Abstract: The invention relates to processing of physiological signal data in patient monitoring. In order to alleviate the problems caused by suppression waveforms in the analysis of physiological signal data, measurement data is derived from a segment of the time series of physiological signal data and valid measurement data is collected from the derived measurement data, thereby to form a set of valid measurement data. The collecting includes selecting measurement data that fulfills at least one predetermined threshold condition. Furthermore, at least a portion of the set of valid measurement data is supplied to a further processing stage when the amount of collected measurement data in the set is at least at a predetermined level. The deriving and collecting may be repeated for consecutive segments of the time series, in which case the supplying is performed for at least some of the consecutive segments of the time series.

Abstract: Method, apparatus and computer program product for monitoring seizure activity in brain are disclosed. At least one parameter set time series is derived from brain wave signal data obtained from a subject, wherein each parameter set sequence comprises sequential parameter sets and each parameter set comprises values for at least two signal parameters, the values being derived from the brain wave signal data. In order to reduce susceptibility to inter-subject variations and to enhance adaptability to each recording, past EEG signal data of the subject is used to determine an envelope object that encompasses the parameter points that sequential parameter sets derived from the past signal data form in a parameter space. A reference point is also determined, whose location in the parameter space depends on the past signal data. At least one new parameter point is then obtained from the subject and an evolution indicator set is determined.

Abstract: Method, apparatus and computer program product for monitoring seizure activity in brain are disclosed. At least one parameter set time series is derived from brain wave signal data obtained from a subject, wherein each parameter set sequence comprises sequential parameter sets and each parameter set comprises values for at least two signal parameters, the values being derived from the brain wave signal data. In order to reduce susceptibility to inter-subject variations and to enhance adaptability to each recording, past EEG signal data of the subject is used to determine an envelope object that encompasses the parameter points that sequential parameter sets derived from the past signal data form in a parameter space. A reference point is also determined, whose location in the parameter space depends on the past signal data. At least one new parameter point is then obtained from the subject and an evolution indicator set is determined.

Abstract: In a method and apparatus for providing an indication suitable for assessing a physiological condition of a patient, at least two biosignals are obtained from the patient. The biosignals contain at least one common physiological data component, such as an EEG or EMG component. An analysis of each of the biosignals is carried out to obtain a complexity value for each of the biosignals. Or, the biosignals may be divided into their components and a complexity value is obtained for the biosignal components. Thereafter and on the basis of the complexity values, a complexity value indicative of at least one physiological data component present in the biosignals is selected and utilized to provide the physiological condition assessment indication of the patient.

Abstract: The invention relates to a method and apparatus for assessing the reactivity observable in a certain physiological signal, especially the EEG signal, of a comatose subject. In order to obtain an objective and a reliable measure of the reactivity automatically and without the presence of a trained EEG specialist, a time reference corresponding to a stimulus is detected and the physiological signal data obtained from the subject is aligned with the time reference. Two sets of values are determined for a measure indicative of the amount of irregularity in the physiological signal data, both sets including at least one value of the said measure and having defined positions with respect to the time reference in time domain. Based on the two sets, the apparatus determines whether reactivity is present in the physiological signal data.

Abstract: The invention relates to a method and apparatus for assessing the reactivity observable in a certain physiological signal, especially the EEG signal, of a comatose subject. In order to obtain an objective and a reliable measure of the reactivity automatically and without the presence of a trained EEG specialist, a time reference corresponding to a stimulus is detected and the physiological signal data obtained from the subject is aligned with the time reference. Two sets of values are determined for a measure indicative of the amount of irregularity in the physiological signal data, both sets including at least one value of the said measure and having defined positions with respect to the time reference in time domain. Based on the two sets, the apparatus determines whether reactivity is present in the physiological signal data.

Abstract: The invention relates to a method and apparatus for assessing the reactivity observable in a certain physiological signal, especially the EEG signal, of a comatose subject. In order to obtain an objective and a reliable measure of the reactivity automatically and without the presence of a trained EEG specialist, a valid signal model is constructed for an EEG signal obtained from the subject. A time reference corresponding to a stimulus is applied and further signal data is obtained from the time series, the further signal data being subsequent to the time reference. By employing the further signal data, the method tests whether the signal model remains to be a valid signal model for the EEG signal also after the stimulus, and indicates, based on the test, whether reactivity is present in the physiological signal.

Abstract: The invention relates to a method and apparatus for assessing the reactivity observable in a certain physiological signal, especially the EEG signal, of a comatose subject. In order to obtain an objective and a reliable measure of the reactivity automatically and without the presence of a trained EEG specialist, a valid signal model is constructed for an EEG signal obtained from the subject. A time reference corresponding to a stimulus is applied and further signal data is obtained from the time series, the further signal data being subsequent to the time reference. By employing the further signal data, the method tests whether the signal model remains to be a valid signal model for the EEG signal also after the stimulus, and indicates, based on the test, whether reactivity is present in the physiological signal.

Abstract: The invention relates to a method and apparatus for monitoring the anesthetic state of a subject. Physiological signal data including EEG and possibly also EMG signal components is acquired from a subject and supplied to a monitoring process configured to derive, based on the said data, a state index indicative of the anesthetic state of the subject. In order to extend the applicability of present-day monitoring processes, the operation of the monitoring process is controlled according to whether at least one drug inducing high frequency EEG signal components is administered to the subject. The presence of the high frequency EEG signal components in the physiological signal data may be detected automatically.

Abstract: The invention relates to a method and apparatus for monitoring the cerebral state of a subject. At least one of a first and second parameters is derived from the physiological signal data obtained from the subject, wherein the first parameter is indicative of the sum of spectral values of the physiological signal data in a first frequency band lying above high frequency EEG activity and the second parameter is indicative of the relative magnitudes of a first sum of k-th order spectral values and a second sum of n-th order spectral values. The second sum is calculated over a frequency band lying above high frequency EEG activity (k>2 and n>1). A state index is then formed, which is dependent on the at least one parameter and indicative of the cerebral state of the subject. The first and second parameters may be used in the Bispectral Index (BIS™) algorithm.

Abstract: The invention seeks to provide a method and a system for identifying a dominant signal component in a biosignal including at least two signal components. A biosignal including a first signal component having a first frequency range and a second signal component having a second frequency range is obtained from a subject. First and second indicators are then determined, which characterize the probability distribution of a predefined property, such as frequency, of the biosignal on predetermined primary and auxiliary frequency bands, respectively. Based on the first and second indicators, the system detects which one of the first and second signal components is currently a dominant signal component in the biosignal. The knowledge of the dominant component may be utilized in different ways in different systems monitoring the state of the subject.

Abstract: The invention relates to detection of encephalopathy based on EEG signal data obtained from a patient. A first signal component is derived from the EEG signal data, the first signal component representing low frequencies of the EEG signal data. A first parameter indicative of disorder in the first signal component and a second parameter indicative of disorder in EEG signal data representing a first frequency band are then computed, wherein the first frequency band includes higher frequencies than said low frequencies. An indicator of encephalopathy is then determined based on the first parameter and the second parameter, the indicator of encephalopathy being indicative of encephalopathy.