Concept Note : T he Integrated Wearable General Check - Up System Project Title - SmartCheck50+: A Low - Cost Integrated Wearable System for Automated General Health Screening in L MICs 1. P roject Summary Adults over 50 in LMICs face a growing burden of diseases, including cardiovascular diseases , diabetes, respiratory disease, metabolic disorders, and multiple cancers. In almost all cases, e arly detection significantly improves outcomes, yet access to routine general health screening is limited by cost, doctor shortages, and logistical barriers. Our SmartCheck50+ project proposes an integrated wireless sensor wearable capable of periodically collecting key clinical vitals essential for an annual general check - up. Data is transmitted securely to a cloud - based analytics platform that screens for locally prevalent diseases using AI - powered algorithms. Personalized results and recommendations are sent digitally to patients and — when needed — to local clinicians. This system will democratize preventive healthcare and enable millions of adults to access early detection without visiting a clinic or making an appointment with a doctor 2. Problem statement In many LMICs a large proportion of chronic conditions — especially cancers and other non - communicable diseases — are diagnosed at an advanced stage, limiting treatment options and worsening outcomes. Systematic reviews and regional studies consistently docume nt long patient and health - system delays and a prevalence of stage II – IV diagnoses for common cancers in LMIC settings, with many papers concluding that late presentation is a dominant driver of high mortality [1] Health workforce shortages compound the problem: doctor and physician densities in much of sub - Saharan Africa and other low - resource regions are far below the levels seen in high - income countries. World Health Organization and regional analyses show very l ow numbers of medical doctors per 10,000 population in many countries and a clinician density that, in practical terms, translates into extremely high patient loads and limited access to routine preventive visits. The direct and indirect costs of routine medical visits and diagnostic tests create an additional barrier to regular check - ups for many households in LMICs. Multiple studies of care - seeking and health - service access show that out - of - pocket costs, travel an d lost income are common reasons people delay or simply ignore preventive care; the WHO and regional agencies also emphasize that much of the burden of NCDs falls on households because preventive services and diagnostics are insufficiently available or aff ordable [2] In fact, a significant proportion of premature deaths from NCDs is considered preventable or avertable through earlier detection , risk - factor control , and timely treatment . Global analyses of preventable and treatable years of life lost (YLLs) for major NCDs report that a large share of the premature burden could be avoided with improved prevention , earlier diagnosis and better access to care — findings the WHO and Lancet analyses have highlighted when quantifying preventable and treatable components of NCD m ortality [3] Finally, although wearable devices and digital health tools are increasingly available, multiple recent reviews and implementation studies note important limitations for LMIC use: many devices remain relatively costly, most commercial wearables are not integrated or optimized for the specific disease burdens and contexts of LMICs, integration with local health - system workflows is limited, and not all consumer wearables meet clinical - grade standards required for diagnostic decision making. These gaps — cost, c ontextual fit, health - system integration , and measurement quality — are commonly cited as barriers to using wearables for routine medical screening in low - resource settings [4] 3. Project Objectives Th is project has five key objectives: 1. Develop a cost - effective integrated wearable capable of capturing clinically meaningful vitals , including : - Heart rate & heart rate variability - Blood pressure - Oxygen saturation (SpO₂) - Respiratory rate - ECG - Body temperature - Blood glucose (non - invasive or minimally invasive) - Activity quality - Optional add - ons: Saliva , stool , sweat , and urine tests for cancer screenings (depending on the availability of suitable sensors) 2. Develop or acquire a cloud - based screening/diagnostic engine to : - Screen for indicators of cardiovascular disease, metabolic disorders, respiratory conditions, arrhythmias, and early cancer risk , etc. - Provide region - specific risk scoring aligned to local disease burdens. 