JP3720768B2 - Newborn and infant diagnostic equipment - Google Patents

Description

【００４６】
【表２】

【００４７】
表２中に示すモロー反射とは、新生児および乳児に突然手ばたきなどの音響刺激または振動を与えると、驚いて手足や躯幹、頚筋を収縮させる反応のことである。選択された１被験児（被験児番号９）について、表２中に示す条件１〜５の各状態での重心位置を１秒毎に１分間継続して演算し、重心位置の移動実績を示す散布図を作成した。
【００４８】
図６は、１被験児の状態別に採取された重心位置散布図を示す。図６（ａ）は、表２中の条件１の目を開けていて泣いていない状態すなわち覚醒し安静状態における重心位置の散布図である。図６（ｂ）は、表２中の条件２の状態である目を開けていて泣いている状態における重心位置の散布図である。図６（ｃ）は、表２中の条件３の目を閉じていて泣いていない状態すなわち睡眠状態における重心位置の散布図である。図６（ｄ）および図６（ｅ）は、表２中の条件４および５の特別な状態である手足をばたつかせている状態およびモロー反射後の状態におけるそれぞれの重心位置の散布図である。
【００４９】
被験児が、睡眠状態およびモロー反射後の筋肉の収縮した状態にあるとき、重心位置はほとんど移動することがないので、ＧＭの特徴を検知することが難しく、神経学的異常および／または筋疾患の評価に用いるデータの採取条件としては適当でない。また目を開けて泣いている状態および手足をばたつかせている状態では、重心位置の移動が甚だしく、不所望に広範囲に散布してしまうので、かえってＧＭの特徴を検知することが難しく、神経学的異常および／または筋疾患の評価に用いるデータの採取条件としては適当でない。したがって、表２中の条件１の覚醒し安静状態にあるとき、重心位置の移動は適度な範囲に散布し、ＧＭの特徴把握に適すると判断されるので、以後条件１の安静状態において重量に関するデータの採取を行うこととする。
【００５０】
本実施の形態のデータ演算手段５には、多種の演算機能が複数併設して備えられ、前記機能選択手段２１によって演算機能を選択して実行できるように構成されるので、以下に各演算機能毎にその態様について説明する。
【００５１】
データ演算手段５の基本的な態様では、前述した１秒毎に検出される重量値を用いて被験児２の重心位置を演算する重心位置演算手段と、重心位置演算手段の出力に応答し、１秒毎に求められる重心位置が、１分間に前記２次元平面内で移動した面積を演算する重心移動面積演算手段とが備えられる。
【００５２】
重心位置演算手段による重心位置の演算は、前述のとおりであり、重心移動面積演算手段による重心位置の移動面積の演算は、次のようにして行われる。図７は重心位置散布のモデル図であり、図８は２次元平面のＸ軸を幅ｄの小区間に分割して面積を求める概要を示す図である。移動面積は、図７に示す重心散布図のように重心が２次元Ｘ−Ｙ平面内で移動した領域を、図８に示すように、Ｘ軸を幅ｄの小区間に分割した個々の面積を求め、その小区間面積の和を演算することによって求められる。このとき、Ｘ軸の分割最小目盛と小分割区間ｄとを同一にすると演算を容易に行うことができる。
【００５３】
図９は、データ演算手段５による重心移動面積演算の動作を説明するフローチャートである。図９を参照して重心移動面積演算の手順を説明する。ステップａ１のスタートでは、メモリ２２から重心位置の移動実績であるＸ−Ｙ座標値が読出されている状態である。ステップａ２では、読出された重心位置がＸ座標値の小さい順番に並べ替えられる。ステップａ３では、小さい順番に並べ替えられたＸ座標値の数（ｎ）が計数される。ここでｎは自然数である。
【００５４】
ステップａ４では、ｉ＝１に設定される。ステップａ５では、並べ替えの順番がｉ番目のＸ座標値におけるＹ座標値の最大値Ｙｍａ、最小値Ｙｍｉが求められる。ステップａ６では、並べ替えの順番が（ｉ＋１）番目のＸ座標値におけるＹ座標値の最大値Ｙｍａ、最小値Ｙｍｉが求められる。なお、ここではｉ番目のＸ座標値と（ｉ＋１）番目のＸ座標値との差の絶対値は、小分割値ｄである。
【００５５】
ステップａ７では、小分割値ｄと、各Ｘ座標値において求めたＹ座標値の最大値Ｙｍａおよび最小値Ｙｍｉとによって、小分割区間の面積ｄｉａを算出する。隣接するＸ座標値と、各Ｘ座標値におけるＹ座標の最大値Ｙｍａおよび最小値Ｙｍｉとによって形成される小区間には種々の形状パターンがあり、個々の形状パターンに応じて面積ｄｉａが演算される。
【００５６】
図１０は幅ｄの小区間の形状パターン例を示す図であり、図１１は図１０（ｂ）を座標表示した図であり、図１２は図１０（ｃ）を座標表示した図であり、図１３は図１０（ｄ）を座標表示した図である。図１０（ａ）は、Ｙ座標値が１点から１点に変化する区間であり、図１０（ｂ）は、Ｙ座標値が１点から２点に変化する区間であり、図１０（ｃ）は、Ｙ座標値が２点から２点に変化する区間であり、図１０（ｄ）は、Ｙ座標値が２点から１点に変化する区間である。
【００５７】
図１０（ａ）に示す区間では、小分割区間の面積は、零と演算される。図１０（ｂ）すなわち図１１に示す区間では、Ｘ座標値ｘ１においてＹ座標の最大値と最小値とが同一である重心位置３１のＸ−Ｙ座標を（ｘ１，ｙ１）、Ｘ座標値ｘ２においてＹ座標の最大値である重心位置３２のＸ−Ｙ座標を（ｘ２，ｙ２）およびＹ座標の最小値である重心位置３３のＸ−Ｙ座標を（ｘ２，ｙ３）とするとき、小分割区間ｄｉａの面積は、式（４）によって求められる。
ｄｉａ＝ｄ・｜ｙ２−ｙ３｜／２ …（４）
ここで、ｄ＝ｘ２−ｘ１
【００５８】
図１０（ｃ）すなわち図１２に示す区間では、Ｘ座標値ｘ１においてＹ座標の最大値である重心位置３４のＸ−Ｙ座標を（ｘ１，ｙ１）、Ｙ座標の最小値である重心位置３５のＸ−Ｙ座標を（ｘ１，ｙ２）、Ｘ座標値ｘ２においてＹ座標の最大値である重心位置３６のＸ−Ｙ座標を（ｘ２，ｙ３）およびＹ座標の最小値である重心位置３７のＸ−Ｙ座標を（ｘ２，ｙ４）とするとき、小分割区間ｄｉａの面積は、式（５）〜（８）によって求められる。
Ｓ１＝ｄ・｜ｙ３−ｙ１｜／２ …（５）
Ｓ２＝ｄ・｜ｙ１−ｙ４｜ …（６）
Ｓ３＝ｄ・｜ｙ４−ｙ２｜／２ …（７）
ｄｉａ＝Ｓ１＋Ｓ２＋Ｓ３ …（８）
ここで、ｄ＝ｘ２−ｘ１
【００５９】
図１０（ｄ）すなわち図１３に示す区間では、Ｘ座標値ｘ１においてＹ座標の最大値である重心位置３８のＸ−Ｙ座標を（ｘ１，ｙ１）およびＹ座標の最小値である重心位置３９のＸ−Ｙ座標を（ｘ１，ｙ２）、Ｘ座標値ｘ２においてＹ座標の最大値と最小値とが同一である重心位置４０のＸ−Ｙ座標を（ｘ２，ｙ３）とするとき、小分割区間ｄｉａの面積は、式（９）によって求められる。
ｄｉａ＝ｄ・｜ｙ１−ｙ２｜／２ …（９）
ここで、ｄ＝ｘ２−ｘ１
【００６０】
図９に戻ってステップａ８では、算出された小区間面積ｄｉａをメモリ２２にストアする。ステップａ９では、ｉを（ｉ＋１）に置換える。ステップａ１０では、ｉが（ｎ−１）と同一であるか否かが判断される。判断結果が否定であるとき、ステップａ５に戻り以降のステップに進む。判断結果が肯定であるとき、ステップａ１１に進む。ステップａ１１では、メモリ２２から算出した小区間面積ｄｉａを読出し、その総和すなわち重心移動面積を算出し、一連の動作を完了する。
【００６１】
図１４は、重心移動面積演算結果の例を示す図である。図１４には、予め頭部超音波断層検査、頭部ＣＴ（Computed Tomography）検査、頭部ＭＲＩ（Magnetic Resonance Imaging）および脳波検査などによって、症例を予備診断した被験児（新生児）１７人について、前述のようにして重心移動面積を演算した結果を棒グラフで示す。図１４中予備診断結果は、被験児である新生児を識別する新生児番号の横に正常児を○印で示し、黄疸および横隔膜ヘルニアなどの症例の被験児を□印、新生児仮死および将来障害予見される症例の被験児を△印、ＰＶＬ（脳室周囲白質軟化症）、脳梗塞、水頭症などを×印で示す。
【００６２】
図１４に示すように、神経学的異常および／または筋疾患を有する被験児によってほぼ占められる群と、正常な被験児によってほぼ占められる群との境界は、重心移動面積が３５ｍｍ²近辺に存在する。神経学的に正常であり、筋疾患のない被験児のＧＭによる重心位置の移動は、異常を有する被験児に比較して広い範囲に及ぶので、重心移動面積の大小によって神経学的な異常および／または筋疾患の有無を診断することが可能と判断される。したがって、予め弁別レベルＡ１として面積値３５ｍｍ²を判断手段６に設定しておくことによって、判断手段６は被験児毎に演算される重心移動面積が弁別レベルＡ１以上であるか否かによって、被験児の神経学的異常および／または筋疾患の有無を判断することが可能になる。
【００６３】
ただし図１４に示すように、弁別レベルＡ１以上の重心移動面積を有し診断装置１による診断結果が正常と判断されるべき群に含まれる被験児にも、予備診断結果では□印および△印で示される異常症例に該当するものが一部存在する。しかしながら、図１４に示す被験児は、複数の種類の異なる異常症例が混在しているので、検出したい神経学的異常および／または筋疾患別に異なる段階の弁別レベルを設定し検出したい神経学的異常および／または筋疾患別の診断をすることによって、さらに診断精度を向上させることが可能であると考える。
【００６４】
図１５は、診断装置１による被験児の神経学的異常および／または筋疾患の有無を重心移動面積によって診断する動作を説明するフローチャートである。図１５のフローチャートを参照し前述した被験児の神経学的異常および／または筋疾患の有無を重心移動面積によって診断する一連の動作を説明する。
【００６５】
ステップｂ１では、被験児である新生児または乳児を仰臥位になるようにコット９に乗せる。ステップｂ２では、重量に関するデータを採取し得る前記条件１すなわち安静状態にあるか否かが判断される。この判断は、たとえば医師によって行われる。判断結果が否定であるとき、安静状態になるまでステップｂ２を繰返す。判断結果が肯定であるとき、ステップｂ３に進む。ステップｂ３では、重量検出センサ３による重量検出のために予め定められる時間ｔ２である１分間のタイマスタートが行われる。このタイマスタートは、たとえば前述した機能選択手段２１にデータ演算機能の選択とともに演算を開始する信号として入力できるように構成することによって実現できる。
【００６６】
ステップｂ４では、重量検出センサ３（ＣＨ１〜ＣＨ４）によって、１秒毎に被験児２の重量を計測する。ステップｂ５では、データ演算手段５の重心位置演算手段によって重心位置（Ｘｉ，Ｙｉ）を演算する。ステップｂ６では、重心位置演算結果をメモリ２２にストアする。ステップｂ７では、１分間の計測時間が経過したか否かが判断される。判断結果が肯定であるとき、ステップｂ８に進み、判断結果が否定であるとき、ステップｂ４に戻って以降のステップに進む。
【００６７】
ステップｂ８では、メモリ２２から重心位置（Ｘｉ，Ｙｉ）を読出し、ステップｂ９では、データ演算手段５の重心移動面積演算手段によって重心移動面積を演算する。ステップｂ１０では、演算結果である重心移動面積が、予め定められる弁別レベルである面積Ａ１以上であるか否かが判断手段６によって判断される。判断結果が肯定であるときステップｂ１１に進み、判断手段６は、出力信号によって表示手段７に判定結果が正常の旨の表示をさせる。判断結果が否定であるときステップｂ１２に進み、判断手段６は、出力信号によって表示手段７に判定結果が異常の旨の表示をさせる。表示手段７による表示後、一連の診断動作が終了する。ここでステップｂ４〜ステップｂ１０までの動作は、診断装置１の制御表示部８に備わる処理回路１６によって実行される。
【００６８】
データ演算手段５の本発明に係る第１の態様では、前述した１秒毎に検出される重量値を用いて被験児２の重心位置を演算する重心位置演算手段と、重心位置演算手段の出力に応答し、１秒毎に求められる重心位置が、１分間に２次元平面の同一座標上に繰返し出現する回数である重心位置度数を演算する重心位置度数演算手段とを含む。重心位置度数は、たとえばＸ軸およびＹ軸をともに１ｍｍ間隔で分割して区画を設定し、１秒毎に１分間すなわち６０回演算される重心位置が、同一の区画内に出現する回数を計数することによって求めることができる。
【００６９】
図１６は、重心位置度数演算結果の例を示す図である。図１６には、前述した図１４に示す新生児番号１０および１６の被験児について、重心位置度数を演算した結果を３次元的にグラフ化して示す。図１６（ｂ）に示すように、神経学的異常を有する新生児番号１６の被験児では、局所的に度数１０を超える重心位置の集中が認められる。一方図１６（ａ）に示すように正常な新生児番号１０の被験児では、重心位置度数が１０を超える場合がなく、前述の新生児番号１６の被験児に比較して重心位置がばらついて分布している。
【００７０】
このように神経学的に正常であり、筋疾患のない被験児のＧＭによる重心位置は、異常を有する被験児のように局所的に集中することがないので、重心位置度数によって神経学的な異常および／または筋疾患の有無を診断することが可能と判断される。したがって、予め弁別レベルＢ１としてたとえば度数１０を判断手段６に設定しておくことによって、判断手段６は被験児毎に演算される重心位置度数が弁別レベルＢ１以下であるか否かによって、被験児の神経学的異常および／または筋疾患の有無を判断することが可能になる。なお弁別レベル度数Ｂ１は、１０に限定されるものではなく、検出したい神経学的異常および／または筋疾患によってその値を変更することができる。
【００７１】
図１７は、診断装置１による被験児の神経学的異常および／または筋疾患の有無を重心位置度数によって診断する動作を説明するフローチャートである。図１７のフローチャートを参照し前述した被験児の神経学的異常および／または筋疾患の有無を重心位置度数によって診断する一連の動作を説明する。図１７に示すフローチャートは、図１５に示すフローチャートに類似し、同一の動作を表すステップについては説明を省略する。
【００７２】
ステップｃ９では、データ演算手段５の重心位置度数演算手段によって重心位置度数を演算する。ステップｃ１０では、演算結果である重心位置度数が、予め定められる弁別レベルである度数Ｂ１以上であるか否かが判断手段６によって判断される。ここでステップｃ４〜ステップｃ１０までの動作は、診断装置１の制御表示部８に備わる処理回路１６によって実行される。
【００７３】
データ演算手段５の本発明に係る第２の態様では、前述した１秒毎に検出される重量値を用いて被験児２の重心位置を演算する重心位置演算手段と、重心位置演算手段の出力に応答し、１秒毎に求められる重心位置が、１分間に２次元平面内で移動する重心位置の移動速度Ｖｉを１秒毎に演算する重心移動速度演算手段と、重心移動速度演算手段の出力に応答し、予め定められる速度間隔で区分される各速度範囲毎の重心移動速度のデータ数である移動速度度数を演算する移動速度度数演算手段とを含む。
【００７４】
重心移動速度Ｖｉは、次のようにして演算することができる。１秒毎に重心位置を演算する１分間の任意の時刻ｔにおける重心位置（Ｘｉ，Ｙｉ）を時刻表示に置換えて重心位置（Ｘｔ，Ｙｔ）とすると、次の重心位置演算時刻である時間ｔ１後の重心位置は（Ｘｔ＋ｔ１，Ｙｔ＋ｔ１）で表される。このとき重心位置（Ｘｔ，Ｙｔ）から時間ｔ１経過後の重心位置（Ｘｔ＋ｔ１，Ｙｔ＋ｔ１）への重心移動速度Ｖｉは、次式（１０）によって求められる。なお本実施の形態では、前述のように時間ｔ１を１秒としているので、重心移動速度Ｖｉを１秒あたりの速度で求める場合、式（１０）の分母を省くことができる。
Ｖｉ＝√｛（Ｘｔ＋ｔ１−Ｘｔ）²＋（Ｙｔ＋ｔ１−Ｙｔ）²｝／ｔ１…（10）
【００７５】
重心の移動速度度数は、たとえば予め定められる速度間隔を１ｍｍ／ｓｅｃで区分し、１秒毎に１分間すなわち６０回演算される重心移動速度Ｖｉが、同一速度区分内に属する数を計数することによって求めることができる。
【００７６】
図１８は、移動速度度数演算結果の例を示す図である。図１８には、前述した図１４に示す新生児番号１０および１６の被験児について、移動速度度数を演算した結果を棒グラフ化して示す。図１８（ｂ）に示すように、神経学的異常を有する新生児番号１６の被験児では、重心移動速度Ｖｉは、速度０〜１ｍｍ／秒（ｓ）の区分範囲に高い度数で集中していることが認められる。一方図１８（ａ）に示すように正常な新生児番号１０の被験児では、重心移動速度Ｖｉは、速度０〜１ｍｍ／秒（ｓ）の区分範囲で最大の度数を示すけれども、その度数は新生児番号１６の被験児に比べて小さく、また速度の速い区分範囲にもばらついて分布している。
【００７７】
このように神経学的に正常であり、筋疾患のない被験児のＧＭによる重心移動速度Ｖｉは、異常を有する被験児のように特定の速度区分範囲に局所的に集中することがないので、移動速度度数によって神経学的な異常および／または筋疾患の有無を診断することが可能と判断される。したがって、予め弁別レベルＣ１としてたとえば度数３５を判断手段６に設定しておくことによって、判断手段６は被験児毎に演算される移動速度度数が、特定の速度区分範囲において弁別レベルＣ１を超えることがあるか否かによって、被験児の神経学的異常および／または筋疾患の有無を判断することが可能になる。なお弁別レベル度数Ｃ１は、３５に限定されるものではなく、検出したい神経学的異常および／または筋疾患によってその値を変更することができる。
【００７８】
図１９は、診断装置１による被験児の神経学的異常および／または筋疾患の有無を移動速度度数によって診断する動作を説明するフローチャートである。図１９のフローチャートを参照し前述した被験児の神経学的異常および／または筋疾患の有無を重心位置度数によって診断する一連の動作を説明する。図１９に示すフローチャートは、図１５に示すフローチャートに類似し、同一の動作を表すステップについては説明を省略する。
【００７９】
ステップｄ９では、データ演算手段５の重心移動速度演算手段によって重心移動速度Ｖｉを演算する。ステップｄ１０では、移動速度度数演算手段によって、重心移動速度Ｖｉを予め定められる速度区分に従って分類し、速度区分毎の移動速度度数を計数する。ステップｄ１１では、演算結果である移動速度度数が、予め定められる弁別レベルである度数Ｃ１以下であるか否かが判断手段６によって判断される。ここでステップｄ４〜ステップｄ１１までの動作は、診断装置１の制御表示部８に備わる処理回路１６によって実行される。
【００８０】
またデータ演算手段５は、前述した１秒毎に検出される重量値を用いて被験児２の重心位置を演算する重心位置演算手段と、重心位置演算手段の出力に応答し、１秒毎に求められる重心位置が、１分間に２次元平面内で移動する重心位置の移動速度Ｖｉを１秒毎に演算する重心移動速度演算手段と、重心移動速度演算手段の出力に応答し、１分間における重心移動速度Ｖｉの平均値である平均移動速度Ｖａｖｅ、重心移動速度Ｖｉの最大値である最大移動速度Ｖｍａｘおよび重心移動速度Ｖｉの最小値である最小移動速度Ｖｍｉｎを演算する移動速度データ演算手段とを含む。
【００８１】
平均移動速度Ｖａｖｅは、前述した重心移動速度演算手段による重心移動速度Ｖｉを用いて次式（１１）によって求められる。
【００８２】
【数１】

