JPH05256955A - Presence detecting apparatus - Google Patents
Presence detecting apparatusInfo
- Publication number
- JPH05256955A JPH05256955A JP5485092A JP5485092A JPH05256955A JP H05256955 A JPH05256955 A JP H05256955A JP 5485092 A JP5485092 A JP 5485092A JP 5485092 A JP5485092 A JP 5485092A JP H05256955 A JPH05256955 A JP H05256955A
- Authority
- JP
- Japan
- Prior art keywords
- heartbeat
- calculating means
- calculating
- passenger
- autocorrelation coefficient
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Landscapes
- Geophysics And Detection Of Objects (AREA)
- Passenger Equipment (AREA)
Abstract
Description
【0001】[0001]
【産業上の利用分野】本発明は、移動体における搭乗者
が在席しているかどうかを検知する在席検知装置に関す
るものである。BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a seating detection device for detecting whether or not a passenger in a moving body is seated.
【0002】[0002]
【従来の技術】従来、搭乗者の心拍を検出するための技
術としては、例えば実開平2−213325号公報に見
られるように被測定部位にバイドにて装着できるように
した腕時計型の心拍検出装置があった。2. Description of the Related Art Conventionally, as a technique for detecting a passenger's heartbeat, for example, a wristwatch-type heartbeat detector which can be attached to a measurement site with a binder as shown in Japanese Utility Model Laid-Open No. 213325/1990. There was a device.
【0003】さらに、人体の在席検知に関しては特開平
3−233391号公報に見られるように座席の二つの
電極間の静電容量の変化で在席を検知するというものが
あった。Further, regarding the detection of the presence of a human body, there is a technique of detecting the presence of a person by changing the electrostatic capacitance between two electrodes of the seat, as disclosed in Japanese Patent Laid-Open No. 3-233391.
【0004】[0004]
【発明が解決しようとする課題】上記従来の方法におい
て、心拍を検出するためには腕部に本体をバンドで固定
せねばならず、利用者にとっては大変煩わしいという課
題があった。In the above conventional method, the main body must be fixed to the arm with a band in order to detect the heartbeat, which is very troublesome for the user.
【0005】また、自動車等の移動体に於て非接触で心
拍を検出しようとする際には、寝床内で検出する場合に
は存在しないノイズ、例えばノッキングや路面の凹凸等
によって発生するノイズをも同時に圧電素子が検知して
しまうという可能性があった。Further, when trying to detect a heartbeat in a moving body such as an automobile in a non-contact manner, noise that does not exist in the case of being detected in the bed, for example, noise generated by knocking or unevenness of the road surface is generated. At the same time, there was a possibility that the piezoelectric element would detect it.
【0006】一方、在席の検知については物体と人体と
の区別が難しいという課題もあった。On the other hand, there is also a problem that it is difficult to distinguish between an object and a human body when detecting the presence of a person.
【0007】本発明は上記課題を解決するもので、その
第1の目的は生体情報検出手段のセンサ部を車内座席に
埋設することによって搭乗者の心拍の非接触検出を行
い、搭乗者が在席していることを検知することにある。The present invention is to solve the above problems. A first object of the present invention is to detect a passenger's heartbeat in a non-contact manner by embedding a sensor portion of a biological information detecting means in a seat in a vehicle, and the passenger is present. It is to detect that you are seated.
【0008】第2の目的は心拍情報以外の信号をノイズ
としてカットし精度の高い心拍情報を得ることにある。A second object is to cut signals other than heartbeat information as noise to obtain highly accurate heartbeat information.
【0009】[0009]
【課題を解決するための手段】上記課題を解決するため
本発明の在席検知装置は、車内座席にセンサ部を埋設し
た生体情報検出手段と、前記生体情報検出手段からの信
号より搭乗者の心拍情報を検出する心拍算出手段と、前
記心拍算出手段からの心拍情報を受信し前記心拍情報の
持つ値が一定範囲内にあるという条件を満たしかつこの
満たされた条件が一定回数以上繰り返された場合には在
席信号を出力する判断手段とを設けたものである。In order to solve the above-mentioned problems, an occupant detection apparatus of the present invention comprises a biometric information detecting means in which a sensor unit is embedded in a vehicle seat, and a signal from the biometric information detecting means indicates the occupant's A heartbeat calculating means for detecting heartbeat information and a condition that the heartbeat information from the heartbeat calculating means is received and the value of the heartbeat information is within a certain range are satisfied, and the satisfied condition is repeated a certain number of times or more. In this case, a judgment means for outputting a seating signal is provided.
