SYSTEM AND METHOD FOR SPO2 INSTABILITY DETECTION AND QUANTIFICATION
First Claim
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1. A method of analyzing data, comprising:
- a processor, of a computer system, receiving data corresponding to at least one time series; and
the processor computing a plurality of sequential instability index values of the data from a corresponding plurality of sequential portions of the time series, wherein the instability index values correspond to at least one aspect of severity of at least one apnea or hypopnea cluster during the corresponding sequential portions of the time series.the processor generating a sequential and substantially real-time output of the sequential instability index values so that patient treatment can be quickly adjusted in response to the severity of apnea or hypopnea clusters.
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Abstract
The disclosed embodiments relate to a system and method for analyzing data. An exemplary method comprises the acts of receiving data corresponding to at least one time series, and computing a plurality of sequential instability index values of the data. An exemplary system comprises a source of data indicative of at least one time series of data, and a processor that is adapted to compute at least one of a plurality of sequential instability index values of the data.
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Citations
66 Claims
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1. A method of analyzing data, comprising:
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a processor, of a computer system, receiving data corresponding to at least one time series; and the processor computing a plurality of sequential instability index values of the data from a corresponding plurality of sequential portions of the time series, wherein the instability index values correspond to at least one aspect of severity of at least one apnea or hypopnea cluster during the corresponding sequential portions of the time series. the processor generating a sequential and substantially real-time output of the sequential instability index values so that patient treatment can be quickly adjusted in response to the severity of apnea or hypopnea clusters. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18)
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19. A system, comprising:
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a source of data indicative of at least one time series of data; and a processor that is adapted to compute at least one of a plurality of sequential instability index values of the data from a corresponding plurality of sequential portions of the time series, wherein the instability index values correspond to at least one aspect of severity of at least one apnea or hypopnea cluster during the corresponding sequential portions of the time series, the processor generating a sequential and substantially real-time output of the sequential instability index values so that patient treatment can be quickly adjusted in response to the severity of apnea or hypopnea clusters. - View Dependent Claims (20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36)
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37. A pulse oximeter, comprising:
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a probe that is adapted to be attached to a body part of a patient to create a signal indicative of an oxygen saturation of blood of the patient; and a processor that is adapted to receive the signal produced by the probe, to calculate an SPO2 time series based on the signal, and to compute a plurality of sequential instability index values of the SPO2 time series, from a corresponding plurality of sequential portions of the time series, wherein the instability index values corresponds to at least one aspect of severity of severity of apnea or hypopnea clusters during the corresponding sequential portions of the time series, the processor generating a substantially real-time output of the sequential instability index values so that patient treatment can be quickly adjusted in response to the severity of apnea or hypopnea clusters after only a brief period of apnea or hypopnea clusters. - View Dependent Claims (38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54)
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55. A system for analyzing data, comprising:
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means for receiving data corresponding to at least one time series derived from a pulse oximeter or a carbon-dioxide detector; and means for computing a plurality of sequential instability index values of the data from a corresponding plurality of sequential portions of the time series, wherein each of the instability index values corresponds to at least one aspect of severity of apnea or hypopnea clusters during each of the corresponding sequential portions of the time series, the processor generating a sequential and substantially real-time output of the sequential instability index values so that patient treatment can be quickly adjusted in response to the severity of apnea or hypopnea clusters.
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56. A non-transitory machine-readable medium, comprising:
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code adapted to access data corresponding to at least one time series; and code adapted to compute a plurality of sequential instability index values of the data from a corresponding plurality of sequential portions of the time series, wherein each of the instability index values corresponds to at least one aspect of severity of apnea or hypopnea clusters during each of the corresponding sequential portions of the time series, the processor generating a sequential and substantially real-time output of the sequential instability index values so that patient treatment can be quickly adjusted in response to the instability index values.
