Introduction to Biosignals Dr. Gari D. Clifford Head: Intelligent Patient Monitoring Group...

Introduction to Biosignals Dr. Gari D. Clifford Head: Intelligent Patient Monitoring Group University Lecturer & Associate Director Centre for Doctoral Training in Healthcare Innovation Institute of Biomedical Engineering Department of Engineering Science University of Oxford [email protected]

Todays course A bit of end-of-week fun... Four short lectures this morning: Me Why Affordable Healthcare Technology? Aoife Physiology & Heart Sounds Marco Blood Pressure Mauro Pulse Oximetry And a lab in the afternoon on these three signals

But first... Why these signals? They are fundamental physiology Theres so much you can do with them! Asthma, COPD, CVD,... They illustrate an important point: There is no correct answer in medicine (This is the point of todays lectures) They are cheap to collect! ... and healthcare spending is making us bankrupt

G. D. Clifford Health Care spending Per Person 2007 Per capita health care spending in poorer countries is ~100 times lower than higher GDP countries Healthcare quality is not f (spending) WHO rankings US 37 th (Costa Rica is 36 th !) Germany 25 th Canada 30 th UK 18 th Mexico 61 st China 144 th India 112 th http://www.photius.com/rankings/healthranks.html The poorest have the worst deal!

Why?...

G. D. Clifford 1. Poor Technology & Infrastructure in Resource-Poor Settings for Health Care Old legacy hardware & instruments Generally paper notes, static information no QA! Poor communication channels Poor drug storage and supply Poor waste disposal Poor transport Intermittent electricity Information shortage Skills shortages Medical errors! Image Robert Malkin / Annu. Rev. Biomed. Eng. Malkin, RA, Design of Health Care Technologies for the Developing World Annu. Rev. Biomed. Eng. 2007. 9:56787

G. D. Clifford Ad-hoc medical facilities Images Gari Clifford, Creative Commons License - http://creativecommons.org/licenses/by-nc-nd/3.0/us/ Free-market without regulation / standards Out of calibration, incorrect supplies, little training

2. Too few trained medical people....

G. D. Clifford Global Maps: Peters Projection Each country is drawn in proportion to its relative surface area (normal world map erroneously enlarges countries nearer the poles.)

G. D. Clifford Global Maps: Population 2002 Each country is drawn in proportion to its relative global population

G. D. Clifford Global Maps: Working Physicians 2004 Relative proportions of physicians working in each country

G. D. Clifford Global Maps: Population 2002 Each country is drawn in proportion to its relative global population

G. D. Clifford 3. Spiraling costs Ageing populations & chronic disease epidemics Increased awareness of diseases - obligation to treat Increased demands for heroic interventions Lack of preventative measures / compliance Increased complexity of treatments & diagnostics => more infrastructure & training NOT SCALABLE!

G. D. Clifford Our solution? Smart phones, dumb (cheap) sensors

G. D. Clifford Design principles Sensors sourced in-country! Use USB for comms and power Clever signal processing on the phone (its built for it!) Upload directly to EMR (reduces errors & allows data mining) Use in-built sensors Interested?: ewh-oxford.org

G. D. Clifford What now? A quick 10m break Then Aoife will introduce the cardiovascular system & explain heart sounds. Then Marco will explain how we can obtain blood pressure measurements without actually putting a sensor into the blood stream! And then Mauro will explain how to find out how much oxygen is in the blood stream, just by shining a light at you!

G. D. Clifford Break Time

G. D. Clifford Recent trends (2010) 739 million mobile users in China, >99.5% coverage 277 million Chinese accessed the Internet through mobile devices in June 2010 (up 18.4% in 6 months!) China Mobile projects 957 million mobile Internet users in 2014 Android handset sales grew 886% worldwide during 2010. (The closest competitor the iPhone - only grew 86% in the same period.)

G. D. Clifford mHealth Projects in my group Open Source Telemedicine Infrastructure for COPD monitoring (SanaMobile.org) Sleep Monitoring ECG Monitoring Heart Sounds for TB Pulse Oximetry & Respiration Analysis; Apnea of Prematurity BP monitoring for hypertension & CVD risk predictor HIV drug-drug interactions

G. D. Clifford 5 Blood Pressure Monitor Phone replaces all expensive parts (Joao, Marco, Mauro, Carlos, David & Arvind) Use cheap BP cuff remove costly analogue manometer Insert cheap electronics Freescale MPxx5050 family Regular Blood Pressure cuff USB 2.0 full-speed, 10- bit ADC MCU. Microchip PIC18 series Android Phone with USBOTG

G. D. Clifford Standard Oscillometric Method Humans are error-prone at reading BP Machines are consistent Cuff pressure signal and oscillation waveform (Lin.C.T et al, 2003) MAP @ peak, SBP @ 70% of peak, DBP @ 50% of max

G. D. Clifford User Interface

G. D. Clifford Assisted interface

G. D. Clifford Integration with Health Records

G. D. Clifford Summary & Future Opportunity to transform healthcare Low cost, high frequency health monitoring (at Nyquist?) using mobile phones Portable, integrated personalised health record at the back-end Local calibration of equipment Multiple independent expert labelling of medical events Train algorithms to do most of the diagnostics & provide feedback to improve data

