Patent Application: US-201314398217-A

Abstract:
the invention relates to a method for detecting a physiological state of a patient deviating from a reference physiological state , in which , after having determined , in each of q frequency bands , r reference matrices pr q , r with qe and rε which correspond to the reference physiological state , the following steps are repeated in a loop : carrying out measurements , in m time segments , of an electroencephalographic signal ; filtering and centering the measurements in q frequency bands to obtain and determine m × q scaled matrices of spatial covariance ; for each time segment m , calculating a deviation from the reference physiological state , and comparing each of the deviations from the reference physiological state to a predefined threshold . the invention also relates to a monitoring device applying said method .

Description:
the invention will now be detailed with reference to its application to the detection of discord between a patient and the breathing assistance device to which he or she is connected . it is assumed here that , in the event of discord , the cerebral activity of the patient is modified relative to a reference physiological state in which the patient is in harmony with the breathing assistance device . any cognitive act results from a cooperation between several spatially distributed neural networks ( varela et al ., 2001 ). at the current time , and despite their recent advances , the main cerebral imaging techniques ( electro - encephalography , magnetoencephalography , functional magnetic resonance imaging and position emission tomography ) provide only a mapping of the cerebral activations , without directly taking into account interactions between these activations . the invention is based on the assumption whereby the dynamic links between the neural groups are manifested by the synchronization of oscillatory activities in a frequency band ( varela et al ., 2001 ). numerous experimental results in animals obtained through recordings by microelectrodes already validate this assumption of synchrony . in humans , studies have shown the existence of synchronizations between remote regions , linked to the cognitive context ( rodriguez et al . 1999 ). the assumption of a role of the synchronies in the integration of the cerebral activities was originally proposed by milner in 1974 to resolve the problem of the figure / background segmentation in a visual scene . milner proposed that the neurons responding to the figure discharge synchronously , whereas those coding for the background discharge randomly . this assumption was consequently taken up by freeman ( freeman , 1975 ) and supported by works on the olfactory bulb of rabbits , and then by von der marlsburg ( von der marlsburg , 1981 ) before sinking into relative oblivion . however , the discovery of synchronous oscillations in animals in the band γ ( 30 - 70 hz ) by gray and singer ( gray and singer , 1989 ) in the visual cortex of cats re - excited interest in this idea : this study showed that two neurons of the visual cortex discharge in phase at frequencies in the vicinity of 40 hz in response to stimulations which seem to originate from the same object . conversely , if the stimuli do not seem to originate from the same object , the neurons discharge also , but not in synchrony . these results fit into an approach which can be expressed in terms of resonant cell assemblies ( varela 1995 ; damasio 1990 ; llinas , ribary et al . 1994 ): the emergence of any cognitive act would correspond to the transient selection of a distributed subset of neurons linked by strong reciprocal connections ( a cell assembly ). because of its very dense network of interconnections , the brain contains an almost infinity of assemblies of this type and each neuron can belong , at different instants , to a myriad of assemblies . the selection would be made by rapidly placing the different neurons belonging to the assembly in synchrony in a specific frequency band ( resonance ). the synchrony would act as a “ glue ” enabling neurons to assemble temporarily in a resonant assembly , and thereby allowing for the neural integration necessary to a cognitive act . it is useful to distinguish two levels of assemblies . at a local level , the formation of micro - assemblies in one and the same cortical area would allow the integration of information of the same kind ( visual , audible ). these local links would correspond to the synchronies observed in animals between close neurons ( singer 1995 ). these micro - assemblies could , in turn , enter into synchrony to form macro - assemblies linking remote cerebral areas . these macro - assemblies would allow for the integration of processes of different kinds in complex cognitive acts . the aim of the present invention is to exploit these assumptions to recognize a change of the cerebral activity linked to an unusual situation , for example a situation of “ modified ” breathing ( inhalatory stress , as can be simulated in the laboratory , or encountered in pathology or under mechanical