Smartphone-based low cost oximeter photoplethysmography

Ahsan H. Khandoker#1, Jim Black*2, Marimuthu Palaniswami#1 # Department of Electrical & Electronic Engineering, The University of Melbourne, Melbourne, VIC 3010, Australia. E-mail:

{ahsank ,palani}@unimelb.edu.au.

* Nossal Institute of Global Health, The University of Melbourne, Melbourne, VIC 3010, Australia. E-mail: jfblack@unimelb.edu.au.

Abstract— The pulse oximeter plethysmograph waveform reflects dynamic net changes in arteriolar inflow and venous outflow of tissue bed capillaries interrogated by the oximeter light emitting diodes. In this study we have developed a simple and low cost oximeter photoplethysmograph device which has been interfaced with mobile phone through USB (Universal Serial Bus). There has been an unprecedented increase in the number of mobile phone subscribers in the developing world which has seen mobile phones used in ways not seen in the developed world. Mobile phones can be used to display the patient’s blood oxygen saturation and pulse rate, thus dramatically reducing the cost, and to provide doctors stationed on site a means of diagnosis before the need for any medical evaluation. Keywords— pulse oximetry, USB, mobile phone, photoplethysmography, light emitting diode

I. INTRODUCTION Worldwide, pneumonia kills at least 2 million people each

year, many of them children in Africa. Sadly, many of these deaths could be avoided if the disease were properly diagnosed and treated. In a modern hospital setting, physicians can use chest X-rays, lab tests, blood oxygen measurements and other diagnostic tools to distinguish between the many causes of respiratory illness. In a remote African village, few such tools are available to determine if a child’s fever and shortness of breath are caused by pneumonia, malaria or some other infectious disease. However, most health workers in third world countries do carry cell phones.

Pulse oximeter plethysmography (PPG) (sometimes referred to simply as “pulse oximetry” or “photo-plethysmogram”) is a standard method of obtaining blood oxygenation data in a non-invasive and continuous manner. Oximeter uses two wavelengths of light to solve for hemoglobin saturation. The waveforms are created by the absorption produced by pulsatile arterial blood volume, which represents the alternating current (AC) signal. The absorption produced by nonpulsatile blood, venous and capillary blood, and tissue absorption is depicted by the direct current (DC) signal [1]. An oximeter measures the oxygen content in red blood cells by measuring the absorption of red and infrared light waves as they pass through a patient’s fingertip or ear lobe. Hemoglobin, the oxygen-carrying component of blood, is often in a depleted state in people with severe pneumonia. The LEDs (light-emitting diodes)

needed for an oximeter sensor are widely available and inexpensive.

The aim of the study is to create a low cost prototype (within the budget of $20) oximeter from the inexpensive LED fingertip sensor that health workers can simply plug into their mobile phone using USB.

II. METHODS We set ourselves a nominal target of a total retail cost of

(Australian) $20 for the components of the sensor, as well as aiming to build the entire sensor from "off-the-shelf" components. Initially an analogue circuit was developed, and the signal was then digitized and passed through a microcontroller on the sensor to communicate with the USB device and ultimately the mobile phone. Comparisons were made with a commercial had-held pulse oximeter, initially with healthy adult volunteers and then with adult hospital in-patients recuperating from acute exacerbations of chronic respiratory disease. In each case measurements were made on each of the participant’s fingers, choosing the fingers in random order and the order of application to each finger randomly (i.e. prototype or commercial oximeter first). Comparisons made in this way on 10 healthy adult volunteers showed agreement to within +/-4%, with all measurements between 93 and 99%. Comparisons made on four recuperating patients showed more variation, with about one quarter of measurement pairs differing by more than 4%. It is notable that these patients had marked finger deformities (clubbing caused by their chronic respiratory illness), and the commercial oximeter was unable to provide readings in about 10% of their fingers [2]. As a result of these initial tests we decided to re-design the finger probe, aiming to accommodate more variation in finger shape without allowing light to leak around the edges. Some photos and the probe circuit have been shown in Figures 1,2, 3 &4.

A. Design of PPG sensors The hardware system shown in Figure 1 was designed to

detect the red and infrared (IR) signals obtained from photodiode’s output. As the photodiode generates current, current to voltage converters are needed to convert the generated current from photodiode to voltage and sent voltage signal to the amplifier.

