TWI579804B - 駕駛者突發性心臟病判斷系統 - Google Patents

駕駛者突發性心臟病判斷系統 Download PDF

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TWI579804B
TWI579804B TW103141510A TW103141510A TWI579804B TW I579804 B TWI579804 B TW I579804B TW 103141510 A TW103141510 A TW 103141510A TW 103141510 A TW103141510 A TW 103141510A TW I579804 B TWI579804 B TW I579804B
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driver
model
threshold
physiological signals
heart disease
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Yan-Cheng Feng
Ming-Kuan Ke
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Description

駕駛者突發性心臟病判斷系統
本發明係有關一種車用判斷駕駛者狀態之技術,特別是指一種駕駛者突發性心臟病判斷系統。
按,車禍發生的原因除了不遵守交通規則,如超速、逆向之外,主要可分為注意力不集中及突發性疾病,注意力不集中可能原因為疲勞駕駛、分心打電話或聊天等,這些因素皆可靠人為方式避免,但突發性疾病為不可預知的,例如心臟病發、昏迷、猝死等,若駕駛失能,不論是突然急停在路中間或是沒有放開油門使車輛繼續前進,皆是相當危險的駕駛行為,甚至若駕駛昏迷後無意識地將油門踩到底,更可能發生嚴重的追撞。
由此可知,突發性疾病無法避免,那如何在發生突發性疾病當下適時採取措施、避免更大的意外發生是相當重要的,而首先便需先偵測駕駛者是否突然發病,其中,又以突發性心臟病最為危急,且很多患者在心臟病發時其實仍有些微行為能力,若偵測出駕駛心臟病發後,車輛可自動剎車、熄火、閃燈、甚至靠邊停車,進一步甚至可同時發出訊息給警察局、醫療單位等,則不但可避免意外發生,更可極大程度保住駕駛者的生命,因此,判斷駕駛者是否突發性心臟病為首要之急。
因此,本發明即提出一種駕駛者突發性心臟病判斷系統,具體架構及其實施方式將詳述於下:
本發明之主要目的在提供一種駕駛者突發性心臟病判斷系統,其係利用複數感測器同時擷取心律訊號、血壓訊號及呼吸頻率訊號等生理訊號,以感知駕駛者的生理狀態,判斷駕駛者是否突發性心臟病。
本發明之另一目的在提供一種駕駛者突發性心臟病判斷系統,利用類神經網路訓練建立專屬於駕駛者個人的呼吸頻率模型、血壓模型及心律模型等個人化模型,達到客製化生理狀態判讀,以增加預測突發性心臟病的準確率,且當駕駛者就醫時這些依據持續擷取的生理訊號所建立出的個人化模型更可供醫生參考。
本發明之再一目的在提供一種駕駛者突發性心臟病判斷系統,當擷取到的生理訊號中至少一者超出閥值時,並判斷另外兩種生理訊號是否也異常,以判斷是否有突發性疾病發生,需提供警示或立即將駕駛者送醫等。
為達上述之目的,本發明提供一種駕駛者突發性心臟病判斷系統,包括複數感測器,持續擷取該駕駛者之複數生理訊號,生理訊號包括一呼吸頻率訊號、一心律訊號及一血壓訊號;以及一監控系統,包括一處理器及一記憶體,處理器依據生理訊號分別訓練出包括一呼吸頻率模型、一心律模型及一血壓模型之複數個人化模型並儲存於記憶體中,且依據呼吸頻率模型、心律模型及血壓模型設定出生理訊號個別之一閥值,處理器判斷是否有任一種生理訊號超出閥值,若有至少一種生理訊號超出閥 值,則依據超出閥值之生理訊號之種類數,判斷駕駛者之狀態危險程度,並發出警示。
底下藉由具體實施例詳加說明,當更容易瞭解本發明之目的、技術內容、特點及其所達成之功效。
10‧‧‧駕駛者突發性心臟病判斷系統
12‧‧‧感測器
122‧‧‧呼吸頻率感測器
124‧‧‧心律感測器
126‧‧‧血壓感測器
14‧‧‧監控系統
142‧‧‧處理器
144‧‧‧記憶體
150‧‧‧個人化模型
152‧‧‧呼吸頻率模型
154‧‧‧心律模型
156‧‧‧血壓模型
第1圖為本發明駕駛者突發性心臟病判斷系統之方塊圖。
第2圖為本發明駕駛者突發性心臟病判斷方法之流程圖。
本發明提供一種駕駛者突發性心臟病判斷系統,請參考第1圖,其為本發明中駕駛者突發性心臟病判斷系統10之方塊圖,此駕駛者突發性心臟病判斷系統10可內建於車輛本身的微電腦中,或是獨立的一台主機,包括複數感測器12及一監控系統14,感測器12包括一呼吸頻率感測器122、一心律感測器124及一血壓感測器126,其中心律感測器124可為貼片式黏貼在駕駛者胸口處,或是裝設在安全帶上,當駕駛者繫上安全帶時心律感測器124緊貼駕駛者胸部便可擷取心跳的訊號,呼吸頻率感測器122與心律感測器124可為同一個貼片或不同貼片,擷取駕駛者的呼吸訊號,而血壓感測器126則可設在方向盤上駕駛者手握持的位置,以光學方式擷取駕駛者的血壓訊號,例如將光照射在手指上,分析反射光的光譜來判斷而壓訊號,三個感測器122、124及126分別擷取駕駛者之呼吸頻率訊號、心律訊號及血壓訊號等生理訊號;監控系統14中包括一處理器142及一記憶體144,處理器142依據生理訊號分別訓練出包括一呼吸頻率模型152、一心律模型 154及一血壓模型156之複數個人化模型150並儲存於記憶體144中,且依據呼吸頻率模型152、心律模型154及血壓模型156設定出三種生理訊號個別的閥值;處理器142除了訓練個人化模型150之外,還可用以判斷是否有任一種生理訊號超出閥值,若生理訊號中有至少一種超出閥值,則依據超出閥值之生理訊號之種類數,判斷駕駛者之狀態危險程度,並發出警示。