【0010】また、心拍算出手段は前記生体情報検出手
段からの信号の自己相関係数を算出する自己相関係数算
出手段と、前記自己相関係数算出手段の結果より基本周
期を算出する基本周期算出手段と、前記基本周期より単
位時間時間当りのサイクルを求める演算手段とを設けた
ものである。Further, the heartbeat calculating means is an autocorrelation coefficient calculating means for calculating an autocorrelation coefficient of the signal from the biological information detecting means, and a basic cycle for calculating a basic cycle from the result of the autocorrelation coefficient calculating means. The calculation means and the calculation means for obtaining the cycle per unit time from the basic cycle are provided.
【0011】[0011]
【作用】上記構成によって、座席に埋設された生体情報
検出手段は、搭乗者と座席の接触面において生じる圧変
化を検知し電気信号に変換する。この圧変化には搭乗者
の心拍によるものも含まれている。心拍算出手段は、生
体情報検出手段からの電気信号について単位時間当りの
心拍数を算出する。判断手段は心拍数の値が一定範囲内
にあるという条件を満たしかつこの満たされた条件が一
定回数以上繰り返された場合には在席信号を出力する。With the above structure, the biometric information detecting means embedded in the seat detects a pressure change occurring at the contact surface between the passenger and the seat and converts it into an electric signal. This change in pressure includes that due to the passenger's heartbeat. The heartbeat calculating means calculates the heartbeat rate per unit time for the electric signal from the biological information detecting means. The determination means outputs a presence signal when the condition that the value of the heart rate is within a certain range is satisfied and the satisfied condition is repeated a certain number of times or more.
【0012】また心拍算出手段において、自己相関係数
算出手段は入力信号についての自己相関係数を算出す
る。基本周期算出手段は、自己相関係数より入力信号の
基本周期を算出する。演算手段は得られた基本周期より
単位時間当りのサイクル数を算出する。In the heartbeat calculating means, the autocorrelation coefficient calculating means calculates the autocorrelation coefficient for the input signal. The basic cycle calculating means calculates the basic cycle of the input signal from the autocorrelation coefficient. The calculation means calculates the number of cycles per unit time from the obtained basic cycle.
【0013】[0013]
【実施例】以下本発明の第1の実施例を図面を参照して
説明する。図1は本発明の第1の実施例の構成図であ
る。生体情報検出手段1はセンサ部として圧電素子2、
または回路部としてフィルタ回路3、増幅回路4、平滑
化回路5より構成され、心拍算出手段6に接続してい
る。心拍算出手段6は、判断手段7に接続されている。DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS A first embodiment of the present invention will be described below with reference to the drawings. FIG. 1 is a block diagram of the first embodiment of the present invention. The biological information detecting means 1 includes a piezoelectric element 2 as a sensor section,
Alternatively, the circuit section includes a filter circuit 3, an amplifier circuit 4, and a smoothing circuit 5, and is connected to the heartbeat calculating means 6. The heartbeat calculating means 6 is connected to the judging means 7.
【0014】なお圧電素子2は、例えば座席の背もたれ
部の搭乗者の心臓に近い部分に埋設されている。圧電素
子2としては例えば薄膜加工したポリフッ化ビニリデン
等が用いられる。The piezoelectric element 2 is embedded, for example, in a portion of the backrest of the seat near the passenger's heart. As the piezoelectric element 2, for example, thin film-processed polyvinylidene fluoride or the like is used.
