JPS6148334A - Eyeball motion measuring apparatus - Google Patents

Abstract

(57) [Summary] This bulletin contains application data before electronic filing, so abstract data is not recorded.

Description

DETAILED DESCRIPTION OF THE INVENTION [Field of Industrial Application] The present invention relates to an eye movement measuring device that obtains various data regarding eye movements based on temporal changes in eye deviation during sleep.

[Prior Art] Analyzing eye movements during sleep is one of the most effective means of determining the stage of activity of the cerebrum and central nervous system, which is called the sleep stage. Therefore, such analysis is indispensable for the diagnosis and treatment of all diseases in the field of neurology and most diseases in the field of medical science. In particular, the rapid movement of the eyeballs called rapid eye movement (hereinafter referred to as REM) is a good indicator of the activity of the cerebrum and central nervous system.
Data regarding REM will be extremely useful for the above diagnosis and treatment. Data on REM, especially the number of REM occurrences, REM interval, and number of REM clusters (REV occurring multiple times in a short period of time), are basic, and doctors can use these data to diagnosis,
Perform a ritual.

[Problems to be Solved by the Invention] Conventionally, the above data has been obtained by manually processing data of eyeball deviation (I'3) and eyeball velocity recorded by a pen recorder. However, the measurement time is long. time 8
~10 hours), so if such I-5 processing was done manually, it would take □1 hour to obtain the results, and there are many errors and oversights, so the results obtained are It was inaccurate.

The present invention has been made in view of the above-mentioned drawbacks, and its purpose is to immediately process eyeball deviation data obtained from an eyeball deviation sensor, calculate the number of REM occurrences, the REM interval, and the REM data.
The goal is to accurately obtain data on the number of swarms.

[Means for Solving Problem 1] Therefore, in the present invention, the REM fi-free signal is calculated from the eyeball deviation signal detected from the eyeball deviation sensor, the signal J3 obtained by firstly differentiating this signal, and the signal J3 obtained by secondarily differentiating this signal. Detects each interval from each point in time when RFM right is detected to the next point in time when REM1 presence is detected, creates frequency data of intervals detected in unit time, and calculates the REM group intervention from this frequency data. The above object has been achieved by creating a device that detects the absence of IJ, totals the number of REMs, intervals, RE M I', and the number of 1-shots for each unit time, and stores this data.

[Example] An embodiment of the present invention will be described below with reference to the drawings.

FIG. 1 shows an eye movement measuring device 1 of an embodiment of the present invention;
, is a configuration diagram. 1 in the figure is an eyeball deviation sensor.

The continuous ball deviation sensor 1 detects the deviation of the eyeball from the reference position and outputs a signal in accordance with the detected deviation of the eyeball. The output signal of the eyeball deviation sensor 1 is arranged to reach a numbing circuit 3 via an A/D converter 2 on the one hand, and a differentiation circuit 4 on the other hand. The output signal of the differentiating circuit 4 is delivered to the arithmetic circuit 3 and the differentiating circuit 6 via the A/D converter 5. Differential circuit 6
The output signal is delivered to an arithmetic circuit 3. a'
The j 'u2 circuit 3 performs a performance using the signals a, b, and c given from the A/D converters 2 and 5 and the differential circuit 6, respectively, and outputs the resulting signal 9 to the presence signal detection device 7. It is. 81 of circuit 3 is specifically shown in Figure 2. In Figure 2, 31 to 35 are clip & limit circuits, 36.37 are anti-111 circuits, and 38 to 35 are clip and limit circuits. 40 is an AND gate, and 41 is an OR gate.This figure shows the state of each signal a~! This example is shown in Figure 3.The signal a directly goes to the clip & limit circuit 31. i) The inversion circuit 36 is connected to the C clip & limit circuit 32. Clip & limit circuits 31, 32
Then, if the given signal is higher than the reference value 0,
It outputs signals 5q-d and e.

The signal goes directly to the clip & limit circuit 33 and also to the clip & limit circuit 34 via the inversion circuit 37. The given values for clip and limit circuits 33 and 34 are the predetermined values. In the above case, signals f and Q which become "lligh" are outputted.

Koushi-C created signal d,! :f is AND gate 3
8 becomes the input signal, and the signals e and 0 become the input signals of AND gate 39. Each of the AND gates 38 and 39 is 2
When both input signals are “old 9h”, “lligh”
A signal! , J. These signals i,
j becomes an input signal to the OR gate 21. OR gate/1
1 is signal 1. When at least one of j is "'1IiQh", a signal k which becomes "lligh" is output.

On the other hand, the signal @C reaches the clip & limit circuit 35. This clip & limit circuit 35 outputs a signal that becomes 'lligh' when the signal C exceeds a predetermined value 00.

The signals and h become the input signals of the AND gate 20. AN
The D gate 20 outputs a signal f in which h is both 'lligh' and 'lligh'.

This is the signal created in this way, or the signal that becomes "ll1iJh" when the eyeball is rapidly displaced.

The signal or significant signal detection device 7 is reached.

The significant signal detection device 7 determines whether the applied signal 1 is in a significant state or not, and outputs a signal according to the result. In this case, the given belief @ evening is “lligh”
It is significant when it becomes true! It becomes &, indicating that REM has occurred at this time? I-RI=M detection signal is output. This RLM detection signal is delivered to the REM interval detection device 8 and the REV data aggregation device.

The REM interval detection device 8 sequentially detects the interval from each REM to the next REM from the RFM detection signal, and transmits the interval data to the REM swarm detection device 1o.
and is output to the REM data aggregation device 9.