【００８３】
前述したように神経学的に正常であり、筋疾患のない被験児のＧＭによる重心移動速度Ｖｉは、異常を有する被験児のように特定の速度区分範囲すなわち遅い速度区分範囲に局所的に集中することがない。したがって、１分間の重心の平均移動速度Ｖａｖｅを算出した場合、正常な被験児の平均移動速度Ｖａｖｅは、異常を有する被験児の平均移動速度Ｖａｖｅに比べて速いという結果が得られるので、平均移動速度Ｖａｖｅによって神経学的な異常および／または筋疾患の有無を診断することが可能と判断される。いうまでもなく症例によっては、逆に異常を有する被験児の平均移動速度Ｖａｖｅの方が速くなる場合も起こりうる。
【００８４】
したがって、予め定められる速度値を弁別レベルＤ１として判断手段６に設定しておくことによって、判断手段６は被験児毎に演算される平均移動速度Ｖａｖｅが、弁別レベルＤ１以上であるか否かによって、被験児の神経学的異常および／または筋疾患の有無を判断することが可能になる。なお弁別レベルＤ１は、検出したい神経学的異常および／または筋疾患によってその値を変更することができる。
【００８５】
図２０は、診断装置１による被験児の神経学的異常および／または筋疾患の有無を重心の平均移動速度Ｖａｖｅによって診断する動作を説明するフローチャートである。図２０のフローチャートを参照し前述した被験児の神経学的異常および／または筋疾患の有無を重心の平均移動速度Ｖａｖｅによって診断する一連の動作を説明する。図２０に示すフローチャートは、図１９に示すフローチャートに類似し、同一の動作を表すステップについては説明を省略する。
【００８６】
ステップｅ１０では、データ演算手段５の平均移動速度演算手段によって重心の平均移動速度Ｖａｖｅを演算する。ステップｅ１１では、演算結果である平均移動速度Ｖａｖｅが、予め定められる弁別レベルである速度Ｄ１以下であるか否かが判断手段６によって判断される。ここでステップｅ４〜ステップｅ１１までの動作は、診断装置１の制御表示部８に備わる処理回路１６によって実行される。
【００８７】
上記の事例では、平均移動速度Ｖａｖｅによって被験児の神経学的異常および／または筋疾患の有無を判断する例について説明したけれども、データ演算手段５によって演算される最大移動速度Ｖｍａｘまたは最小移動速度Ｖｍｉｎによっても同様にして判断することができる。また、平均移動速度Ｖａｖｅ、最大移動速度Ｖｍａｘおよび最小移動速度Ｖｍｉｎのうちから選択されるいずれか２つの速度の組合せによって判断しても良く、さらに３つの速度すべてを用いて判断するようにしても良い。
【００８８】
またデータ演算手段５は、前述した１秒毎に検出される重量値を用いて被験児２の重心位置を演算する重心位置演算手段と、重心位置演算手段の出力に応答し、１秒毎に求められる重心位置が、１分間に２次元平面内で移動する重心位置の移動加速度αｉを１秒毎に演算する重心移動加速度演算手段と、重心移動加速度演算手段の出力に応答し、１分間における重心移動加速度αｉの平均値である平均移動加速度αａｖｅを演算する平均移動加速度演算手段、重心移動加速度αｉの最大値である最大移動加速度αｍａｘおよび重心移動加速度αｉの最小値である最小移動加速度αｍｉｎを演算する移動加速度データ演算手段とを含む。
【００８９】
重心移動加速度αｉは、式（１２）によって求められ、平均移動加速度αａｖｅは、式（１３）によって求められる。
【００９０】
【数２】

