JP2007000280A - Arousal lowering determination device - Google Patents

Arousal lowering determination device Download PDF

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JP2007000280A
JP2007000280A JP2005182420A JP2005182420A JP2007000280A JP 2007000280 A JP2007000280 A JP 2007000280A JP 2005182420 A JP2005182420 A JP 2005182420A JP 2005182420 A JP2005182420 A JP 2005182420A JP 2007000280 A JP2007000280 A JP 2007000280A
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arousal level
arousal
index
level
physiological index
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Yoshiyuki Hatakeyama
善幸 畠山
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Toyota Motor Corp
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Toyota Motor Corp
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Abstract

<P>PROBLEM TO BE SOLVED: To provide an arousal lowering determination device capable of highly precisely determining the lowering state of the arousal of a specific subject. <P>SOLUTION: When measuring detecting signals of brain wave, respiration, body temperature, blinking and heart rate, or a physiological index group of a specific user (ST2), this arousal lowering determination device computes the physiological index feature quantity such as the brain wave α/β and the like of the specific user (ST3), and calculates a first main component obtained by analyzing the main component of the physiological index feature quantity and having no cross-correlation as an arousal lowering determination index (ST4). In this case, this device uses an eigenvector of the first main component prestored in the eigenvector database and corresponding to the specific user. This device thus computes a time mean value of the arousal lowering determination index corresponding to the specific user (ST5), and highly precisely determines and outputs the lowering state of the arousal of the specific user according to the time mean value (ST6 and ST7). <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

本発明は、例えば車両の運転者などの特定被験者の覚醒度の低下状況を判定する覚醒度低下判定装置に関するものである。   The present invention relates to a wakefulness reduction determination device that determines a state of reduction in wakefulness of a specific subject such as a vehicle driver.

従来、車両運転者を特定する運転者特定装置と、車両運転者の覚醒度の低下状態を判定する覚醒度低下状態判定部とを備えた車両用注意力低下防止装置が一般に知られている。この車両用注意力低下防止装置において、覚醒度低下状態判定部は、心拍数が瞬間的に増加した際の拍動間隔データに基づいて運転者の覚醒度の低下状態を判定するように構成されている(例えば特許文献1参照)。   2. Description of the Related Art Conventionally, there is generally known a vehicle attention level reduction preventing apparatus that includes a driver identification device that identifies a vehicle driver and an arousal level reduction state determination unit that determines a reduction level of a vehicle driver's arousal level. In this vehicle attention level reduction preventing device, the arousal level reduction state determination unit is configured to determine the reduction level of the driver's arousal level based on beat interval data when the heart rate increases instantaneously. (For example, refer to Patent Document 1).

また、被験者の体温、心拍、呼吸などの生体情報を計測して統合することにより被験者の睡眠状態を判定する睡眠状態判定装置が一般に知られている。この睡眠状態判定装置において、体温、心拍、呼吸などの生体情報は、ベクトル量子化などのクラスタリングの手法により統合される(例えば特許文献2参照)。
特開平11−314534号公報(段落番号18、段落番号19) 特開2004−254827号公報(段落番号10、段落番号15、段落番号31)
In addition, a sleep state determination apparatus that determines the sleep state of a subject by measuring and integrating biological information such as the subject's body temperature, heart rate, and breathing is generally known. In this sleep state determination apparatus, biological information such as body temperature, heartbeat, and respiration is integrated by a clustering technique such as vector quantization (see, for example, Patent Document 2).
JP 11-314534 A (paragraph number 18, paragraph number 19) JP 2004-254827 A (paragraph number 10, paragraph number 15, paragraph number 31)

ところで、特許文献1に記載された覚醒度低下状態判定部は、単に心拍数が瞬間的に増加した際の拍動間隔データに基づいて運転者の覚醒度の低下状態を判定するように構成されているため、その覚醒度の低下状態を精度良く判定するのが難しいという問題がある。   By the way, the arousal level reduction state determination unit described in Patent Document 1 is configured to determine the reduction level of the driver's arousal level simply based on pulsation interval data when the heart rate instantaneously increases. Therefore, there is a problem that it is difficult to accurately determine the state of decrease in the arousal level.

また、特許文献2に記載された睡眠状態判定装置は、ベクトル量子化などのクラスタリングの手法により体温、心拍、呼吸などの生体情報(生理指標)を統合しているため、生体情報(生理指標)同士の相互相関が高く、覚醒度低下時に特有の変化を注出することが困難であり、睡眠状態を精度良く判定するのが難しいという問題がある。   Moreover, since the sleep state determination apparatus described in Patent Document 2 integrates biological information (physiological indices) such as body temperature, heartbeat, and respiration by a clustering technique such as vector quantization, biological information (physiological indices). There is a problem that mutual correlation is high, it is difficult to pour out a specific change when the arousal level is lowered, and it is difficult to accurately determine the sleep state.

そこで、本発明は、特定被験者の覚醒度の低下状況を精度良く判定することができる覚醒度低下判定装置を提供することを課題とする。   Then, this invention makes it a subject to provide the wakefulness fall determination apparatus which can determine the fall state of the wakefulness of a specific test subject accurately.