Two GPIO (General Purpose Input/Output) ports from microcontroller were connected to the gates of both

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MOSFETs. If GPIO1 gives 6V, current flows through Red LED turning it ON; if the GPIO1 gives 0V, no current flows through Red LED turning it OFF. Similarly, for infrared LED, GPIO2 was used. The analog data (voltage output ) from amplifier were converted to digital data by ADC (Analog to digital converter), and stored in the RAM. Finally, digital data were transmitted to mobile phone via USB interface.

B. USB interface and data acquisition USB (Universal Serial Bus) is a popular standard for

connecting peripherals and portable consumer electronic devices such as digital cameras and hand-held computers to host PCs. The On-The-Go (OTG) Supplement to the USB Specification extends USB to peer-to-peer application. Using USB OTG technology consumer electronics, peripherals and portable devices can connect to each other (for example, a digital camera can connect directly to a printer, or a keyboard can connect to a Personal Digital Assistant) to exchange data. The USB Dual-Mode (DM) controller integrated into the Freescale's MCF51JM128 microprocessor chip provides limited host functionality as well as device solutions for implementing a USB 2.0 full-speed/low-speed compliant peripheral. Research was carried out to verify the type of USB controller of the HTC Kaiser TyTN II [3]. The handset had a Qualcomm MSM7200 with USB-OTG capabilities. The MCF51JM128 possesses also bulk, interrupt and control endpoints types, through which data is exchanged between devices. As pulse oximetry is a slow-varying signal, the bulk type was chosen. USB communication is implemented through firmware and no dedicated USB hardware controllers are necessary inside the microcontroller. The actual core operation of the firmware is quite straightforward and involves a never-ending loop -run after a procedure of initialization which involves configuring the registers in the micro-controller. Within the loop, the ADC’s registers in the microcontroller are accessed after waiting for a time equal to the sampling rate, then processing done to compute from earlier data values (normally stored in a variable array) any extra information necessary to be displayed. Finally, the data is sent through the USB host controller in the processor and out to the USB port. The loop repeats at an interval equal to the sampling rate. The USB descriptors are configured during the development stage, and not actually changed while the code is run. Figure 2 summarises this in a flowchart. StickOS [StickOS 2010; www.cpustick.com] open source firmware which runs on the MCF51JM128 microcontroller from Freescale semiconductor -has been used to digitize the PPG signal.

Fig.1 Oximeter system architecture

Fig. 2 General flowchart for the software to display the PPG signals

To display the PPG (red or IR) signals on the HTC Kaiser

TyTN II running the Windows Mobile 6.0 Classic Edition platform, a program was written using Windows 32 commands in a Visual C++ environment. The PPG on phone is shown in Figure 3. StickOS was used for the firmware in the microcontroller USB interface. This firmware loads a USB virtual COM port driver into the laptop. The author’s Visual C++ software reads and writes data to this COM port to display the PPG signals. However, a very simple program in the BASIC language can be programmed in to the microcontroller using StickOS so that the processor would know at which one of its ADC registers to receive the PPG

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data from, and how quickly it needs to send the PPG data to the USB port (the sampling rate). Figure 4 shows an example of blood oxygen saturation and pulse rate of a healthy person tested using our system.

Fig.3 Photoplethysmogram (PPG) signals on the mobile phone

Fig. 4 Display of oxygen saturation and pulse rate information on the mobile phone

III. DISCUSSIONS Mobile phone technology can provide the basis for a new

generation of affordable, easy to distribute electronic health solutions for resource-poor communities. We argued in favour of “local applications” as we do not believe that the model based on remote analysis would work in this context. In this paper, we extended mobile phone’s processing and interface capabilities with external sensors to create low-cost pulse oximeter device.

It is our experience that even people on very low incomes in developing countries are acquiring and using mobile phones. They are used for many purposes, including checking market prices and keeping in touch with relatives who migrate to urban areas - rarely for health care purposes.

Nonetheless, all but the simplest mobile phones now have operating systems, and some have very sophisticated and powerful processors. Therefore, it is possible to explore this capability and write simple applications that run on front-line health-workers’ own mobile phones, providing simple “tools” to aid in their daily activities. It seems that implementation of low-cost, high penetration “analysis, diagnosis and consultation” solutions that explore mobile phones’ processing and interfacing capabilities is achievable. These solutions will deliver simple tools to aid front-line workers in their daily activities. Typical commercial oximeter machines today cost in excess of five hundred dollars. Table 1 provides the Bill of Materials for the oximeter on mobile phone. From the total cost stated in the table, it is possible that the entire oximeter system -including the USB interface which would contain a microcontroller chip costing only a couple of dollars when bought in bulk -will cost around Australian $20.

