Respiratory InsufficiencyNCT06442488
Wearable Wireless Respiratory Monitoring System That Detects and Predicts Opioid Induced Respiratory Depression
An observational study of Respiratory Insufficiency and Clinical Deterioration, run by Jeffrey Joseph at 1 site in United States.
Trial summary
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. Read more about this study
- Who is it for?
- Ages 18 to 70 yearsHealthy volunteers can take part
- Conditions the study is for
- Respiratory Insufficiency, Clinical Deterioration
- What is being tested?
- Respiratory Monitoring System
- Type of treatment
- Medical device
- How many people
- 14 participants
- Where
- 1 siteUnited States
- Study dates
- 1 May 2024to 30 Sep 2024
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 70 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: 14 participants that meet the inclusion/exclusion criteria. Approximately equal number of male/female participants.
Who may be able to join
- Age 18 to 70 years.
- BMI 20 to 38.
- 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.
Who cannot join
- Age <18 years>70.
- BMI < 20 or > 38.
- Does not understand written and spoken English.
- Anxiety or claustrophobia related to wearing a face mask.
- History of skin irritation or inflammation related to the adhesive, adhesive tape, or materials used in the trachea sound sensor or facemask.
- Active infection or inflammation of the skin above the proximal trachea.
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- Excessive facial hair that may prevent a tight seal around the facemask.
- Unstable cardiac, vascular, pulmonary, hepatic, renal, immune function at the discretion of the investigator.
- Pregnancy or breast feeding.
- Current participation in an industry sponsored pharmaceutical study or a medical device study.
Trial locations and contacts
1 site in 1 country.
United States1 site
Thomas Jefferson University
Philadelphia, Pennsylvania, 19107
About this study
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.
Read the 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.
- Conditions
- Respiratory Insufficiency, Clinical Deterioration
- Being tested
- Respiratory Monitoring System
- Keywords
- Respiratory Monitoring System, Detection of Respiratory Insufficiency, Prediction of Respiratory Insufficiency, Wearable, Wireless Respiratory Sensor
- Medical subject headings
- Respiratory Insufficiency, Clinical Deterioration
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Respiratory Monitoring SystemDevice
Comparing the SNR and accuracy of measurement (RR, TV, MV, apnea duration) in a noisy external environment when the RMS has adaptive filtering and active noise cancellation turned on versus turned off.
What is being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: 90 minutes
Secondary outcomes (1)
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.
Measured: 90 minutes
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted4 Jun 2024
- Study start1 May 2024
- Primary completion30 Sep 2024
- Study completion30 Sep 2024
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (6)Papers the sponsor has linked to this study.
- Other trials for Respiratory InsufficiencyStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 14 participants (actual)
Sponsor and investigators
- Lead sponsor
- Jeffrey Joseph
- Sponsor type
- University, hospital or other
- Collaborators
- RTM Vital Signs, LLC
- Responsible party
- Sponsor-investigator, Jeffrey Joseph, Thomas Jefferson University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06442488
- Sponsor's protocol ID
- 1R44DA059491-01
- Status last verified
- Oct 2025
- First submitted
- 29 May 2024
- Last updated
- 15 Oct 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- Yes
- Individual data sharing
- No: We do not plan to share IPD data with other researchers.
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.
PubMed 23407106Chen 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.
PubMed 25570253Thakor 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.
PubMed 1937512Ramsay 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.
PubMed 23632055Harper 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.
PubMed 12617519Patino 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.
PubMed 28448390
Study at a glance
From the registry record, last updated by the sponsor on 15 Oct 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Wearable Wireless Respiratory Monitoring System That Detects and Predicts Opioid Induced Respiratory Depression
- ClinicalTrials.gov ID
- NCT06442488
- Acronym / sponsor ID
- 1R44DA059491-01
- Conditions
- Respiratory Insufficiency, Clinical Deterioration
- Keywords
- Respiratory Monitoring System, Detection of Respiratory Insufficiency, Prediction of Respiratory Insufficiency, Wearable, Wireless Respiratory Sensor
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 14 participants (actual)
- Lead sponsor
- Jeffrey JosephUniversity, hospital or other
- Collaborators
- RTM Vital Signs, LLC
- Study start
- 1 May 2024 (actual)
- Primary completion
- 30 Sep 2024 (actual)
- Study completion
- 30 Sep 2024 (actual)
- First posted
- 4 Jun 2024 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
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 design
- Observational model
- Cohort
- Time perspective
- Prospective
Who may qualify
- Ages
- 18 to 70 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- 14 participants that meet the inclusion/exclusion criteria. Approximately equal number of male/female participants.
Key inclusion criteria (3 listed)
- Age 18 to 70 years.
- BMI 20 to 38.
- 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.
Key exclusion criteria (10 listed)
- Age <18 years>70.
- BMI < 20 or > 38.
- Does not understand written and spoken English.
- Anxiety or claustrophobia related to wearing a face mask.
- History of skin irritation or inflammation related to the adhesive, adhesive tape, or materials used in the trachea sound sensor or facemask.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Respiratory Monitoring SystemComparing the SNR and accuracy of measurement (RR, TV, MV, apnea duration) in a noisy external environment when the RMS has adaptive filtering and active noise cancellation turned on versus turned off. | Device | – |
Primary outcome
Accuracy of respiratory rate (RR) measurement in a noisy environment when RMS adaptive filtering and active noise cancellation is turned on versus turned off.
Time frame: 90 minutes
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.
Accuracy of tidal volume (TV) measurement in a noisy environment when RMS adaptive filtering and active noise cancellation is turned on versus turned off.
Time frame: 90 minutes
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.
Accuracy of minute ventilation (MV) measurement in a noisy environment when RMS adaptive filtering and active noise cancellation is turned on versus turned off.
Time frame: 90 minutes
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.
Accuracy of duration of apnea measurement in a noisy environment when RMS adaptive filtering and active noise cancellation is turned on versus turned off.
Time frame: 90 minutes
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.
1 secondary outcome
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.
Time frame: 90 minutes
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 15 Oct 2025.
- Background: PubMed 23407106Yu 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.
- Background: PubMed 25570253Chen 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.
- Background: PubMed 1937512Thakor 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.
- Background: PubMed 23632055Ramsay 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.
- Background: PubMed 12617519Harper 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.
- Background: PubMed 28448390Patino 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.
- Individual participant dataSharing planned: No. We do not plan to share IPD data with other researchers.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
The record lists no contact. Use the official record to reach the sponsor.
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Respiratory Insufficiency and Clinical Deterioration, run by Jeffrey Joseph at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 10 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 15 Oct 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Accuracy of respiratory rate (RR) measurement in a noisy environment when RMS adaptive filtering and active noise cancellation is turned on versus turned off. (time frame: 90 minutes). The study lists 4 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT06442488, which also lists 6 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 15 Oct 2025.