本発明に係る覚醒度低下判定装置は、入力された特定被験者の生理指標群の計測データに基づいて特定被験者の覚醒度の低下状況を判定する装置であって、計測データに基づき特定被験者の覚醒度の低下に関連する複数の生理指標特徴量を求めると共に、求めた複数の生理指標特徴量を主成分分析した第1主成分を覚醒度低下判定指標として求め、かつ、この覚醒度低下判定指標の時間平均値を求める演算手段と、演算手段により求められた覚醒度低下判定指標の時間平均値に応じて特定被験者の覚醒度の低下状況を出力する出力手段と、特定被験者に対応する前記第1主成分の固有ベクトルが予め記憶された記憶手段とを備え、演算手段は、記憶手段に予め記憶された特定被験者に対応する第1主成分の固有ベクトルを使用して第1主成分である覚醒度低下判定指標を決定することを特徴とする。   The arousal level decrease determination device according to the present invention is a device that determines a decrease state of a specific subject's arousal level based on the input measurement data of a specific subject's physiological index group, and the specific subject's arousal level based on the measurement data A plurality of physiological index feature values related to a decrease in the degree, a first principal component obtained by principal component analysis of the obtained plurality of physiological index feature values is obtained as an arousal level decrease determination index, and the arousal level decrease determination index Calculating means for calculating the time average value of the first subject, output means for outputting the state of decrease in the arousal level of the specific subject according to the time average value of the wakefulness level reduction determination index obtained by the calculating means, and the first corresponding to the specific subject Storage means in which an eigenvector of one principal component is stored in advance, and the computing means uses the eigenvector of the first principal component corresponding to the specific subject stored in advance in the storage means. And determining a certain awareness decrease determination indicator.

本発明に係る覚醒度低下判定装置では、特定被験者の生理指標群の計測データが入力されると、この計測データに基づき演算手段が複数の生理指標特徴量を求めると共に、この複数の生理指標特徴量を主成分分析した相互相関のない第1主成分を覚醒度低下判定指標として求める。その際、演算手段は、記憶手段に予め記憶された特定被験者に対応する第1主成分の固有ベクトルを使用して第1主成分である覚醒度低下判定指標を決定し、この覚醒度低下判定指標の時間平均値を求める。そして、この覚醒度低下判定指標の時間平均値に応じて出力手段が特定被験者の覚醒度の低下状況を出力する。   In the arousal level decrease determination device according to the present invention, when measurement data of a physiological index group of a specific subject is input, a calculation unit obtains a plurality of physiological index feature amounts based on the measurement data, and the plurality of physiological index features. The first principal component having no cross-correlation obtained by performing principal component analysis of the amount is obtained as a wakefulness reduction determination index. At that time, the computing means determines the arousal level reduction determination index as the first principal component using the eigenvector of the first principal component corresponding to the specific subject stored in advance in the storage means, and this arousal level reduction determination index. Find the time average of. And according to the time average value of this arousal level reduction determination index, the output means outputs the reduction status of the specific subject's arousal level.

ここで、本発明の覚醒度低下判定装置は、覚醒度低下時に変化が現れ易い生理指標として、脳波、呼吸、体温、瞬目、心拍、皮ふ電位の何れかの項目が生理指標群に含まれていることを特徴とする。   Here, in the wakefulness reduction determination apparatus of the present invention, any of the items of electroencephalogram, respiration, body temperature, blink, heartbeat, and skin potential is included in the physiological index group as a physiological index that easily changes when the wakefulness is lowered. It is characterized by.

また、本発明の覚醒度低下判定装置は、覚醒度低下時に変化が現れ易いと知見された脳波のα波パワーとβ波パワーとの比率が生理指標特徴量に含まれていることを特徴とする。   Further, the wakefulness reduction determination apparatus of the present invention is characterized in that the ratio between the electroencephalogram α wave power and the β wave power, which has been found to change easily when the wakefulness is lowered, is included in the physiological index feature amount. To do.

本発明に係る覚醒度低下判定装置によれば、特定被験者の生理指標群の計測データに基づき演算手段が複数の生理指標特徴量を求めると共に、この複数の生理指標特徴量を主成分分析した相互相関のない第1主成分を覚醒度低下判定指標として求めるため、特定ユーザの覚醒度の低下状況を精度良く注出することができる。   According to the device for determining arousal level reduction according to the present invention, the calculation means obtains a plurality of physiological index feature values based on the measurement data of the physiological index group of the specific subject, and the mutual analysis is performed by principal component analysis of the plurality of physiological index feature values. Since the first principal component having no correlation is obtained as the arousal level reduction determination index, it is possible to accurately extract the reduction status of the arousal level of the specific user.

また、演算手段は、複数の生理指標特徴量を主成分分析した第1主成分を覚醒度低下判定指標として求める際、記憶手段に予め記憶された特定被験者に対応する第1主成分の固有ベクトルを使用して第1主成分である覚醒度低下判定指標を決定し、この覚醒度低下判定指標の時間平均値を求めるため、生理指標特徴量のの演算データの個人差に拘わらず、特定被験者の覚醒度の低下状況を精度良く判定して出力することができる。   Further, when the calculation means obtains the first principal component obtained by principal component analysis of a plurality of physiological index feature values as a wakefulness reduction determination index, an eigenvector of the first principal component corresponding to the specific subject stored in advance in the storage means is obtained. In order to use the first principal component to determine the arousal level decrease determination index and obtain the time average value of the arousal level decrease determination index, regardless of the individual difference in the calculation data of the physiological index feature amount, It is possible to accurately determine and output the state of decrease in arousal level.

