Inspiration

Have you ever had shortness of breath, a high temperature, and a really dry cough? Well, I am sure you might say you had COVID-19. In fact, 20% of these cases are asymptomatic.

You might not know you are infected!

What if there was a time where you never had to go to a doctor to get checked up, to find what you had?

We would like to build the much needed medical tricorder of our time, to automatically diagnose and screen infectious diseases remotely without the patient's intervention.

The problem our project solves

COVID-19 has impacted the lives of literally everyone on the planet. As such we now live in a different world, and even beyond the COVID-19 effective preventative measures need to be put in place in all public settings including hospitals, airports, hotels, workplaces, and so on. Our vision is to build a screening machine that could be used readily for the screening of diseases. Our final product will look something like a conventional metal-detector chamber installed at airports, but will the capability to screen people for diseases and infections. For this to be possible, none of the existing methods, include X-Rays/CT/PET/MRI etc, can be used as they all involved the use of ionising radiation and hence cannot be used in public spaces. Not to mention these solutions are bulky and expensive in addition to having long scan times to produce their results.

Our solution utilises harmless non-ionising RF radiation, with emission levels on par with cellphones, ensuring the complete safety of the public and the machine operator. We plan to initially focus on the airport screening application, and are hoping that our product will help open up the airports once again. After proving the effectiveness of our product on airports, we plan to scale up to other immediate verticals including hospitals and workplaces. In this way we are aiming for a huge global-scale impact through our products.

What it does

Our Solution is an AI-powered remote/non-invasive Telediagnostic detection and screening tool for diseases and infections, saving trillions of pounds and millions of lives to effectively diagnose late-stage COVID-19. Our software tells you the percentage chance of having COVID-19 as well as relay vital information to the primary care specialist for further diagnosis. Our key differentiator from other AI software is that our powerful software can successfully distinguish between bacterial and viral infections.

In the hardware part, we plan to build a handheld portable microwave tomography system based on impulse radio ultrawideband (UWB) radar technology. Microwave tomography is the only non-ionising tomography technique which is not only safe for human beings but also is much more compact, cheap and fast. It generates images on par with CT scans to quickly image the internal human organs for on-the-spot decision making by health professionals, cutting the wait out of lengthy conventional tomography procedures using expensive equipment.

How we built it

We are using Imagenet to do transfer learning on 1000+ CT and X-Rays scans. With an API using Flast and Node.JS to serve data from our API to doctors/frontline staff via our Web App.

In the hardware part, we plan to build an impulse radio ultrawideband (UWB) radar based handheld microwave tomography system. Microwave tomography is the only non-ionising tomography technique which is not only safe for human beings but also is much more compact and cheap.

Challenges we ran into

Getting contacts in the healthcare industry and space has been a challenge to validate our idea, which we have partially overcome by interviewing two doctors and one clinical pharmacist until now.

Our further challenges include working with hospitals and the governments to guide the development of our product. Any contacts will be valuable.

Getting approval from the medical boards and the legal compliance will be the key challenges to address.

Accomplishments that we're proud of

We believe we are the best people to build this tech, as Kashif has a PhD in Radar technology with 13 publications and pioneered Radar-based remote telemetry technology for pedestrian safety, for which he has won the British Engineering Excellence Award in 2015.

Cyril has 5 years of experience in building startups. He worked Human-Computer Interaction Lab and built software for screening anxiety/depression and physical therapy that went on to get funding from the NSF and NIH. He has 3 patents issued with the design and software of Unmanned Aerial Vehicles.

What's next for TeleDoc

We are part of Entrepreneur First Accelerator and looking to take our product to market according to the following roadmap:

Jun 2020: AI-powered COVID-19 triage tool MVP release

Sep 2020: Radar-based remote pulse/heart-rate monitor prototype release. Also, AI triage tool final release.

Dec 2020: Radar-based remote pulse/heart-rate monitor final release. Also, Radar-based remote blood pressure monitor prototype release

Mar 2021: Radar-based remote blood pressure monitor final release. Also, Radar-based remote blood glucose monitor prototype release

Jun 2021: Radar-based remote blood glucose monitor final release. Also, Radar-based remote chest wall dynamics monitor prototype release

References

J. Marimuthu, K. S. Bialkowski and A. M. Abbosh, "Software-Defined Radar for Medical Imaging," in IEEE Transactions on Microwave Theory and Techniques, vol. 64, no. 2, pp. 643-652, Feb. 2016.

Paulson, C. N., Chang, J. T., Romero, C. E., Watson, J., Pearce, F. J., & Levin, N. (2005). Ultra-wideband radar methods and techniques of medical sensing and imaging. In B. M. Cullum, & J. C. Carter (Eds.), Proceedings of SPIE - The International Society for Optical Engineering (Vol. 6007). [60070L] [https://doi.org/10.1117/12.630004]

T. Lauteslager, M. Tømmer, T. S. Lande and T. G. Constandinou, "Coherent UWB Radar-on-Chip for In-Body Measurement of Cardiovascular Dynamics," in IEEE Transactions on Biomedical Circuits and Systems, vol. 13, no. 5, pp. 814-824, Oct. 2019

Y. Han, T. Lauteslager, T. S. Lande and T. G. Constandinou, "UWB Radar for Non-contact Heart Rate Variability Monitoring and Mental State Classification," 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Berlin, Germany, 2019, pp. 6578-6582.

Vejella, Sujitha. “A MEMS BASED MICROWAVE PIXEL FOR UWB RADAR BASED 3-D DIAGNOSTIC IMAGING.” (2017).

Lee, Y., Park, J., Choi, Y. et al. A Novel Non-contact Heart Rate Monitor Using Impulse-Radio Ultra-Wideband (IR-UWB) Radar Technology. Sci Rep 8, 13053 (2018). https://doi.org/10.1038/s41598-018-31411-8

Semenov S. Microwave tomography: review of the progress towards clinical applications. Philos Trans A Math Phys Eng Sci. 2009;367(1900):3021–3042. doi:10.1098/rsta.2009.0092

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