5G and Me: And the Golden Hour

What is the “Golden Hour”?

The Golden Hour is within the first hours of the Stroke or acute CHF or MI. Every minute that the blood flow is not restored in the brain (where it is lost), nearly two million additional nerve cells die. Therefore, it becomes imperative for the patients with stroke to get to necessarily equipped care locations.

In this blog we will discuss how 5G technology has a profound effect on the golden hour and how this technology can save lives.

Who does Stroke and CHF effect?

We just celebrated a grim annual event — the World Stroke Day on 29th October. Combined, Stroke, CHF (Congestive Heart Failure) and Myocardial Infarctions (MI) are the leading causes of death and disability in the world.

A “Stroke” happens when the blood supply to a part of the brain is cut off — without blood, these brain cells get damaged and perish. Its severity depends on which part of the brain is affected and can affect a person’s mobility, speech, and the ability to think and feel.

Congestive Heart Failure and Myocardial Infarction are chronic conditions where the heart operates less efficiently than normal. The circulatory system cannot carry oxygen and other nutrients to the body, causing the heart to stretch or stiffen, causing the kidneys to retain more fluid and salts.

Globally, 1 in 4 people over the age of 25 are at risk for stroke during their lifetime In the US, the incidence of and deaths from Heart Disease has increased within the past 10 years (especially in rural areas). It is the No. 1 killer in the US (and almost all other countries in the world):

The Current Problem:

Since most care is moving away from the hospital and to the home (or remote clinic), Point-of-Care Imaging (PoCI) will become one of the most important diagnostic areas of the future.

Even though Head CT (computed tomography) is the standard method to determine stroke and identifies a wide range of abnormalities, ultrasound is slowly becoming the go-to modality for remote imaging, especially for carotid atherosclerosis, especially using Transcranial Color-Doppler imaging (TCDI). Color Doppler imaging is also advantageous for CHF and MI assessment at the point of care.

Current ambulance platforms are modern marvels with some of the latest instrumentation on-board. However, from a data perspective, they do not utilize the knowledge and imaging available at their hub locations (usually the hospital). Most current techniques for remote ultrasound (tele-sonography) use asynchronous transmission which have incurred significant transmission delays.

Reliability has been a central theme as variable levels of image degradation have been reported, which resulted in reduced sensitivity and specificity. Outcomes including image quality and transmission reliability suggest it may be problematic to transmit real time images from an ambulance. In situations like this, every minute matters so it has to be both accurate and in real time.

The Solution 5G Brings:

The connected ambulance 5G network slicing concepts were demonstrated at the Mobile World Congress (MWC) in Barcelona, Spain in Feb 2019 by Dell EMC Cork Centre of Excellence (CoE).

Network slicing is a type of virtual networking architecture similar to software-defined networking (SDN) and network functions virtualization (NFV) whose goal is software-based network automation. This technology allows the creation of multiple virtual networks on a shared physical infrastructure.

There are many algorithms that measure and score Stroke and CHF: Emergency Heart Failure Mortality Risk Grade (EHFMRG), the NIH Stroke Scale (NIHSS), Cincinnati Prehospital Stroke Scale (CPSS), Los Angeles Pre-hospital Stroke Scale (LAPSS) and Face, Arm, Speech Time Test (FAST), etc.

The goal for the future of connected care in emergencies would be to identify the conditions for Stroke, CHF & MI; measure and score at site, predictively collect Electronic Medical Record (EMR) metadata in conjunction with specific image studies via DICOM (Digital Imaging and Communications in Medicine) and combine this with the metadata from disease-specific epidemiological studies for that geographic region — all within the “golden hour”. This combinatorial analysis at the “point of care” is the future and can prevent disability and death at scale — especially since not all the ambulance visits are emergencies.

Dell Technologies is leading the path on the journey to 5G and partnering with Telcos as their build their networks. We are committed to bringing this technology to the market because we believe in the life-saving capabilities of 5G.