以下、図面を参照して本発明に係る覚醒度低下判定装置の実施の形態を説明する。参照する図面において、図1は一実施形態に係る覚醒度低下判定装置のブロック構成図である。   DESCRIPTION OF EMBODIMENTS Hereinafter, an embodiment of a wakefulness reduction determination apparatus according to the present invention will be described with reference to the drawings. In the drawings to be referred to, FIG. 1 is a block configuration diagram of a wakefulness reduction determination device according to an embodiment.

一実施形態の覚醒度低下判定装置は、入力された特定ユーザ(特定被験者)の生理指標群、すなわち、脳波、呼吸、体温、瞬目、心拍の計測データに基づいて特定ユーザの覚醒度の低下状況を判定する装置であって、図1に示すように、ユーザ情報入力部1、生理指標群計測部2、生理指標特徴量演算部3、覚醒度低下判定指標演算部4、固有ベクトルデータベース5、判定指標平均化演算部6、覚醒度低下判定信号出力部7を備えて構成されている。   The arousal level reduction determination apparatus according to an embodiment reduces a wakefulness level of a specific user based on the input physiological index group of the specific user (specific test subject), that is, measurement data of an electroencephalogram, respiration, body temperature, blink, and heart rate. An apparatus for determining a situation, as shown in FIG. 1, as shown in FIG. 1, a user information input unit 1, a physiological index group measurement unit 2, a physiological index feature value calculation unit 3, a wakefulness level decrease determination index calculation unit 4, an eigenvector database 5, The determination index averaging calculation unit 6 and the arousal level decrease determination signal output unit 7 are provided.

ユーザ情報入力部1〜覚醒度低下判定信号出力部7は、入出力インターフェースI/O、A/Dコンバータ、プログラムおよびデータを記憶したROM(Read Only Memory)、入力データ等を一時記憶するRAM(Random Access Memory)、プログラムを実行するCPU(CentralProcessing Unit)等を備えたマイクロコンピュータのハードウェアおよびソフトウェアを利用して構成されている。   The user information input unit 1 to the arousal level determination signal output unit 7 include an input / output interface I / O, an A / D converter, a ROM (Read Only Memory) storing programs and data, and a RAM (temporarily storing input data) Random Access Memory), microcomputer (CPU) that executes a program, and the like are configured using microcomputer hardware and software.

ここで、ユーザ情報入力部1には、今回の覚醒度低下判定の対象となるユーザ(被験者)を特定するため、そのユーザの名前、イニシャル、ID番号などが入力される。このユーザ情報入力部1は、入力された特定ユーザの名前、イニシャル、ID番号などのユーザ情報信号を生理指標群計測部2および固有ベクトルデータベース5に出力する。   Here, in order to identify the user (subject) to be subjected to the current arousal level determination, the user information input unit 1 is input with the user's name, initials, ID number, and the like. The user information input unit 1 outputs the input user information signal such as the name, initials, and ID number of the specific user to the physiological index group measurement unit 2 and the eigenvector database 5.

生理指標群計測部2は、ユーザ情報入力部1から特定ユーザの情報信号が入力されると、図示しない各種のセンサから特定ユーザの脳波、呼吸、脇の下体温、瞬目、心拍の検出信号を入力して計測する。そして、この生理指標群計測部2は、計測したデータを生理指標特徴量演算部3に出力する。   When the information signal of the specific user is input from the user information input unit 1, the physiological index group measurement unit 2 inputs the detection signal of the specific user's brain wave, respiration, armpit body temperature, blink, and heart rate from various sensors (not shown). And measure. Then, the physiological index group measurement unit 2 outputs the measured data to the physiological index feature amount calculation unit 3.

生理指標特徴量演算部3、覚醒度低下判定指標演算部4および覚醒度低下判定指標平均部6は演算手段を構成しており、生理指標特徴量演算部3は、生理指標群計測部2から特定ユーザの生理指標群の計測データが入力されると、その計測データに基づいて後述する第1〜8の生理指標特徴量x1〜x8を演算し、その演算データを覚醒度低下判定指標演算部4に出力する。   The physiological index feature value calculation unit 3, the arousal level decrease determination index calculation unit 4, and the arousal level decrease determination index average unit 6 constitute a calculation unit, and the physiological index feature value calculation unit 3 is derived from the physiological index group measurement unit 2. When measurement data of a specific user's physiological index group is input, first to eighth physiological index feature amounts x1 to x8, which will be described later, are calculated based on the measurement data, and the calculated data is used as a wakefulness reduction determination index calculation unit. 4 is output.

生理指標特徴量演算部3が演算する第1〜8の生理指標特徴量x1〜x8としては、一般にユーザの覚醒度の低下に大きく関連するものが選定される。ここで、図2は、その代表例として知見されたユーザの脳波α/β(脳波α波パワーに対する脳波β波パワーの比率)のレベルと覚醒度のレベルとの関係を示すグラフである。また、図3はユーザの脳波α波パワーのレベルと覚醒度のレベルとの関係を示すグラフであり、図4はユーザの脳波β波パワーのレベルと覚醒度のレベルとの関係を示すグラフである。   As the 1st to 8th physiological index feature values x1 to x8 calculated by the physiological index feature value calculation unit 3, generally those greatly related to a decrease in the user's arousal level are selected. Here, FIG. 2 is a graph showing the relationship between the level of the user's brain wave α / β (ratio of the brain wave β wave power to the brain wave α wave power) and the level of arousal level, which has been found as a representative example. 3 is a graph showing the relationship between the level of the brain wave α wave power of the user and the level of wakefulness, and FIG. 4 is a graph showing the relationship between the level of the brain wave β wave power of the user and the level of wakefulness. is there.