【００９１】
前述したように神経学的に正常であり、筋疾患のない被験児のＧＭによる重心移動速度Ｖｉは、異常を有する被験児のように特定の速度区分範囲すなわち遅い速度区分範囲に局所的に集中することがない。したがって、１分間の重心の平均移動加速度αａｖｅを算出した場合、正常な被験児の平均移動加速度αａｖｅは、異常を有する被験児の平均移動加速度αａｖｅに比べて速いという結果が得られるので、平均移動加速度αａｖｅによって神経学的な異常および／または筋疾患の有無を診断することが可能と判断される。
【００９２】
したがって、予め定められる加速度値を弁別レベルＥ１として判断手段６に設定しておくことによって、判断手段６は被験児毎に演算される平均移動加速度αａｖｅが、弁別レベルＥ１以上であるか否かによって、被験児の神経学的異常および／または筋疾患の有無を判断することが可能になる。なお弁別レベルＥ１は、検出したい神経学的異常および／または筋疾患によってその値を変更することができる。
【００９３】
図２１は、診断装置１による被験児の神経学的異常および／または筋疾患の有無を重心の平均移動加速度αａｖｅによって診断する動作を説明するフローチャートである。図２１のフローチャートを参照し前述した被験児の神経学的異常および／または筋疾患の有無を重心の平均移動加速度αａｖｅによって診断する一連の動作を説明する。図２１に示すフローチャートは、図１９に示すフローチャートに類似し、同一の動作を表すステップについては説明を省略する。
【００９４】
ステップｆ９では、データ演算手段５の重心移動加速度演算手段によって重心移動加速度αｉを演算する。ステップｆ１０では、重心移動加速度演算結果に応答し、重心の平均移動加速度αａｖｅを演算する。ステップｆ１１では、演算結果である平均移動加速度αａｖｅが、予め定められる弁別レベルである加速度値Ｅ１以上であるか否かが判断手段６によって判断される。ここでステップｆ４〜ステップｆ１１までの動作は、診断装置１の制御表示部８に備わる処理回路１６によって実行される。
【００９５】
上記の事例では、平均移動加速度αａｖｅによって被験児の神経学的異常および／または筋疾患の有無を判断する例について説明したけれども、データ演算手段５によって演算される最大移動加速度αｍａｘまたは最小移動加速度αｍｉｎによっても同様にして判断することができる。また、平均移動加速度αａｖｅ、最大移動加速度αｍａｘおよび最小移動加速度αｍｉｎのうちから選択されるいずれか２つの加速度の組合せによって判断しても良く、さらに３つの加速度すべてを用いて判断するようにしても良い。
【００９６】
またデータ演算手段５は、前述した１秒毎に検出される重量値を用いて被験児２の重心位置を演算する重心位置演算手段と、重心位置演算手段の出力に応答し、１秒毎に求められる重心位置が、１分間に前記２次元平面内で移動した実績である各座標値を記憶する重心位置散布記憶手段とを含む。重心位置散布記憶手段は、ＲＡＭなどからなるメモリであり、データ演算手段５の中に設けられてもよく、また前記メモリ２２を利用するように構成されてもよい。
【００９７】
重心位置散布記憶手段から読出される重心位置の移動実績は、Ｘ−Ｙ座標系における散布図として表される。この散布図は、前述した表示手段７の表示画面をたとえば機能選択手段２１に予め設けられる切換えスイッチによって散布図表示に切換えて表示することによって、また処理回路１６に接続されるプリンタ２３に印字出力することによって、目視観察可能にすることができる。
【００９８】
判断手段６による被験児における異常の有無の判断は、たとえば予め症例別に散布図の典型例を判断手段６に設定しておき、被験児毎に得られる重心位置移動の散布図を典型例と比較照合することによって行う。
【００９９】
図２２は正常な新生児番号１０の被験児の散布図であり、図２３は神経学的異常を有する新生児番号１６の被験児の散布図である。図２２に示すように正常な新生児番号１０の被験児では、重心位置は、Ｘ軸方向およびＹ軸方向の両方の広い範囲に散布している。一方図２３に示すように、神経学的異常を有する新生児番号１６の被験児では、重心位置は、Ｘ軸方向およびＹ軸方向ともにその散布範囲が小さいという特徴を有する。したがって、たとえば被験児のデータとしての散布図と典型例として設定される散布図とを比較照合し弁別することによって、被験児の異常の有無をおおよそ判断することができる。
【０１００】
データ演算手段５の本発明に係る第３の態様では、前述した１秒毎に検出される重量値を用いて被験児２の重心位置を演算する重心位置演算手段と、重心位置演算手段の出力に応答し、１秒毎に求められる重心位置が、１分間に前記２次元Ｘ−Ｙ平面内で移動した実績に基づいて、回帰直線を演算する回帰演算手段と、回帰演算手段の出力に応答し、回帰直線を新たなＸ軸とし、回帰直線に直交する軸を新たなＹ軸として重心位置のＸ−Ｙ座標値を変換する座標変換手段と、座標変換手段によって変換される新たなＸ−Ｙ座標系における重心位置移動実績のＸ軸方向の最大値Ｘｍａｘと最小値Ｘｍｉｎとの差（＝Ｘｍａｘ−Ｘｍｉｎ）の絶対値Ｘｍｘと、重心位置移動実績のＹ軸方向の最大値Ｙｍａｘと最小値Ｙｍｉｎとの差（＝Ｙｍａｘ−Ｙｍｉｎ）の絶対値Ｙｍｘとの比である縦横比（Ｘｍｘ／Ｙｍｘ）を演算する縦横比演算手段とを含む。
【０１０１】
以下に縦横比（Ｘｍｘ／Ｙｍｘ）の演算方法について説明する。図２４は、縦横比の演算方法の概略を示す図である。まず、回帰演算手段によって、１分間に演算される６０個の重心位置データの回帰直線（Ｙ＝ａＸ＋ｂ）を演算する。回帰直線は、最小２乗法によって求められ次の式（１４）によって与えられる。
【０１０２】
【数３】

【０１０３】
なお、回帰直線の傾きａおよび切片ｂは、それぞれ式（１９）および（２０）によって与えられる。
【０１０４】
【数４】

【０１０５】
次に、前述のようにして求められる回帰直線（Ｙ＝ａＸ＋ｂ）を新たなＸ軸とし、新たなＸ軸に直交する軸を新たなＹ軸とするように、座標変換手段によって座標系を変換する。この新たに設定されるＸ軸とＹ軸とには、アルファベットＮを添えてＸＮ軸、ＹＮ軸と呼ぶことにし、前のＸ−Ｙ軸と区別する。ＸＮ−ＹＮ座標は、図２４上では、Ｘ−Ｙ軸を、Ｙ軸方向に切片ｂだけ平行移動し、その後Ｘ軸と回帰直線であるＸＮ軸とのなす角度θだけ回転（角変位）させることによって得ることができる。旧Ｘ−Ｙ座標系における座標値は、以下の行列式（２１）によって、ＸＮ−ＹＮ座標系における座標値に変換される。
【０１０６】
【数５】

