초록 ▼

The present invention relates to a method and a system designed to determine an individual's state of attention from an individual's respiratory signal. The method of the invention comprises a first learning step, wherein the characteristics of an individual's normal state are determined by selectin

The present invention relates to a method and a system designed to determine an individual's state of attention from an individual's respiratory signal. The method of the invention comprises a first learning step, wherein the characteristics of an individual's normal state are determined by selecting a respiratory signal fragment that is considered to be normal according to a pre-established criterion, and a second analysis phase, wherein the individual's state of attention is determined from parameters extracted from the respiratory signal on the basis of some pre-defined rules and the individual's normal state previously characterised. The method of the invention is implemented in two embodiments. A first embodiment is based on the identification of pre-defined patterns in the respiratory signal and, in the second embodiment, an index indicative of the variability of the respiratory signal is defined.

대표청구항 ▼

1. A method for determining an individual's state of attention, which comprises the following operational steps: a) providing a respiratory signal capture apparatus,b) obtaining an individual's respiratory signal with the respiratory signal capture apparatus,c) segmenting said respiratory signal int

1. A method for determining an individual's state of attention, which comprises the following operational steps: a) providing a respiratory signal capture apparatus,b) obtaining an individual's respiratory signal with the respiratory signal capture apparatus,c) segmenting said respiratory signal into a plurality of segments,d) extracting at least one parameter from each segment of the respiratory signal,e) characterising a normal state of attention for the individual by selecting a respiratory signal fragment that is considered to be normal according to a pre-established criterion and, in the event that no respiratory signal fragment is found that meets said pre-established criterion, characterising the normal state of attention for the individual on the basis of certain data stored in a memory device, andf) determining the individual's state of attention from the at least one parameter extracted from each segment on the basis of pre-defined rules and the normal state of attention for the individual, wherein step d) comprises obtaining at least one fuzzy parameter from the at least one parameter extracted from each segment, and step f) comprises: evaluating a degree of similarity of each segment with respect to each one of a plurality of pre-determined phases, by comparing the at least one fuzzy parameter of each segment to characteristic parameters for said pre-determined phases, and determining the individual's state of attention from the degree of similarity of the segments of the signal with respect to said pre-determined phases on the basis of certain pre-defined rules. 2. The method for determining an individual's state of attention, according to claim 1, characterised in that said certain data stored in the memory device are data pertaining to the subject him/herself and/or data for a set of subjects that statistically represent a population. 3. The method for determining an individual's state of attention, according to claim 1, characterised in that step e) comprises: determining the variability of the respiratory signal in the signal fragment considered, or evaluating the degree of similarity of the respiratory signal fragment considered with respect to a model respiratory signal pattern, or evaluating the homogeneity of certain given variables in the respiratory cycles within the respiratory signal fragment in question. 4. The method for determining an individual's state of attention, according to claim 1, characterised in that the at least one parameter is selected from the group constituted by amplitude, frequency, minimum value, maximum value, amplitude symmetry and frequency symmetry. 5. The method for determining an individual's state of attention, according to claim 1, characterised in that step c), wherein the respiratory signal is segmented, comprises using a watershed relevant peak algorithm in order to reduce the amount of information to be processed. 6. The method for determining an individual's state of attention, according to claim 1, characterised in that at least one of the pre-determined phases is selected from the group constituted by normal respiration, low-amplitude relaxation respiration, low-frequency relaxation respiration, relaxation sigh, fatigue sigh, chaotic phase, yawning, talking, singing/humming and M pattern. 7. The method for determining an individual's state of attention, according to claim 6, characterised in that the “normal respiration” phase corresponds to a normal, symmetric frequency, a normal, symmetric amplitude, a normal maximum value and a normal minimum value. 8. The method for determining an individual's state of attention, according to claim 6, characterised in that the “low-amplitude relaxation respiration” phase corresponds to a normal, symmetric frequency, a low, symmetric amplitude, a normal or low maximum and a normal minimum, or a normal, symmetric frequency, a low, symmetric amplitude, a normal maximum, and a normal or high minimum. 9. The method for determining an individual's state of attention, according to claim 6, characterised in that the “low-frequency relaxation respiration” phase corresponds to a low, symmetric frequency, a normal, symmetric amplitude, a normal or low maximum and a normal minimum, or a low, symmetric frequency, a normal, symmetric amplitude, a normal maximum, and a normal or high minimum. 10. The method for determining an individual's state of attention, according to claim 6, characterised in that the “relaxation sigh” phase corresponds to a low frequency, a high or very high maximum, and a low or very low minimum. 11. The method for determining an individual's state of attention, according to claim 6, characterised in that the “fatigue sigh” phase corresponds to a low or very low frequency, a very high, asymmetric or very asymmetric amplitude, a very high maximum, and a very low minimum. 12. The method for determining an individual's state of attention, according to claim 6, characterised in that the “chaotic respiration” phase corresponds to a low or very low, asymmetric or very asymmetric frequency, a low or very low, asymmetric or very asymmetric amplitude, a normal or high maximum, and a normal or low minimum. 13. The method for determining an individual's state of attention, according to claim 6, characterised in that the “M pattern” phase corresponds to a signal fragment with three consecutive minima that exhibit the following characteristics: the left minimum is normal, the central minimum is high or very high, the right minimum is normal, the left maximum is low or normal, and the right maximum is low or normal. 14. The method for determining an individual's state of attention, according to claim 1, characterised in that the determination of the individual's state of attention comprises supplementing the analysis of the respiratory signal with data obtained from a second source. 15. The method for determining an individual's state of attention, according to claim 1, characterised in that it comprises informing the individual of the state of attention determined. 