図2〜図4のグラフにおいて、覚醒度のレベルの変化は点線で示されており、覚醒度のレベルが大きく低下して眠くなった状態では、図2に実線で示される脳波α/βのレベルが急激に上昇している。これに対し、図3に実線で示される脳波α波パワーのレベルは、覚醒度のレベルの低下前から低下時にわたって高いレベルを示しており、図4に実線で示される脳波β波パワーのレベルは、覚醒度のレベルの低下に対応して低下している。   In the graphs of FIGS. 2 to 4, the change in the level of wakefulness is indicated by a dotted line, and in the state where the level of wakefulness is greatly reduced and sleepy, the brain wave α / β indicated by the solid line in FIG. The level is rising rapidly. On the other hand, the level of the electroencephalogram α wave power indicated by the solid line in FIG. 3 shows a high level from before the level of wakefulness to the time of reduction, and the level of the electroencephalogram β wave power indicated by the solid line in FIG. Is corresponding to a decrease in the level of arousal.

このような比較検討の結果、図2に実線で示される脳波α/βのレベルがユーザの覚醒度のレベル低下に大きく関連していることが知見され、この脳波α/βのレベルが第1の生理指標特徴量x1として選定されている。なお、第2〜8の生理指標特徴量x2〜x8としては、以下の表1に示すように、呼吸周期(秒)、脇の下体温(℃)、瞬目回数(単位時間当たり)、心拍ゆらぎの0.15〜0.5Hzの高周波成分H、心拍ゆらぎの0.01〜0.15Hzの低周波成分L、毎分心拍数RRI、心拍ゆらぎの低周波成分Lに対する高周波成分Hの比率である心拍ゆらぎL/Hが選定されている。

Figure 2007000280
As a result of such comparative study, it has been found that the level of the brain wave α / β indicated by the solid line in FIG. 2 is greatly related to the decrease in the user's arousal level, and the level of the brain wave α / β is the first level. Is selected as the physiological index feature amount x1. As shown in Table 1 below, as the second to eighth physiological index feature amounts x2 to x8, the respiratory cycle (seconds), armpit body temperature (° C.), number of blinks (per unit time), heart rate fluctuation Heart rate which is the ratio of high frequency component H to high frequency component H of 0.15-0.5 Hz, low frequency component L of 0.01 to 0.15 Hz of heart rate fluctuation, heart rate RRI per minute, low frequency component L of heart rate fluctuation Fluctuation L / H is selected.
Figure 2007000280

ここで、生理指標特徴量演算部3は、生理指標群計測部2から特定ユーザの生理指標群の計測データが所定の時間間隔で順次入力される都度、その計測データに基づいて表1に示す第1〜8の生理指標特徴量x1〜x8を演算し、その演算データを覚醒度低下判定指標演算部4に出力する。この場合、生理指標特徴量x1〜x8は、過去1時間分の平均および標準偏差を用いて標準化した値として演算される。   Here, whenever the measurement data of the physiological index group of the specific user is sequentially input from the physiological index group measurement unit 2 at a predetermined time interval, the physiological index feature value calculation unit 3 is shown in Table 1 based on the measurement data. The first to eighth physiological index feature amounts x1 to x8 are calculated, and the calculated data is output to the arousal level decrease determination index calculation unit 4. In this case, the physiological index feature amounts x1 to x8 are calculated as values standardized using the average and standard deviation for the past one hour.

覚醒度低下判定指標演算部4は、生理指標特徴量演算部3から第1〜8の生理指標特徴量x1〜x8の標準化された値の演算データが入力される都度、その演算データに基づき第1〜8の生理指標特徴量x1〜x8を主成分分析(Principal Component Analysis)してその第1主成分を求め、この第1主成分を覚醒度低下判定指標とする。この覚醒度低下判定指標をA、第1主成分の固有ベクトルをU1(=u1,u2,u3,u4,u5,u6,u7,u8)とすると、覚醒度低下判定指標Aは次の数式(1)で表される。

Figure 2007000280
Each time the awakening level decrease determination index calculation unit 4 receives the calculation data of the standardized values of the first to eighth physiological index feature amounts x1 to x8 from the physiological index feature amount calculation unit 3, the awakening degree decrease determination index calculation unit 4 Physiological index feature amounts x1 to x8 of 1 to 8 are subjected to principal component analysis to obtain a first principal component, and this first principal component is used as a wakefulness reduction determination index. If this arousal level decrease determination index is A and the eigenvector of the first principal component is U1 (= u1, u2, u3, u4, u5, u6, u7, u8), the arousal level decrease determination index A is expressed by the following formula (1 ).
Figure 2007000280

