Device and method for detecting respiratory movements

1. A method for monitoring the respiration of a patient, comprising the following steps:

i) providing at least one passive infrared detector targeting at least one location on the patient capable of exhibiting respiratory movements,

ii) providing, at a sampling frequency fE ( 110 ), at least one sequence of discrete measurement signals ( 200 ) originating from the at least one passive infrared detector,

iii) defining a series of N sliding time windows ( 210 ), starting at different successive moments T in,i , where i is an integer from 1 to N representing each sliding time window with a length of ΔT i =T f,i −T in,i , where T f,i denotes a final time of a sliding time window numbered i,

iv) subtracting from each of said discrete measurement signals present in the same sliding time window ( 300 ) a continuous component calculated over a plurality of these discrete measurement signals ( 300 ) present in the same sliding time window, to obtain at least one temporal sequence of useful discrete signals ( 400 ),

v) generating at each final time T f,i an indicator of respiratory movements ( 410 ), calculated on the basis of a mean amplitude calculated over a set of useful discrete signals included in a sliding time window with a length of ΔT i preceding said time T f,i of the sliding time window numbered i.

2. The method as claimed in claim 1 , further comprising a step consisting in:

providing at least one additional passive infrared detector targeting at least one location on the patient not capable of exhibiting respiratory movements, or targeting the patient's environment,

subtracting from the discrete measurement signals ( 200 ) of step ii) a background signal originating from the at least one passive infrared detector targeting at least one location on the patient not capable of exhibiting respiratory movements or targeting the patient's environment.

3. The method as claimed in claim 1 or 2 , further comprising a step of calculating a mean amplitude comprising the steps consisting of:

calculating an RMS amplitude value of a set of useful discrete signals ( 400 ) included in a sliding time window with a length of ΔT i ,

comparing said RMS amplitude value with a predefined threshold of detection of a respiratory movement by calculation of a mean amplitude.

4. The method as claimed in claim 3 , further comprising a step consisting in:

generating a spectral signal ( 610 ) of a set of useful discrete signals ( 400 ) included in a sliding time window with a length of ΔT i ,

determining the two highest peaks of said spectral signal ( 700 ),

comparing ( 710 ) the frequency of the highest peak with a plausible frequency range of the respiratory movements,

calculating ( 720 ) a coefficient ( 900 ) according to the formula:

(

H

⁢

⁢

1

-

H

⁢

⁢

2

)

2

Hx

where

H1 is the amplitude of the highest peak,

H2 is the amplitude of the second highest peak,

Hx is the amplitude of the second highest peak if this amplitude is other than zero, or the amplitude of the highest peak if the amplitude of the second highest peak is zero,

determining the presence of a respiratory movement by a comparison between the coefficient ( 900 ) obtained in the preceding step and a predetermined threshold of detection of a respiratory movement by calculation of a coefficient.

5. The method as claimed in any one of the preceding claims, further comprising a step consisting in:

determining, for a sliding time window, whether said set of useful discrete signals ( 400 ) included in said sliding time window indicates the detection of a respiratory movement ( 500 ),

if no sliding time window indicates an absence of detection of a respiratory movement ( 600 or 800 ), classifying said sliding time window as containing no respiratory movement,

if a predetermined number of successive sliding time windows are classified as containing no respiratory movement ( 600 or 800 ), triggering a visual and/or audible alarm.

6. The method as claimed in any one of the preceding claims, characterized in that the sampling frequency fE is in the range from 0.1 Hz to 50 Hz.

7. The method as claimed in any one of the preceding claims, characterized in that a median filter and a low-pass filter are applied to said temporal sequence of discrete measurement signals ( 200 ) of step ii).

8. The method as claimed in any one of the preceding claims, characterized in that a sliding time window has a length ΔT i in the range from 5 to 20 seconds.

9. The method as claimed in claims 3 to 7 , characterized in that the threshold of detection of a respiratory movement by calculation of a mean amplitude of a set of useful discrete signals ( 400 ) included in a sliding time window with a length of ΔT i is in the range from 150 mV to 160 mV.

10. The method as claimed in claims 4 to 9 , characterized in that the threshold of detection of a respiratory movement by a coefficient is greater than or equal to 10.

11. A device for monitoring the respiration of a person or an animal, comprising:

at least one passive infrared detector ( 4 ) adapted to target at least one location on a patient ( 1 ) capable of exhibiting respiratory movements,

at least one amplifier ( 6 ) for the at least one passive infrared detector ( 4 ),

at least one signal processing means ( 7 ) programmed to execute steps iii), iv) and v) of claim 1 ,

at least one visual and/or audible alarm ( 8 ).

12. The device as claimed in the preceding claim, characterized in that the signal processing means ( 7 ) is also programmed to execute a step of any one of claims 2 , 3 , 4 , 5 , 7 or 8 .

13. The device as claimed in claim 11 or 12 , characterized in that it includes at least one additional passive infrared detector ( 10 ), adapted to target a part of the body not capable of exhibiting respiratory movements or adapted to target the environment of a person.