"Screening for early detection of a disease is required to reveal groups of individuals from the general population in whom the likelihood of the disease is increased and who could benefit from further medical evaluation. The ideal screening test is high-accuracy, low-cost, non-invasive, easily repeatable, effortlessly operated by a lay-person and has minimal impact on the subject's daily activities. In the SNIFFPHONE project, we aim to tackle these requirements by integrating nano-technologies into a device attached to a mobile phone to detect disease markers from exhaled breath. This approach is based on a unique sensor array response to the breath sample, which is recorded, stored and pre-processed via the cell phone. Subsequent to the initial pre-processing, the relevant sensor response signals are conveyed wirelessly via the cellular network to an external server. Statistical pattern recognition methods are then applied on the received data in order to decipher and annotate the array's response. In general, the different statistical programs compare the responsive pattern of the sensor array to previously known samples which have been a-priori fed to the program as a training set. This analysis is then translated to a screening result harboring a level of certainty of the particular breath sample, originating from a ""Sick"" or ""Healthy"" individual. The combination of this breath analysis with additional personal information such as age, weight, etc., leads to the generation of a clinical report which is sent back to the designated receiver (e.g. specialist, family doctor). SNIFFPHONE represents a new concept addressing major societal challenges in health and well-being of the general population. We envision the SNIFFPHONE concept to serve as a novel platform from which more innovative ideas and projects may immerge. In this regard the SNIFFPHONE project has its own sustainable growth prospect.
In addition to pre-screening, the new SNIFFPHONE add-on device shall have the potential to be utilized as an on-going treatment diagnostic tool. The fact that a patient is able to take countless diagnostic measurements at different time points during the day in a practically effortless manner is a great advantage. Moreover, the wealth of data generated by these tests may be automatically processed and analyzed to generate a continues and comprehensive surveillance report to be evaluated periodically by the treating doctor. Indeed, the chain of events described above, may actually convert a person's typical every day privet life environment to a very sophisticated monitoring environment, circumventing the need for long post-treatment hospitalization periods. Besides the research and development as well as clinical units, the SNIFFPHONE project also involves four European SMEs and one big industrial company, thus fostering European multidisciplinary and competitive ecosystems.
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