Classifications

• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B5/00—Measuring for diagnostic purposes; Identification of persons
  • A61B5/48—Other medical applications
  • A61B5/4806—Sleep evaluation
  • A61B5/4818—Sleep apnoea
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B5/00—Measuring for diagnostic purposes; Identification of persons
  • A61B5/08—Measuring devices for evaluating the respiratory organs
  • A61B5/087—Measuring breath flow
  • A61B5/0878—Measuring breath flow using temperature sensing means
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B5/00—Measuring for diagnostic purposes; Identification of persons
  • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
  • A61B5/7235—Details of waveform analysis
  • A61B5/7264—Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B5/00—Measuring for diagnostic purposes; Identification of persons
  • A61B5/03—Measuring fluid pressure within the body other than blood pressure, e.g. cerebral pressure ; Measuring pressure in body tissues or organs
  • A61B5/036—Measuring fluid pressure within the body other than blood pressure, e.g. cerebral pressure ; Measuring pressure in body tissues or organs by means introduced into body tracts
• • A—HUMAN NECESSITIES
  • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
  • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
  • A61B7/00—Instruments for auscultation
  • A61B7/003—Detecting lung or respiration noise
• • G—PHYSICS
  • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
  • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
  • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
  • G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems

Definitions

• This invention relates to a method and an assembly for the detection and analysis of breathing disturbances.
• OSAS Obstructive Sleep Apnea Syndrome
• the known method does, however, not obtain sufficient information about the breathing of the patient, as it would not provide information of cessations below the point of measurement. It is another object of this invention to provide a method and an assembly being capable of indicating the existence of a cessation below the measuring point .
• the objects of the invention are obtained using a method and an assembly characterized as described in claim 1 and 5, respectively.
• a compact air flow sensor may be obtained indirectly by using a temperature sensor.
• the temperature of the air flow will vary according to its direction, since the air inside the lungs will have a higher temperature than the air drawn in from outside. Also a small contribution may be added as the evaporation from the sensor will be more effective when the air is moving, giving a cooling effect.
• Figure 1 gives a schematic view of a cross section of a patient with a measuring instrument positioned in the airways and related organs .
• Figure 2 shows a flow chart illustrating the analysis of the measured signal.
• Figure 3 illustrates schematically the assembly according to the invention.
• Figure 1 illustrates the position of an instrument through the patients nose and extending down into the pharynx.
• the pressure sensors 2 may be positioned in chosen positions along a catheter 1 to detect obstructions in different parts of the pharynx. In the figure the lower end of the catheter 1 and the sensors 2 are positioned in the oesophagus .
• the pressure sensors 2 may be of any suitable kind being at least small enough to be mounted on e.g. a catheter to be positioned in the breathing organs. They should also be easy to clean and robust, which may be obtained providing a protective layer of silicone. Preferably the pressure sensors have a sensitivity in the mm H 2 0 range. Semiconductor strain gauges are preferred, but capacitive, fibre optic or piezoelectric sensors may also be used.
• the sensors are mounted in a Wheatstone bridge configuration, which in addition to high sensitivity allows for temperature compensation.
• a temperature sensor 3 may be positioned externally, with sensor elements in front of both the nose and the mouth, or in the throat. As was the case with the pressure sensors 2 the temperature sensor 3 should be robust and easy to clean. They should have a sensitivity in the desiKelvin range and be able to measure the temperature both of the oral and the nasal air flow, both the temperature of the inhaled air and the temperature of the exhaled air. Many sensors satisfy these requirements, e.g. thermistors, thermocouples and resistance temperature detectors (RTD) . The chosen sensor type may vary depending on the positioning of the sensor and the measurements needed.
• Snoring - understood as sound emissions during sleep - may be measured using one or more acoustic sensors 4 (see figure 3) , by attaching a vibration sensor to the outside of the throat of the patient, by placing a microphone in the vicinity of the patient or by using one of the pressure sensors extracting the acoustic frequencies using band pass filtering in a per se known way.
• band pass filtering followed by rectification and low pass filtering at suitable frequencies each according to well known techniques, will yield a level proportinal to the generated sound, and remove disturbing signals caused by other sounds made during sleep, based on known parameters of the sound generated when snoring. These parameters may be adjusted according to the specific patient.
• the classification of apneic events are performed by first filtering the measured signals in order to avoid interfering noise.
• the signals are preferably band pass filtered at the approximate breathing frequency, for example within a range of 50-500mHz.
• the temperature signal is also compensated for zero offset by removing the mean value prior to band pass filtering.
• the signals are digitized at a chosen frequency f s , e.g. 5 Hz .
• the filtered digital signals within one or more chosen intervals of time are analysed to find the maximum and minimum value, and the difference y in measured value is found. Thus a value is found for each time interval indicating a degree of fluctuation of the measured value.
• the time interval may be chosen according to the use of the invention. In the case of classification of apneic events the interval may typically be 10 seconds.
• the classification of the apneas using at least one acoustic sensor, one or more pressure sensors and an air flow sensor/temperature sensor, is illustrated in figure 2, and is based upon the fact that an obstruction will lead to a pressure fluctuation below the obstruction, as the patient tries to breath. The air flow will stop in the entire system, and the pressure will not fluctuate above the obstruction.
• an obstruction may be indicated if the pressure fluctuates and the temperature variation stops, or is reduced.
• the criterion for indicating a cessation of air flow may be chosen according to the standard deviation S y of the signals.
• a cessation in the temperature signals, and thus a cessation in air flow, is defined when y t ⁇ 0.3 ⁇ S yt
• a cessation in the pressure signals is defined when y p ⁇ 0.3xS yp .
• a marked pressure fluctuation may be indicated when y p -- 0.3 S yp .
• the factor 0.3 is based on experience and comparative tests with conventional methods for sleep analysis.
• the apnea is classified as mixed MA if it is followed by a pressure fluctuations PF S for at least 5 seconds .
• Reduced breathing, hypoapnea H has been detected if reduced temperature fluctuations RF 10 defined as y t ⁇ 0.5xS yt , are detected for at least 10 seconds.
• Snoring is a symptom indicating an increase in breathing resistance and is defined as acoustic energy above a threshold, the threshold being well above the background noise level.
• the acoustic signal is converted to an electrical signal using a suitable transducer, e.g. a microphone or vibration sensor, being band pass filtered.
• the envelope curve is digitized and stored at the same rate as the other signals. If snoring is detected the pressure gradients are computed as well as the location of the maximum obstruction, the latter being performed by level analysis.
• the analysis done during snoring may be excactly the same as when the hypopnea is detected.
• the snoring can be chosen and set as acoustic source level limit by the user of the analysis software .
• Figure 3 illustrates schematically an assembly according to one embodiment of the invention, in which a number of pressure sensors 2 one temperature sensor 3 and a microphone 4 are connected to the apneagraph 5 which stores the signals in a RAM-card 6.
• the RAM-card may be connected to a computer 7, which may be of any suitable kind being capable of performing the necessary analysis.
• the pressure sensors 2 are located at different positions in the oesophagus. This provides a possibility to find the position of the possible obstructions, which provides a more detailed classification of the apneas. While the use of one pressure 2 and one air flow 3 sensor will provide a possibility to classify the type of apnea, the embodiment shown in figure 3 will provide a possibility to find the position of the problem.
• the event may be classified as an obstructive apnea.
• This obstructive event is caused by pharyngeal collapse in the segment between sensors with no (or restricted) pressure fluctuations and the adjacent distal transducer with augmented fluctuations.
• An acoustic sensor is also connected to the assembly in figure 3. This sensor may also be contained in the central apneagraph if it is to be positioned in the same room as the patient.

