Clinical trial NCT06442488: Wearable Wireless Respiratory Monitoring System That Detects and Predicts Opioid Induced Respiratory Depression
Official title: Wearable Wireless Respiratory Monitoring System That Detects and Predicts Opioid Induced Respiratory Depression
Study type: OBSERVATIONAL
Overall status: RECRUITING
Conditions: Respiratory Insufficiency
Clinical Deterioration
Keywords: Respiratory Monitoring System
Detection of Respiratory Insufficiency
Prediction of Respiratory Insufficiency
Wearable, Wireless Respiratory Sensor
Lead sponsor: Thomas Jefferson University
Sponsor class: OTHER
Collaborators: name: RTM Vital Signs, LLC
First posted: 2024-06-04
Enrollment: 14
Sex: ALL
Minimum age (years): 18
Maximum age (years): 70
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: 14 participants that meet the inclusion/exclusion criteria. Approximately equal number of male/female participants.

Brief 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. 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.

Eligibility criteria: 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.

Primary outcomes:
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.
timeFrame: 90 minutes
measure: Accuracy of tidal volume (TV) measurement in a noisy environment when RMS adaptive filtering and active noise cancellation is turned on versus turned off.
timeFrame: 90 minutes
measure: Accuracy of minute ventilation (MV) measurement in a noisy environment when RMS adaptive filtering and active noise cancellation is turned on versus turned off.
timeFrame: 90 minutes
measure: Accuracy of duration of apnea measurement in a noisy environment when RMS adaptive filtering and active noise cancellation is turned on versus turned off.
timeFrame: 90 minutes
Secondary outcomes:
measure: 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.
timeFrame: 90 minutes
Other outcomes:
Locations:
city: Philadelphia
country: United States
facility: Thomas Jefferson University
state: Pennsylvania
Study officials:
References:
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