Artificial intelligence-enabled detection and assessment of Parkinson’s disease using nocturnal breathing signals - Nature Medicine

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Using a neural network-based model, ParkinsonsDisease can be diagnosed and its severity monitored based on breathing patterns while someone is asleep, with the potential for at-home touchless monitoring. AI DigitalMedicine PD MIT MIT_CSAIL

The Udall dataset is comprised of PD and normal participants who underwent an in-home observational study between 1 June 2019 and 1 January 2021. Inclusion criteria require participants to be at least 30 years of age, able and willing to provide informed consent, have Wi-Fi in their residence, have English fluency and be resident in the United States.

The study protocol was reviewed and approved by the University of Rochester Research Subjects Review Boards ; MIT Institutional Review Board and Boston University Charles River Campus IRB ceded to the Rochester IRB. The participants provided written informed consent to participate in this study.The MIT control dataset is comprised of participants who underwent an in-home observational study between 1 June 2020 and 1 June 2021.

 

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That's cool. Could be picked up when someone is already in for a sleep examination. But we already know sleep disorders dramatically increase risk factors across all patients including parkinsons. 50% of children with adhd have a corresponding sleep disorder. Usually untreated.

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