【０１０７】
変換されたＸＮ−ＹＮ座標系における重心位置のＸＮ座標値を小さい順番に並替えて、その最大値ＸＮｍａｘおよび最小値ＸＮｍｉｎとを求め、次に最大値ＸＮｍａｘと最小値ＸＮｍｉｎとの差の絶対値Ｘｍｘ（＝｜ＸＮｍａｘ−ＸＮｍｉｎ｜）を求める。同様にしてＸＮ−ＹＮ座標系における重心位置のＹＮ座標値を小さい順番に並替えて、その最大値ＹＮｍａｘおよび最小値ＹＮｍｉｎとを求め、次に最大値ＹＮｍａｘと最小値ＹＮｍｉｎとの差の絶対値Ｙｍｘ（＝｜ＹＮｍａｘ−ＹＮｍｉｎ｜）を求める。
【０１０８】
図２４中では、絶対値Ｘｍｘは、重心位置４１と重心位置４２との間のＸＮ軸方向の距離ＬＸＮであり、絶対値Ｙｍｘは、重心位置４３と重心位置４４との間のＹＮ軸方向の距離ＬＹＮである。縦横比は、前述した絶対値Ｘｍｘと絶対値Ｙｍｘとの比（Ｘｍｘ／Ｙｍｘ）で求められる。縦横比（Ｘｍｘ／Ｙｍｘ）は、前記距離ＬＮＸと距離ＬＮＹとの比であり、１分間に移動した重心位置の散布の状態を定量的に特徴付けることができる。
【０１０９】
神経学的に正常であり、筋疾患のない被験児のＧＭによる重心位置の移動は、異常を有する被験児に比較して広い範囲に及ぶ。一方神経学的異常および／または筋疾患を有する被験児のＧＭでは、重心位置が局所的に集中するとともに、頭足方向もしくは左右の両手方向に片寄って移動する傾向がある。したがって、縦横比（Ｘｍｘ／Ｙｍｘ）でみた場合、神経学的異常および／または筋疾患を有する被験児では、その値は極端に大きいかまたは小さいという特徴を有するけれども、正常な被験児では、その値は異常を有する被験児の中間値付近で大きくばらつかないという特徴がある。
【０１１０】
このことから、縦横比（Ｘｍｘ／Ｙｍｘ）の大小によって神経学的な異常および／または筋疾患の有無を診断することが可能と判断される。予め弁別レベルＦ１もしくは、弁別レベルの上限値と下限値としてＦ１１およびＦ１２を判断手段６に設定しておくことによって、判断手段６は被験児毎に演算される縦横比（Ｘｍｘ／Ｙｍｘ）を弁別レベルＦ１またはＦ１１およびＦ１２と比較することによって、被験児の神経学的異常および／または筋疾患の有無を判断することが可能になる。
【０１１１】
図２５は、診断装置１による被験児の神経学的異常および／または筋疾患の有無を縦横比（Ｘｍｘ／Ｙｍｘ）によって診断する動作を説明するフローチャートである。図２５のフローチャートを参照し前述した被験児の神経学的異常および／または筋疾患の有無を縦横比（Ｘｍｘ／Ｙｍｘ）によって診断する一連の動作を説明する。図２５に示すフローチャートは、図１５に示すフローチャートに類似し、同一の動作を表すステップについては説明を省略する。
【０１１２】
ステップｇ９では、データ演算手段５の回帰演算手段によって重心データの回帰直線（Ｙ＝ａＸ＋ｂ）を演算する。ステップｇ１０では、回帰直線の演算結果に応答し、座標変換手段が、回帰直線を新たなＸＮ軸とし、ＸＮ軸に直交する軸を新たなＹＮ軸として、重心位置の座標値を新たなＸＮ−ＹＮ座標系の座標値に変換する。ステップｇ１１では、縦横比演算手段が、重心位置のＸＮ座標値の最大値ＸＮｍａｘ、最小値ＸＮｍｉｎと、重心位置のＹＮ座標値の最大値ＹＮｍａｘ、最小値ＹＮｍｉｎとから、縦横比（Ｘｍｘ／Ｙｍｘ）を演算する。ステップｇ１２では、判断手段６が、縦横比（Ｘｍｘ／Ｙｍｘ）が、予め定められる弁別レベルである比Ｆ１以上であるか否かが判断手段６によって判断される。なお、予め定められる弁別レベルは、前述したように上限値Ｆ１１と下限値Ｆ１２とが設定され、縦横比（Ｘｍｘ／Ｙｍｘ）が上下限値Ｆ１１，Ｆ１２の間であるか否かが判断されるようにしてもよい。ここでステップｇ４〜ステップｇ１２までの動作は、診断装置１の制御表示部８に備わる処理回路１６によって実行される。
【０１１３】
またデータ演算手段５は、前記重量検出センサ３によって１秒毎に検出される重量値を用い、前記２次元平面における被験児の重心位置を、１秒毎に演算する重心位置演算手段と、重心位置演算手段によって求められる重心位置または複数設けられる重量検出センサ３のうちの少なくとも１つの重量検出センサ設置位置における重量データの周波数を解析する周波数解析手段とを含む。
【０１１４】
重心位置または重量検出センサ設置位置における重量データの周波数解析手段は、たとえば高速フーリエ変換（ＦＦＴ）などの手法によって実現することができる。本実施の態様では、重心位置および重量検出センサ３ａ（ＣＨ１）設置位置における重量データの周波数解析を行い、周波数成分と振幅とを求めた。
【０１１５】
図２６は正常な新生児番号１０の被験児の周波数解析結果を示す図であり、図２７は神経学的異常を有する新生児番号１６の被験児の解析結果を示す図である。正常な被験児と神経学的異常を有する被験児との差異は、特にＣＨ１の周波数解析結果において顕著に認められる。
【０１１６】
図２６に示すように正常な新生児番号１０の被験児では、各周波数成分において振幅がある程度均一であり、特別大きく突出した振幅を示す周波数成分を見出すことができない。一方図２７に示すように、神経学的異常を有する新生児番号１６の被験児では、周波数成分によって振幅の片寄りが認められる。したがって、周波数成分とその周波数成分の振幅の弁別レベルを予め設定しておくことによって、周波数解析結果に基づいて被験児の異常の有無をおおよそ判断することができる。
【０１１７】
また、新生児または乳児の重量を複数の重量検出センサ３によって検出するステップと、重量検出センサ３によって予め定められる一定時間ｔ１毎に検出される重量値を用いて重量に関するデータを演算するステップと、重量に関するデータの演算結果に応答し、前記データによって新生児または乳児に異常があるかを判断するステップと、新生児または乳児に異常があるかの判断結果を表示手段によって表示するステップとを、コンピュータに実行させるための新生児および乳児の診断プログラムにすることができる。
【０１１８】
このような新生児および乳児の診断プログラムは、重量に関するデータを演算するステップが多種の態様によって具現化されるので、たとえば、図１５のフローチャートに示すステップｂ４〜ステップｂ１０、図１７のフローチャートに示すステップｃ４〜ステップｃ１０、図１９のフローチャートに示すステップｄ４〜ステップｄ１１、図２０のフローチャートに示すステップｅ４〜ステップｅ１１、図２１のフローチャートに示すｆ４〜ステップｆ１１、図２５のフローチャートに示すステップｇ４〜ステップｇ１２をマイクロコンピュータである処理回路１６に実行させるプログラムとして実現される。
【０１１９】
この新生児および乳児の診断プログラムをコンピュータに実行させることによって、新生児および乳児の重量を測定し、その重量に関するデータを演算した結果によって新生児および乳児の神経学的異常および／または筋疾患の有無を客観的に判断し、その判断結果の表示が可能になる。
【０１２０】
さらに新生児および乳児の診断プログラムを、コンピュータによる読取り可能にたとえばフレキシブルディスク（ＦＤ）またはコンパクトディスク−レコーダブル（ＣＤ−Ｒ）などの記録媒体に記録させることができる。このような記録媒体として新生児および乳児の診断プログラムが提供されることによって、汎用コンピュータ、重量検出センサおよび表示手段という簡易な構成で、新生児および乳児の神経学的な異常および／または筋疾患の有無の診断をすることが可能になる。
【０１２１】
以上に述べたように本実施の形態では、データ演算手段５には、各種の態様で表される演算機能を備えるけれども、これに限定されることなく、データ演算手段５は単独の演算機能を備える構成であってもよく、また選択される２つ以上の演算機能を備える構成であってもよい。また診断装置１に設けられる重量検出センサの数は４つであるけれども、これに限定されることなく、重心位置を求めるに必要な３つ以上が設けられる構成であればよい。また予め定められる一定時間ｔ１を１秒、予め定められる時間ｔ２を１分として重量に関するデータを演算しているけれども、時間はこれらに限定されることなく、より短い時間またはより長い時間がｔ１およびｔ２として選択されてもよい。
【０１２２】
【発明の効果】
本発明によれば、新生児または乳児の重心位置を一定時間ｔ１毎に演算し、演算される重心位置の予め定められる時間ｔ２内に２次元平面の同一座標上に繰返し出現する回数である重心位置度数を演算し、演算された重心位置の座標と重心位置度数の大小とに基づいて、新生児および乳児の神経学的な異常および／または筋疾患の有無を判断するので、容易に的確な診断をすることが可能になる。成人では中枢神経系の発達が完成しているのでＭＲＩ（Magnetic Resonance Imaging）、ＣＴ（Computed Tomography）などの画像診断における異常所見が、機能異常を相当な確率をもって診断できると考えられる。しかしながら、新生児、乳児においては中枢神経系は発達途上にあり、未発達であるため画像診断上の異常所見は必ずしも成人のように機能異常を診断できない。
【０１２３】
そこでこの装置は中枢神経系の統御された機能を客観的に評価できるため、ＭＲＩなどで正確に診断できない生後まもない時期における神経学的異常および／または筋疾患の有無の客観的判断が可能になるので、早期に効果的な治療を施すことができる。
【０１２６】
また本発明によれば、新生児または乳児の重心位置を一定時間ｔ１毎に演算し、演算される重心位置が予め定められる時間ｔ２内に２次元平面内で移動する重心位置の移動速度を求め、該重心移動速度の予め定められる速度間隔で区分される各速度範囲毎のデータ数である移動速度度数に基づいて、新生児および乳児の神経学的な異常および／または筋疾患の有無を判断するので、容易に的確な診断をすることが可能になる。
【０１２９】
また本発明によれば、重心位置の各座標値の散布状態を示す散布図から求められる縦横比（Ｘｍｘ／Ｙｍｘ）、すなわち散布図の形状の特徴に基づいて、新生児および乳児の神経学的な異常および／または筋疾患の有無を判断するので、容易に一層的確な診断をすることが可能になる。
【図面の簡単な説明】
【図１】本発明の実施の一形態である新生児および乳児の診断装置１の構成を簡略化して示す系統図である。
【図２】図１の新生児および乳児の診断装置１に備えられるコット９を示す平面図である。
【図３】診断装置１の電気的構成を示すブロック図である。
【図４】コット９の簡略化した平面図である。
【図５】表示手段７によって表示される表示画面の１例を示すイメージ図である。
【図６】１被験児の状態別に採取された重心位置散布図を示す。
【図７】重心位置散布のモデル図である。
【図８】２次元平面のＸ軸を幅ｄの小区間に分割して面積を求める概要を示す図である。
【図９】データ演算手段５による重心移動面積演算手段の動作を説明するフローチャートである。
【図１０】幅ｄの小区間の形状パターン例を示す図である。
【図１１】図１０（ｂ）を座標表示した図である。
【図１２】図１０（ｃ）を座標表示した図である。
【図１３】図１０（ｄ）を座標表示した図である。
【図１４】重心位置移動面積演算結果の例を示す図である。
【図１５】診断装置１による被験児の神経学的異常および／または筋疾患の有無を重心移動面積によって診断する動作を説明するフローチャートである。
【図１６】重心位置度数演算結果の例を示す図である。
【図１７】診断装置１による被験児の神経学的異常および／または筋疾患の有無を重心位置度数によって診断する動作を説明するフローチャートである。
【図１８】移動速度度数演算結果の例を示す図である。
【図１９】診断装置１による被験児の神経学的異常および／または筋疾患の有無を移動速度度数によって診断する動作を説明するフローチャートである。
【図２０】診断装置１による被験児の神経学的異常および／または筋疾患の有無を重心の平均移動速度Ｖａｖｅによって診断する動作を説明するフローチャートである。
【図２１】診断装置１による被験児の神経学的異常および／または筋疾患の有無を重心の平均移動加速度αａｖｅによって診断する動作を説明するフローチャートである。
【図２２】正常な新生児番号１０の被験児の散布図である。
【図２３】神経学的異常を有する新生児番号１６の被験児の散布図である。
【図２４】縦横比の演算方法の概略を示す図である。
【図２５】診断装置１による被験児の神経学的異常および／または筋疾患の有無を縦横比（Ｘｍｘ／Ｙｍｘ）によって診断する動作を説明するフローチャートである。
【図２６】正常な新生児番号１０の被験児の周波数解析結果を示す図である。
【図２７】神経学的異常を有する新生児番号１６の被験児の解析結果を示す図である。
【符号の説明】
１ 診断装置
２ 被験児
３ 重量検出センサ
４ 検出部
５ データ演算手段
６ 判断手段
７ 表示手段
８ 制御表示部
９ コット
１０ ワゴン
１６ 処理回路
１７ 撮像装置
２２ メモリ[0001]
BACKGROUND OF THE INVENTION
The present invention relates to a diagnostic apparatus for newborns and infants for diagnosing the presence or absence of neurological abnormalities and / or muscle diseases that may occur in newborns or infants.
[0002]
[Prior art]
Newborns and infants up to about 6 months of age have a spontaneous movement called General Movement (hereinafter abbreviated as GM) that cannot be understood as a simple reflex movement. This GM is considered to reflect the dynamics of the cranial nervous system and the musculoskeletal system, and is a movement that occurs throughout the body, including the extremities, especially when the newborn and infant are in a supine position and are in good mood.
[0003]
Neurological abnormalities and / or muscular disorders that may develop in humans may not be able to be effectively treated after the manifestation of obvious symptoms, and early detection and early treatment are desired. . The aforementioned neonatal and infant GMs are believed to have potential for use in the assessment of neurological abnormalities and / or muscle diseases. Based on such a viewpoint, the prior art which tries to measure GM of a newborn and an infant quantitatively is disclosed by Taga et al. (BPSE 2000 15th Symposium on Biological and Physiological Engineering, p165-168, for example). ). In this prior art, a plurality of markers are attached to each part of the body of a newborn or an infant (hereinafter may be collectively referred to as a test child), and only light reflected from the markers by a photographing device equipped with a specific strobe and filter is used. Is taken for a predetermined time, and the trajectory of the subject's movement is obtained.
[0004]
[Problems to be solved by the invention]
The prior art described above has the following problems. In order to obtain the movement trajectory of the subject child, there is a problem that a large-scale apparatus must be prepared so that an imaging apparatus including at least a plurality of cameras, a strobe, and a filter and an image analysis apparatus are required. In addition, since the marker attached to the subject is photographed with a camera and the trajectory is captured, there is a problem that the marker image as data may be lost depending on the state of movement of the subject.
[0005]
Further, as a prior art for grasping a human motion state, there is a center-of-gravity oscillating meter disclosed in, for example, Japanese Patent Laid-Open No. 7-250822, in addition to the above-described technique for photographing a marker attached to each part of the body.
[0006]
The center-of-gravity oscillating meter disclosed in Japanese Patent Laid-Open No. 7-250822 detects a load, which is the weight of a subject in a standing posture, using a plurality of load sensors, and calculates the position of the subject's center of gravity using each detected load. The trajectory of the center of gravity movement within a predetermined time is obtained. This center-of-gravity oscillometer is used mainly by the subject and the doctor to grasp the recovery state of the motor function by comparing the intention to suppress the subject's center of gravity variation with the actual locus of the center of gravity variation. . That is, the technique disclosed in Japanese Patent Application Laid-Open No. 7-250822 is merely a visual observation of the locus of center of gravity swing to ask the conformity with the subject's intention. It is impossible to find a technical idea of making a judgment of general abnormality and / or muscle disease.
[0007]
An object of the present invention is to provide a diagnostic apparatus for newborns and infants that can determine the presence or absence of neurological abnormalities and / or muscle diseases in newborns and infants with a simple configuration.
[0012]
[Means for Solving the Problems]
The present invention comprises a plurality of weight detection sensors for detecting the weight of a newborn or infant in a supine or prone position;
Using the weight value detected at a predetermined time t1 predetermined by the weight detection sensor, the center of gravity position of the newborn or infant on the two-dimensional plane that is a virtual plane including the plurality of weight detection sensors is determined at the predetermined time t1. In response to the output of the center-of-gravity position calculating means and the position of the center-of-gravity position calculating means, the center-of-gravity position obtained at every predetermined time t1 repeatedly appears on the same coordinates on the two-dimensional plane within a predetermined time t2. A data calculation means comprising a centroid position frequency calculation means for calculating the centroid position frequency that is the number of times;
In response to the output of the center-of-gravity position frequency calculation means, the determination means for discriminating whether the center-of-gravity position frequency is level-determined by a frequency B1, which is a predetermined discrimination level, and whether there is an abnormality in the newborn or the infant;
A newborn and infant diagnostic apparatus comprising: a display means for displaying the presence or absence of a neurological abnormality and / or a muscular disease in a newborn or an infant in response to an output of a judging means.
[0013]
According to the present invention, the position of the center of gravity of a newborn or infant is calculated every predetermined time t1, and the position of the center of gravity is the number of times that it repeatedly appears on the same coordinates on the two-dimensional plane within a predetermined time t2 of the calculated position of the center of gravity. The frequency is calculated, and based on the calculated coordinates of the center of gravity position and the magnitude of the center of gravity position frequency, the presence or absence of neurological abnormalities and / or muscular diseases in newborns and infants is judged, making accurate diagnosis easy. It becomes possible to do.
[0014]
The present invention also includes a plurality of weight detection sensors for detecting the weight of a newborn or infant in a supine or prone position,
Using the weight value detected at a predetermined time t1 predetermined by the weight detection sensor, the center of gravity position of the newborn or infant on the two-dimensional plane that is a virtual plane including the plurality of weight detection sensors is determined at the predetermined time t1. In response to the output of the center-of-gravity position calculating means and the output of the center-of-gravity position calculating means, the moving speed of the center-of-gravity position that moves in the two-dimensional plane within a predetermined time t2 is calculated for each predetermined time t1. In response to the output of the center-of-gravity movement speed calculation means and the movement speed of the center-of-gravity calculation means, a movement speed frequency calculation that calculates the movement speed frequency that is the number of data of the center-of-gravity movement speed for each speed range divided by a predetermined speed interval. Data computing means comprising means,
In response to the output of the moving speed frequency calculating means, the judging means for discriminating whether the moving speed frequency is leveled by a frequency C1 which is a predetermined discrimination level and whether there is an abnormality in the newborn or the infant;
A newborn and infant diagnostic apparatus comprising: a display means for displaying the presence or absence of a neurological abnormality and / or a muscular disease in a newborn or an infant in response to an output of a judging means.
[0015]
