Wearable Wireless Respiratory Monitoring System That Detects and Predicts Opioid Induced Respiratory Depression

An observational study will be conducted in approximately 14 participants to evaluate the ability of a wearable, wireless acoustic Respiratory Monitoring System (RMS) to accurately measure a participant's respiratory rate, tidal volume, minute ventilation, and duration of apnea in a noisy environment. Sensor accuracy will be measured with adaptive filtering and active noise cancellation turned on versus turned off.

Study Overview

• Status: Completed
• Conditions: Respiratory Insufficiency; Clinical Deterioration
• Intervention / Treatment: Device: Respiratory Monitoring System

Detailed Description

The Respiratory Monitoring System (RMS) consists of a miniature acoustic sensor and a soft flexible cradle that is adhered to the skin of the neck over the proximal trachea (within the sternal notch) with medical grade adhesive. The sensor body consists of a miniature bell stethoscope head, electronics, a microphone that faces the trachea and a microphone that faces the external environment, a Bluetooth low energy transmitter/receiver, an antenna, and a rechargeable battery. The sensor is secured by the cradle at the optimal location to measures the sounds of airflow in the proximal trachea during inhalation and exhalation.

Proprietary machine learning/AI algorithms convert the sounds of airflow into the measurements of respiratory rate (RR), tidal volume (TV), minute ventilation (MV), and duration of apnea. Sensor information is transmitted to a bedside PC that displays the vital sign data in real-time. The wearable, wireless RMS is being developed for hospital and outpatient use as a tool to detect and predict respiratory compromise/clinical deterioration in a more-timely and accurately manor (fewer false alerts/alarms) than current methods.

The breathing data from 14 to 20 participants will be recorded during one study session lasting approximately 90 minutes with the sensor/cradle adhered to the neck over the proximal trachea. Reference breathing data will be recorded simultaneously using a hospital ventilator's pneumotach and capnometer attached to a tight-fitting face mask.

Each subject will be instructed to breath the following protocol 3 or 4 times:

Record RMS data and pneumotach/capnometer data for ~400 seconds with the study subject breathing a normal RR and TV.

Record RMS data and pneumotach/capnometer data for ~70 seconds with the study subject breathing a normal RR and an increased TV.

Record RMS data and pneumotach/capnometer data for ~70 seconds with the study subject breathing a normal RR and decreased TV.

Record RMS data and pneumotach/capnometer data for ~120 seconds with the study subject breathing a normal RR and normal TV with a period of apnea in the middle (15 seconds).

Record RMS data and pneumotach/capnometer data for ~120 seconds with the study subject breathing a normal RR and decreased TV, with a period of apnea in the middle (15 seconds).

Record RMS data and pneumotach/capnometer data for ~120 seconds with the study subject breathing a decreased RR and decrease TV with a period of apnea in the middle (15 seconds).

RMS data will be compared to reference pneumotach/capnometer data (RR, TV, MV, and duration of apnea) to determine the accuracy of measurement. Data will be recorded in an environment with simulated hospital noise with adaptive filtering and active noise cancellation turned on and turned off.

This observational human study will compare the signal-to-noise ratio (SNR) and the measurement accuracy of the RMS in a noisy environment with the adaptive filtering and active noise cancellation turned on versus turned off.

Participants will be contacted by telephone 3 to 4 days later to confirm no adverse effects from the study methods or wearing the sensor.

• Study Type: Observational
• Enrollment (Actual): 14

Contacts and Locations

Study Locations

• United States
  • Pennsylvania
    • Philadelphia, Pennsylvania, United States, 19107
      • Thomas Jefferson University

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: Yes

• Sampling Method: Non-Probability Sample

Study Population

14 participants that meet the inclusion/exclusion criteria. Approximately equal number of male/female participants.

Description

Inclusion Criteria:

1. Age 18 to 70 years.
2. BMI 20 to 38.
3. Subject understands the English language, understands the risks, benefits, and alternatives to this research study, and is willing and able to give written informed consent.

Exclusion Criteria:

1. Age <18 years>70.
2. BMI < 20 or > 38.
3. Does not understand written and spoken English.
4. Anxiety or claustrophobia related to wearing a face mask.
5. History of skin irritation or inflammation related to the adhesive, adhesive tape, or materials used in the trachea sound sensor or facemask.
6. Active infection or inflammation of the skin above the proximal trachea.
7. Excessive facial hair that may prevent a tight seal around the facemask.
8. Unstable cardiac, vascular, pulmonary, hepatic, renal, immune function at the discretion of the investigator.
9. Pregnancy or breast feeding.
10. Current participation in an industry sponsored pharmaceutical study or a medical device study.

Study Plan

How is the study designed?