【0015】つぎに、本発明の第1の実施例における作
用について述べる。生体情報検出手段1に於て圧電素子
2は、搭乗者の心拍を初め埋設部分に加えられる様々な
圧変化を、電気信号に変換する。次にフィルタ回路3が
心拍に対応する周波数帯域の信号をろ波する。自動車の
場合にはエンジンの振動が座席に伝わるため、少なくと
も8〜10Hz以上の周波数の信号はカットされる。増幅
回路4はフィルタ回路3を通過した電気信号を増幅す
る。平滑化回路5は増幅された信号を整流、積分する。Next, the operation of the first embodiment of the present invention will be described. In the biological information detecting means 1, the piezoelectric element 2 converts various pressure changes applied to the buried portion, such as the occupant's heartbeat, into electric signals. Next, the filter circuit 3 filters the signal in the frequency band corresponding to the heartbeat. In the case of automobiles, the vibration of the engine is transmitted to the seat, so that signals with a frequency of at least 8 to 10 Hz or higher are cut. The amplifier circuit 4 amplifies the electric signal that has passed through the filter circuit 3. The smoothing circuit 5 rectifies and integrates the amplified signal.
【0016】心拍算出手段6は、生体情報検出手段1か
らの信号より単位時間当りの心拍数を算出する。これ
は、A/D変換回路とマイコンなどで実現することが出
来る。The heartbeat calculating means 6 calculates the heartbeat rate per unit time from the signal from the biological information detecting means 1. This can be realized by an A / D conversion circuit and a microcomputer.
【0017】判断手段は、心拍算出手段からの心拍情報
が通常の人の心拍数範囲に入っており、かつその状態が
一定回数繰り返された場合に人が在席していると判断し
て、在席検知信号を出力する。The judging means judges that the person is present when the heartbeat information from the heartbeat calculating means is within the normal human heart rate range and the state is repeated a certain number of times, Outputs the presence detection signal.
【0018】なお本実施例では心拍数の検出を行なって
いるが、生体情報としては心拍以外に呼吸を用いてもも
ちろんかまわない。この時にはフィルタ回路3におい
て、ろ波される周波数帯域は更に低くなる。Although the heart rate is detected in this embodiment, respiration other than the heartbeat may be used as the biological information. At this time, the frequency band to be filtered in the filter circuit 3 is further lowered.
【0019】図2は、本発明の第2の実施例の構成図で
ある。心拍算出手段6において自己相関係数算出手段8
は、基本周期算出手段9と接続している。基本周期算出
手段9は演算手段10と接続している。なお自己相関係
数算出手段8、基本周期算出手段9、演算手段10はマ
イコンのソフトウェアとして組み込むことが可能であ
る。FIG. 2 is a block diagram of the second embodiment of the present invention. In the heartbeat calculating means 6, the autocorrelation coefficient calculating means 8
Is connected to the basic period calculation means 9. The basic period calculation means 9 is connected to the calculation means 10. The autocorrelation coefficient calculating means 8, the basic period calculating means 9, and the calculating means 10 can be incorporated as software of a microcomputer.
【0020】図3は自己相関係数を用いた基本周波数の
算出アルゴリズムを表わすフローチャートである。自己
相関係数を求める場合にはまず自己相関関数を求める。
自己相関関数はある時点の値とそこから任意の時間τ
(ラグと呼ばれている)だけ離れた時点の値との相関を
表す関数である。本実施例では20Hzのサンプリングレ
ートにより離散データを得ているものとする。従ってτ
はp・Δtと表すことが出来る。pはサンプリングデー
タの個数、Δtはサンプリング周期を表す。ラグの最大
値τmaxはN・Δtを超えない範囲で設定しなければ
ならない。M=N−τmaxとしたとき、一般に自己相
関関数C(p)は、FIG. 3 is a flow chart showing an algorithm for calculating the fundamental frequency using the autocorrelation coefficient. When obtaining the autocorrelation coefficient, the autocorrelation function is first obtained.