breathing assistance ), compared to a reference activity or physiological state . the recognition of such a situation makes it possible , for example , to order a modification of the operation of the breathing assistance device to return the patient to a situation of comfort characterized by a normal cerebral activity . having set the general context of the invention , the method of the invention will now be detailed . the principle of the invention is first explained with reference to fig1 , in which can be seen the patient 1 lying on a bed 2 and equipped with a mask 3 connected by an air intake to a breathing assistance device 4 . the patient is equipped with a headset 5 bearing n electrodes designed to measure electro - encephalographic signals . the headset 5 is connected to a monitoring device 6 , here a computer comprising a central unit 7 executing a monitoring program , which receives the electro - encephalographic measurements , processes them , and generates in response setpoints intended for the breathing assistance device to which the monitoring device 6 is connected . the monitoring device implements a real - time monitoring algorithm , illustrated in fig2 , which implements the method of the invention to permanently monitor the electro - encephalographic activity of the patient . the advantage of the method of the invention is that the monitoring cycle is very short and the monitoring device can thus react rapidly to the detection of a deviant physiological state . the device here comprises means for reacting to the detection of a threshold overshoot , for example a loudspeaker 8 for emitting an alarm , and thus warning the caring personnel , but is also programmed to generate a setpoint intended for the breathing assistance device 4 to which it is connected by a cable 9 . to operate , the monitoring device 6 must have first characterized a reference physiological state of the patient , for example a state of comfort in which the patient feels no breathing discomfort . for this , as indicated in fig3 , the monitoring device 6 measures electro - encephalographic signals of the patient in real - time and thus performs the measurements in m time segments . each measurement gives rise to a matrix x m ref of n signals measured at p instants during the time segment m , thus forming p samples in each time segment . then , the monitoring device 6 filters and centers each measurement matrix x m ref in q frequency bands ( preferably the five usual frequency bands for studying electro - encephalograms : 1 - 4 hz , 4 - 8 hz , 8 - 12 hz , 12 - 24 hz and 24 - 48 hz ) to obtain m × q filtered reference measurement matrices x m , q ref . from the filtered measurement matrices , the monitoring device 6 determines m × q standardized reference matrices of spatial covariance c m , q ref by the formula : the spatial covariance matrices c m , q ref characterize the synchronization of the neural activities over time . these spatial covariance matrices comprise , in the diagonal , the local synchronizations and , outside the diagonal , the remote synchronizations which are then the characteristics of the dynamics of the neural network . then , in each frequency band , reference matrices or prototypes pr q , r rε [ 1 . . . r ] are determined from the distribution of the spatial covariance matrices c m , q ref . each prototype is a representative of a sub - class of the synchronization , and is here estimated by a karcher means of the neighboring reference matrices of spatial covariance c m , q ref . the procedure for computing the prototypes pr q , r used in the present implementation is described hereinbelow and is applied for each frequency band . this computation here relies on the dynamic swarms algorithm ( e . diday , 1971 ) adapted to the riemannian metric . it will in effect be noted that , in processing the signal the conventional frobenius norm is usually used to define distances between covariance matrices ( which are by definition positive - definite hermitian matrices ). this approach presupposes a normed vector space of zero curvature . however , the space of the positive - definite hermitian matrices pertains rather to the metric spaces with negative curvature . the approach proposed in the context of the invention preferably uses the tools of riemannian geometry to manipulate the covariance matrices . in this context , the distance between two matrices corresponds to the geodesic in the space generated by their hermitian property ; and the mean of the covariance matrices no longer corresponds to an arithmetic mean as conventionally , but to a geometrical mean . 