Automatic Analytical Apparatus

1 . An automatic analytical apparatus, comprising:

a reaction container for mixing a sample with a reagent to react the sample to the reagent;

a measurement unit that irradiates a reaction solution in the reaction container with light and measures the intensity of transmitted light or scattered light;

a control unit that processes time-series light intensity data obtained through the measurement in the measurement unit;

a storage unit that stores one or more approximation functions each approximating to a time-series change in the light intensity data; and

an output unit that outputs a processing result of the control unit,

wherein the control unit

selects any one of the approximation functions stored in the storage unit,

calculates an approximate curve indicating a time-series change in the light intensity data using the selected approximation function,

calculates deviation feature information based on deviation information between the light intensity data and the approximate curve, and

detects and classifies abnormality included in the light intensity data using the deviation feature information, and

the output unit outputs information on the detected and classified abnormality.

2 . The automatic analytical apparatus according to claim 1 ,

wherein the control unit

calculates time-series error data indicating a time-series change in an error between the light intensity data and the approximate curve, and

detects and classifies the abnormality using the time-series error data as the deviation feature information.

3 . The automatic analytical apparatus according to claim 2 ,

wherein the control unit

calculates a predetermined index from the light intensity data or the approximate curve,

calculates an abnormality occurrence range in which an abnormality occurs in the light intensity data on the basis of the time-series error data,

calculates a feature amount of the time-series error data in the abnormality occurrence range, and

classifies the abnormality using the feature amount and the index.

4 . The automatic analytical apparatus according to claim 3 ,

wherein the index is a tentative analysis result calculated from the approximate curve.

5 . The automatic analytical apparatus according to claim 1 ,

wherein the control unit

normalizes the deviation feature information on the basis of information obtained from at least one of the light intensity data and the approximate curve, and

detects and classifies the abnormality using the normalized deviation feature information.

6 . The automatic analytical apparatus according to claim 5 ,

wherein the control unit

normalizes information on time included in the deviation feature information on the basis of information on time obtained from at least one of the light intensity data and the approximate curve, and

normalizes information on the light intensity included in the deviation feature information on the basis of information on the light intensity obtained from at least one of the light intensity data and the approximate curve.

7 . The automatic analytical apparatus according to claim 1 ,

wherein the control unit

takes the light intensity data in a predetermined period,

calculates deviation feature information based on deviation information between the light intensity data in the period and the approximate curve, and

detects and classifies abnormality included in the light intensity data using the deviation feature information.

8 . The automatic analytical apparatus according to claim 7 ,

wherein the control unit determines whether the measurement in the measurement unit stops or continues on the basis of the classified type of abnormality.

9 . The automatic analytical apparatus according to claim 1 ,

wherein the approximation function is a function having

a first area in which a change amount of the light intensity with respect to a time gradually increases, and

a second area in which a change amount of the light intensity with respect to the time is smaller than that in the first area at a time after the first area.

10 . The automatic analytical apparatus according to claim 1 ,

wherein the output unit outputs at least one of:

(1) the light intensity data output using time as a first axis and a light intensity value as a second axis,

(2) the approximate curve output using time as a first axis and a light intensity value as a second axis,

(3) the deviation feature information,

(4) a result of analysis,

(5) an equation of the approximation function,

(6) a result of detection of an abnormality,

(7) a result of classification of an abnormality, and

(8) information on a process of coping with the abnormality.

11 . The automatic analytical apparatus according to claim 1 ,

wherein a blood coagulation reaction is analyzed.

12 . The automatic analytical apparatus according to claim 1 ,

wherein the control unit classifies the deviation feature information on the basis of a decision tree stored in the storage unit.

13 . The automatic analytical apparatus according to claim 1 ,

wherein the storage unit stores any one of:

(1) at least one any-dimensional vector associated with the type of abnormality,

(2) an identification, boundary in at least one any-dimensional space associated with the type of abnormality,

(3) a partial space in at least one any-dimensional space associated with the type of abnormality, and

(4) an evaluation function in which an any-dimensional vector is used as an argument and a value associated with the type of abnormality is used as an output value, and

the control unit

converts the deviation feature information into any-dimensional vector feature information through linear or non-linear mapping, and

classifies the type of abnormality on the basis of the any-dimensional vector, the identification boundary, the partial space, or the output value of the evaluation function.

14 . The automatic analytical apparatus according to claim 1 ,

wherein the abnormality includes at least one of:

(1) an abnormality in which the amount of change in light intensity value in the light intensity data suddenly increases or decreases,

(2) an abnormality in which the amount of change in light intensity value in the light intensity data once increases and decreases, and then, increases again, and

(3) an abnormality in which the amount of change in light intensity value in the light intensity data remains at a certain value or in a predetermined range.