  • The Global Burden of Disease 2016 Lifetime Risk of Stroke Collaborators, “Global, Regional, and Country-Specific Lifetime Risks of Stroke, 1990-2016″, NEJM (Dec 2018),https://www.nejm.org/doi/full/10.1056/NEJMoa1804492
  • The US Centers for Disease Control (CDC). “Heart Disease and Stroke Maps”, https://www.cdc.gov/dhdsp/maps/quick-maps/index.htm (Last viewed 31Oct2019)
  • Marsh-Feiley G, Eadie L, Wilson P (2018), “Telesonography in emergency medicine: A systematic review.”, PLoS ONE 13(5): e0194840, https://doi.org/10.1371/journal.pone.0194840
  • Bøtker et al., “The role of point of care ultrasound in prehospital critical care: a systematic review.”, Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine, (2018) 26:51, https://doi.org/10.1186/s13049-018-0518-x
  • Ketelaars et al. “ABCDE of prehospital ultrasonography: a narrative review.”, Critical Ultrasound J (2018) 10:17, https://doi.org/10.1186/s13089-018-0099-y
  • Saxena et al., “Imaging modalities to diagnose carotid artery stenosis: progress and prospect.”, BioMed Eng OnLine, (2019) 18:66, https://doi.org/10.1186/s12938-019-0685-7
  • Herzberg et al., “Prehospital stroke diagnostics based on neurological examination and transcranial ultrasound.”, Critical Ultrasound Journal 2014, 6:3, http://www.criticalultrasoundjournal.com/content/6/1/3
  • Marsh-Feiley G, et al., “Paramedic and physician perspectives on the potential use of remotely supported prehospital ultrasound.”, Rural and Remote Health 2018; 18: 4574. https://doi.org/10.22605/RRH4574

About the Author: Sanjay Joshi

Sanjay Joshi is Industry CTO Healthcare at the Dell Global CTO Office. Based in Seattle, he has spanned the gamut of life-sciences from clinical and biotechnology research to healthcare informatics to medical devices. A "skunkworks" engineer and informaticist, he defines himself as a "non-reductionist" with a "systems view of the world.” His current focus is a systems-level understanding of Healthcare, Genomics, Proteomics, Microbiomics, Imaging and IoT processes, and data infrastructures. Recent experience has included AI platforms, data management and instruments for Electronic Medical Records; Proteomics and Flow Cytometry; FDA and HIPAA verification and validation; Lab Information Management Systems (LIMS); Translational Genomics research and Imaging. Sanjay holds a patent in multi-dimensional flow cytometry analytics. He began his career developing and building X-Ray machines. Sanjay was the recipient of a National Institutes of Health (NIH) Small Business Innovation Research (SBIR) grant and has been a consultant or co-Principal-Investigator on several NIH grants. He is actively involved in non-profit biotech networking and educational organizations in the Seattle area and beyond. Sanjay holds a Master of Biomedical Engineering from the University of New South Wales, Sydney and a Bachelor of Instrumentation Technology from Bangalore University. He completed several medical school and PhD level courses (in Sydney and Seattle). A list of selected recent invited talks and panels: • Next Generation Bioinformatics & Biotech Conf, Oct 2019: Mumbai India, Keynote, “Time Series, Machine Learning and the Microbiome: A summary” • GratiFi Summit, Jul 2019, Seattle WA, Panelist, “AI in Biotechnology.” • 601 Club, Jun 2019, Seattle WA, Moderator, “Artificial Intelligence and the Future of Health.” • Bio2Device & Silicon Vikings, Apr 2019, Palo Alto CA, Panelist, “Digital Health.” • BioIT World West, Mar 2019, San Francisco CA, Chair and Speaker, “Streamed Postcards from the Edge: Medical Device Architectures.” • Data Day Texas, Jan 2019: Austin TX, “Morals from a Type 2 Diabetes dataset analytics journey.” • Global AI Conference, Jan 2019: Santa Clara, CA, “Medical Device Architectures: Machine Learning on Streams” • Next Generation Bioinformatics & Biotech Conf, Oct 2018: Jaipur India, Keynote, “A Machine Learning Operational Analytics Story” • EPPICGlobal conference, Oct 2018, Burlingame CA, “Digital Health Keynote Panel” • AI in Healthcare Summit, Jun 2018: San Francisco CA, Chair and Panelist, “Executive Physician Roundtable” • BioIT World, May 2018, Boston MA, Chair and Speaker, Machine Learning and Data Science track • Medical Imaging in Clinical Research, Feb 2018 San Francisco CA; Speaker “Operational Imaging in Clinical Trials.” • AI in Healthcare Summit, Jan 2018 Boston MA: Keynote Panel and Genomics AI moderator • Kaiser Permanente Machine Learning Day, Dec 2017 Oakland CA: Panelist on AI in Healthcare • Interface Summit, Oct 2017, Vancouver Canada; Speaker “Pain: can AI shine a light on it?” • MinneAnalytics HALICON; Oct 2017, Minneapolis MN; Speaker “Two use-cases and a summary: Diabetes and Communicable Disease.” • mHealth Israel; Sep 2017, Jerusalem, Israel; Speaker “AI in Health: Hope or Hype?”