ここで、記憶手段である固有ベクトルデータベース5には、予め決められた特定ユーザを含む複数のユーザ毎に対応する第1主成分の固有ベクトル値U1(=u1,u2,u3,u4,u5,u6,u7,u8)が予め記憶されている。このユーザ毎の固有ベクトル値U1(=u1,u2,u3,u4,u5,u6,u7,u8)は、予め生理指標群計測部2により計測された各生理指標群の計測データに基づいて生理指標特徴量演算部3により演算された各生理指標特徴量x1〜x8を覚醒度低下判定指標演算部4が主成分分析して演算したものであり、例えば次の表2に示す値のように、ユーザ毎に個人差が認められる。

Figure 2007000280
Here, the eigenvector database 5 serving as the storage means stores the eigenvector values U1 (= u1, u2, u3, u4, u5, u6) of the first principal component corresponding to a plurality of users including a predetermined specific user. u7, u8) are stored in advance. The eigenvector value U1 (= u1, u2, u3, u4, u5, u6, u7, u8) for each user is based on measurement data of each physiological index group measured in advance by the physiological index group measuring unit 2. The physiological index feature amounts x1 to x8 calculated by the feature amount calculation unit 3 are calculated by the principal component analysis by the arousal level reduction determination index calculation unit 4, and for example, as shown in the following Table 2, Individual differences are recognized for each user.
Figure 2007000280

固有ベクトルデータベース5は、ユーザ情報入力部1から特定ユーザの名前、イニシャル、ID番号などの情報信号が入力されると、特定ユーザに対応する固有ベクトル値u1〜u8を覚醒度低下判定指標演算部4に出力する。例えば特定ユーザOの名前が信号入力されると、表2のユーザOに対応した列の固有ベクトルu1〜u8の値をユーザOの固有ベクトルU1として覚醒度低下判定指標演算部4に出力する。   When an information signal such as the name, initials, and ID number of a specific user is input from the user information input unit 1, the eigenvector database 5 stores the eigenvector values u <b> 1 to u <b> 8 corresponding to the specific user to the arousal level decrease determination index calculation unit 4. Output. For example, when the name of the specific user O is input as a signal, the values of the eigenvectors u1 to u8 in the column corresponding to the user O in Table 2 are output as the eigenvector U1 of the user O to the arousal level reduction determination index calculation unit 4.

ここで、覚醒度低下判定指標演算部4は、前述のように表1に示した第1〜8の生理指標特徴量x1〜x8を主成分分析してその第1主成分である覚醒度低下判定指標Aを数式(1)により求める際、固有ベクトルデータベース5から入力した特定ユーザOに対応する固有ベクトルu1〜u8の値(表2参照)を数式(1)中のu1〜u8の値として使用する。   Here, the arousal level decrease determination index calculation unit 4 performs principal component analysis on the first to eighth physiological index feature amounts x1 to x8 shown in Table 1 as described above, and the arousal level decrease is the first main component. When the determination index A is obtained from the equation (1), the values of the eigenvectors u1 to u8 (see Table 2) corresponding to the specific user O input from the eigenvector database 5 are used as the values of u1 to u8 in the equation (1). .

その際、覚醒度低下判定指標演算部4は、生理指標特徴量演算部3が今回(時間t=0)演算した特定ユーザOの生理指標特徴量x1〜x8の標準化された値が例えば次の表3に示す値である場合、今回(時間t=0)の覚醒度低下判定指標AとしてA(t=0)=1.89の値を演算し、その演算データを覚醒度低下判定指標平均部6に出力する。同様に、覚醒度低下判定指標演算部4は、既に生理指標特徴量演算部3が前回(時間t=−1)演算した特定ユーザOの生理指標特徴量x1〜x8の標準化された値に応じ、前回(時間t=−1)の覚醒度低下判定指標Aとして、例えばA(t=−1)=1.90の値の演算データを覚醒度低下判定指標平均部6に出力している。

Figure 2007000280
At that time, the wakefulness level decrease determination index calculation unit 4 uses, for example, the standardized values of the physiological index feature values x1 to x8 of the specific user O calculated by the physiological index feature value calculation unit 3 this time (time t = 0) as follows. In the case of the values shown in Table 3, the value of A (t = 0) = 1.89 is calculated as the arousal level decrease determination index A this time (time t = 0), and the calculated data is averaged for the awakening level decrease determination index. Output to unit 6. Similarly, the arousal level reduction determination index calculation unit 4 responds to the standardized values of the physiological index feature values x1 to x8 of the specific user O that the physiological index feature value calculation unit 3 has previously calculated (time t = −1). As the previous (time t = −1) wakefulness level decrease determination index A, for example, arithmetic data having a value of A (t = −1) = 1.90 is output to the wakefulness level decrease determination index average unit 6.
Figure 2007000280

判定指標平均化演算部6は、覚醒度低下判定指標演算部4から所定の時間間隔で順次入力された複数の覚醒度低下判定指標Aを次の数式(2)により時間平均することにより覚醒度低下判定指標Aの時間平均値Ameanを演算し、その演算データを覚醒度低下判定信号出力部7に出力する。なお、数式(2)において、Tはサンプル個数、Nは現在までのサンプル総数、iはサンプル番号を表している。

Figure 2007000280
The determination index averaging calculation unit 6 performs time averaging of a plurality of arousal level decrease determination indexes A sequentially input from the arousal level decrease determination index calculation unit 4 at predetermined time intervals by the following equation (2). The time average value Amean of the decrease determination index A is calculated, and the calculated data is output to the arousal level decrease determination signal output unit 7. In Equation (2), T represents the number of samples, N represents the total number of samples up to the present, and i represents the sample number.
Figure 2007000280