16. The method for determining an individual's state of attention, according to claim 15, characterised in that it comprises activating an alarm in response to the detection of a given state of attention. 17. A method for determining an individual's state of attention, which comprises the following operational steps: a) providing a respiratory signal capture apparatus,b) obtaining an individual's respiratory signal with the respiratory signal capture apparatus,c) segmenting said respiratory signal into a plurality of segments,d) extracting at least one parameter from each segment of the respiratory signal,e) characterising a normal state of attention for the individual by selecting a respiratory signal fragment that is considered to be normal according to a pre-established criterion and, in the event that no respiratory signal fragment is found that meets said pre-established criterion, characterising the normal state of attention for the individual on the basis of certain data stored in a memory device, andf) determining the individual's state of attention from the at least one parameter extracted from each segment on the basis of pre-defined rules and the normal state of attention for the individual, characterised in that: step f) comprises: determining the time between successive crossings with the same slope sign of the respiratory signal with a threshold Th obtained from the individual's respiratory signal in a normal state of attention, normalising said time between successive crossings by a time Tresp corresponding to the average respiratory period of the individual's respiratory signal in a normal state of attention, filtering to obtain a signal Ks, and filtering the absolute value of the derivative of signal Ks, normalised by the value corresponding to the average absolute value of the derivative of signal Ks in the stable respiratory interval, where threshold Th and the average respiratory period of the individual's respiratory signal in a normal state of attention are obtained from the respiratory signal fragment selected to characterise the individual's normal state of attention, or from the data stored in the memory device, in the event that no respiratory signal fragment is found that meets said pre-established criterion. 18. The method for determining an individual's state of attention, according to claim 17, characterised in that step f) comprises determining the individual's state of attention by comparing the normalised, filtered absolute value of the derivative of signal Ks to at least one threshold, and, optionally, taking into consideration the states of attention determined at previous times. 19. The method for determining an individual's state of attention, according to claim 17, characterised in that level Th of the stable respiratory interval is determined as a percentile of the individual's respiratory signal in a normal state of attention greater than 50%. 20. The method for determining an individual's state of attention, according to claim 17, characterised in that the determination of the individual's respiratory signal in a normal state of attention comprises: calculating a statistical variable RCXWi for different respiratory signal fragments, and selecting the fragment with the most stable variance, which minimises statistical variable RCXWi. 21. The method for determining an individual's state of attention, according to claim 20, characterised in that statistical variable RCXWi is obtained from a heteroscedasticity test. 22. The method for determining an individual's state of attention, according to claim 21, characterised in that statistical variable RCXWi is: RCXWi=1M⁢∑n=1M⁢[∑i=1n⁢(Resp⁡(i))2∑i=1M⁢(Resp⁡(i))2]-nM⁢where Resp(i) is the i-th respiratory sample within a window with M samples of the sampled respiratory signal. 23. A system for determining an individual's state of attention, the system comprising: a respiratory signal capture apparatus; anda processor for performing the following:a) receiving an individual's respiratory signal from the respiratory signal capture apparatus,b) segmenting said respiratory signal into a plurality of segments,c) extracting at least one parameter from each segment of the respiratory signal,d) characterising a normal state of attention for the individual by selecting a respiratory signal fragment that is considered to be normal according to a pre-established criterion and, in the event that no respiratory signal fragment is found that meets said pre-established criterion, characterising the normal state of attention for the individual on the basis of certain data stored in a memory device, ande) determining the individual's state of attention from the at least one parameter extracted from each segment on the basis of pre-defined rules and the normal state of attention for the individual,wherein step c) comprises obtaining at least one fuzzy parameter from the at least one parameter extracted from each segment, and step e) comprises: evaluating the degree of similarity of each segment with respect to each one of a plurality of pre-determined phases, by comparing the at least one fuzzy parameter of each segment to characteristic parameters for said pre-determined phases, and determining the individual's state of attention from the degree of similarity of the segments of the signal with respect to said pre-determined phases on the basis of certain pre-defined rules. 24. The system for determining an individual's state of attention, according to claim 23, which comprises means for capturing a respiratory signal. 25. The system for determining an individual's state of attention, according to claim 23, which comprises means for interacting with the individual, in order to inform them of a given state of attention. 26. The system for determining an individual's state of attention, according to claim 25, wherein the means for interacting with the individual are adapted for activating an alarm in response to the detection of a state of attention. 27. A vehicle that comprises the system, according to claim 23. 28. A computer readable medium having program code means embodied therein for determining an individual's state of attention, the program code means comprising: a) obtaining an individual's respiratory signal from a respiratory signal capture apparatus,b) segmenting said respiratory signal into a plurality of segments,c) extracting at least one parameter from each segment of the respiratory signal,d) characterising a normal state of attention for the individual by selecting a respiratory signal fragment that is considered to be normal according to a pre-established criterion and, in the event that no respiratory signal fragment is found that meets said pre-established criterion, characterising the normal state of attention for the individual on the basis of certain data stored in a memory device, ande) determining the individual's state of attention from the at least one parameter extracted from each segment on the basis of pre-defined rules and the normal state of attention for the individual, wherein step c) comprises obtaining at least one fuzzy parameter from the at least one parameter extracted from each segment, and step e) comprises: evaluating a degree of similarity of each segment with respect to each one of a plurality of pre-determined phases, by comparing the at least one fuzzy parameter of each segment to characteristic parameters for said pre-determined phases, and determining the individual's state of attention from the degree of similarity of the segments of the signal with respect to said pre-determined phases on the basis of certain pre-defined rules.