JP5155856B2 - 臨床症状の予測および監視技術 - Google Patents
臨床症状の予測および監視技術 Download PDFInfo
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Description
前記生物学的変調は、連続測定を基にしたバイオフィードバック技法を用いる試みをしており、測定したパラメータの強度に係わる視覚/聴覚フィードバックを構成している。
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ことからなる方法を提供する。
(a)1以上の高調波に関連するエネルギレベルと最大周波数に関連するエネルギレベルから選ばれた第一エネルギレベルと、
(b)1以上の高調波に関連する第二エネルギレベルとの関係を求め、
前記関係を基準関係レベルと比較し、
比較結果の少なくとも一部に応じて発作の発症を予測することを特徴とする臨床発作の発症を予測する方法を提供する。
時間領域信号を周波数領域信号に変換し、周波数領域信号の呼吸関連周波数範囲の最大値を特定して対象者の呼吸数を測定し、最大周波数の1以上の高調波を求める制御ユニットとからなり、
(a)1以上の高調波に関連するエネルギレベルと最大周波数に関連するエネルギレベルから選ばれた第一エネルギレベルと、
(b)1以上の高調波に関連する第二エネルギレベルとの関係を求め、前記関係を基準関係レベルと比較し、比較結果の少なくとも一部に応じて発作の発症を予測する
ことを特徴とする臨床発作の発症予測装置を提供する。
● 主にREM睡眠中に起こる比較的早く変化するランダムな呼吸パターン
● たとえば、チェーン・ストークス呼吸(CSR)や周期性呼吸などの数秒から数分の持続時間を有する周期的呼吸数変動パターン
● 徐呼吸数傾向(主に、健常対象者の通常の睡眠中の徐呼吸数傾向には、通常数時間継続する時間において区分化された単調減少呼吸が含まれるが、例として図5を参照に後述するように喘息など特定の慢性症状を持つ対象者では単調減少呼吸数が僅かに顕れるか、顕れないことがある。)
● 咳や他の睡眠を阻害する症状のような呼吸パターンの中断や、一時的な覚醒によって起こる呼吸パターンの中断
これらの呼吸パターンは睡眠期の不安定性および体温などの様々な生理的パラメータに関連する。たとえば、REM睡眠は通常、不規則で多様な呼吸パターンになるが、熟睡期ではより規則的で安定したパターンになる。異常に高い体温が呼吸数を増加させるが、通常は正常な周期的呼吸数の変動パターンを示す。不安感などの心理学的要因もまた、睡眠中の呼吸パターンの変調を起こし、更には、その効果は通常、睡眠の経過とともに低下する。喘息などの咳や一時的な覚醒など、あるいは、それらに関連しない病変によって起こる呼吸パターンの中断は前後関係で診断評価する。
● 咳、睡眠障害、覚醒などによる呼吸パターンの中断: モジュール22は、これらの症状を定量化し、潜在的な喘息発作の予測の関連性を判定する。
F=A1*ΔP1+A2*ΔP2 + ・・・ + An*ΔPn・・・(式1)
式において、AiはパラメータPiに与えられた相対重み、ΔPiは設定された夜の値Piと値Piの基準値との差を表す。Fは、時間もしくは夜間を基準として算出され、個人の履歴を基に設定された参照値と比較する。値Fが参照値を越えた場合、システムは対象者あるいは医療従事者に警報を与える。パラメータPiのいずれかが適正である場合、ΔPiの符号付き値の代わりにΔPiの絶対値を求めることができる。また、パラメータPiのいずれかが適正である場合、平方、平方根、指数関数、対数、あるいは、その他の関数を求めることができる。
たとえば、コンビネーションの観察の確率を、システム10が予め設定した、あるいは、学習した閾値と比較してもよい。確率が閾値より少なければ、システム10が、発作が切迫していることより高い確率があることを警告するアラームを発する。本発明の適用例として、上記の式1のように各パラメータのスコアに重み付けをすることができる。
J(i)=(l−alpha)*J(i−l)+alpha*abs(X(i))
・・・(式2)
式において、X(i)は運動センサー30からサンプルされた未処理信号である。
パターン分析モジュール16によって、合成スコアを第一閾値および第一閾値より大きい第二閾値と比較する。合成スコアが第一閾値と第二閾値の間であれば、システム10は将来予期される臨床発作を表す警報を出す。合成スコアが第二閾値より大きい場合、システムは現在臨床発作を発症していることを表すアラームを送出する。別の方法として、スコアおよび合成スコアをベクトルで表すことができる。