本發明中駕駛者突發性心臟病判斷方法之流程圖如第2圖所示,首先在步驟S10中利用至少一個感測器分別擷取駕駛者之複數生理訊號,並傳送到一監控系統,擷取的生理訊號包括一呼吸頻率訊號、一心律訊號及一血壓訊號,感測器持續擷取這些生理訊號,並每隔一段時間顯示擷取結果一次,如每5分鐘;步驟S12中監控系統中之處理器利用類神經網路技術將生理訊號分別訓練建立出專屬於駕駛者之複數個人化模型,包括至少一呼吸頻率模型、一心律模型及一血壓模型,每一個人化模型具有一閥值;當建立了專屬於駕駛者的個人化模型後,再如步驟S14所述,監控系統判斷所擷取的複數生理訊號中是否有任一種生理訊號超出閥值,若生理訊號均未超出閥值,則回到步驟S10繼續擷取呼吸頻率訊號、心律訊號及血壓訊號等生理訊號,反之,若生理訊號中有至少一種超出閥值,則如步驟S16所述,監控系統依據超出閥值之生理訊號之種類數,判斷駕駛者之狀態危險程度,並發出警示。
心律模型係擷取駕駛者的心電圖,從時域訊號傅立葉轉換成頻域訊號,此訊號的頻率在0~60赫茲之間,心律訓練模型包含每分鐘心跳數、0-60赫茲頻域訊號等,再利用類神經網路技術將這些訊號訓練出個人化之駕駛者的心律模型;呼吸頻率模型則是依據呼吸訊號的頻率、強度及斜 率等資訊以類神經網路技術訓練出;血壓模型是依據舒張壓、收縮壓以及平均動脈壓等資訊,同樣以類神經網路技術訓練出,且上述三個模型皆可接收新進的生理訊號增加樣本數,不斷訓練,使模型更接近駕駛者本身。
上述生理訊號閥值之初始值可設定一符合大眾化之生理警示閥值,例如呼吸頻率模型的閥值為每分鐘呼吸次數為平均值的兩倍,若呼吸頻率小於平均值的兩倍時,為正常值,輸出0,若呼吸頻率大於平均值的兩倍則為不正常,輸出1;血壓模型的閥值為收縮壓是90mmHg,若收縮壓大於90mmHg為正常,輸出0,若收縮壓小於90mmHg為不正常,輸出1;心律模型的閥值為每分鐘心跳數150下,若每分鐘心跳小於150下為正常,輸出0,若每分鐘心跳大於150下則為不正常,輸出1。因此全部正常時,輸出為(0,0,0),有一項不正常時,輸出為(1,0,0)、(0,1,0)或(0,0,1),危險程度低,有兩項不正常時,輸出為(1,0,1)、(0,1,1)或(1,1,0),危險程度中,若三項皆不正常時,輸出為(1,1,1),危險程度高,如下表一所示。
表一
設定這三種閥值為參考醫學期刊之大眾化理論數據,可設定為初始值,透過類神經網路訓練個人化之生理數據後,會將此初始值依個人化狀態而進行調整。例如,經類神經網路訓練後,駕駛者A之閥值會調整為心跳每分鐘大於130下則判斷為不正常,血壓調整為小於80mmHg則判斷為不正常,呼吸頻率調整為超過平時的1.5倍則判斷為不正常。
舉例而言,假設監控系統偵測到輸入的三種生理訊號中有一個超出個人化模型的閥值,例如呼吸頻率大於平均值的兩倍時,監控系統會同時判斷另外兩個生理訊號(血壓及心跳)是否正常,以預設的初始值做為閥值(尚未訓練出個人化的生理數據時)為例,若血壓穩定則暫無立即危險,若血壓不穩定則同時判斷心跳,若心跳每分鐘小於150下,代表三項生理訊號中僅有兩項不正常,可就近找附近醫院就診,反之,若心跳每分鐘大於150下,則駕駛可能是心臟病發,屬高度危險。再例如,若偵測到異常的是心跳,則同時判斷呼吸訊號是否正常,若呼吸訊號正常則暫無立即危險,若呼吸訊號也異常,則同時判斷血壓訊號是否穩定,若血壓穩定則代表三項生理訊號中僅有兩項不正常,可就近找附近醫院就診,反之,若血壓不穩定,則代表駕駛可能是心臟病發,屬高度危險。當判斷駕駛者心臟病發時,本發明之系統更可與車輛系統連結,立即煞車、閃燈或其他緊急狀態顯示方式,以避免在駕駛者失去意識的狀態下繼續踩油門而發生車禍。
由於某些狀況下可能導致訊號異常,因此藉由偵測三種生理訊號,可將這些狀況排除,避免誤判。例如講話、大笑可能導致呼吸異常, 而被突然出現的行人或貓狗驚嚇則會使心跳加快、血壓上升。
突發性疾病可能藉由血壓、心跳、呼吸頻率等任一種生理訊號異常判斷出,但若是心臟病發時通常會有兩種以上生理訊號異常,且心跳頻率異常為必然,伴隨無法呼吸(呼吸頻率異常)或血壓下降,因此若要判斷駕駛者是否為突發性心臟病,則必須三種生理訊號整體同時判斷。
由於不同人的呼吸頻率、心律和血壓皆不盡相同,因此依據駕駛者生理訊號所建立的呼吸頻率模型、心律模型及血壓模型也會有所差異,而這些個人化模型可提供駕駛者就醫時極大的參考作用。
綜上所述,本發明所提供之駕駛者突發性心臟病判斷系統係藉由同時擷取心律訊號、血壓訊號及呼吸頻率訊號,利用類神經網路訓練建立專屬於駕駛者的個人化模型,利用三種生理訊號同時擷取、分別判斷的方式,除了可判斷駕駛者是否突發性心臟病,更可增加預測突發性心臟病的準確率,當駕駛者就醫時這些個人化模型更可供醫生參考。
唯以上所述者,僅為本發明之較佳實施例而已,並非用來限定本發明實施之範圍。故即凡依本發明申請範圍所述之特徵及精神所為之均等變化或修飾,均應包括於本發明之申請專利範圍內。
10‧‧‧駕駛者突發性心臟病判斷系統
12‧‧‧感測器
122‧‧‧呼吸頻率感測器
124‧‧‧心律感測器
126‧‧‧血壓感測器
14‧‧‧監控系統
142‧‧‧處理器
144‧‧‧記憶體
150‧‧‧個人化模型
152‧‧‧呼吸頻率模型
154‧‧‧心律模型
156‧‧‧血壓模型