TABLE I

COST ESTIMATE OF THE OXIMETR PPG (THE PRICE IS RETAIL PRICE FROM THOSE BRANDS)

Components Price(AUD$) Brand Microprocessor MC9S08JM60

3.05 www.freescale.com

InfraRed LED 1.35 www.farnell.com Red LED 0.86 www.farnell.com Photodiode 3.27 www.farnell.com battery 3.95 www.jaycar.com.au USB Cable 6.00 www.jaycar.com.au Op-Amp (LM324) 1.50 www.jaycar.com.au SUM 19.98

Fig. 5 The developed prototype device that will allow health workers to use their mobile phones to better diagnose and treat pneumonia and other health issues.

Mobile phones are bridging the digital divide and

transforming many economic, social, and medical realities, particularly in developing countries. With the penetration of low-cost handsets and the omnipresence of mobile phone networks, tens of millions of people who never had a computer now use mobile devices. On the other hand, trained health workers and diagnostic testing facilities are a scarce

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resource in poor countries’ rural areas, especially in Africa [4]. Despite the billions of dollars invested in health in Africa, the shortage of appropriate health workers particularly in rural areas in many countries is a major barrier to health service coverage for the poor [5]. The growing ubiquity of mobile services allows the creation of a new generation of electronic health systems based on mobile computing. Mobile Health (mHealth) is emerging as an important segment of the field of electronic health (eHealth) [6] that advocates the utilisation of mobile technology supporting the next generation health systems. We suggest that even the simplest solutions would provide a major contribution to health development in these communities. It is possible to create a range of mobile phone applications and low-cost diagnostic devices that will run on health workers’ own mobile phones, making them useful for daily activities. The environment imposes severe restrictions, however. First, resource constraints mean that we must avoid introducing new costs, whether capital or recurrent -- developing country health services have tiny per capita annual budgets! Second, limitations in specialized workforce availability mean that we cannot rely on distant experts to interpret data or provide the diagnosis. We expect to operate in areas with poor radio coverage and the applications will execute in low-end mobile devices. Finally, due to logistic limitations we must avoid the need for training to operate the solution. Therefore, we argue that a model based on data transmission for distant analysis is unlikely to work. The first working principle of developing low cost medical device is that wherever possible we should avoid creating new capital or recurrent costs. This means making minimum use of the network capabilities of the phones (no calls, no SMS, no data transfer) and concentrating on using them as tiny computers. The second principle is to make the new applications and devices as simple as possible so that they require a minimum of training and can be used by as many health workers as possible - even into the waiting room for use by relatively untrained assistants. To achieve this end the applications must look and feel as much as possible like the normal functions of a mobile phone, and ideally require no more skill than looking up a missed call or adding a new contact. (After all, people have already taught themselves how to use mobile phones without any formal training.) The third basic principle is to provide useful answers directly to the health worker in the clinic. There should be no reliance on distant experts or computer

networks, which are less likely to be available exactly when they are needed.

ACKNOWLEDGMENT This study was supported by a grant from Microsoft

External Research and Australian Research Council Research Networks on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) at the University of Melbourne. The authors would like to thank Prof Liz Sonenberg, Dr Fernando Koch, A/Prof Rens Scheepers and Mr Nay Lin Soe of Department of Information Systems and Mr Edgar Charry of Dept of Electrical Engineering of the University of Melbourne and other members of research and innovation team of low cost clinical devices for developing countries for their valuable advices, feedback and support.

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[2] J. Black, F. Koch, L. Sonnenberg, R. Scheepers, A.H. Khandoker, E. Charry, B. Walker, N. Soe, “Mobile Health Solutions for Front-Line Workers in Developing Countries”. 11th International Conference on e-Health Networking, Application & Services (HealthCom 2009), pp 89-93, Sydney, Australia, December 16-18, 2009.

[3] B. Walker, A.H. Khandoker and J. Black (2009) “Low Cost ECG Monitor for Developing Countries”, Proceedings of Fifth International Conference on Intelligent Sensors, Sensor Networks And Information Processing, pp 195-199 , December 7-10, Melbourne, 2009.

[4] World Health Organization. 2006. The global shortage of health workers and its impact. April 2006. Fact sheet 302.

[5] The World Bank. 2008. Health Workers Needed: Poor Left Without Care in Africa’s Rural Areas. 26 February 2008.

[6] R. Istepanian, S. Laxminarayan, and C. Pattichis. 2006. M-Health. s.l. : Springer , 2006. p. 623. 978-0-387-26558-2.

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