Hemoflow is placed on the injured limb at the ankle or wrist. Light
emitters & detectors are used to collect 32 data points a second.
The data collected is run through our proprietary software
& deep learning artificial intelligence to determine the
hemodynamics in the limb.
The outputs of our diagnostic engine are displayed in a user interface for
physicians to make key recommendations for a patient.
Monitoring perfusion and the nuances of hemodynamics in the extremity is incredibly difficult for caregivers. One of these such ailments is Acute Compartment Syndrome (ACS). ACS occurs when the tissue pressure within a muscle compartment exceeds the perfusion pressure resulting in the crushing of veins and nerves in the limb. This is commonly caused by fractures, burns, and other trauma related injuries to limbs.
The current standard of care is inserting a 16 gauge needle into the muscle compartment every few hours to monitor the pressure over time. Many physicians consider this tool inaccurate and barbaric.
Watch current diagnosis
An emergency fasciotomy must be performed on the patient. A fasciotomy is a highly invasive surgical procedure where the muscle compartment is cut open to relieve tension and pressure.
Watch a fasciotomy
Patients are often too quickly recommended for emergency fasciotomies. The US Department of Defense estimates that 85% of conducted fasciotomies are perfromed unnecessarily.
Meet the people responsible for making the magic happen.
Steven received his Bachelor of Science degree with an emphasis in Sports Medicine and Biology from Purdue University. Graduating as a Certified Athletic Trainer, he gained a thorough understanding of common medical malpractice and diagnostic procedure for compartment syndrome. Using his understanding of medicine, he attended Northwestern University Pritzker School of Law, where he studied entrepreneurship law, medical device regulation, and intellectual property law.
Ruchira received her Master of Science degree in Electrical and Computer Engineering with concentration in Signals and Systems, from the University of California, Riverside. She is experienced in signal and image processing, computer vision, biomedical signal processing, deep learning and data science. Ruchira previously worked as a data scientist at BlueBarrel Solutions.
Hope received her PhD in Biomedical Engineering from Texas A&M University, with a specialization in Biomedical Optics. She has nine years of previous experience as a Senior Research Biomedical Engineer, Principal Investigator and Program Manager in the Optical Radiation Bioeffects Branch of the Air Force Research Laboratory. She has authored 40 journal articles, 7 patents and about 40 conference proceedings. During her tenure at AFRL, she received the AFRL Early Career Award, the John L. McLucas Award, which recognizes the top Basic Science Researcher, and was Principal Investigator on an Air Force Office on Scientific Research “Star” Team, which recognizes the top <10% of AFRL Basic Research teams.
Paul received both his Bachelor of Science, Engineering and Master of Science, Industrial Administration (MBA) degrees from Purdue University. Leaving the Midwest for CA’s Silicon Valley / Bay Area, he spent the next 40 years in numerous business and executive leadership positions in companies such as Hewlett-Packard, Fujitsu, NetApp, Brocade Communications, and Bloom Energy among others. Paul brings strategy, business planning, product and operational expertise to the company.
Mr. Vallejo is a retired U.S. Army First Sergeant with over 35 years experience as a results-driven leader, combat medic, flight medic and trainer in Emergency Health Care. Mr. Vallejo has conducted business relating to current real-world medical training and education with Government, Industry and Academia worldwide. With almost four decades of applicable experience in EMS, in both clinical and combat environments internationally, Mr. Vallejo brings an in-depth knowledge for real case use.
Vicente received his Master of Science in Biomedical Engineering from a collaborative program between Stanford University and the Technical University of Denmark (DTU). He specialized in medical signal processing and artificial intelligence, and is currently pursuing further training in genetics and proteomics. Prior to working with Odin Technologies, he conducted research on portable health technologies to detect mental disorders at Stanford Children’s Hospital. Vicente brings this technical insight and experience to his role as Lead Product Engineer.
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