Claims (27)
- 対象者もしくは対象者が着用する衣類に接触せずに、もしくは、視認せずに、対象者の呼吸を検出し、対象者もしくは対象者が着用する衣類に接触せずに、もしくは、視認せずに、対象者の心拍を検出するセンサーと、
出力モジュールと、
検出呼吸に応じて対象者の少なくとも1つの呼吸パターンを測定し、検出心拍に応じて対象者の少なくとも1つの心拍パターンを測定し、互いに異なる第一および第二閾値を設定し、前記呼吸パターンと心拍パターンを分析してスコアを生成して前記呼吸パターンと心拍パターンを分析し、斯かるスコアが第一閾値と第二閾値の範囲内に入る場合に臨床発作症状の予測発症を表す第一出力を生成するよう前記出力モジュールを駆動し、斯かるスコアが第二閾値を超える場合はその時点で臨床発作症状を発症していることを表す第二出力を生成するよう前記出力モジュールを駆動する機能を持たせることによって、斯かる分析結果に応じて臨床症状の病態を表す出力を生成するよう前記出力モジュールを駆動する制御ユニットとを備えることを特徴とする装置。 - 請求項1において、前記センサーは、前記呼吸を検出する第一センサーと、前記心拍を検出する第二センサーとを備えることを特徴とする装置。
- 請求項1において、前記制御ユニットに、前記呼吸パターンを基準呼吸パターンと比較し、前記心拍パターンを基準心拍パターンと比較し、斯かる比較結果に応じて前記出力を生成するよう前記出力モジュールを駆動する機能を持たせたことを特徴とする装置。
- 請求項1において、前記心拍パターンが心拍数パターンを含み、前記制御ユニットに、前記心拍数パターンを測定する機能を持たせたことを特徴とする装置。
- 請求項1において、前記制御ユニットに、臨床発作症状の発症の少なくとも1時間前に前記呼吸パターンと心拍パターンに応じて臨床発作症状の発症を予測し、斯かる予測結果に応じて前記出力を生成するよう前記出力モジュールを駆動する機能を持たせたことを特徴とする装置。
- 請求項1において、前記センサーに、少なくとも1時間の間、ほぼ連続して前記呼吸と心拍を検出する機能を持たせたことを特徴とする装置。
- 請求項6において、前記制御ユニットに、臨床発作症状の発症の少なくとも1時間前に前記呼吸パターンと心拍パターンに応じて臨床発作症状の発症を予測し、斯かる予測結果に応じて前記出力を生成するよう前記出力モジュールを駆動する機能を持たせたことを特徴とする装置。
- 請求項1において、前記センサーに、対象者が夜間睡眠中の少なくとも80%の間、ほぼ連続して前記呼吸と心拍を検出する機能を持たせたことを特徴とする装置。
- 請求項8において、前記制御ユニットに、臨床発作症状の発症の少なくとも1時間前に前記呼吸パターンと心拍パターンに応じて臨床発作症状の発症を予測し、斯かる予測結果に応じて前記出力を生成するよう前記出力モジュールを駆動する機能を持たせたことを特徴とする装置。
- 請求項1において、前記センサーに、ヒトの協力を必要とせずに前記呼吸と心拍を検出する機能を持たせたことを特徴とする装置。
- 請求項1において、前記センサーが少なくとも10平方cmの表面を有する剛性容器に格納された力センサーを含み、前記力センサーに、対象者もしくは対象者が着用する衣類に接触しないで対象者の運動関連パラメータを検出する機能を持たせ、前記制御ユニットに、前記運動関連パラメータから積極的呼吸数および前記心拍を導き出す機能を持たせたことを特徴とする装置。
- 請求項1において、前記制御ユニットに、前記分析結果に応じて臨床発作症状の発症を特定し、前記発症の特定後に休止し、休止後に特定発症を対象者に警告するよう前記出力モジュールを駆動する機能を持たせたことを特徴とする装置。
- 請求項1において、前記呼吸パターンが呼吸数パターンを含み、前記制御ユニットに、前記呼吸数パターンを測定する機能を持たせたことを特徴とする装置。
- 請求項13において、前記呼吸数パターンが徐呼吸数傾向パターンを含み、前記制御ユニットに、前記徐呼吸数傾向パターンを測定する機能を持たせたことを特徴とする装置。
- 対象者もしくは対象者が着用する衣類に接触せずに、もしくは、視認せずに、対象者の呼吸をセンサーを用いて検出し、
対象者もしくは対象者が着用する衣類に接触せずに、もしくは、視認せずに、対象者の心拍をセンサーを用いて検出し、
制御ユニットを用いて、検出呼吸に応じて対象者の少なくとも1つの呼吸パターンを測定すると共に、検出心拍に応じて対象者の少なくとも1つの心拍パターンを測定し、
