Our Acoustic Ventilation Monitoring Device

Global access to health care is far from adequate, with health disparities widening; the rise of economic inequities and shortages in the health workforce are contributors. Indeed, in the United States, the opioid crisis has reached new heights:

• Drug overdose is the most common cause of death in the USA in people under 50 years old
• The Centers for Disease Control (CDC)estimate the economic burden of prescription opioid misuse exceeds $78.5 Billion/year
• The total economic cost of the “Opioid Crisis” was estimated by the Council of Economic Advisors (CEA, November 2017) to be ~ $500 Billion

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.

According to American Nurse Today routine monitoring of vital signs may fail to detect early signs of respiratory depression. Many nurses focus on pulse oximetry, blood pressure, and respiratory rate when assessing a patient for opioid-related over-sedation. But pulse oximetry also may not provide accurate information, especially in a patient receiving oxygen. Also, bradypnea is a poor predictor of oxygen desaturation and occur late in respiratory depression—or not at all. In opioid-naïve patients, respiratory rate is a notoriously poor predictor of respiratory depression; it may be normal despite significant hypoventilation. Also be aware that the patient’s respiratory status may change rapidly, and these changes may elude conventional monitoring techniques used in most settings today.

The RTM Acoustic Ventilation Monitoring Device (AVMD) provides a continuous monitoring solution for ambulatory patients (both in and out of the hospital) on opioid pain management therapy. The miniature wearable acoustic sensor uses a microphone to monitor the adequacy of an ambulatory patient’s breathing- capable of predicting hypoventilation and preventing death from an opioid overdose. We are developing machine learning (AI) diagnostic algorithms that accurately detect & predict opioid-induced respiratory depression in real-time from the tracheal sound. A continuous risk-index score will alert providers when the algorithm predicts impending moderate hypoventilation (PaCO2 >50 mm Hg) and will alarm when the algorithm predicts impending severe hypoventilation (PaCO2 > 60 mm Hg). The algorithms and data will also inform better dosing for pain management.

Additional Research: Screen Heart attacks Before they Happen (Drexel University Research Magazine)

Non-invasive, wearable Vital Sign Monitoring System with an acoustic sensor located over the trachea. Real-time data is displayed and analyzed using any device.

RTM’s long-term goal is to commercialize a series of wearable vital sign sensors that continuously monitor and analyze an ambulatory patient’s blood pressure, electrocardiogram, hemoglobin oxygen saturation, temperature, respiratory rate, tidal volume, sounds of the upper airway/heart/lungs, body position, and activity level. The wearable sensors can be used to monitor ambulatory out-patients with asthma, COPD, pneumonia, ischemic heart disease, congestive heart failure, arrhythmias, and other chronic diseases. Machine learning (AI) algorithms will analyze the real-time vital sign sensor trend data to increase the accuracy and timeliness of diagnosis and the safety/effectiveness of medical therapy.