G. D. Clifford Appendices

G. D. Clifford What is wrong with data analysis in healthcare? Weve essentially digitized a paper process Technology is interfering with data recording, slowing the process Transcribing data with time delays leads to clinically significant errors

G. D. Clifford Under-sampling & under- automating Compare nurse-verified IBP with re-derived IBP from original waveform Nurse samples every 1- 120 minutes (median 60 min, IQR 30 min) Nurse over-estimates BP by av of 20 mmHg AND hypotensive events missed for av 4 hours Repeated transient hypotension (linked with mortality) lasts minutes Hug et al.Critical Care Medicine,2010

G. D. Clifford How can we satisfy Nyquist and make the data more honest? Obviously we could sample more frequently Impractical, so sample irregularly! (.. to beat average Nyquist) Avoid human data transcription & deletion by using personal monitoring with low cost sensors Even so how are we going to synthesise all this new data? We do not cope with existing data This is a GLOBAL opportunity to reform healthcare data analysis

The global burden of disease & injury WHO: In 2030 Disability-Adjusted Life Years (DALYs) lost will be: 20% of total will be from communicable diseases, maternal and nutritional conditions (c.f. 40% now) 66% will be from non-communicable disease (all income groups globally) The Global Burden of Disease: 2004 Update. World Health Organization. 2004.

Healthcare in the future 9 out of the 10 top burdens on our healthcare systems in 2030 are likely to be noncommunicable diseases Basic issues are diagnostics, treatment delivery (supply chains) and compliance The lack of trained healthcare workers in resource poor regions means we need to deliver healthcare through telemedicine Mobile phones are almost ubiquitous and represent the cheapest method for transmitting and recording information to and from remote locations They solve the supply chain issue!

G. D. Clifford Where is the need/opportunity largest? The more resource-constrained the region, the greater the need The Guatemalan highlands The Scottish Islands Rural China, etc These places also offer the greatest opportunity They have the biggest incentive to drive change Smaller financial incentive for large companies to push traditional economics Lack of regulation : need to self-regulate before politics & industry coalesce The consumer or patient will demand (and pay for low-cost healthcare) and take responsibility for their own care (and medical data) How will they do this? Look at what is changing the fastest

World Mobile (GSM) Coverage, Jan 2005 (from http://www.coveragemaps.com/gsmposter.htm)

World Mobile (GSM) Coverage, Jan 2007 (from http://www.coveragemaps.com/gsmposter.htm)

G. D. Clifford TiGo in Guatemala, Honduras & El Salvador http://alum.mit.edu/www/gari/ TiGo GSM Coverage: Image TiGo Guatemala http://tigo.com.gt/

G. D. Clifford Global Maps: Public Health Spending 2002 Each country is drawn in proportion to its relative global spending on public health http://alum.mit.edu/www/gari/

G. D. Clifford Global Maps: Private Health Spending 2002 Each country is drawn in proportion to its relative global spending on private health

G. D. Clifford The global problems with healthcare Spiraling costs Ageing populations & chronic disease epidemics Increased awareness of diseases - obligation to treat Increased demands for heroic interventions Lack of preventative measures / compliance Increased complexity of treatments & diagnostics => more infrastructure & training Lack of longitudinal medical records (& portability) Data! Lack of standards & monitoring of compliance Interchangeability / interoperability Lack of data collection Artifacts & noise in data (Lack of data fusion) Medical errors Human fallibility (tiredness, confusion, overwork, transcription) Contradictory or missing information (broken equipment, different manufacturers) Drug issues (interactions, incorrect dosage/drug, counterfeit) Errors of omission (forgetting to perform tests, treatment compliance, losing results) Training (Lack of suitable training courses or available skilled professionals) Too few trained medical professionals With poor communication & physical infrastructure / equipment

G. D. Clifford Changing landscape of communication devices Smart phones cross over with cheap phones

G. D. Clifford Growth of mobile subscriptions left - Mobile cellular subscriptions by level of development in 2000, 2005 and 2010*; right - Mobile cellular subscriptions per 100 inhabitants between 2000-2010*. (International Telecommunication Union Statistics )

Moving to patient-centric care Mobile phone infrastructure to capture and transmit Written/typed notes Voice notes Images (e.g. photos, radiologic, etc) Videos (e.g. ultrasound, ECHOs) Removing technology from being a barrier between patient and doctor its now a (passive?) intermediary Phone=security (something you have/know) Access to a longitudinal, portable medical record to which you can add information Automatically notes your activity and provides feedback moving to proactive care Your patterns can be compared with your past and 6billion+ others rare events now have precedents.

Automated diagnostics the mobile phone as a medical instrument Suite of sensors + USB connections Ubiquitous connections to database and network of experts Product of expert labeling Sufficient computational power for automated or semi-automated diagnosis and treatment recommendations http://sanamobile.org/demo.html

Introduction to Biosignals Dr. Gari D. Clifford Head: Intelligent Patient Monitoring Group...

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