Our Acoustic Ventilation Device

Every day, more than 115 people in the United States die after overdosing on opioids. The Centers for Disease Control and Prevention estimates that the total "economic burden" of prescription opioid misuse alone in the United States is $78.5 billion a year, including the costs of healthcare, lost productivity, addiction treatment, and criminal justice involvement.

rtm vital signs

The Joint Commission, which is an independent not-for-profit organization that accredits more than 21,000 US Health Care Organizations and Programs, recommends ongoing respiratory monitoring for patients on opioid therapy.

A significant decrease in hospital admissions for opioid overdoses across Pennsylvania may have more to do with evolving treatment and the widespread availability of a lifesaving antidote than any major drop in drug abuse, experts said following the release of a report on overdose hospitalizations.

Researchers at the Pennsylvania Health Care Cost Containment Council tracked overdose hospitalizations in the state between 2016 and 2018 and found that admissions for opioid overdoses dropped from 3,500 to 2,667 — or nearly 24% — due to the availability of receiving Narcan in time. In fact, an extremely small incident of death (0.49%) results if Narcan is administered and the patient refuses to go to the hospital.

It’s clear that real-time alerts to administer Narcan substantially reduces trips to the ER, reduces health care system costs, and results in saving lives. The RTM Acoustic Ventilation Monitoring Device will only improve these statistics and further reduce costs.


Additional Research:
Assessing the Risk of Prehospital Administration of Naloxone with Subsequent Refusal of Care
No deaths associated with patient refusal of transport after naloxone-reversed opioid overdose


Our device has a tremendous potential impact on the opioid crisis. The device is a wearable, non-invasive acoustic sensor that accurately measures and monitors the respiratory rate and tidal volume (minute ventilation), hemoglobin oxygen saturation, temperature, body position and activity level of ambulatory patients at risk for respiratory failure (hypoventilation and hypoxemia) due to an opioid overdose, congestive heart failure, pulmonary embolism, asthma, COPD and/or pneumonia. The sensor will transmit information to a designated smartphone that contains a predictive machine learning algorithm capable of diagnosing impending hypoventilation and hypoxemia due to an opioid overdose or worsening pulmonary/cardiovascular function. Additional commercial applications for this device include situations presenting asphyxiation potential in a military or industrial setting.

This device has a high potential impact on the opioid crisis:

  • Most opioid overdose occurs when individuals are alone and unobserved.  Therefore automatic detection is essential to save lives
  • Incorporation of machine learning and predictive algorithms allowing for a timely warning of impending hypoventilation problems, rather than alarming when breathing stops altogether
  • Predictive algorithm capabilities can automatically notify third party/emergency personnel; automatically trigger life-saving injections of naloxone