互いに異なる第一および第二閾値を設定し、前記呼吸パターンと心拍パターンを分析してスコアを生成して前記呼吸パターンと心拍パターンを分析し、
斯かるスコアが第一閾値と第二閾値の範囲内に入る場合に臨床発作症状の予測発症を表す第一出力を生成するよう前記出力モジュールを駆動し、斯かるスコアが第二閾値を超える場合はその時点で臨床発作症状を発症していることを表す第二出力を生成するよう前記出力モジュールを駆動する機能を持たせることによって、斯かる分析結果に応じて臨床症状の病態を表す出力を生成する
ことを特徴とする方法。 - 請求項15において、分析には、前記呼吸パターンと基準呼吸パターンを比較すると共に前記心拍パターンと基準心拍パターンを比較する処理が含まれ、前記出力の生成には、斯かる比較結果に応じて前記出力を生成する処理が含まれることを特徴とする方法。
- 請求項15において、前記心拍パターンの測定には、心拍数パターンを測定する処理が含まれることを特徴とする方法。
- 請求項15において、分析には、臨床発作症状の発症の少なくとも1時間前に前記呼吸パターンと心拍パターンに応じて臨床発作症状の発症を予測する処理が含まれ、前記出力の生成には、斯かる予測結果に応じて前記出力を生成する処理が含まれることを特徴とする方法。
- 請求項15において、前記呼吸と心拍の検出には、少なくとも1時間の間、ほぼ連続して前記呼吸と心拍を検出する処理が含まれることを特徴とする方法。
- 請求項19において、分析には、臨床発作症状の発症の少なくとも1時間前に前記呼吸パターンと心拍パターンに応じて臨床発作症状の発症を予測する処理が含まれ、前記出力の生成には、斯かる予測結果に応じて前記出力を生成する処理が含まれることを特徴とする方法。
- 請求項15において、前記呼吸と心拍の検出には、対象者が夜間睡眠中の少なくとも80%の間、ほぼ連続して前記呼吸と心拍を検出する処理が含まれることを特徴とする方法。
- 請求項21において、分析には、臨床発作症状の発症の少なくとも1時間前に前記呼吸パターンと心拍パターンに応じて臨床発作症状の発症を予測する処理が含まれ、前記出力の生成には、斯かる予測結果に応じて前記出力を生成する処理が含まれることを特徴とする方法。
- 請求項15において、前記呼吸と心拍の検出には、ヒトの協力を必要とせずに前記呼吸と心拍を検出する処理が含まれることを特徴とする方法。
- 請求項15において、分析には、前記呼吸パターンと心拍パターンを分析して臨床発作症状の発症を特定する処理が含まれ、前記出力の生成には、前記発症の特定後に休止し、休止後に特定発症を対象者に警告する処理が含まれることを特徴とする方法。
- 請求項15において、前記呼吸パターンの測定には、呼吸数パターンを測定する処理が含まれることを特徴とする方法。
- 請求項25において、前記呼吸数パターンの測定には、徐呼吸数傾向パターンを測定する処理が含まれることを特徴とする方法。
- 請求項15において、前記出力の生成には、臨床症状の病態を医療従事者に通知する処理が含まれることを特徴とする方法。
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IL188307A0 (en) | 2008-04-13 |
IL188307A (en) | 2014-02-27 |
AU2006260535A2 (en) | 2008-02-21 |
KR101182994B1 (ko) | 2012-09-19 |
US20060241510A1 (en) | 2006-10-26 |
WO2006137067A2 (en) | 2006-12-28 |
CA2613460A1 (en) | 2006-12-28 |
WO2006137067A3 (en) | 2007-09-27 |
US7314451B2 (en) | 2008-01-01 |
EP2505131A1 (en) | 2012-10-03 |
KR20080034437A (ko) | 2008-04-21 |
EP1898777A4 (en) | 2010-03-03 |
AU2006260535B2 (en) | 2012-12-06 |
CA2613460C (en) | 2012-05-08 |
AU2006260535A1 (en) | 2006-12-28 |
JP2009501557A (ja) | 2009-01-22 |
EP1898777A2 (en) | 2008-03-19 |
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