ここで、覚醒度低下判定指標Aの時間平均値Ameanは、例えば図5のグラフに示すように、ユーザの覚醒度のレベルに応じて漸次変化する特性を有する。すなわち、ユーザの覚醒度のレベルが高く意識がはっきりしている状態では、Ameanの値は、その重心が0より小さい負側となり、ユーザの覚醒度のレベルが極めて低く眠い状態では、Ameanの値は、その重心が0より大きい正側となる。換言すれば、覚醒度低下判定指標Aの時間平均値Ameanは、一般に図6に示すように、ユーザの覚醒度のレベルが高い状態では負の値をとり、ユーザの覚醒度のレベルが低い状態では正の値をとる。   Here, the time average value Amean of the arousal level decrease determination index A has a characteristic that gradually changes according to the level of the user's arousal level, for example, as shown in the graph of FIG. That is, in a state where the level of the user's arousal level is high and the consciousness is clear, the value of American is a negative side whose center of gravity is smaller than 0, and in a state where the level of the user's arousal level is extremely low and sleepy, the value of American Is the positive side whose center of gravity is greater than zero. In other words, as shown in FIG. 6, the time average value Amean of the wakefulness level decrease determination index A generally takes a negative value when the user's wakefulness level is high and the user's wakefulness level is low. Then take a positive value.

そこで、出力手段としての覚醒度低下判定信号出力部7は、判定指標平均化演算部6から覚醒度低下判定指標Aの時間平均値Ameanが入力されると、その値が所定の判定閾値TH(例えばゼロ)より大きいか否かを判定する。そして、覚醒度低下判定信号出力部7は、覚醒度低下判定指標Aの時間平均値Ameanが判定閾値TH(例えばゼロ)より大きい場合には、特定ユーザの覚醒度のレベルが低下しているものと判定し、その覚醒度低下判定信号を図示しない警報装置などに出力して特定ユーザの覚醒を促す。   Therefore, when the time average value Amean of the arousal level decrease determination index A is input from the determination index averaging calculation unit 6, the awakening level decrease determination signal output unit 7 as an output unit receives the value as a predetermined determination threshold value TH ( For example, it is determined whether it is greater than zero. Then, the arousal level decrease determination signal output unit 7 has a reduced level of arousal level of a specific user when the time average value Amean of the arousal level decrease determination index A is larger than a determination threshold TH (for example, zero). And the wakefulness lowering determination signal is output to an alarm device (not shown) or the like to urge the specific user to wake up.

以上のように構成された一実施形態の覚醒度低下判定装置は、例えば任意の自動車に装備し、その自動車を運転するユーザに固有の前述した固有ベクトル値U1(=u1,u2,u3,u4,u5,u6,u7,u8)のデータを固有ベクトルデータベース5に予め記憶させておくことにより、特定ユーザの居眠り運転を未然に防止するために使用することができる。この場合、その自動車を運転するユーザは、複数人設定することができる。   The wakefulness reduction determination apparatus according to an embodiment configured as described above is equipped with, for example, an arbitrary automobile and the above-described eigenvector values U1 (= u1, u2, u3, u4, unique to a user driving the automobile). By storing the data of u5, u6, u7, u8) in the eigenvector database 5 in advance, it can be used to prevent a specific user from falling asleep. In this case, a plurality of users who drive the car can be set.

このように使用される一実施形態の覚醒度低下判定装置においては、図7に示すフローチャートの処理手順に沿って特定ユーザの覚醒度の低下状況が判定される。まず、ステップS1で運転者である特定ユーザがその名前、イニシャル、ID番号などの情報をユーザ情報入力部1に入力すると、続くステップS2では、生理指標群計測部2が図示しない各種のセンサから特定ユーザの生理指標群である脳波、呼吸、体温、瞬目、心拍の検出信号を入力して計測する。   In the arousal level decrease determination apparatus according to the embodiment used in this way, a decrease state of the specific user's arousal level is determined in accordance with the processing procedure of the flowchart shown in FIG. First, when a specific user who is a driver inputs information such as a name, initials, and ID number to the user information input unit 1 in step S1, in step S2, the physiological index group measurement unit 2 detects various sensors (not shown). Measurement is performed by inputting detection signals of brain waves, respiration, body temperature, blinks, and heartbeats, which are physiological index groups of a specific user.

次のステップS3では、特定ユーザの脳波、呼吸、体温、瞬目、心拍の計測データに基づき、生理指標特徴量演算部3が特定ユーザの生理指標特徴量、すなわち、表1に示した第1〜8の生理指標特徴量x1〜x8を演算する。   In the next step S3, based on the measurement data of the brain wave, respiration, body temperature, blink, and heart rate of the specific user, the physiological index feature value calculation unit 3 sets the specific user's physiological index feature value, that is, the first shown in Table 1. Physiological index feature amounts x1 to x8 of ˜8 are calculated.