RE M jsf detection ratio detection device 10 detects the REM group 0 and 0 for each unit time from the given interval data. This detection is performed as follows. For example, the hulls (detected at 0.1 second vehicle position) are classified by length, and the appearance frequency of each length is calculated. Then, based on the preset interval interval J5 and the respective frequency thresholds, the above 2.
It determines whether the REV swarm is right or not in o seconds. Data indicating this result is output from the REM data aggregation device q9L.

1,' RE V data aggregation device 9 receives the REM detection signal outputted from the significant signal detection device 7, +\, interval data outputted from the REM internor\detection device 8,
Based on the data indicating the presence or absence of REM swarm output from the REM swarm detection device 10, the number of REMs, the interval of REM, and the number of REM swarms are counted for each unit time.

11 is a REV data storage device. This REM data storage device 11 stores the aggregated data of the REM data aggregating device 9.

As described above, according to the device of this embodiment, data on eyeball deviation obtained from the eyeball deviation sensor is immediately processed, and data on the number of R'EMs, the REM interval, and the number of R[M clusters are .

Incidentally, the processing of the signal output from the A/D converter moxibustion device 2.5 shown in FIG. 1 can be performed by a computer. Here, as an example, a case will be described in which the processing performed by the significant signal detection device 7 is changed to the processing performed by the computer. When the signal λ output from the interference circuit 3 is processed by a computer, FIG. 4 shows 41. %, and the R that the computer has
The significant signal detection device, the processing device, and the auxiliary storage device are divided into "m" according to their functions. Fig. 5 is a flowchart of the processing performed by the computer 1.
To explain the computer processing according to both figures, after the start of the first ten measurements, in step 101, the significant signal detection device holds until a significant signal is detected, and if there is a significant signal, the process branches to YES, and in step 102, the processing device detects the significant signal. Outputs the λ insertion signal. In step 103, the processing device that received this interrupt signal
The detection of EM is memorized, and in step 104, the elapsed time from the previous REM detection time to the current time is RE
Record as V interval. After the processing in step 104, the process returns to step 101 again. Step 101 above
.about.104 are repeated in short cycles (for example, 0.1 seconds). In contrast to the processing flow of steps 101 to 104, there is another processing flow. This is a flow for processing REM detection and REM interval data recorded within a predetermined time (for example, 20 seconds) in steps 103 and 104 above. To explain this, first, in step 201, the processing device waits until the aggregation unit time period (predetermined time described above) has elapsed, and when the aggregation unit time period has elapsed, Y
The process branches to S, and in step 202, the RE M r, It emission is detected from the REM interval and recorded. Then, in step 203, the number of times of REM, RFM inter-pulse, and number of REM clusters are totaled for each unit time, and then, in step 204, the totaled data is stored in the auxiliary display device.

\L' Steps 103 and 104 above are R shown in Figure 1.
The above step 201.
Reference numeral 202 corresponds to the REV swarm detection device 10 shown in FIG. 1, and step 203 corresponds to the REM data aggregation device 9, respectively.

[Effects of the Invention] According to the present invention, the data of the eyeball position determined from the eyeball deviation hinge can be quickly processed without manual intervention, and the RLM interval i15 J: and R["M
It is possible to calculate the number of l'J-shots exactly 45I. The REV data obtained in this way can provide powerful clues for the diagnosis of central nervous system disorders, brain disorders, intellectual disabilities, mental disorders, 2 behavioral disorders, 2 behavioral abnormalities, etc. When an abnormality is observed in the REV data, it is often the case that there is a disorder in areas such as the suprachiasmatic nucleus, pineal gland, hypothalamus, raphe nucleus, focal nucleus, optic attraction, basal nucleus, or frontal lobe. Accurate diagnosis of these areas has not been possible until now without 211 examinations, but using the device of the present invention, it is now possible to perform non-invasive and highly accurate diagnosis using the accurate data provided. It's possible.

[Brief explanation of the drawing]

Figure 1 is the overall high-level configuration diagram of the device of the present invention. Figure 2 is the internal configuration diagram of the Q circuit.
1 is a diagram showing an example of the state of each signal shown in FIG. 1, FIG. 4 is an explanatory diagram when the apparatus of the present invention is configured using a computer, and FIG. 5 is a diagram illustrating its processing flow. 1... Eyeball deviation sensor 2.5... A/D converter 4.6... - Differential circuit 3-... Performance Q circuit 7...
Significant signal detection device 8...RE M interval detection device 10...RE
M swarm detection device 9-・REM data aggregation device 11... REM data storage device special M'Fl:l:iIi'l! EB Yur for the director of the Institute of Industrial Science and Technology. Figure 2 Figure 3 0-zu-111=-λ

Claims (1)

[Claims] an eyeball deviation sensor that detects the deviation of the eyeball; a first differentiator that differentiates the output signal of the eyeball deviation sensor; and a second differentiator that differentiates the output signal of the first differentiator; rapid eye movement detection means for detecting the presence or absence of rapid eye movement based on the output signal of the eyeball deviation sensor and the output signals of the first and second differentiating means; An interval detection means detects each interval from the time when the presence of movement is detected to the time when the presence of the next rapid eye movement is detected, and data on the frequency of the interval detected every unit time by the interval detection means are used to detect the rapid eye movement. swarm detection means for detecting the presence or absence of eye movement clusters; the number of rapid eye movements detected by the rapid eye movement detection means; the intervals detected by the interval detection means; and the rapid eye movements detected by the swarm detection means. An eye movement measuring device comprising: a totalizing means for totalizing the number of swarms for each unit time; and a storage means for storing data compiled by the totaling means.