Claims (5)

  1. 一種駕駛者突發性心臟病判斷系統,其係判斷一車輛之一駕駛人是否有突發性心臟病,包括:複數感測器,持續擷取該駕駛者之複數生理訊號,該等生理訊號包括一呼吸頻率訊號、一心律訊號及一血壓訊號;以及一監控系統,包括一處理器及一記憶體,該處理器依據該等生理訊號分別訓練出包括一呼吸頻率模型、一心律模型及一血壓模型之複數個人化模型並儲存於該記憶體中,且依據該呼吸頻率模型、該心律模型及該血壓模型設定出該等生理訊號個別之一閥值,該處理器判斷是否有任一種生理訊號超出該閥值,若該等生理訊號中有至少一種超出該閥值,則依據超出該等閥值之生理訊號之種類數,判斷該駕駛者之狀態危險程度,並發出警示。
  2. 如請求項1所述之駕駛者突發性心臟病判斷系統,其中該超出該等閥值之生理訊號之種類數為一時,該駕駛者之狀態危險程度為低,該超出該等閥值之生理訊號之種類數為二時,該駕駛者之狀態危險程度為中,該超出該等閥值之生理訊號之種類數為三時,該駕駛者之狀態危險程度為高。
  3. 如請求項2所述之駕駛者突發性心臟病判斷系統,其中該呼吸頻率訊號之閥值為每分鐘大於平均值的兩倍。
  4. 如請求項2所述之駕駛者突發性心臟病判斷系統,其中該心律訊號之閥值為每分鐘大於150下。
  5. 如請求項2所述之駕駛者突發性心臟病判斷系統,其中該血壓訊號之閥值為收縮壓小於90mmHg。
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