9 : label ( i ):= arg min j = 1 : l [ dist ( pr j , c i )] here , and according to a particular aspect of the invention , the distance dist between the matrices used here is the following riemannian distance : if p 1 , p 2 are two matrices , then in which the λ k are the k specific values of the joint matrix p 1 − 1 · p 2 . this riemannian distance verifies the three properties of a distance ( symmetry , separation and triangular inequality ). the computation of the karcher mean m r of a set of matrices can be performed using a gradient descent procedure which converges rapidly ( pennec et al ., 2006 ): once the reference matrices or prototypes pr q , r have been determined , the monitoring device computes a threshold s by the following method . the distances between each reference spatial covariance matrix c m , q ref and the closest prototype pr q , r are computed , and the median distance dm of all the duly computed distances is determined . the threshold s is then taken to be equal to the arithmetic mean of the absolute values mva of the deviations of each of the duly computed distances from the median distance dm : 3 : d ( i ):= arg min j = 1 : l [ dist ( s j , c i )]); as a variant , the threshold can be determined in any other way . for example , the statistical mean of all the duly computed distances can be retained as threshold , increased by three standard deviations . the preliminary step of characterization of the reference physiological state now having been carried out , the monitoring device 6 can implement the monitoring of the physiological state of the patient in real time as follows . as indicated in fig2 , the monitoring device 6 measures electro - encephalographic signals of the patient in real time and thus performs measurements in m time segments are thus performed . each measurement gives rise to a matrix x m of n signals measured at p instants during the time segment m . then , the monitoring device 6 filters and centers each measurement matrix x m in q frequency bands ( preferably the five usual frequency bands 1 - 4 hz , 4 - 8 hz , 8 - 12 hz , 12 - 24 hz and 24 - 48 hz ) to obtain m × q filtered measurement matrices x m , q . from the filtered measurement matrices , m × q standardized matrices of spatial covariance c m , q are determined by the formula for each time segment m , the monitoring device computes a deviation from the reference physiological state e m by : if one of the duly determined deviations is greater than the threshold s , this is then the sign that the physiological state of the patient is far from the reference physiological state . in this case , the monitoring device 6 modifies the setpoint sent to the breathing assistance device 4 to modify its operation in a direction tending to return the patient to the reference physiological state . the steps of fig2 are repeated in a loop to enable the patient to be monitored permanently . the p time samples of the n signals forming the measurement matrices x m or x m ref can be obtained by using n distinct electro - encephalographic pathways , which makes it possible to take into account the spatial extension of the encephalographic activity . however , it is possible to reconstruct n usable signals from a smaller number r of electro - encephalographic pathways by the time plunge technique ( see lachaux et al ., 1997 ). for this , it is sufficient to determine , for each electro - encephalographic pathway , a time delay δt which is preferably taken to be equal to the time delay taken by the return to the value 1 / e of the self - correlation function of the electro - encephalographic pathway concerned . from a given electro - encephalographic pathway v , it is thus possible to reconstruct q virtual pathways , giving as many usable signals : the parameter k is called time plunge . at the extreme , it is possible to use only a single electro - encephalographic pathway to reconstruct n virtual pathways giving the usable signals in the context of the invention . it is also possible to mix the two methods to obtain a space - time plunge , by using r electro - encephalographic pathways from each of which q virtual pathways are reconstructed such that r × q = n . the graph of fig4 show a test of identification , according to the method of the invention , of the physiological state of a patient induced by encephalographic modifications following a respiratory stress . the part of the curve referenced vs corresponds to a spontaneous ventilation situation used as reference , whereas the part of the curve entitled load corresponds to a provoked discord . the top graph is the deviation between the reference state and the current physiological state of the patient , plotted as a function of time . the bottom graph is the result of the detection of the discord state , for different periods of integration over moving windows of 4 , 8 , 12 seconds , respectively . it is found that a few false alarms are detected in spontaneous ventilation situation over 500 windows analyzed ( 0 . 6 %) following the integration performed over an overall duration of 2000 seconds . it is found that the situation of discord is detected positively by the implementation of the method of the invention . the invention is not limited to what has just been described , but , on the contrary , encompasses any variant falling within the context defined by the claims . in particular , although the monitoring device is here external to the assistance device , it can of course be incorporated therein . damasio , a . r . 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