Ignite Creation Date:
2024-06-16 @ 11:51 AM
Last Modification Date:
2024-10-26 @ 3:31 PM
Study NCT ID:
NCT06442488
Status:
RECRUITING
Last Update Posted:
2024-06-04
First Post:
2024-05-29
Brief Title:
Wearable Wireless Respiratory Monitoring System That Detects and Predicts Opioid Induced Respiratory Depression
Sponsor:
Jeffrey Joseph
Organization:
Thomas Jefferson University
Study Overview
Official Title:
Wearable Wireless Respiratory Monitoring System That Detects and Predicts Opioid Induced Respiratory Depression
Status:
RECRUITING
Status Verified Date:
2024-05
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
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 participants 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 transmitterreceiver 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 learningAI 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 compromiseclinical deterioration in a more-timely and accurately manor fewer false alertsalarms than current methods
The breathing data from 14 to 20 participants will be recorded during one study session lasting approximately 90 minutes with the sensorcradle adhered to the neck over the proximal trachea Reference breathing data will be recorded simultaneously using a hospital ventilators 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 pneumotachcapnometer data for 400 seconds with the study subject breathing a normal RR and TV
Record RMS data and pneumotachcapnometer data for 70 seconds with the study subject breathing a normal RR and an increased TV
Record RMS data and pneumotachcapnometer data for 70 seconds with the study subject breathing a normal RR and decreased TV
Record RMS data and pneumotachcapnometer 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 pneumotachcapnometer 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 pneumotachcapnometer 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 pneumotachcapnometer 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
Proprietary machine learningAI 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 compromiseclinical deterioration in a more-timely and accurately manor fewer false alertsalarms than current methods
The breathing data from 14 to 20 participants will be recorded during one study session lasting approximately 90 minutes with the sensorcradle adhered to the neck over the proximal trachea Reference breathing data will be recorded simultaneously using a hospital ventilators 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 pneumotachcapnometer data for 400 seconds with the study subject breathing a normal RR and TV
Record RMS data and pneumotachcapnometer data for 70 seconds with the study subject breathing a normal RR and an increased TV
Record RMS data and pneumotachcapnometer data for 70 seconds with the study subject breathing a normal RR and decreased TV
Record RMS data and pneumotachcapnometer 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 pneumotachcapnometer 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 pneumotachcapnometer 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 pneumotachcapnometer 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 Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
True
Is an Unapproved Device?:
True
Is a PPSD?:
None
Is a US Export?:
False
Is an FDA AA801 Violation?:
None