AI Article Synopsis

  • The incentive spirometer is commonly used in medicine, but there's a lack of data collection and clear evidence on its effectiveness in preventing respiratory complications post-surgery.
  • The study aimed to develop an add-on device that captures data from the spirometer, achieving high accuracy in tracking usage and flow.
  • Testing showed the device effectively classifies breaths with high sensitivity and specificity, and it can operate in real-time as a video game controller, showcasing its potential for enhanced patient monitoring.

Article Abstract

Background: The incentive spirometer is a basic and common medical device from which electronic health care data cannot be directly collected. As a result, despite numerous studies investigating clinical use, there remains little consensus on optimal device use and sparse evidence supporting its intended benefits such as prevention of postoperative respiratory complications.

Objective: The aim of the study is to develop and test an add-on hardware device for data capture of the incentive spirometer.

Methods: An add-on device was designed, built, and tested using reflective optical sensors to identify the real-time location of the volume piston and flow bobbin of a common incentive spirometer. Investigators manually tested sensor level accuracies and triggering range calibrations using a digital flowmeter. A valid breath classification algorithm was created and tested to determine valid from invalid breath attempts. To assess real-time use, a video game was developed using the incentive spirometer and add-on device as a controller using the Apple iPad.

Results: In user testing, sensor locations were captured at an accuracy of 99% (SD 1.4%) for volume and 100% accuracy for flow. Median and average volumes were within 7.5% (SD 6%) of target volume sensor levels, and maximum sensor triggering values seldom exceeded intended sensor levels, showing a good correlation to placement on 2 similar but distinct incentive spirometer designs. The breath classification algorithm displayed a 100% sensitivity and a 99% specificity on user testing, and the device operated as a video game controller in real time without noticeable interference or delay.

Conclusions: An effective and reusable add-on device for the incentive spirometer was created to allow the collection of previously inaccessible incentive spirometer data and demonstrate Internet-of-Things use on a common hospital device. This design showed high sensor accuracies and the ability to use data in real-time applications, showing promise in the ability to capture currently inaccessible clinical data. Further use of this device could facilitate improved research into the incentive spirometer to improve adoption, incentivize adherence, and investigate the clinical effectiveness to help guide clinical care.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11041496PMC
http://dx.doi.org/10.2196/46653DOI Listing

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