Healthcare technologies for low resource settings (session 2): Challenges and solutions in delivering effective healthcare in low resource settings
Leading on from session one, session two delved into the people aspect of delivering effective healthcare in environments with low resources faces many challenges.
Some factors which may be detrimental to the provision of adequate healthcare in low resource settings include lack of sufficient financial resources, facilities and infrastructure; insufficient and/or inadequately educated and trained staff; lack of test equipment, manuals and spare parts; inappropriate equipment donations; large number of healthcare equipment out of service; unreliable power and water supplies; political instability and war.
Enhancing Family Planning Services through Digital Health Education: A Collaborative Initiative between DKT Myanmar and Z-waka
Speaker Dr. Khine Pwint Nwe, Founder and CEO z-waka
Myanmar faces significant challenges in reproductive health, exacerbated by ongoing political instability and the deterioration of the public healthcare sector. Limited access to family planning services has contributed to high rates of unintended pregnancies and maternal health issues. The need for effective family planning education and services is critical, particularly in low-resource settings where traditional healthcare delivery methods are strained.
The objective is to evaluate the impact of a digital health education program on the knowledge and practices of healthcare providers (HCPs) in family planning, and to assess the feasibility and effectiveness of such interventions in low-resource settings.
Talk 2: Enhancing Theta Rhythms in Dementia Rehabilitation Through Virtual Reality: A Machine Learning Approach Inspired by Hippocampal Oscillation Studies
Speaker: Thathsara Nanayakkara, Scientific Researcher, Pukyong National University
The increasing prevalence of dementia, particularly among the elderly, poses significant challenges to healthcare systems worldwide, especially in low-resource settings. This study addresses the urgent need for innovative and affordable interventions by exploring the potential of Virtual Reality (VR) combined with machine learning to enhance cognitive rehabilitation in individuals with Mild Cognitive Impairment (MCI) and early-stage dementia.
Authors: Prof. Byeong-il Lee
Talk 3: Evaluation of the applicability of ECG signals synthesized from PPG signals by open-source technologies to the real-world scenario of detecting obstructive sleep apnoea events
Speaker: Fabian Degen, B. Sc. Computer Science student at the Technical University of Munich
Photoplethysmography (PPG) is a non-invasive and cost-effective technique that measures cardiac physiology utilizing optical methods. Due to the widespread availability of PPG in consumer wearables, it is highly relevant and beneficial to be able to make health-based predictions on the grounds of this data, especially considering the high prevalence of cardiovascular diseases (CVDs). However, Electrocardiography (ECG) still remains the gold standard for predicting cardiovascular diseases. This study evaluates open-source models that synthesize single-lead ECG data from PPG data in both quantitative and qualitative terms. After selecting the best-performing model on a number of datasets, this study then tests the applicability of the synthesized ECG signals to real-world scenarios by training a model that detects obstructive sleep apnoea events on purely synthesized ECG data and comparing the performance to a model trained on real ECG data.