The DREAM Project
The DREAM Project
Detection of CardioRespiratory Events Using Acoustic Monitoring in Preterm Infants on CPAP (DREAM)
Continuous, non-invasive detection of airflow using acoustic monitoring.
Continuous, non-invasive detection of airflow using acoustic monitoring.
Continuous, non-invasive detection of airflow using acoustic monitoring.
Apneas, or breathing pauses, are common in babies born before 31 weeks’ gestation. They can lead to longer hospital stays and increased long-term risks of respiratory and neurodevelopmental impairment. Current monitoring tools in the NICU are not capable of capturing respiratory airflow, making it hard to detect airway blockages. We are exploring a potential solution: continuous, non-invasive detection of airflow using acoustic monitoring. We have teamed up with Northwestern University and Ann & Robert H Lurie Children’s Hospital of Chicago to create a wireless acoustic sensor that attaches to a baby’s chest with medical-grade adhesive and records breathing sounds and chest movements.
We are testing this novel sensor in our study at the Montreal Children’s with 50 preterm infants, more specifically, how well it detects airflow and breathing effort compared to traditional methods. If successful, this technology could help doctors spot airway problems in real time and provide personalized care, potentially leading to better outcomes for these tiny patients.
Apneas, or breathing pauses, are common in babies born before 31 weeks’ gestation. They can lead to longer hospital stays and increased long-term risks of respiratory and neurodevelopmental impairment. Current monitoring tools in the NICU are not capable of capturing respiratory airflow, making it hard to detect airway blockages. We are exploring a potential solution: continuous, non-invasive detection of airflow using acoustic monitoring. We have teamed up with Northwestern University and Ann & Robert H Lurie Children’s Hospital of Chicago to create a wireless acoustic sensor that attaches to a baby’s chest with medical-grade adhesive and records breathing sounds and chest movements.
We are testing this novel sensor in our study at the Montreal Children’s with 50 preterm infants, more specifically, how well it detects airflow and breathing effort compared to traditional methods. If successful, this technology could help doctors spot airway problems in real time and provide personalized care, potentially leading to better outcomes for these tiny patients.
Apneas, or breathing pauses, are common in babies born before 31 weeks’ gestation. They can lead to longer hospital stays and increased long-term risks of respiratory and neurodevelopmental impairment. Current monitoring tools in the NICU are not capable of capturing respiratory airflow, making it hard to detect airway blockages. We are exploring a potential solution: continuous, non-invasive detection of airflow using acoustic monitoring. We have teamed up with Northwestern University and Ann & Robert H Lurie Children’s Hospital of Chicago to create a wireless acoustic sensor that attaches to a baby’s chest with medical-grade adhesive and records breathing sounds and chest movements.
We are testing this novel sensor in our study at the Montreal Children’s with 50 preterm infants, more specifically, how well it detects airflow and breathing effort compared to traditional methods. If successful, this technology could help doctors spot airway problems in real time and provide personalized care, potentially leading to better outcomes for these tiny patients.
Team:
Dr. Wissam Shalish,
Principal Investigator
Dr. Wissam Shalish,
Principal Investigator
Dr. Wissam Shalish,
Principal Investigator
Dr. Robert Kearney,
Principal Investigator
Dr. Robert Kearney,
Principal Investigator
Dr. Robert Kearney,
Principal Investigator
Ana Saavedra Ruiz,
Research Coordinator
Ana Saavedra Ruiz,
Research Coordinator
Ana Saavedra Ruiz,
Research Coordinator
Emily Jeanne,
PhD Candidate
Emily Jeanne,
PhD Candidate
Emily Jeanne,
PhD Candidate
Emily Campbell,
MSc Candidate
Emily Campbell,
MSc Candidate
Emily Campbell,
MSc Candidate