According to the present invention, the center of gravity position of a newborn or an infant is calculated every predetermined time t1, and the movement speed of the center of gravity position where the calculated center of gravity position moves within a two-dimensional plane within a predetermined time t2 is determined in advance. It is calculated every time t1, and the presence or absence of neurological abnormalities and / or muscular diseases in newborns and infants is judged based on the calculated magnitude and distribution of the center of gravity movement speed. It becomes possible to do.
[0022]
The present invention also includes a plurality of weight detection sensors for detecting the weight of a newborn or infant in a supine or prone position,
Using the weight value detected at a predetermined time t1 predetermined by the weight detection sensor, the center of gravity position of the newborn or infant on the two-dimensional XY plane that is a virtual plane including the plurality of weight detection sensors is determined as the constant The center of gravity position calculating means for calculating at every time t1, and the results of the movement of the center of gravity determined at the predetermined time t1 within the two-dimensional plane within the predetermined time t2 in response to the output of the center of gravity position calculating means. XY of the center-of-gravity position with the regression line as the new XN axis and the axis orthogonal to the regression line as the new YN axis in response to the output of the regression line The coordinate conversion means for converting the coordinate value into the coordinate value of the XN-YN coordinate system, and the maximum of the center of gravity position movement record in the new XN-YN coordinate system converted by the coordinate conversion means in the XN-axis direction The absolute value Xmx of the difference (= XNmax−XNmin) between XNmax and the minimum value XNmin, and the absolute value Ymx of the difference (= YNmax−YNmin) between the maximum value YNmax and the minimum value YNmin in the YN-axis direction of the center of gravity position movement record A data calculation means comprising: an aspect ratio calculation means for calculating an aspect ratio (Xmx / Ymx) which is a ratio of
In response to the output of the aspect ratio calculation means, the aspect ratio (Xmx / Ymx) is discriminated at a predetermined discrimination level F1 to determine whether there is an abnormality in the newborn or the infant;
A newborn and infant diagnostic apparatus comprising: a display means for displaying the presence or absence of a neurological abnormality and / or a muscular disease in a newborn or an infant in response to an output of a judging means.
[0023]
According to the present invention, based on the aspect ratio (Xmx / Ymx) obtained from the scatter diagram, that is, the characteristics of the shape of the scatter diagram, the presence or absence of neurological abnormalities and / or muscular diseases in newborns and infants is determined. Therefore, it becomes possible to make a more accurate diagnosis easily.
[0030]
DETAILED DESCRIPTION OF THE INVENTION
FIG. 1 is a system diagram schematically showing a configuration of a newborn and infant diagnostic apparatus 1 according to an embodiment of the present invention, and FIG. 2 shows a cot 9 provided in the newborn and infant diagnostic apparatus 1 of FIG. FIG.
[0031]
The neonatal and infant diagnostic apparatus 1 (hereinafter simply referred to as diagnostic apparatus 1) of the present embodiment is a newborn or infant in a supine or prone position (hereinafter collectively referred to as test subject 2). Detecting unit 4 provided with a plurality of weight detection sensors 3a, 3b, 3c, and 3d (four in the present embodiment, and the weight detection sensors are omitted). And a data calculation means 5 for calculating weight-related data using a weight value detected at a predetermined time t1 determined in advance by the weight detection sensor 3, and a newborn or A control display unit 8 is provided that includes a determination unit 6 that determines whether there is an abnormality in the infant and a display unit 7 that displays the presence or absence of abnormality of the subject child 2 in response to the output of the determination unit 6.
[0032]
The detection unit 4 includes a cot 9 that accommodates the subject child 2 and a wagon 10 that supports the cot 9. The cot 9 is a hollow container made of, for example, an acrylic resin having a substantially rectangular parallelepiped shape. An opening is formed on one surface, and the subject 2 can be accommodated in the internal space from the opening. A flat plate 11 covered with a mat-like elastic member is provided inside the cot 9, and the test child 2 described above is accommodated on the flat plate 11 in a supine position or a prone position.
[0033]
The wagon 10 is formed by fixing four metal pipes 12 formed in an inverted J shape to the four corners of a rectangular base plate 13 as viewed from above. The metal pipes 12 juxtaposed in the short side direction of the wagon 10 are connected by a straight pipe member 14, and the metal pipes 12 juxtaposed in the long side direction are connected by a mold steel member 15. The weight detection sensor 3 described above is provided on the upper surface of the steel plate member 15 (the surface facing the upper side in FIG. 1), and the cot 9 is mounted on the wagon 10 from the upper side of the weight detection sensor 3.
[0034]
As shown in FIG. 2, the four weight detection sensors 3 a, 3 b, 3 c, and 3 d are provided to support the four corners of the cot 9 when the cott 9 is viewed in plan view. While the subject 2 is in the supine position in the cot 9, the weight detection sensor 3a provided at the right hand position is sometimes referred to as CH1, and similarly, the weight detection sensor 3b at the left hand position is CH2 and the weight at the right foot position. The detection sensor 3c may be referred to as CH3, and the weight detection sensor 3d at the left foot position may be referred to as CH4. Since the weight detection sensor 3 is electrically connected to the control display unit 8 by the cable 19, the detected weight value is given to the control display unit 8.
[0035]
The data calculation means 5 and the determination means 6 provided in the control display unit 8 are a processing circuit 16 realized by a microcomputer or the like having a CPU (Central Processing Unit). The display means 7 is realized by a cathode ray tube, a liquid crystal display, or the like, and displays a data calculation result and a determination result in response to an output from the processing circuit 16.
[0036]
In the diagnostic device 1 of the present embodiment, the imaging device 17 can be provided, for example, supported by a partition 18 or the like. The imaging device 17 may be an optical camera or a CCD (Charge Coupled Device). Video information from the imaging device 17 is given to the control display unit 8 through the cable 20. The doctor can utilize the GM visual data of the subject child 2 obtained by the imaging device 17 for diagnosis. Furthermore, the diagnostic device 1 can be provided with a biological data measuring device 50. A sensor cable 51 for measuring the biological data of the test child 2 is connected to the biological data measuring device 50, and the measured biological data is given to the control display unit 8 through the cable 52. The biological data measuring device 50 can measure general biological data (body temperature, arterial blood oxygen saturation, etc.) of the test child 2 and perform a more accurate diagnosis together with the determination result by the diagnostic device 1.
[0037]
FIG. 3 is a block diagram showing an electrical configuration of the diagnostic apparatus 1. The processing circuit 16 is provided with outputs from the weight detection sensors 3a, 3b, 3c, 3d, the imaging device 17 and the biological data measuring device 50, and is executed from among various calculation functions provided in the data calculation means 5 described later. An output from function selection means 21 for selecting a function to be performed is given. The function selection means 21 may be set so that various calculation functions are selected in association with, for example, keyboard keys connected to the control display unit 8, and a touch panel is provided on the cathode ray tube or the liquid crystal display as the display means 7. It may be set so that various calculation functions are selected by the method.
[0038]
The processing circuit 16 includes a display unit 7 and a memory 22, and a printer 23 that prints display content on the display unit 7 on a recording sheet, for example. The memory 22 includes a ROM (Read Only Memory) and a RAM (Random Access Memory). The ROM stores a program for the diagnostic device 1 to execute a diagnostic process by the processing circuit 16, and the data calculation result and the determination result are written to and read from the RAM as needed.
[0039]
First, a calculation method of the center of gravity position of the test child 2 by the diagnostic apparatus 1 that is used as basic data for evaluation of the neurological abnormality and / or muscle disease of the test child 2 will be described below. The weights measured by the respective weight detection sensors 3a to 3d in a state where the test child 2 is not mounted on the cot 9 are represented by Wa0 to Wd0, and each of the states in the state where the test child 2 is mounted on the cot 9 The weights measured by the weight detection sensors 3a to 3d are represented by Wa1 to Wd1, respectively, and the weight based only on the body weight of the test child 2 measured by the respective weight detection sensors 3a to 3d is represented by Wa, Wb, Wc, and Wd. If it represents, the weight W of the test child 2 will be calculated | required by Formula (1).
W = Wa + Wb + Wc + Wd (1)
Here, Wa = Wa1-Wa0
Wb = Wb1-Wb0
Wc = Wc1-Wc0
Wd = Wd1-Wd0
[0040]
FIG. 4 is a simplified plan view of the cot 9. Assuming a two-dimensional plane including the four weight detection sensors 3, the longitudinal direction of the cot 9 on the two-dimensional plane is the X axis, the direction perpendicular to the longitudinal direction is the Y axis, and the origin is 0. The position (GX, GY) is a position in the two-dimensional plane. When the length in the longitudinal direction of the cot 9 is Lx and the length in the width direction perpendicular to the longitudinal direction is Ly, the coordinate position GX in the X direction of the center of gravity G and the coordinate position GY on the Y axis are expressed by the equation (2 ) And formula (3).
GX = {(Wa + Wb) / W} · Lx−Lx / 2 (2)
GY = {(Wb + Wd) / W} · Ly−Ly / 2 (3)
[0041]
The calculation of the center of gravity (GX, GY) of the test child 2 is executed by the data calculation means 5 described above. In the present embodiment, the predetermined time t1 is set to 1 second, for example, and the predetermined time t2 is set to 60 seconds (1 minute), for example. The calculation was executed and 60 gravity center position data were obtained in one minute. The center-of-gravity position calculation result and the weight value detected by the weight detection sensor 3 as the original data are stored in the memory 22.
[0042]
The barycentric position, which is the calculation result, is displayed on the display means 7 as a scatter diagram indicating the result of marking and moving the barycentric position on the two-dimensional plane, and is recorded on the recording paper by the printer 23. FIG. 5 is an image diagram showing an example of a display screen displayed by the display means 7. In FIG. 5, a scatter diagram display unit 25 is provided in the lower right portion toward the display screen 24, and is configured so that the movement results of the center of gravity position of the test child 2 can be visually recognized. In the example of the display screen 24, the latest coordinate position of the movement results of the center of gravity position is indicated by a black circle 26 having a large diameter, and a plurality of predetermined past positions are indicated by black circles 27 having a small diameter. Since the diameter of the black circle is reduced and displayed as it becomes, it is possible to know the progress of the movement of the center of gravity. Note that the progress of the movement of the center of gravity position can be displayed by a mark having the same size.
[0043]
In the display screen 24, an image display unit 28 for displaying the image data of the test subject 2 by the imaging device 17 is provided on the upper right side of the screen, and each weight detection sensor 3a is displayed on the left side of the display screen 24. A body weight data display unit 29 is provided for displaying the detected weight value by 3d and the XY coordinate value of the center of gravity position.
[0044]
The data on the center of gravity of the test child 2 as described above must be collected in the same state so that the test children 2 can be compared with each other, and for evaluation of neurological abnormalities and / or muscle diseases. It is required to be collected in such a state that the characteristics of the GM to be used can be detected. The status of newborn infants and infants as test subjects is classified as shown in Table 1, for example, by Volpe et al., But is further simplified to see if the eyes are open, i.e. whether they are awake or crying Since it seems possible to classify according to whether or not it is in a special exercise state, conditions suitable for collecting data on weight were examined for conditions 1 to 5 according to the state classification shown in Table 2.
[0045]
[Table 1]