The autocorrelation function is the value at a certain time and the arbitrary time τ
It is a function that represents the correlation with the value at a time point (called a lag). In this embodiment, it is assumed that discrete data is obtained at a sampling rate of 20 Hz. Therefore τ
Can be expressed as p · Δt. p represents the number of sampling data, and Δt represents the sampling period. The maximum value τmax of the lag must be set within a range not exceeding N · Δt. When M = N−τmax, generally, the autocorrelation function C (p) is
【0021】[0021]
【数1】 [Equation 1]
【0022】で求められる。しかし本実施例では原波形
に対し平滑化回路5において整流及び積分処理が施され
ているため、date(i)には直流成分It is calculated by However, in this embodiment, since the original waveform is subjected to the rectification and integration processing in the smoothing circuit 5, the direct current component is included in date (i).
【0023】[0023]
【外1】 [Outer 1]
【0024】が含まれているとみることが出来るから、
C(p)は以下のようにして求める方がよい。Since it can be considered that the
It is better to obtain C (p) as follows.
【0025】[0025]
【数2】 [Equation 2]
【0026】[0026]
【数3】 [Equation 3]
【0027】自己相関係数R(p)は、以下の式で得ら
れる。 R(p)=C(p)/C(0) 次に自己相関係数から基本周波数を求める手段について
説明する。図4は求められた自己相関係数をグラフにし
たものである。自己相関係数は理論的にはτが基本周期
分である時に極大値をとる。そこでまず極大点となる点
を求める。図4では極大点として点a,b,c,d,e
があるが、誤差により偶然極大点となった点も含まれて
いるから閾値関数を設定しこれを超える点のみを極大点
として扱う。ここでは点c,d,eが極大点集合の要素
となる。次にこの内の最大値eに対応する周期を仮の基
本周期とする。これは、真の基本周期の整数倍である可
能性があるため、その整数分の1の周期の近傍に第2の
極大点集合の要素があるかを探索する。本第3の実施例
では点cがそれにあたるので、点cに対応する点を基本
周期Tとする。The autocorrelation coefficient R (p) is obtained by the following equation. R (p) = C (p) / C (0) Next, the means for obtaining the fundamental frequency from the autocorrelation coefficient will be described. FIG. 4 is a graph of the obtained autocorrelation coefficient. The autocorrelation coefficient theoretically takes a maximum value when τ is a fundamental period. Therefore, the point that becomes the maximum point is first obtained. In FIG. 4, points a, b, c, d, and e are set as maximum points.
However, since a point that happens to be a maximum point due to an error is also included, a threshold function is set and only points that exceed this are treated as maximum points. Here, the points c, d, and e are the elements of the maximum point set. Next, the cycle corresponding to the maximum value e of these is set as a temporary basic cycle. Since this may be an integral multiple of the true fundamental period, a search is made for an element of the second maximum point set in the vicinity of the period of 1 / integer. In the third embodiment, the point c corresponds to this, so the point corresponding to the point c is the basic cycle T.
【0028】基本周期Tが得られると、単位時間あたり
の心拍数が算出できる。1分あたりの心拍数HRは、 HR=60・サンプリング周波数/T で得られる。なお搭乗者が在席していない場合には、心
拍数は0とする。また単位時間当りの心拍数を求めず、
単に基本周期の値だけで在席の判断を行っても構わな
い。When the basic period T is obtained, the heart rate per unit time can be calculated. The heart rate HR per minute is obtained at HR = 60 · sampling frequency / T 2. The heart rate is set to 0 when no passenger is present. Also, without calculating the heart rate per unit time,
The presence determination may be made based only on the value of the basic cycle.
【0029】[0029]
【発明の効果】以上説明したように本発明の在席検知装
置は、在席にいる乗客の心拍を検出できるため、物体と
区別して搭乗者の在席を検知できる。As described above, since the seating detection apparatus of the present invention can detect the heartbeat of a passenger who is seated, the seating of a passenger can be detected separately from an object.
【0030】また、自己相関係数を用いて心拍算出を行
なうため心拍以外に混入するノイズに強く、正確な心拍
数を得ることが出来るという効果がある。Further, since the heartbeat is calculated using the autocorrelation coefficient, there is an effect that it is resistant to noise mixed in other than the heartbeat and an accurate heartbeat can be obtained.