そして、ステップS4では、第1〜8の生理指標特徴量x1〜x8の演算データに基づき、覚醒度低下判定指標演算部4が第1〜8の生理指標特徴量x1〜x8を主成分分析し、その相互相関のない第1主成分を覚醒度低下判定指標Aとして演算する(数式(1)参照)。   In step S4, based on the calculation data of the first to eighth physiological index feature amounts x1 to x8, the arousal level decrease determination index calculation unit 4 performs principal component analysis on the first to eighth physiological index feature amounts x1 to x8. Then, the first principal component having no cross-correlation is calculated as the arousal level decrease determination index A (see Formula (1)).

ここで、覚醒度低下判定指標演算部4は、数式(1)の覚醒度低下判定指標Aを演算する際、固有ベクトルデータベース5に予め記憶された特定ユーザに対応する固有ベクトルu1〜u8の値(表2参照)を数式(1)中のu1〜u8の値として使用することで、特定ユーザの覚醒度低下判定指標Aを決定する。   Here, the arousal level decrease determination index calculation unit 4 calculates the values of eigenvectors u1 to u8 corresponding to specific users stored in the eigenvector database 5 in advance (table) when calculating the arousal level decrease determination index A of Equation (1). 2) is used as the values of u1 to u8 in the formula (1) to determine the arousal level decrease determination index A of the specific user.

続くステップS5では、覚醒度低下判定指標演算部4から所定の時間間隔で順次入力された複数の覚醒度低下判定指標Aを判定指標平均化演算部6が数式(2)により時間平均することで覚醒度低下判定指標Aの時間平均値Ameanを演算する。   In subsequent step S5, the determination index averaging calculation unit 6 performs time averaging of the plurality of arousal level decrease determination indexes A sequentially input from the arousal level decrease determination index calculation unit 4 at predetermined time intervals according to Equation (2). The time average value Amean of the arousal level decrease determination index A is calculated.

そして、ステップS6では、覚醒度低下判定信号出力部7において、覚醒度低下判定指標Aの時間平均値Ameanが所定の判定閾値TH(例えばゼロ)より大きいか否かが判定される、すなわち、特定ユーザの覚醒度が低下しているか否かが判定される。   In step S6, the wakefulness level decrease determination signal output unit 7 determines whether or not the time average value Amean of the wakefulness level decrease determination index A is greater than a predetermined determination threshold value TH (for example, zero). It is determined whether or not the user's arousal level is reduced.

ここで、ステップS6の判定結果がNOであって特定ユーザの覚醒度が低下していないと判定された場合には、ステップS2の処理に戻るが、判定結果がYESであって特定ユーザの覚醒度が低下していると判定された場合には、続くステップS7において、覚醒度低下判定信号出力部7が覚醒度低下判定信号をを図示しない警報装置などに出力して特定ユーザの覚醒を促す。   Here, if the determination result in step S6 is NO and it is determined that the awakening level of the specific user has not decreased, the process returns to step S2, but the determination result is YES and the awakening of the specific user. If it is determined that the degree is low, in a subsequent step S7, the wakefulness reduction determination signal output unit 7 outputs a wakefulness reduction determination signal to an alarm device (not shown) or the like to urge the specific user to wake up. .

このように、一実施形態の覚醒度低下判定装置によれば、ステップS3において、ユーザの覚醒度の低下に大きく関連する生理指標特徴量x1〜x8、すなわち表1に示した第1〜8の生理指標特徴量x1〜x8を演算すると共に、ステップS4において、第1〜8の生理指標特徴量x1〜x8を主成分分析し、その相互相関のない第1主成分を覚醒度低下判定指標Aとして演算するため、特定ユーザの覚醒度の低下状況を精度良く注出することができる。   As described above, according to the device for determining arousal level according to the embodiment, in step S3, physiological index feature amounts x1 to x8 that are largely related to a decrease in the user's arousal level, that is, the first to eighth values shown in Table 1. In addition to calculating the physiological index feature amounts x1 to x8, in step S4, the first to eighth physiological index feature amounts x1 to x8 are subjected to principal component analysis, and the first principal component having no cross-correlation is determined as the arousal level reduction determination index A. Therefore, it is possible to accurately extract the state of decrease in the arousal level of the specific user.

また、ステップS4において数式(1)の覚醒度低下判定指標Aを演算する際には、固有ベクトルデータベース5に予め記憶された特定ユーザに対応する固有ベクトルu1〜u8の値(表2参照)を使用することで、特定ユーザの覚醒度低下判定指標Aを決定すると共に、ステップS5においては覚醒度低下判定指標Aの時間平均値Ameanを演算するため、表1に示した第1〜8の生理指標特徴量x1〜x8の演算データの個人差に拘わらず、特定ユーザの覚醒度の低下状況を精度良く判定して出力することができる。   Further, when calculating the arousal level decrease determination index A of Formula (1) in step S4, the values of the eigenvectors u1 to u8 corresponding to the specific user stored in advance in the eigenvector database 5 (see Table 2) are used. Thus, the wakefulness level decrease determination index A of the specific user is determined, and the time average value Amean of the wakefulness level decrease determination index A is calculated in step S5. Regardless of individual differences in the calculation data of the amounts x1 to x8, it is possible to accurately determine and output the state of decrease in the arousal level of the specific user.