[0046]
[Table 2]

[0047]
The Morrow reflex shown in Table 2 is a reaction that surprisingly contracts the limbs, trunk, and neck muscles when an acoustic stimulus or vibration such as flapping is suddenly applied to a newborn and an infant. For one selected child (subject number 9), the center of gravity position in each of the conditions 1 to 5 shown in Table 2 is continuously calculated for 1 minute every second, and the movement result of the center of gravity position is shown. A scatter plot was created.
[0048]
FIG. 6 shows the center-of-gravity position scatter diagram collected for each subject's condition. FIG. 6A is a scatter diagram of the positions of the center of gravity in a state where the eyes of condition 1 in Table 2 are open and not crying, that is, awake and resting. FIG. 6B is a scatter diagram of the center-of-gravity positions in the state of condition 2 in Table 2 with the eyes open and crying. FIG. 6C is a scatter diagram of the positions of the center of gravity in the state where the eyes of condition 3 in Table 2 are closed and not crying, that is, the sleeping state. 6 (d) and 6 (e) are scatter diagrams of the positions of the center of gravity in the state of flapping limbs and the state after Morrow reflection, which are special states of conditions 4 and 5 in Table 2. FIG. is there.
[0049]
When the subject is in a sleep state and in a contracted state of muscle after the Moro reflex, the position of the center of gravity hardly moves, so that it is difficult to detect the characteristics of GM, and neurological abnormalities and / or muscle diseases It is not appropriate as a data collection condition for the evaluation. Also, in the state of crying with the eyes open and the state of flapping the limbs, the movement of the center of gravity is so severe that it spreads undesirably over a wide area, so it is difficult to detect the characteristics of GM. It is not appropriate as a condition for collecting data used for the evaluation of neurological abnormalities and / or myopathy. Accordingly, when the condition 1 in Table 2 is awake and resting, it is determined that the movement of the center of gravity is dispersed within an appropriate range and is suitable for GM characteristic grasping. Data will be collected.
[0050]
The data calculation means 5 of the present embodiment is provided with a plurality of various calculation functions, and is configured so that the function selection means 21 can select and execute the calculation functions. Each aspect will be described.
[0051]
In the basic mode of the data calculation means 5, in response to the output of the gravity center position calculation means, the gravity center position calculation means for calculating the gravity center position of the subject 2 using the weight value detected every second described above, Center-of-gravity movement area calculation means for calculating the area of the center-of-gravity position obtained every second in the two-dimensional plane within one minute is provided.
[0052]
The calculation of the center of gravity position by the center of gravity position calculating means is as described above, and the calculation of the moving area of the center of gravity position by the center of gravity moving area calculating means is performed as follows. FIG. 7 is a model diagram of centroid position distribution, and FIG. 8 is a diagram showing an outline of obtaining an area by dividing the X axis of a two-dimensional plane into small sections having a width d. The moving area is the individual area obtained by dividing the area where the center of gravity moves in the two-dimensional XY plane as shown in the center of gravity scatter diagram shown in FIG. 7 and dividing the X axis into small sections of width d as shown in FIG. Is obtained by calculating the sum of the sub-section areas. At this time, if the X-axis division minimum scale and the small division section d are the same, the calculation can be easily performed.
[0053]
FIG. 9 is a flowchart for explaining the operation of the center-of-gravity movement area calculation by the data calculation means 5. The procedure for calculating the center of gravity movement area will be described with reference to FIG. At the start of step a1, the XY coordinate value, which is the movement result of the center of gravity position, is read from the memory 22. In step a2, the read barycentric positions are rearranged in ascending order of the X coordinate values. In step a3, the number (n) of X coordinate values rearranged in ascending order is counted. Here, n is a natural number.
[0054]
In step a4, i = 1 is set. In step a5, the maximum value Yma and the minimum value Ymi of the Y coordinate values in the i-th X coordinate value in the rearrangement order are obtained. In step a6, the maximum value Yma and the minimum value Ymi of the Y coordinate values in the (i + 1) th X coordinate value in the rearrangement order are obtained. Here, the absolute value of the difference between the i-th X coordinate value and the (i + 1) -th X coordinate value is the small division value d.
[0055]
In step a7, the area dia of the subdivision section is calculated from the subdivision value d and the maximum value Yma and the minimum value Ymi of the Y coordinate values obtained for each X coordinate value. There are various shape patterns in the small section formed by the adjacent X coordinate values and the maximum value Yma and minimum value Ymi of the Y coordinate in each X coordinate value, and the area dia is calculated according to each shape pattern. The
[0056]
FIG. 10 is a diagram showing an example of a shape pattern of a small section having a width d, FIG. 11 is a diagram showing coordinates of FIG. 10B, and FIG. 12 is a diagram showing coordinates of FIG. FIG. 13 is a diagram showing the coordinates of FIG. FIG. 10A shows a section where the Y coordinate value changes from one point to one point, and FIG. 10B shows a section where the Y coordinate value changes from one point to two points. ) Is a section where the Y coordinate value changes from two points to two points, and FIG. 10D is a section where the Y coordinate value changes from two points to one point.
[0057]
In the section shown in FIG. 10A, the area of the small divided section is calculated as zero. In the section shown in FIG. 10B, that is, in FIG. 11, the X-Y coordinates of the barycentric position 31 where the maximum value and the minimum value of the Y coordinate are the same in the X coordinate value x1 are (x1, y1), and the X coordinate value x2. Sub-division when the XY coordinate of the centroid position 32 that is the maximum value of the Y coordinate is (x2, y2) and the XY coordinate of the centroid position 33 that is the minimum value of the Y coordinate is (x2, y3). The area of the section dia is obtained by Expression (4).
dia = d · | y2-y3 | / 2 (4)
Where d = x2-x1
[0058]
In the section shown in FIG. 10C, that is, in FIG. 12, the XY coordinates of the centroid position 34 that is the maximum value of the Y coordinate in the X coordinate value x1 are (x1, y1), and the centroid position 35 that is the minimum value of the Y coordinate. X-Y coordinates of (x1, y2), X-coordinates of centroid position 36 that is the maximum value of Y coordinates in X-coordinate value x2 are (x2, y3), and centroid position 37 of minimum value of Y-coordinates. When the XY coordinates are (x2, y4), the area of the small divided section dia is obtained by the equations (5) to (8).
S1 = d · | y3-y1 | / 2 (5)
S2 = d · | y1-y4 | (6)
S3 = d · | y4-y2 | / 2 (7)
dia = S1 + S2 + S3 (8)
Where d = x2-x1
[0059]
In the section shown in FIG. 10D, that is, in FIG. 13, the X-Y coordinate of the barycentric position 38 that is the maximum value of the Y coordinate in the X coordinate value x1 is (x1, y1) and the barycentric position 39 that is the minimum value of the Y coordinate. When the XY coordinate of (x1, y2) and the XY coordinate of the center of gravity position 40 where the maximum value and the minimum value of the Y coordinate are the same in the X coordinate value x2 are (x2, y3), subdivision The area of the section dia is obtained by Expression (9).
dia = d · | y1-y2 | / 2 (9)
Where d = x2-x1
[0060]
Returning to FIG. 9, in step a <b> 8, the calculated small section area dia is stored in the memory 22. In step a9, i is replaced with (i + 1). In step a10, it is determined whether i is the same as (n-1). When the determination result is negative, the process returns to step a5 and proceeds to the subsequent steps. When the determination result is affirmative, the process proceeds to step a11. In step a11, the small section area dia calculated from the memory 22 is read, the sum, that is, the center of gravity movement area is calculated, and the series of operations is completed.
[0061]
FIG. 14 is a diagram illustrating an example of a calculation result of the center of gravity movement area. FIG. 14 shows 17 subjects (newborns) who were prediagnosed by a head ultrasonic tomography, head CT (Computed Tomography) examination, head MRI (Magnetic Resonance Imaging), electroencephalogram examination, etc. The bar graph shows the result of calculating the center of gravity movement area as described above. In FIG. 14, the preliminary diagnosis results indicate that the normal infant is indicated by a circle next to the newborn number identifying the newborn infant, the subject infant in cases such as jaundice and diaphragmatic hernia is indicated by □, neonatal asphyxia and future disability are predicted. △ mark, PVL (periventricular leukomalacia), cerebral infarction, hydrocephalus, etc. are indicated by X mark.
[0062]
As shown in FIG. 14, the boundary between the group almost occupied by the subject having neurological abnormality and / or muscle disease and the group almost occupied by the normal subject has a center-of-gravity movement area of 35 mm. ² It exists in the vicinity. Since the movement of the center of gravity by the GM of a test child who is neurologically normal and has no muscular disease covers a wide range compared to a test child having an abnormality, the neurological abnormality and It is determined that it is possible to diagnose the presence or absence of muscle disease. Therefore, the area value is 35 mm as the discrimination level A1 in advance. ² Is set in the determination means 6, the determination means 6 determines whether or not the center-of-gravity movement area calculated for each test child is equal to or higher than the discrimination level A1. It becomes possible to determine the presence or absence of.
[0063]
However, as shown in FIG. 14, even in the case of a test subject included in a group having a center-of-gravity moving area of the discrimination level A1 or higher and whose diagnosis result by the diagnosis apparatus 1 should be determined to be normal, There are some cases that correspond to the abnormal cases indicated by. However, since the test child shown in FIG. 14 includes a plurality of different types of abnormal cases, neurological abnormalities to be detected and / or neurological abnormalities to be detected by setting different levels of discrimination levels according to muscle diseases. It is considered that the diagnosis accuracy can be further improved by making a diagnosis for each muscle disease.
[0064]
FIG. 15 is a flowchart for explaining an operation of diagnosing the presence / absence of a neurological abnormality and / or a muscular disease in the test child by the diagnostic device 1 based on the movement area of the center of gravity. With reference to the flowchart of FIG. 15, a series of operations for diagnosing the presence or absence of the neurological abnormality and / or muscular disease of the test child described above based on the center of gravity movement area will be described.
[0065]
In step b1, a newborn or infant as a test child is placed on the cot 9 so as to be in a supine position. In step b2, it is determined whether or not the condition 1 in which data relating to weight can be collected, that is, whether or not the vehicle is in a resting state. This determination is made by, for example, a doctor. When the determination result is negative, step b2 is repeated until a resting state is reached. When the determination result is affirmative, the process proceeds to step b3. In step b3, a one-minute timer start, which is a predetermined time t2 for weight detection by the weight detection sensor 3, is performed. This timer start can be realized, for example, by being configured so that it can be input to the above-described function selection means 21 as a signal for starting the calculation together with the selection of the data calculation function.
[0066]
In step b4, the weight of the test child 2 is measured every second by the weight detection sensor 3 (CH1 to CH4). In step b5, the gravity center position (Xi, Yi) is calculated by the gravity center position calculation means of the data calculation means 5. In step b6, the gravity center position calculation result is stored in the memory 22. In step b7, it is determined whether or not a measurement time of 1 minute has elapsed. When the determination result is affirmative, the process proceeds to step b8. When the determination result is negative, the process returns to step b4 and proceeds to the subsequent steps.
[0067]
In step b8, the gravity center position (Xi, Yi) is read from the memory 22, and in step b9, the gravity center movement area is calculated by the gravity center movement area calculation means of the data calculation means 5. In step b10, the judging means 6 judges whether or not the center-of-gravity movement area as a calculation result is equal to or larger than an area A1 that is a predetermined discrimination level. When the determination result is affirmative, the process proceeds to step b11, and the determination means 6 causes the display means 7 to display that the determination result is normal by the output signal. When the determination result is negative, the process proceeds to step b12, and the determination means 6 causes the display means 7 to display that the determination result is abnormal by the output signal. After the display by the display means 7, a series of diagnostic operations is completed. Here, the operations from step b4 to step b10 are executed by the processing circuit 16 provided in the control display unit 8 of the diagnostic apparatus 1.
[0068]
In the first aspect according to the present invention of the data calculation means 5, the center-of-gravity position calculation means for calculating the center-of-gravity position of the subject 2 using the weight value detected every second described above, and the output of the center-of-gravity position calculation means Centroid position frequency calculating means for calculating a centroid position frequency that is the number of times that the centroid position obtained every second appears repeatedly on the same coordinates on the two-dimensional plane per minute. The center-of-gravity position frequency is determined by dividing the X-axis and the Y-axis at intervals of 1 mm, for example, and setting the section, and counting the number of times the center-of-gravity position calculated for one minute every 60 seconds appears in the same section. You can ask for it.
[0069]
FIG. 16 is a diagram illustrating an example of the result of the gravity center position frequency calculation. FIG. 16 is a three-dimensional graph showing the results of calculating the center-of-gravity position frequency for the test children of the newborn numbers 10 and 16 shown in FIG. 14 described above. As shown in FIG. 16 (b), in the test child of the newborn number 16 having a neurological abnormality, the concentration of the center of gravity exceeding the frequency of 10 is recognized locally. On the other hand, as shown in FIG. 16 (a), the normal neonate No. 10 test child does not have a center-of-gravity position frequency exceeding 10, and the center-of-gravity position varies and is distributed as compared with the above-described neonate No. 16 test child. ing.
[0070]
Since the centroid position by GM of the test child who is neurologically normal and has no muscular disease does not concentrate locally unlike the test child having an abnormality, the neurological position depends on the frequency of the centroid position. It is judged possible to diagnose the presence of abnormalities and / or muscle diseases. Therefore, by setting, for example, the frequency 10 in the determination means 6 as the discrimination level B1 in advance, the determination means 6 determines whether the center-of-gravity position frequency calculated for each test child is equal to or lower than the discrimination level B1. It is possible to determine the presence or absence of neurological abnormalities and / or muscle diseases. The discrimination level frequency B1 is not limited to 10, and can be changed depending on the neurological abnormality and / or muscle disease to be detected.
[0071]
FIG. 17 is a flowchart illustrating an operation of diagnosing the presence / absence of neurological abnormality and / or muscular disease in the test child by the diagnostic apparatus 1 based on the position of the center of gravity. A series of operations for diagnosing the presence or absence of the above-described neurological abnormality and / or muscular disease in the subject child with reference to the flowchart of FIG. 17 will be described. The flowchart shown in FIG. 17 is similar to the flowchart shown in FIG. 15, and description of steps representing the same operation is omitted.
[0072]
In step c9, the gravity center position frequency is calculated by the gravity center position frequency calculation means of the data calculation means 5. In step c10, it is judged by the judging means 6 whether or not the center-of-gravity position frequency that is the calculation result is equal to or higher than the frequency B1 that is a predetermined discrimination level. Here, the operations from step c4 to step c10 are executed by the processing circuit 16 provided in the control display unit 8 of the diagnostic apparatus 1.
[0073]
In the second aspect according to the present invention of the data calculating means 5, the center-of-gravity position calculating means for calculating the center-of-gravity position of the subject 2 using the weight value detected every second as described above, and the output of the center-of-gravity position calculating means Centroid movement speed calculation means for calculating the movement speed Vi of the gravity center position that moves within a two-dimensional plane per minute, and the gravity center movement speed calculation means In response to the output, a moving speed frequency calculating means for calculating a moving speed frequency that is the number of data of the center of gravity moving speed for each speed range divided by a predetermined speed interval is included.
[0074]
The center-of-gravity moving speed Vi can be calculated as follows. When the barycentric position (Xi, Yi) at an arbitrary time t for 1 minute for calculating the barycentric position every second is replaced with a time display to obtain the barycentric position (Xt, Yt), time t1 which is the next barycentric position calculating time The subsequent center of gravity position is represented by (Xt + t1, Yt + t1). At this time, the center-of-gravity moving speed Vi from the center-of-gravity position (Xt, Yt) to the center-of-gravity position (Xt + t1, Yt + t1) after the elapse of time t1 is obtained by the following equation (10). In the present embodiment, since the time t1 is 1 second as described above, the denominator of the equation (10) can be omitted when the center-of-gravity moving speed Vi is obtained at a speed per second.
Vi = √ {(Xt + t1−Xt) ² + (Yt + t1-Yt) ² } / T1 (10)
[0075]
The center-of-gravity moving speed frequency is determined by, for example, dividing a predetermined speed interval by 1 mm / sec, and counting the number of center-of-gravity moving speeds Vi calculated for one minute, that is, 60 times per second, belonging to the same speed section. Can be obtained.
[0076]
FIG. 18 is a diagram illustrating an example of the moving speed frequency calculation result. FIG. 18 is a bar graph showing the results of calculating the moving speed frequency for the test children of the newborn numbers 10 and 16 shown in FIG. 14 described above. As shown in FIG. 18B, in the test child of the newborn number 16 having neurological abnormality, the center-of-gravity moving speed Vi is concentrated at a high frequency in the segment range of speed 0 to 1 mm / second (s). It is recognized that On the other hand, as shown in FIG. 18 (a), in the normal neonate No. 10 test subject, the center-of-gravity moving speed Vi shows the maximum frequency in the segment range of speed 0 to 1 mm / sec (s). It is smaller than the test child of No. 16 and distributed in a high speed range.
[0077]
Thus, the center-of-gravity movement speed Vi by the GM of a test child who is neurologically normal and has no muscular disease does not concentrate locally in a specific speed segment range as in a test child having an abnormality. It is judged that the presence or absence of neurological abnormalities and / or muscular diseases can be diagnosed based on the moving speed frequency. Accordingly, by setting, for example, the frequency 35 in the determination means 6 in advance as the discrimination level C1, the determination means 6 allows the moving speed frequency calculated for each subject child to exceed the discrimination level C1 in a specific speed category range. Whether or not there is a neurological abnormality and / or muscular disease in the subject can be determined. The discrimination level frequency C1 is not limited to 35, and can be changed depending on the neurological abnormality and / or muscle disease to be detected.
[0078]
FIG. 19 is a flowchart illustrating an operation of diagnosing the presence / absence of a neurological abnormality and / or muscular disease in a subject by the diagnostic device 1 based on the moving speed frequency. A series of operations for diagnosing the presence or absence of the neurological abnormality and / or muscular disease of the test child described above based on the frequency of the center of gravity will be described with reference to the flowchart of FIG. The flowchart shown in FIG. 19 is similar to the flowchart shown in FIG. 15, and description of steps representing the same operation is omitted.
[0079]
In step d9, the center of gravity moving speed Vi is calculated by the center of gravity moving speed calculating means of the data calculating means 5. In step d10, the moving speed frequency calculating means classifies the center-of-gravity moving speed Vi according to a predetermined speed category, and counts the moving speed frequency for each speed category. In step d11, it is judged by the judging means 6 whether or not the moving speed frequency that is the calculation result is equal to or less than the frequency C1 that is a predetermined discrimination level. Here, the operations from step d4 to step d11 are executed by the processing circuit 16 provided in the control display unit 8 of the diagnostic apparatus 1.
[0080]
Also Data calculation means 5 is The barycentric position calculating means for calculating the barycentric position of the subject 2 using the weight value detected every second described above, and the barycentric position obtained every second in response to the output of the barycentric position calculating means, The center-of-gravity movement speed calculation means for calculating the movement speed Vi of the center-of-gravity position that moves within the two-dimensional plane per minute, and the average of the center-of-gravity movement speed Vi in one minute in response to the output of the center-of-gravity movement speed calculation means Moving speed data calculating means for calculating an average moving speed Vave as a value, a maximum moving speed Vmax as a maximum value of the center of gravity moving speed Vi, and a minimum moving speed Vmin as a minimum value of the center of gravity moving speed Vi.
[0081]
The average moving speed Vave is obtained by the following equation (11) using the center-of-gravity moving speed Vi by the center-of-gravity moving speed calculating means described above.
[0082]
[Expression 1]