【図1】本発明の第1の実施例における在席検知装置の
構成を示すブロック図FIG. 1 is a block diagram showing a configuration of an occupancy detection device according to a first embodiment of the present invention.
【図2】本発明の第2の実施例における同装置の心拍数
算出手段の構成を示すブロック図FIG. 2 is a block diagram showing the configuration of a heart rate calculation means of the same apparatus according to the second embodiment of the present invention.
【図3】同装置における心拍算出アルゴリズムのフロー
チャートFIG. 3 is a flowchart of a heartbeat calculation algorithm in the device.
【図4】第2の実施例同装置における自己相関係数のグ
ラフFIG. 4 is a graph of an autocorrelation coefficient in the same apparatus as the second embodiment.
1 生体情報検出手段 6 心拍算出手段 7 判断手段 8 自己相関係数算出手段 9 基本周期算出手段 10 演算手段 1 biometric information detecting means 6 heartbeat calculating means 7 judging means 8 autocorrelation coefficient calculating means 9 basic period calculating means 10 calculating means
Claims (2)
検出手段と、前記生体情報検出手段からの信号より搭乗
者の心拍情報を検出する心拍算出手段と、前記心拍算出
手段からの心拍情報を受信し前記心拍情報の持つ値が一
定範囲内にあるという条件を満たしかつこの満たされた
条件が一定回数以上繰り返された場合には前記搭乗者が
前記座席にいるという在席信号を出力する判断手段とを
備えた在席検知装置。1. A biometric information detecting means in which a sensor unit is embedded in a seat in a vehicle, a heartbeat calculating means for detecting heartbeat information of an occupant from a signal from the biometric information detecting means, and heartbeat information from the heartbeat calculating means. Is received and the condition that the value of the heartbeat information is within a certain range is satisfied and the satisfied condition is repeated a certain number of times or more, a seating signal indicating that the passenger is in the seat is output. An occupancy detection device having a determination means.
号の自己相関係数を算出する自己相関係数算出手段と、
前記自己相関係数算出手段の結果より基本周期を算出す
る基本周期算出手段と、前記基本周期より単位時間時間
当りのサイクルを求める演算手段とを備えた請求項1記
載の在席検知装置。2. The heartbeat calculating means includes an autocorrelation coefficient calculating means for calculating an autocorrelation coefficient of a signal from the biological information detecting means,
The presence detection apparatus according to claim 1, further comprising: a basic cycle calculating means for calculating a basic cycle from a result of the autocorrelation coefficient calculating means; and a calculating means for calculating a cycle per unit time from the basic cycle.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
JP5485092A JP3150403B2 (en) | 1992-03-13 | 1992-03-13 | Presence detection device |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
JP5485092A JP3150403B2 (en) | 1992-03-13 | 1992-03-13 | Presence detection device |
Publications (2)
Publication Number | Publication Date |
---|---|
JPH05256955A true JPH05256955A (en) | 1993-10-08 |
JP3150403B2 JP3150403B2 (en) | 2001-03-26 |
Family
ID=12982077
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
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JP5485092A Expired - Fee Related JP3150403B2 (en) | 1992-03-13 | 1992-03-13 | Presence detection device |
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JP (1) | JP3150403B2 (en) |
Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPH021227A (en) * | 1988-11-04 | 1990-01-05 | Terumo Corp | Cycle measuring apparatus |
JPH043709U (en) * | 1990-04-24 | 1992-01-14 | ||
JPH0428344A (en) * | 1990-05-25 | 1992-01-30 | Matsushita Electric Ind Co Ltd | On-bed state monitoring device |
-
1992
- 1992-03-13 JP JP5485092A patent/JP3150403B2/en not_active Expired - Fee Related
Patent Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPH021227A (en) * | 1988-11-04 | 1990-01-05 | Terumo Corp | Cycle measuring apparatus |
JPH043709U (en) * | 1990-04-24 | 1992-01-14 | ||
JPH0428344A (en) * | 1990-05-25 | 1992-01-30 | Matsushita Electric Ind Co Ltd | On-bed state monitoring device |
Also Published As
Publication number | Publication date |
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JP3150403B2 (en) | 2001-03-26 |
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