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57. A method of analyzing data, comprising:
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receiving data corresponding to at least one time series derived from a pulse oximeter or a carbon-dioxide detector; detecting at least one pattern in the data; and computing a plurality of sequential instability index values of the data based at least in part on the at least one pattern from a corresponding plurality of sequential portions of the time series, wherein each of the instability index values corresponds to at least one aspect of severity of apnea or hypopnea clusters during each of the corresponding sequential portions of the time series, a processor generating a sequential and substantially real-time output of the sequential instability index values so that patient treatment can be quickly adjusted in response to the instability index values. - View Dependent Claims (58)
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59. A method of analyzing data, comprising:
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receiving data corresponding to at least one time series derived from a pulse oximeter or a carbon-dioxide detector; and detecting a plurality of pattern components of the data;
computing a plurality of sequential instability index values of the data based at least in part on at least one of the plurality of pattern components from a corresponding plurality of sequential portions of the time series, wherein each of the instability index values corresponds to at least one aspect of severity of apnea or hypopnea clusters during each of the corresponding sequential portions of the time series, a processor generating a sequential and substantially real-time output of the sequential instability index values so that patient treatment can be quickly adjusted in response to the severity of apnea or hypopnea clusters.
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60. A method of analyzing data, comprising:
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receiving data corresponding to at least one time series derived from a pulse oximeter or a carbon-dioxide detector; and
detecting a plurality of abnormal values in the data; andcomputing a plurality of sequential instability index values of the data based at least in part on at least one of the plurality of abnormal values from a corresponding plurality of sequential portions of the time series, wherein each of the instability index values corresponds to at least one aspect of severity of apnea or hypopnea clusters during the corresponding sequential portions of the time series, a processor generating a sequential and substantially real-time output of the sequential instability index values so that patient treatment can be quickly adjusted in response to the severity of apnea or hypopnea clusters.
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61. A method of analyzing data, comprising:
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receiving data corresponding to at least one time series derived from a pulse oximeter or a carbon-dioxide detector; detecting a plurality of abnormal values in the data; and detecting at least one pattern of at least a subset of the abnormal values, computing a plurality of sequential instability index values based at least in part on the detecting of the plurality of abnormal values and the at least one pattern induced by at least one apnea or hypopnea clusters from a corresponding plurality of sequential portions of the time series, wherein each of the instability index values corresponds to at least one aspect of severity of the pattern, a processor generating a sequential and substantially real-time output of the sequential instability index values so that patient treatment can be quickly adjusted in response to the severity of the pattern.
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62. A method of analyzing data from a patient, comprising:
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receiving data corresponding to at least one time series having at least one complex pattern; computing a plurality of sequential instability index values indicative of an instability of the at least one pattern induced by a cluster of apnea or hypopnea; and converting the plurality of sequential instability index values into an instability index time series from a corresponding plurality of sequential portions of the time series, wherein each of the instability index values corresponds to at least one aspect of severity of the pattern, a processor generating a sequential and substantially real-time output of the sequential instability index values so that patient treatment can be quickly adjusted in response to the severity of the pattern.
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63. A method of analyzing data from a patient, comprising:
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receiving data corresponding to at least one time series; and computing a plurality of sequential instability index values indicative of a plurality of sequential indications of a magnitude of instability of the patient from a corresponding plurality of sequential portions of the time series, wherein each of the instability index values corresponds to at least one aspect of severity of apnea or hypopnea clusters during each of the corresponding sequential portions of the time series, a processor generating a sequential and substantially real-time output of the sequential instability index values so that patient treatment can be quickly adjusted in response to the severity of apnea or hypopnea clusters. - View Dependent Claims (64)
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65. A method of analyzing data from a patient, comprising:
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receiving data corresponding to at least one time series; and computing a plurality of sequential instability index values indicative of at least one pattern of magnitude of instability of the patient from a corresponding plurality of sequential portions of the time series, wherein each of the sequential instability index values corresponds to at least one aspect of severity of apnea or hypopnea clusters during each of the corresponding sequential portions of the time series, a sequential and substantially real-time output of the sequential instability index values being generated so that patient treatment can be quickly adjusted in response to the severity of apnea or hypopnea clusters. - View Dependent Claims (66)
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Specification