[0083]
As described above, the center-of-gravity movement speed Vi by the GM of a neurologically normal test subject without muscle disease is locally concentrated in a specific speed segment range, that is, a slow rate segment range as in a test subject having an abnormality. There is nothing to do. Therefore, when the average moving speed Vave of the center of gravity for one minute is calculated, the average moving speed Vave of the normal test child is faster than the average moving speed Vave of the test child having an abnormality, so the average moving speed is obtained. It is judged that the presence or absence of a neurological abnormality and / or muscle disease can be diagnosed by the speed Vave. Needless to say, depending on the case, the average movement speed Vave of the test child having an abnormality may be faster.
[0084]
Therefore, by setting a predetermined speed value as the discrimination level D1 in the determination unit 6, the determination unit 6 determines whether the average moving speed Vave calculated for each subject is equal to or higher than the discrimination level D1. It becomes possible to determine the presence or absence of neurological abnormalities and / or muscular diseases in the test children. The value of the discrimination level D1 can be changed depending on the neurological abnormality and / or muscle disease to be detected.
[0085]
FIG. 20 is a flowchart illustrating an operation of diagnosing the presence or absence of a neurological abnormality and / or muscular disease in the subject child by the diagnostic device 1 based on the average moving speed Vave of the center of gravity. A series of operations for diagnosing the presence or absence of the neurological abnormality and / or muscular disease in the test child based on the average moving speed Vave of the center of gravity will be described with reference to the flowchart of FIG. The flowchart shown in FIG. 20 is similar to the flowchart shown in FIG. 19, and the description of steps representing the same operation is omitted.
[0086]
In step e10, the average moving speed Vave of the center of gravity is calculated by the average moving speed calculating means of the data calculating means 5. In step e11, it is judged by the judging means 6 whether or not the average moving speed Vave as a calculation result is equal to or lower than a speed D1 that is a predetermined discrimination level. Here, the operations from step e4 to step e11 are executed by the processing circuit 16 provided in the control display unit 8 of the diagnostic apparatus 1.
[0087]
Examples above In the above, an example in which the presence or absence of a neurological abnormality and / or muscle disease in the subject child is determined based on the average moving speed Vave has been described, but the same applies to the maximum moving speed Vmax or the minimum moving speed Vmin calculated by the data calculating means 5. Judgment can be made. Further, the determination may be made based on a combination of any two speeds selected from the average moving speed Vave, the maximum moving speed Vmax, and the minimum moving speed Vmin, and may be determined using all three speeds. good.
[0088]
Also Data calculation means 5 is The barycentric position calculating means for calculating the barycentric position of the subject 2 using the weight value detected every second described above, and the barycentric position obtained every second in response to the output of the barycentric position calculating means, The center-of-gravity movement acceleration calculation means for calculating the movement acceleration αi of the center-of-gravity position that moves within a two-dimensional plane per minute, and the average of the center-of-gravity movement acceleration αi for one minute in response to the output of the center-of-gravity movement acceleration calculation means Average moving acceleration calculating means for calculating the average moving acceleration αave which is a value, moving acceleration data calculating for calculating the maximum moving acceleration αmax which is the maximum value of the centroid moving acceleration αi and the minimum moving acceleration αmin which is the minimum value of the centroid moving acceleration αi Means.
[0089]
The center-of-gravity movement acceleration αi is obtained by Expression (12), and the average movement acceleration αave is obtained by Expression (13).
[0090]
[Expression 2]

[0091]
As described above, the center-of-gravity movement speed Vi by the GM of a neurologically normal test subject without muscle disease is locally concentrated in a specific speed segment range, that is, a slow rate segment range as in a test subject having an abnormality. There is nothing to do. Therefore, when the average movement acceleration αave of the center of gravity for one minute is calculated, the average movement acceleration αave of the normal test child is faster than the average movement acceleration αave of the test child having an abnormality. It is judged that the presence or absence of neurological abnormalities and / or muscle diseases can be diagnosed by the acceleration αave.
[0092]
Therefore, by setting a predetermined acceleration value in the determination unit 6 as the discrimination level E1, the determination unit 6 determines whether the average moving acceleration αave calculated for each subject is equal to or higher than the discrimination level E1. It becomes possible to determine the presence or absence of neurological abnormalities and / or muscular diseases in the test children. The value of the discrimination level E1 can be changed depending on the neurological abnormality and / or muscle disease to be detected.
[0093]
FIG. 21 is a flowchart for explaining an operation of diagnosing the presence or absence of a neurological abnormality and / or muscular disease in the subject child by the diagnostic device 1 using the average movement acceleration αave of the center of gravity. A series of operations for diagnosing the presence / absence of the neurological abnormality and / or muscular disease of the test child described above with the average movement acceleration αave of the center of gravity will be described with reference to the flowchart of FIG. The flowchart shown in FIG. 21 is similar to the flowchart shown in FIG. 19, and the description of steps representing the same operation is omitted.
[0094]
In step f9, the center-of-gravity moving acceleration αi is calculated by the center-of-gravity moving acceleration calculating means of the data calculating means 5. In step f10, the average moving acceleration αave of the center of gravity is calculated in response to the result of calculating the center of gravity moving acceleration. In step f11, it is judged by the judging means 6 whether or not the average moving acceleration αave as the calculation result is equal to or higher than an acceleration value E1 that is a predetermined discrimination level. Here, the operations from step f4 to step f11 are executed by the processing circuit 16 provided in the control display unit 8 of the diagnostic apparatus 1.
[0095]
Examples above In the above, an example in which the presence or absence of a neurological abnormality and / or a muscular disease in the subject child is determined based on the average movement acceleration αave has been described, but the same applies to the maximum movement acceleration αmax or the minimum movement acceleration αmin calculated by the data calculation means 5. Judgment can be made. Further, the determination may be made based on a combination of any two accelerations selected from the average movement acceleration αave, the maximum movement acceleration αmax, and the minimum movement acceleration αmin, and may be determined using all three accelerations. good.
[0096]
Also Data calculation means 5 is The barycentric position calculating means for calculating the barycentric position of the subject 2 using the weight value detected every second described above, and the barycentric position obtained every second in response to the output of the barycentric position calculating means, Center-of-gravity position distribution storage means for storing each coordinate value that is a result of movement in the two-dimensional plane in one minute. The center-of-gravity position distribution storage unit is a memory including a RAM or the like, and may be provided in the data calculation unit 5 or may be configured to use the memory 22.
[0097]
The movement result of the gravity center position read from the gravity center position scatter storage means is expressed as a scatter diagram in the XY coordinate system. This scatter diagram is printed out by switching the display screen of the display means 7 described above to a scatter diagram display, for example, by means of a switch provided in advance in the function selecting means 21 and printing it to the printer 23 connected to the processing circuit 16. By doing so, visual observation can be made possible.
[0098]
The determination means 6 determines whether or not there is an abnormality in the test child by, for example, setting a typical example of a scatter diagram for each case in advance in the determination means 6 and comparing the scatter diagram of center of gravity position movement obtained for each test child with the typical example. This is done by matching.
[0099]
FIG. 22 is a scatter diagram of a normal neonate No. 10 test subject, and FIG. 23 is a scatter diagram of a newborn No. 16 test subject having a neurological abnormality. As shown in FIG. 22, in the normal infant No. 10 test subject, the positions of the center of gravity are scattered over a wide range in both the X-axis direction and the Y-axis direction. On the other hand, as shown in FIG. 23, in the test child of the newborn baby number 16 having a neurological abnormality, the center of gravity position has a feature that its spraying range is small in both the X-axis direction and the Y-axis direction. Therefore, for example, by comparing and comparing the scatter diagram as the data of the test child and the scatter diagram set as a typical example, it is possible to roughly determine the presence or absence of the test child's abnormality.
[0100]
The data calculation means 5 according to the present invention 3 In this aspect, the center-of-gravity position calculating means for calculating the center-of-gravity position of the subject 2 using the weight value detected every second described above, and the center of gravity obtained every second in response to the output of the center-of-gravity position calculating means Based on the result of the position moving within the two-dimensional XY plane in one minute, a regression calculation means for calculating a regression line, and responding to the output of the regression calculation means, the regression line is set as a new X axis, Coordinate conversion means for converting the XY coordinate value of the centroid position using the axis orthogonal to the regression line as the new Y axis, and the X axis of the centroid position movement record in the new XY coordinate system converted by the coordinate conversion means The difference (= Ymax−Ymin) between the absolute value Xmx of the difference (= Xmax−Xmin) between the maximum value Xmax and the minimum value Xmin in the direction and the maximum value Ymax and the minimum value Ymin in the Y axis direction of the center of gravity position movement record It is the ratio to the absolute value Ymx And a aspect ratio calculating means for calculating the aspect ratio (Xmx / Ymx).
[0101]
A method for calculating the aspect ratio (Xmx / Ymx) will be described below. FIG. 24 is a diagram showing an outline of an aspect ratio calculation method. First, a regression line (Y = aX + b) of 60 centroid position data calculated per minute is calculated by the regression calculation means. The regression line is obtained by the least square method and is given by the following equation (14).
[0102]
[Equation 3]

[0103]
The slope a and intercept b of the regression line are given by equations (19) and (20), respectively.
[0104]
[Expression 4]

[0105]
Next, the coordinate conversion means converts the coordinate system so that the regression line (Y = aX + b) obtained as described above is used as a new X axis and the axis orthogonal to the new X axis is used as a new Y axis. To do. The newly set X-axis and Y-axis are referred to as the XN-axis and the YN-axis by adding an alphabet N, and are distinguished from the previous XY axes. In FIG. 24, the XN-YN coordinates are translated (angular displacement) by an angle θ between the X-axis and the XN axis which is a regression line after the XY axis is translated by the intercept b in the Y-axis direction. Can be obtained. The coordinate value in the old XY coordinate system is converted into the coordinate value in the XN-YN coordinate system by the following determinant (21).
[0106]
[Equation 5]