3. Deliver actionable results directly to users or clinicians via: - WhatsApp (with integration ) - Mobile app - SMS - Printed reports at partner clinics 4. Integrate with national health systems and local clinics for follow - up and referral 5. Develop an additional system to track Improvement in early detection rates for adults over 50 and provide related reports The project intends to improve early detection rates by at least 3 0% within three years 4. Proposed System Architecture 1. Wearable Device Layer - Networked and integrated multi - sensor package (e.g., smart vest + optional patch) , - Low - energy Bluetooth & GSM - compatible modules , - Local, temporary data storage for offline environments. 2. Transmission Layer - Mobile phone connectivity via app , - Direct SIM - based transmission for populations without smartphones 3. Cloud and Analytics Layer - Secure encrypted cloud storage , - AI - driven diagnostic algorithms - Automatic risk stratification (low/medium/high risk) Examples of d isease - specific screening modules: - Colon cancer (based on integrated stool test + symptom data) - Hypertension - Diabetes - COPD risk - Atrial fibrillation - Etc. 4. User and Clinician Interface - Simple multi - language dashboard , - Alerts for urgent abnormal findings , - Referral pathway to local clinics (public or private) - Integration with clinic management systems (optional) 5. Expected Impact 1. Health System Impact - Reduced burden on clinics through digital pre - screening , - Increased early detection of silent killers , - Improved resource allocation (clinics only see high - risk individuals) , - Lower long - term treatment costs for dreadful diseases (e.g. cancer). 2. Community and Population - Level Impact - Empowered patients managing their health at home , - Reduced travel and appointment barriers , - Increased life expectancy for adults over 50 (MDGs), - Improved quality of life for aging populations in LMICs 3. Economic Impact - Lower the sky - rocketing health expenditure , - Reduce burden on the already - stretched health workers , - Job creation for local distribution, training, and tech support for the new system. 6. Proposed Implementation Strategy Phase 1: Feasibility & Wearable Prototyping (0 – 9 months) - Identify design partners for wearable sensors , and start on the wearable device and transmission layer s , - Select disease screening algorithms for LMIC needs , - Conduct a pilot with 200 – 500 participants in South Africa Phase 2 : System Integration & Validation (6 – 18 months) - Clinical validation studies , - L ocali s ation to regional disease burdens , - Data privacy compliance (POPIA, GDPR, HIPAA , where relevant) Phase 3 : Implementation and Scale - Up ( 18 – 36 months) - Finalise d istribution channels (through shops, clinics, pharmacies, insurance schemes , etc.), - Integration with national health screening programs , - Make the model and system available to other African countries. 7. High - Level Estimated Budget Developing an adoptable SmartCheck50+ device and related cloud infrastructure demands substantial, upfront investment. A compliant , clinical - grade wearable cannot be produced through piecemeal funding or improvised laboratory work. Significant R&D, regulatory preparation, and multidisciplinary expertise are required before meaningful prototyping can even begin. Dedicated fundraising for BMERC to host this massive project is necessary to assemble the specialised teams and resources this innovation demands. Total Estimated Budget: R 32.5 million – R 48.7 million (Timeframe: 36 months) This estimate is based on comparable international digital health device development costs, African medical device regulatory requirements, UCT overhead structures, sensor integration costs, cloud/AI development budgets, and clinical validation study norms Basically, the budget is presented in 5 categories as specified : A. Core R&D and Prototyping (Year 1 – 2) Line Item Estimate (ZAR) Notes Hardware design, PCB development R 2,8 – 4,5 million Includes custom PCB fabrication, low - energy communication modules, low - volume testing batches Sensor procurement & integration R 3,5 – 6,2 million ECG, PPG, BP, SpO₂, temp, respiration, accelerometer, possible non - invasive glucose sensors Mechanical design & enclosure prototyping R 1,2 – 2,0 million 3D printing iterations, water resistance, durability testing Firmware development R 1,5 – 3,0 million BLE/GSM stack, edge processing, secure data handling Testing equipment for BMERC labs R 900,000 – 1,8 million Calibration devices, biostandards, phantom systems Subtotal R 9,9 – 17,5 million B. AI/Cloud Platform Development (Year 1 – 3) Line Item Estimate (ZAR) Notes Backend infrastructure + cloud costs (3 years) R 1,5 – 2,5 million Compute, storage, encryption AI/ML algorithm development R 3,2 – 5,5 million Signal processing, disease - screening classifiers, validation Line Item Estimate (ZAR) Notes Mobile app (Android + iOS) R 1,8 – 2,6 million Multi - language (11 to 12 languages for South Africa) , LMIC - friendly UI Data privacy, POPIA/HIPAA - grade architecture R 900,000 – 1,6 million Audit trails, consent, and cybersecurity Subtotal R 7,4 – 12,2 million C. Regulatory, Quality & Compliance (South Africa + potential CE Mark) Line Item Estimate (ZAR) Notes ISO 13485 quality management system set - up R 1,8 – 3,0 million 12 – 18 months to implement Biocompatibility & safety testing R 650,000 – 1,1 million ISO 10993, electrical safety Software validation (IEC 62304) R 600,000 – 1,0 million Required for clinical - grade software Technical file & regulatory submission fees (SAHPRA) R 300,000 – 500,000 Includes legal consultation Subtotal R 3,3 – 5,6 million D. Clinical Validation (Pilot & Extended Study) Line Item Estimate (ZAR) Notes Pilot study (150 – 250 participants) R 1,8 – 2,5 million Ethics approval, CRFs, nurse support Multi - site clinical validation (600 – 1000 pts) R 3,5 – 5,0 million Partner clinics, ECG/BP benchmarking Data management & statistical analysis R 700,000 – 1,2 million Academic + external analyst support Subtotal R 6,0 – 8,7 million E. Multidisciplinary Team (36 months) BMERC will require contributions from: - Biomedical engineers - Software engineers - Signal processing specialists - AI/ML scientists - Clinicians (GPs, cardiology consultants, public health specialists) - Regulatory consultants - Industrial , UI/UX designers , and adoption specialists - Project coordination management - Community engagement & health economics specialists F. Contingencies / UCT Overheads (15 – 20%) R 4,1 – 6,2 million TOTAL PROJECT COST (36 months) R 32.5 million – R 48.7 million (≈ USD 1.7 million – USD 2.7 million ) 8. Conclusion SmartCheck50+ has the potential to revolutionize preventive healthcare for millions of older adults in LMICs. By combining low - cost wearables, digital diagnostics, and locally tailored disease screening, the system could offer a scalable, sustainable pathway toward early detection, improved outcomes, and stronger health systems. The proposed solution directly supports the WHO Global NCD Action Plan and aligns with Africa CDC’s Digital Health Transformation Strategy. While informal design and development methods by one individual with limited funding may eventually bring this innovation into clinical practice, it would take many years to realize, with high potential for failure. The time is right for a bold, contextually tailored digital screening innovation at BMERC — one that brings annual check - ups to everyone , especially for those most at risk. 9. REFERENCES [1] N. R. Brand, L. G. Qu, A. Chao, and A. M. Ilbawi, “Delays and Barriers to Cancer Care in Low - and Middle - Income Countries: A Systematic Review,” Oncologist , vol. 24, no. 12, pp. e1371 – e1380, Dec. 2019, doi: 10.1634/theoncologist.2019 - 0057. [2] B. Dawkins, C. Renwick, T. Ensor, B. Shinkins, D. Jayne, and D. Meads, “What factors affect patients’ ability to access healthcare? An overview of systematic reviews,” Oct. 01, 2021, John Wiley and Sons Inc . doi: 10.1111/tmi.13651. [3] C. Frick et al. , “Quantitative estimates of preventable and treatable deaths from 36 cancers worldwide: a population - based study,” Lancet Glob Health , vol. 11, no. 11, pp. e1700 – e1712, Nov. 2023, doi: 10.1016/S2214 - 109X(23)00406 - 0. [4] M. H. Swahn et al. , “Advancing mHealth Research in Low - Resource Settings: Young Women’s Insights and Implementation Challenges with Wearable Smartwatch Devices in Uganda,” Sensors , vol. 24, no. 17, Sep. 2024, doi: 10.3390/s24175591.