System And Method For Discrimination Of Central And Obstructive Disordered Breathing Events

• US 20090112116A1
• Filed: 12/22/2008
• Published: 04/30/2009
• Est. Priority Date: 09/18/2003
• Status: Active Grant

• Current Assignee: Jeffrey Stahmann, Jesse W. Hartley, John D. Hatlestad, Kent Lee, Qingsheng Zhu, Quan Ni
• Original Assignee: Jeffrey Stahmann, Jesse W. Hartley, John D. Hatlestad, Kent Lee, Qingsheng Zhu, Quan Ni
• Inventors: Lee, Kent, Hartley, Jesse W., Hatlestad, John D., Zhu, Qingsheng, Ni, Quan, Stahmann, Jeffrey
• Granted Patent: US 9,814,429 B2
• Time in Patent Office: Days
• US Class Current: 600/534
• CPC Class Codes: A61B 5/0031 Implanted circuitry
• CPC Class Codes: A61B 5/0205 Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
• CPC Class Codes: A61B 5/08 Detecting, measuring or recording devices for evaluating the respiratory organs A61B5/0205 takes precedence
• CPC Class Codes: A61B 5/0809 by impedance pneumography
• CPC Class Codes: A61B 5/11 Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb for measuring pulse A61B5/02 ;A61B5/1038 takes precedence; motion detection to correct for motion artifacts in physiological signals A61B5/721
• CPC Class Codes: A61B 5/113 occurring during breathing
• CPC Class Codes: A61B 5/1135 by monitoring thoracic expansion
• CPC Class Codes: A61B 5/291 for electroencephalography [EEG]
• CPC Class Codes: A61B 5/369 Electroencephalography [EEG] devices for psychotechnics A61B5/16
• CPC Class Codes: A61B 5/389 Electromyography [EMG]
• CPC Class Codes: A61B 5/398 Electrooculography [EOG], e.g. detecting nystagmus; Electroretinography [ERG]
• CPC Class Codes: A61B 5/4818 Sleep apnoea
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems

Abstract

Disordered breathing events may be classified as central, obstructive or a combination of central an obstructive in origin based on patient motion associated with respiratory effort. Central disordered breathing is associated with disrupted respiration with reduced respiratory effort. Obstructive disordered breathing is associated with disrupted respiration accompanied by respiratory effort. A disordered breathing classification system includes a disordered breathing detector and a respiratory effort motion sensor. Components of the disordered breathing classification system may be fully or partially implantable.

Claims

1. A method of operating an implantable device to classify disordered breathing events of a patient, comprising:

sensing respiration and generating a respiration signal indicating patient respiration cycles;

sensing chest wall motion and generating a motion signal indicating chest wall motion associated with inspiratory effort;

detecting disordered breathing based on the respiration signal;

time correlating the motion signal with the respiration signal; and

classifying the disordered breathing event as a central disordered breathing event in response to the signal remaining below a motion threshold during a time period in which the respiration signal remains below an inspiration threshold.

2. The method of claim 1, further comprising classifying the disordered breathing event as an obstructive disordered breathing event in response to the motion signal rising above a motion threshold during a time period in which the respiration signal remains below the inspiration threshold.

3. The method of claim 1, wherein:

sensing respiration and generating the respiration signal comprises sensing and generating using a transthoracic impedance sensor; and

sensing chest wall motion and generating the motion signal comprises sensing and generating using an accelerometer signal.