本発明に係る覚醒度低下判定装置は、前述した一実施形態に限定されるものではない。例えば、ユーザ情報入力部1は、予め登録された複数のユーザ(被験者)の名前を画面表示し、そのうち今回の特定ユーザ(特定被験者)の名前をスイッチ操作などにより選択するように構成されていてもよい。   The arousal level decrease determination device according to the present invention is not limited to the above-described embodiment. For example, the user information input unit 1 is configured to display the names of a plurality of pre-registered users (subjects) on the screen, and select the name of the specific user (specific subject) this time by a switch operation or the like. Also good.

また、覚醒度低下判定信号出力部7は、警報装置に限らず、特定ユーザの覚醒を促す適宜の装置、例えば特定ユーザの顔面などの皮ふ感覚に刺激を与える装置に覚醒度低下判定信号を出力するように構成してもよい。   Further, the arousal level decrease determination signal output unit 7 outputs a wakefulness level decrease determination signal not only to an alarm device but also to an appropriate device that promotes a specific user's arousal, for example, a device that stimulates a skin sensation such as a specific user's face. You may comprise.

本発明の一実施形態に係る覚醒度低下判定装置のブロック構成図である。It is a block block diagram of the arousal level fall determination apparatus which concerns on one Embodiment of this invention. ユーザの脳波α/βのレベルと覚醒度のレベルとの関係を示すグラフである。It is a graph which shows the relationship between the level of a user's brain wave (alpha) / (beta), and the level of arousal level. ユーザの脳波α波パワーのレベルと覚醒度のレベルとの関係を示すグラフである。It is a graph which shows the relationship between the level of a user's brain wave alpha wave power, and the level of arousal level. ユーザの脳波β波パワーのレベルと覚醒度のレベルとの関係を示すグラフである。It is a graph which shows the relationship between the level of a user's brain wave beta wave power, and the level of arousal level. ユーザの覚醒度のレベルと覚醒度低下判定指標の時間平均値Ameanとの関係を示すグラフである。It is a graph which shows the relationship between the level of a user's arousal level, and the time average value Amean of the arousal level fall determination parameter | index. ユーザの覚醒度のレベル低下に対応した覚醒度低下判定指標の時間平均値Ameanの変化を示すグラフである。It is a graph which shows the change of the time average value Amean of the arousal level fall determination parameter | index corresponding to the level fall of a user's arousal level. 一実施形態の覚醒度低下判定装置の処理手順の概略を示すフローチャートである。It is a flowchart which shows the outline of the process sequence of the arousal level fall determination apparatus of one Embodiment.

符号の説明Explanation of symbols

1 ユーザ情報入力部
2 生理指標群計測部
3 生理指標特徴量演算部
4 覚醒度低下判定指標演算部
5 固有ベクトルデータベース
6 覚醒度低下判定指標平均部
7 覚醒度低下判定信号出力部
DESCRIPTION OF SYMBOLS 1 User information input part 2 Physiological index group measurement part 3 Physiological index feature-value calculation part 4 Arousal level fall determination parameter | index calculation part 5 Eigenvector database 6 Arousal level fall determination parameter | index average part 7 Arousal level fall determination signal output part

Claims (3)

入力された特定被験者の生理指標群の計測データに基づいて特定被験者の覚醒度の低下状況を判定する装置であって、
前記計測データに基づき特定被験者の覚醒度の低下に関連する複数の生理指標特徴量を求めると共に、求めた複数の生理指標特徴量を主成分分析した第1主成分を覚醒度低下判定指標として求め、かつ、この覚醒度低下判定指標の時間平均値を求める演算手段と、
前記演算手段により求められた覚醒度低下判定指標の時間平均値に応じて特定被験者の覚醒度の低下状況を出力する出力手段と、
特定被験者に対応する前記第1主成分の固有ベクトルが予め記憶された記憶手段とを備え、
前記演算手段は、前記記憶手段に予め記憶された特定被験者に対応する第1主成分の固有ベクトルを使用して第1主成分である覚醒度低下判定指標を決定することを特徴とする覚醒度低下判定装置。
A device for determining a decrease in arousal level of a specific subject based on input measurement data of a physiological index group of the specific subject,
Based on the measurement data, a plurality of physiological index feature values related to a decrease in arousal level of a specific subject are obtained, and a first principal component obtained by principal component analysis of the obtained plurality of physiological index feature values is obtained as a wakefulness reduction determination index. And the calculating means for obtaining the time average value of this arousal level decrease determination index,
An output means for outputting a state of decrease in arousal level of the specific subject according to a time average value of the arousal level decrease determination index obtained by the calculation means;
Storage means in which the eigenvector of the first principal component corresponding to the specific subject is stored in advance,
The arithmetic means determines a wakefulness reduction determination index that is a first principal component using an eigenvector of a first principal component corresponding to a specific subject stored in advance in the storage means, Judgment device.
前記生理指標群には、脳波、呼吸、体温、瞬目、心拍、皮ふ電位の何れかの項目が含まれることを特徴とする請求項1に記載の覚醒度低下判定装置。   The wakefulness reduction determination apparatus according to claim 1, wherein the physiological index group includes any of the following items: electroencephalogram, respiration, body temperature, blink, heartbeat, and skin potential. 前記複数の生理指標特徴量には、少なくとも脳波のα波パワーとβ波パワーとの比率が含まれていることを特徴とする請求項1に記載の覚醒度低下判定装置。   The wakefulness level decrease determination apparatus according to claim 1, wherein the plurality of physiological index feature amounts include at least a ratio of α wave power and β wave power of an electroencephalogram.
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