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Accuracy of respiratory rate (RR) measurement in a noisy environment when RMS adaptive filtering and active noise cancellation is turned on versus turned off.	RMS breathing data and reference pneumotach/capnogram data will be recorded with RMS adaptive filtering and active noise cancellation turned on and turned off to calculate the accuracy of RR measurement.	90 minutes
Accuracy of tidal volume (TV) measurement in a noisy environment when RMS adaptive filtering and active noise cancellation is turned on versus turned off.	RMS breathing data and reference pneumotach/capnogram data will be recorded with RMS adaptive filtering and active noise cancellation turned on and turned off to calculate the accuracy of TV measurement.	90 minutes
Accuracy of minute ventilation (MV) measurement in a noisy environment when RMS adaptive filtering and active noise cancellation is turned on versus turned off.	RMS breathing data and reference pneumotach/capnogram data will be recorded with RMS adaptive filtering and active noise cancellation turned on and turned off to calculate the accuracy of MV measurement.	90 minutes
Accuracy of duration of apnea measurement in a noisy environment when RMS adaptive filtering and active noise cancellation is turned on versus turned off.	RMS breathing data and reference pneumotach/capnogram data will be recorded with RMS adaptive filtering and active noise cancellation turned on and turned off to calculate the accuracy of duration of apnea measurement.	90 minutes

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Measure the signal-to-noise ratio of the RMS output signal in a noisy external environment with adaptive filtering and active noise cancellation turned on and off.	RMS breathing data and reference pneumotach/capnogram data will be recorded with RMS adaptive filtering and active noise cancellation turned on and turned off to calculate the sensor's signal-to-noise ratio.	90 minutes

Collaborators and Investigators

• Sponsor: Jeffrey Joseph
• Collaborators: RTM Vital Signs, LLC

Publications and helpful links

General Publications

• Yu L, Ting CK, Hill BE, Orr JA, Brewer LM, Johnson KB, Egan TD, Westenskow DR. Using the entropy of tracheal sounds to detect apnea during sedation in healthy nonobese volunteers. Anesthesiology. 2013 Jun;118(6):1341-9. doi: 10.1097/ALN.0b013e318289bb30.
• Ramsay MA, Usman M, Lagow E, Mendoza M, Untalan E, De Vol E. The accuracy, precision and reliability of measuring ventilatory rate and detecting ventilatory pause by rainbow acoustic monitoring and capnometry. Anesth Analg. 2013 Jul;117(1):69-75. doi: 10.1213/ANE.0b013e318290c798. Epub 2013 Apr 30.
• Chen G, de la Cruz I, Rodriguez-Villegas E. Automatic lung tidal volumes estimation from tracheal sounds. Annu Int Conf IEEE Eng Med Biol Soc. 2014;2014:1497-500. doi: 10.1109/EMBC.2014.6943885.
• Harper VP, Pasterkamp H, Kiyokawa H, Wodicka GR. Modeling and measurement of flow effects on tracheal sounds. IEEE Trans Biomed Eng. 2003 Jan;50(1):1-10. doi: 10.1109/TBME.2002.807327.
• Thakor NV, Zhu YS. Applications of adaptive filtering to ECG analysis: noise cancellation and arrhythmia detection. IEEE Trans Biomed Eng. 1991 Aug;38(8):785-94. doi: 10.1109/10.83591.
• Patino M, Kalin M, Griffin A, Minhajuddin A, Ding L, Williams T, Ishman S, Mahmoud M, Kurth CD, Szmuk P. Comparison of Postoperative Respiratory Monitoring by Acoustic and Transthoracic Impedance Technologies in Pediatric Patients at Risk of Respiratory Depression. Anesth Analg. 2017 Jun;124(6):1937-1942. doi: 10.1213/ANE.0000000000002062.

Study record dates

Study Major Dates

• Study Start (Actual): May 1, 2024
• Primary Completion (Actual): September 30, 2024
• Study Completion (Actual): September 30, 2024

Study Registration Dates

• First Submitted: May 29, 2024
• First Submitted That Met QC Criteria: May 29, 2024
• First Posted (Actual): June 4, 2024

Study Record Updates

• Last Update Posted (Estimated): October 15, 2025
• Last Update Submitted That Met QC Criteria: October 13, 2025
• Last Verified: October 1, 2025

More Information

Terms related to this study

• Keywords: Respiratory Monitoring System; Detection of Respiratory Insufficiency; Prediction of Respiratory Insufficiency; Wearable, Wireless Respiratory Sensor
• Additional Relevant MeSH Terms: Pathologic Processes; Disease Attributes; Respiratory Tract Diseases; Respiration Disorders; Disease Progression; Pathological Conditions, Signs and Symptoms; Clinical Deterioration; Respiratory Insufficiency
• Other Study ID Numbers: 1R44DA059491-01 (U.S. NIH Grant/Contract)

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO
• IPD Plan Description: We do not plan to share IPD data with other researchers.

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: Yes
• product manufactured in and exported from the U.S.: No