel and Its Troubleshooting and Scheduled Maintenance.

Existing ecofriendly apprehensions about climate change have directed scientists to discover plant-based vegetable oils for use as fuels, such as straight vegetable oils and their biodiesels, because of their renewability, nontoxic nature, biodegradability, and environmental friendliness. This experimental study intended to reveal the tribological aspects of 90 °C preheated straight vegetable oil (PHSVO90) used in a 7.35 kW, 1000 rpm constant speed indirect injection (IDI) diesel engine and likened to conventional diesel operation by conducting an elongated term durability examination for 512 h as per IS:10000 standards.

Assessment of the compliance with minimum quality standards by public primary healthcare facilities in Nigeria.

Achieving universal health coverage (UHC) and the Sustainable Development Goals (SDG) by 2030 relies on the delivery of quality healthcare services through effective primary healthcare (PHC) systems. This necessitates robust infrastructure, adequately skilled health workers and the availability of essential medicines and commodities. Despite the critical role of minimum standards in benchmarking PHC quality, no global consensus on these standards exists.

RSM integrated GWO, Driving Training, and Election-Based Algorithms for optimising ethylic biodiesel from ternary oil of neem, animal fat, and jatropha.

The worldwide exploration of the ethanolysis protocol (EP) has decreased despite the multifaceted benefits of ethanol, such as lower toxicity, higher oxygen content, higher renewability, and fewer emission tail compared to methanol, and the enhanced fuel properties with improved engine characteristics of multiple-oily feedstocks (MOFs) compared to single-oily feedstocks. The study first proposed a strategy for the optimisation of ethylic biodiesel synthesis from MOFs: neem, animal fat, and jatropha oil (NFJO) on a batch reactor. The project's goals were to ensure environmental benignity and encourage the use of totally biobased products.

Advancing robot-guided techniques in lumbar spine surgery: a systematic review and meta-analysis.

Background: Lumbar spine surgery is a crucial intervention for addressing spinal injuries or conditions affecting the spine, often involving lumbar fusion through pedicle screw (PS) insertion. The precision of PS placement is pivotal in orthopedic surgery. This systematic review compares the accuracy of robot-guided (RG) surgery with free-hand fluoroscopy-guided (FFG), free-hand without fluoroscopy-guided (FHG), and computed tomography image-guided (CTG) techniques for PS insertion.

Investigation of flow behaviour in the nozzle of a Pelton wheel: Effects and analysis of influencing parameters.

The performance of a Pelton wheel is influenced by the jet created by the nozzle. Therefore, a Computational Fluid Dynamics (CFD) simulation was proposed. In this study, the significant output parameters (outlet velocity, outlet pressure, and tangential force component) and input parameters (different pressure and spear locations) were examined.

Strengthening care for emergencies: what is the level of awareness and utilization of Emergency Medical Services (EMS) in FCT, Nigeria?

Background: As part of the Federal Government of Nigeria's desire to increase medical coverage among the citizenry, the National Emergency Medical Service and Ambulance Scheme (NEMSAS) was set up and piloted in the FCT in 2022. To gauge the progress so far, this study sought to assess the level and determinants of public awareness and utilization of Emergency Medical Services (EMS) among residents of the Federal Capital Territory, Abuja.

Methods: A cross-sectional study was conducted in June 2023 among 1177 respondents residing in FCT Abuja at the time of the survey.