PhysioNet/Computing in Cardiology Challenge 2011

According to the World Health Organization, cardiovascular diseases (CVD) are the number one cause of death worldwide. Of these deaths, 82% take place in low- and middle-income countries. Given their computing power and pervasiveness, is it possible for mobile phones to aid in delivery of quality health care, particularly to rural populations distant from physicians with the expertise needed to diagnose CVD?

Advances in mobile phone technology have resulted in global availability of portable computing devices capable of performing many of the functions traditionally requiring desktop and larger computers. In addition to their technological features, mobile phones have a large cultural impact. They are user-friendly and are among the most efficient and most widely used means of communication. Currently there is about one cell phone for every two humans in the world.

India is experiencing a double burden of disease with persistent infectious disease coupled with increasing incidence of chronic disease. Two chronic diseases – CVD and cancer – currently account for nearly 20% of the total disease burden, which is expected to double to 40% by 2016. Unfortunately, due to a lack of adequate primary care capacity, most chronic diseases are diagnosed at an advanced stage, when the cost of treatment and rehabilitation is prohibitive for the masses, particularly the poor. This is true for other middle-income developing countries such as Brazil, China, Indonesia and South Africa as well.

India’s large population spread, in conjunction with the increase in heart-related diseases, is a public health concern that has led to a joint collaboration between Narayana Hrudayalaya (one of India‚Äôs leading health-care providers) and Sana (an open-source, student-managed, mobile telemedicine group at MIT; see http://www.sanamobile.org/). Sana’s specific objective in this venture is to enable an inexperienced nurse or paramedic to collect and transmit electrocardiograms (ECGs) from rural patients for remote analysis by cardiologists at a city hospital. While Sana has been successful in developing open-source software for transmitting and archiving ECGs through Bluetooth recording, significant obstacles still remain. PhysioNet has partnered with Sana to identify some of the crucial obstacles involved in having an inexperienced person record ECGs usable for diagnostic interpretation from a mobile device.

The aim of the PhysioNet/Computing in Cardiology Challenge 2011 is to develop an efficient algorithm able to run in near real-time within a mobile phone, that can provide useful feedback to a layperson in the process of acquiring a diagnostically useful ECG recording. At a minimum, the software should be able to indicate within a few seconds, while the patient is still present, if the ECG is of adequate quality for interpretation, or if another recording should be made. Ideally, the software should identify common problems (such as misplaced electrodes, poor skin-electrode contact, external electrical interference, and artifact resulting from patient motion) and either compensate for these deficiencies or provide guidance for correcting them.

Data to support development and evaluation of challenge entries are being collected by the Sana project, and will be provided freely via PhysioNet. The data set will include ten-second recordings of twelve-lead ECGs; age, sex, weight, and possibly other relevant information about the patients; and (for some patients) a photo of the electrode placement taken using the mobile phone. Although some of the recordings will be identified initially as acceptable or unacceptable, challenge participants and others interested will have an opportunity to assist in establishing a “gold standard” classification of the quality of the recordings in the challenge data set.

Please visit this page (http://physionet.org/challenge/2011/) for further details that will be posted during the next several months. Sample recordings will be posted in October 2010, and the complete challenge data set will be posted in mid-January 2011. Participants may enter the challenge by completing a classification task to be described in the January posting. Participants wishing to be eligible for Challenge awards will also need to submit an abstract describing their work on the Challenge no later than 1 May 2011, and must attend Computing in Cardiology 2011 (18-21 September 2011 in Hangzhou, China) to present their work and discuss their findings with other participants and CinC attendees.

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