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• Health & Medical Sciences (AREA)
• Life Sciences & Earth Sciences (AREA)
• Engineering & Computer Science (AREA)
• Physics & Mathematics (AREA)
• General Health & Medical Sciences (AREA)
• Pathology (AREA)
• Biomedical Technology (AREA)
• Heart & Thoracic Surgery (AREA)
• Medical Informatics (AREA)
• Molecular Biology (AREA)
• Surgery (AREA)
• Animal Behavior & Ethology (AREA)
• Biophysics (AREA)
• Public Health (AREA)
• Veterinary Medicine (AREA)
• Artificial Intelligence (AREA)
• Physiology (AREA)
• Evolutionary Computation (AREA)
• Fuzzy Systems (AREA)
• Mathematical Physics (AREA)
• Computer Vision & Pattern Recognition (AREA)
• Psychiatry (AREA)
• Signal Processing (AREA)
• Pulmonology (AREA)
• Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)

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Cited By (2)

Citations (6)

• 2000
  • 2000-05-16 NO NO20002538A patent/NO20002538L/no not_active Application Discontinuation
• 2001
  • 2001-05-09 AU AU2001260810A patent/AU2001260810A1/en not_active Abandoned
  • 2001-05-09 WO PCT/NO2001/000192 patent/WO2001087156A1/en active Application Filing

Patent Citations (6)

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