[0107]
The XN coordinate values of the center of gravity in the converted XN-YN coordinate system are rearranged in ascending order to obtain the maximum value XNmax and the minimum value XNmin, and then the absolute value of the difference between the maximum value XNmax and the minimum value XNmin Xmx (= | XNmax−XNmin |) is obtained. Similarly, the YN coordinate values of the barycentric positions in the XN-YN coordinate system are rearranged in ascending order to obtain the maximum value YNmax and the minimum value YNmin, and then the absolute value of the difference between the maximum value YNmax and the minimum value YNmin Ymx (= | YNmax−YNmin |) is obtained.
[0108]
In FIG. 24, the absolute value Xmx is the distance LXN in the XN-axis direction between the gravity center position 41 and the gravity center position 42, and the absolute value Ymx is in the YN-axis direction between the gravity center position 43 and the gravity center position 44. Distance LYN. The aspect ratio is obtained by the ratio (Xmx / Ymx) of the absolute value Xmx and the absolute value Ymx described above. The aspect ratio (Xmx / Ymx) is a ratio between the distance LNX and the distance LNY, and can quantitatively characterize the state of dispersion of the center of gravity moved in one minute.
[0109]
The shift of the center of gravity by GM of a test child who is neurologically normal and has no muscular disease covers a wide range compared to a test child having an abnormality. On the other hand, in the GM of a test child having a neurological abnormality and / or a muscular disease, the center of gravity position is concentrated locally and tends to move toward the head and feet or both left and right hands. Therefore, when viewed in terms of aspect ratio (Xmx / Ymx), in subjects with neurological abnormalities and / or muscular disorders, the value is extremely large or small, but in normal subjects, The value is characterized in that it does not vary greatly around the median value of test subjects with abnormalities.
[0110]
From this, it is determined that the presence or absence of neurological abnormalities and / or muscular diseases can be diagnosed based on the aspect ratio (Xmx / Ymx). By setting F11 and F12 as the discrimination level F1 or the upper limit value and the lower limit value of the discrimination level in the judgment means 6 in advance, the judgment means 6 discriminates the aspect ratio (Xmx / Ymx) calculated for each subject. By comparing with the levels F1 or F11 and F12, it becomes possible to determine the presence or absence of neurological abnormalities and / or muscle diseases in the test children.
[0111]
FIG. 25 is a flowchart illustrating an operation of diagnosing the presence / absence of a neurological abnormality and / or muscular disease in a test child by the diagnostic apparatus 1 using an aspect ratio (Xmx / Ymx). A series of operations for diagnosing the presence / absence of neurological abnormalities and / or muscular diseases in the test child described above by the aspect ratio (Xmx / Ymx) will be described with reference to the flowchart of FIG. The flowchart shown in FIG. 25 is similar to the flowchart shown in FIG. 15, and description of steps representing the same operation will be omitted.
[0112]
In step g9, the regression line of the centroid data (Y = aX + b) is calculated by the regression calculation unit of the data calculation unit 5. In step g10, in response to the calculation result of the regression line, the coordinate conversion means sets the regression line as the new XN axis, the axis orthogonal to the XN axis as the new YN axis, and sets the coordinate value of the gravity center position as the new XN−. Convert to coordinate values in YN coordinate system. In step g11, the aspect ratio calculating means calculates the aspect ratio (Xmx / Ymx) from the maximum value XNmax and minimum value XNmin of the XN coordinate value of the center of gravity position, and the maximum value YNmax and minimum value YNmin of the YN coordinate value of the center of gravity position. Is calculated. In step g12, the determination means 6 determines whether or not the aspect ratio (Xmx / Ymx) is equal to or greater than a ratio F1 that is a predetermined discrimination level. As described above, the upper limit value F11 and the lower limit value F12 are set as the predetermined discrimination level, and it is determined whether or not the aspect ratio (Xmx / Ymx) is between the upper and lower limit values F11 and F12. You may do it. Here, the operations from step g4 to step g12 are executed by the processing circuit 16 provided in the control display unit 8 of the diagnostic apparatus 1.
[0113]
Also Data calculation means 5 is Using the weight value detected every second by the weight detection sensor 3, the center of gravity position calculating means for calculating the center of gravity position of the subject on the two-dimensional plane every second is obtained by the center of gravity position calculating means. Frequency analysis means for analyzing the frequency of weight data at the position of the center of gravity or at least one weight detection sensor installation position among the plurality of weight detection sensors 3 provided.
[0114]
The frequency analysis means for the weight data at the center of gravity position or the weight detection sensor installation position can be realized by a technique such as Fast Fourier Transform (FFT). In the present embodiment, the frequency analysis of the weight data at the center of gravity position and the weight detection sensor 3a (CH1) installation position is performed, and the frequency component and the amplitude are obtained.
[0115]
FIG. 26 is a diagram showing the frequency analysis result of a normal neonate No. 10 test child, and FIG. 27 is a diagram showing the analysis result of a neonatal No. 16 test child having a neurological abnormality. The difference between a normal test subject and a test subject having a neurological abnormality is particularly noticeable in the CH1 frequency analysis results.
[0116]
As shown in FIG. 26, in the normal infant No. 10 test child, the amplitude is uniform to some extent in each frequency component, and it is not possible to find a frequency component having a particularly large protruding amplitude. On the other hand, as shown in FIG. 27, the deviation of the amplitude is recognized by the frequency component in the test child of the newborn No. 16 having the neurological abnormality. Therefore, by setting the frequency component and the discrimination level of the amplitude of the frequency component in advance, it is possible to roughly determine whether the subject has an abnormality based on the frequency analysis result.
[0117]
A step of detecting the weight of the newborn or infant by the plurality of weight detection sensors 3; a step of calculating weight-related data using a weight value detected by the weight detection sensor 3 every predetermined time t1; In response to the calculation result of the weight-related data, a step of determining whether there is an abnormality in the newborn or infant based on the data and a step of displaying the determination result on whether there is an abnormality in the newborn or infant on the computer are displayed on the computer. It can be a newborn and infant diagnostic program to be implemented.
[0118]
In such a diagnostic program for newborns and infants, the step of calculating the weight-related data is embodied in various aspects, and therefore, for example, steps b4 to b10 shown in the flowchart of FIG. 15 and steps shown in the flowchart of FIG. c4 to step c10, step d4 to step d11 shown in the flowchart of FIG. 19, step e4 to step e11 shown in the flowchart of FIG. 20, f4 to step f11 shown in the flowchart of FIG. 21, step g4 to step shown in the flowchart of FIG. This is realized as a program for causing g12 to be executed by the processing circuit 16 which is a microcomputer.
[0119]
By executing this diagnostic program for newborns and infants on a computer, the weights of the newborns and infants were measured, and the data on the weights were calculated to objectively determine the presence or absence of neurological abnormalities and / or muscle diseases in the newborns and infants. Judgment and display of the judgment result becomes possible.
[0120]
Furthermore, the diagnostic program for newborns and infants can be recorded on a recording medium such as a flexible disk (FD) or a compact disk-recordable (CD-R) so as to be readable by a computer. By providing a diagnostic program for newborns and infants as such a recording medium, with a simple configuration of a general-purpose computer, a weight detection sensor and a display means, the presence or absence of neurological abnormalities and / or muscle diseases in the newborns and infants Can be diagnosed.
[0121]
As described above, in the present embodiment, the data calculation means 5 is provided with calculation functions represented in various aspects, but the data calculation means 5 is not limited to this, and the data calculation means 5 has a single calculation function. The structure provided may be sufficient, and the structure provided with two or more selected calculation functions may be sufficient. Although the number of weight detection sensors provided in the diagnostic apparatus 1 is four, the configuration is not limited to this, and any configuration may be used as long as three or more necessary for obtaining the position of the center of gravity are provided. The weight-related data is calculated by setting the predetermined time t1 as 1 second and the predetermined time t2 as 1 minute. However, the time is not limited to these, and the shorter time or the longer time is t1 and It may be selected as t2.
[0122]
【The invention's effect】
According to the present invention, the position of the center of gravity of a newborn or an infant is calculated every certain time t1, and the position of the center of gravity is the number of times that it repeatedly appears on the same coordinates on the two-dimensional plane within a predetermined time t2 of the calculated position of the center of gravity. The frequency is calculated, and based on the calculated coordinates of the center of gravity position and the magnitude of the center of gravity position frequency, the presence or absence of neurological abnormalities and / or muscular diseases in newborns and infants is judged, making accurate diagnosis easy. It becomes possible to do. Since adults have completed development of the central nervous system, abnormal findings in diagnostic imaging such as MRI (Magnetic Resonance Imaging) and CT (Computed Tomography) are considered to be able to diagnose functional abnormalities with a considerable probability. However, in neonates and infants, the central nervous system is still developing and is not yet developed, so abnormal findings in diagnostic imaging cannot always diagnose functional abnormalities like adults.
[0123]
Therefore, since this device can objectively evaluate the centralized functions of the central nervous system, it is possible to objectively determine the presence or absence of neurological abnormalities and / or muscular diseases at an early age that cannot be accurately diagnosed by MRI or the like. Therefore, effective treatment can be performed at an early stage.
[0126]
Further, according to the present invention, the center of gravity position of a newborn or infant is calculated at a constant time t1, and the center of gravity position moving speed at which the calculated center of gravity position moves within a two-dimensional plane within a predetermined time t2 is calculated. The moving speed frequency is the number of data for each speed range divided by the predetermined speed interval of the center of gravity moving speed Based on the above, since it is determined whether or not there is a neurological abnormality and / or a muscular disease in a newborn and an infant, an accurate diagnosis can be easily performed.
[0129]
Also according to the invention, Shows the distribution status of each coordinate value of the center of gravity Based on the aspect ratio (Xmx / Ymx) obtained from the scatter plot, that is, the shape characteristics of the scatter plot, the presence or absence of neurological abnormalities and / or muscular diseases in newborns and infants is easily determined. Diagnosis is possible.
[Brief description of the drawings]
FIG. 1 is a system diagram showing a simplified configuration of a diagnostic apparatus 1 for newborns and infants according to an embodiment of the present invention.
2 is a plan view showing a cot 9 provided in the newborn and infant diagnostic apparatus 1 of FIG. 1; FIG.
FIG. 3 is a block diagram showing an electrical configuration of the diagnostic apparatus 1;
4 is a simplified plan view of the cot 9. FIG.
FIG. 5 is an image diagram showing an example of a display screen displayed by the display means 7;
FIG. 6 is a scatter diagram of the center of gravity collected for each subject's condition.
FIG. 7 is a model diagram of centroid position scattering.
FIG. 8 is a diagram showing an outline of obtaining an area by dividing an X axis of a two-dimensional plane into small sections having a width d.
FIG. 9 is a flowchart for explaining the operation of the center-of-gravity movement area calculation means by the data calculation means 5;
FIG. 10 is a diagram illustrating an example of a shape pattern of a small section having a width d.
FIG. 11 is a diagram showing coordinates of FIG.
12 is a diagram showing coordinates of FIG. 10 (c).
13 is a diagram showing coordinates of FIG. 10 (d).
FIG. 14 is a diagram illustrating an example of a calculation result of a gravity center position movement area.
FIG. 15 is a flowchart for explaining an operation of diagnosing the presence or absence of a neurological abnormality and / or a muscular disease in a subject by the diagnostic apparatus 1 based on the center of gravity movement area.
FIG. 16 is a diagram illustrating an example of a result of calculating a gravity center position frequency.
FIG. 17 is a flowchart for explaining an operation of diagnosing the presence or absence of a neurological abnormality and / or muscular disease in a test child by the diagnostic device 1 based on the position of the center of gravity.
FIG. 18 is a diagram illustrating an example of a moving speed frequency calculation result.
FIG. 19 is a flowchart illustrating an operation of diagnosing the presence / absence of a neurological abnormality and / or muscular disease in a test child by the diagnostic device 1 based on the moving speed frequency.
FIG. 20 is a flowchart for explaining an operation of diagnosing the presence or absence of a neurological abnormality and / or muscular disease in the subject child by the diagnostic apparatus 1 based on the average moving speed Vave of the center of gravity.
FIG. 21 is a flowchart illustrating an operation of diagnosing the presence or absence of a neurological abnormality and / or muscular disease in a test child by the diagnostic apparatus 1 based on the average movement acceleration αave of the center of gravity.
FIG. 22 is a scatter diagram of a normal neonate No. 10 test child.
FIG. 23 is a scatter diagram of a test infant with neonate number 16 having neurological abnormalities.
FIG. 24 is a diagram showing an outline of a method for calculating an aspect ratio.
FIG. 25 is a flowchart illustrating an operation of diagnosing the presence / absence of a neurological abnormality and / or muscular disease in a test child by the diagnostic apparatus 1 using an aspect ratio (Xmx / Ymx).
FIG. 26 is a diagram showing the frequency analysis result of a normal infant No. 10 test child.
FIG. 27 is a diagram showing an analysis result of a test child of a newborn number 16 having a neurological abnormality.
[Explanation of symbols]
1 Diagnostic device
2 test children
3 Weight detection sensor
4 detector
5 Data calculation means
6 Judgment means
7 Display means
8 Control display section
9 cots
10 wagons
16 Processing circuit
17 Imaging device
22 memory

Claims (3)

A plurality of weight detection sensors for detecting the weight of a newborn or infant in a supine or prone position;
Using the weight value detected at a predetermined time t1 predetermined by the weight detection sensor, the center of gravity position of the newborn or infant on the two-dimensional plane that is a virtual plane including the plurality of weight detection sensors is determined at the predetermined time t1. In response to the output of the center-of-gravity position calculating means and the position of the center-of-gravity position calculating means, the center-of-gravity position obtained at every predetermined time t1 repeatedly appears on the same coordinates on the two-dimensional plane within a predetermined time t2. A data calculation means comprising a centroid position frequency calculation means for calculating the centroid position frequency that is the number of times;
In response to the output of the center-of-gravity position frequency calculation means, the determination means for discriminating whether the center-of-gravity position frequency is level-determined by a frequency B1, which is a predetermined discrimination level, and whether there is an abnormality in the newborn or the infant;
A diagnostic apparatus for newborns and infants, comprising display means for displaying the presence or absence of neurological abnormalities and / or muscular diseases in the newborn or infant in response to the output of the judging means. A plurality of weight detection sensors for detecting the weight of a newborn or infant in a supine or prone position;
Using the weight value detected at a predetermined time t1 predetermined by the weight detection sensor, the center of gravity position of the newborn or infant on the two-dimensional plane that is a virtual plane including the plurality of weight detection sensors is determined at the predetermined time t1. In response to the output of the center-of-gravity position calculating means and the output of the center-of-gravity position calculating means, the moving speed of the center-of-gravity position that moves in the two-dimensional plane within a predetermined time t2 is calculated for each predetermined time t1. In response to the output of the center-of-gravity movement speed calculation means and the movement speed of the center-of-gravity calculation means, a movement speed frequency calculation that calculates the movement speed frequency that is the number of data of the center-of-gravity movement speed for each speed range divided by a predetermined speed interval. Data computing means comprising means,
In response to the output of the moving speed frequency calculating means, the judging means for discriminating whether the moving speed frequency is leveled by a frequency C1 which is a predetermined discrimination level and whether there is an abnormality in the newborn or the infant;
A diagnostic apparatus for newborns and infants, comprising display means for displaying the presence or absence of neurological abnormalities and / or muscular diseases in the newborn or infant in response to the output of the judging means. A plurality of weight detection sensors for detecting the weight of a newborn or infant in a supine or prone position;
Using the weight value detected at a predetermined time t1 predetermined by the weight detection sensor, the center of gravity position of the newborn or infant on the two-dimensional XY plane that is a virtual plane including the plurality of weight detection sensors is determined as the constant The center of gravity position calculating means for calculating at every time t1, and the results of the movement of the center of gravity determined at the predetermined time t1 within the two-dimensional plane within the predetermined time t2 in response to the output of the center of gravity position calculating means. XY of the center-of-gravity position with the regression line as the new XN axis and the axis orthogonal to the regression line as the new YN axis in response to the output of the regression line The coordinate conversion means for converting the coordinate value into the coordinate value of the XN-YN coordinate system, and the maximum of the center of gravity position movement record in the new XN-YN coordinate system converted by the coordinate conversion means in the XN-axis direction The absolute value Xmx of the difference (= XNmax−XNmin) between XNmax and the minimum value XNmin, and the absolute value Ymx of the difference (= YNmax−YNmin) between the maximum value YNmax and the minimum value YNmin in the YN-axis direction of the center of gravity position movement record A data calculation means comprising: an aspect ratio calculation means for calculating an aspect ratio (Xmx / Ymx) which is a ratio of
In response to the output of the aspect ratio calculation means, the aspect ratio (Xmx / Ymx) is discriminated at a predetermined discrimination level F1 to determine whether there is an abnormality in the newborn or the infant;
A diagnostic apparatus for newborns and infants, comprising display means for displaying the presence or absence of neurological abnormalities and / or muscular diseases in the newborn or infant in response to the output of the judging means.

Images