TW202041190A - 非接觸式酒駕評判系統及相關方法 - Google Patents
非接觸式酒駕評判系統及相關方法 Download PDFInfo
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Abstract
一種酒駕評判系統,包含一影像擷取模組,用來獲得多張相關於一受測者之影像;一生理參數計算模組,耦接於該影像擷取模組,用來根據該多張相關於一受測者之影像,產生至少一生理參數,其中該至少一生理參數包含一遠程光體積變化描記、一心率、一心律變異、一血氧、一呼吸速率和一血壓中的至少一者;以及一酒精偵測運算單元,耦接於該生理參數計算模組,用來根據該至少一生理參數,產生一酒駕判斷結果,以指示該受測者是否酒駕。
Description
本發明是有關於一種酒駕評判系統及相關方法,尤指一種根據駕駛影像來判斷是否酒駕的影像式酒駕評判系統及相關方法。
飲酒駕車往往造成慘劇,害人害己。如何防範和監督酒後駕車,成為一個亟待解決的問題。習知的酒駕評判方式多是利用呼氣酒測器來進行,受測者須對呼氣酒測器吹氣,以根據氣體中的酒精濃度來估計血液中的酒精濃度。然而,呼氣酒測器乃一次性測試,無法隨時追蹤駕駛在開車途中飲酒的情況。此外,呼氣酒測器的準確率也會受到採集的氣體量所影響。
有鑑於此,如何提供新的酒測評斷系統方法來輔助現有呼氣酒測器不足,並在不接觸使用者的情況下輕鬆快速地檢測是否酒駕,已成為本領域的新興課題。
因此,本發明的目的即在於提供一種影像式酒駕評判系統及相關方法,以在不接觸使用者的情況下輕鬆快速地檢測是否酒駕。
本發明揭露一種酒駕評判系統,包含一影像擷取模組,用來獲得多張相關於一受測者之影像;一生理參數計算模組,耦接於該影像擷取模組,用來根據該多張相關於一受測者之影像,產生至少一生理參數,其中該至少一生理參數包含一遠程光體積變化描記、一心率、一心律變異、一血氧、一呼吸速率和一血壓中的至少一者;以及一酒精偵測運算單元,耦接於該生理參數計算模組,用來根據該至少一生理參數,產生一酒駕判斷結果,以指示該受測者是否酒駕。
本發明揭露一種酒駕評判方法,包含獲得多張相關於一受測者之影像;將該多張相關於一受測者之影像輸入至一生理參數計算單元,以產生至少一生理參數,其中該至少一生理參數包含一遠程光體積變化描記、一心率、一心律變異、一血氧、一呼吸速率和一血壓中的至少一者;以及將該至少一生理參數輸入至一酒精偵測運算單元,以產生一酒駕判斷結果,以指示該受測者是否酒駕。
本發明將受測者的影像轉換為遠程光體積變化描記,以進行心率、心律變異、血氧、呼吸速率、血壓等生理參數之分析,據此判斷受測者是否酒駕。如此一來,在酒駕評判系統的架構下,本發明可以在不接觸使用者的情況下,輕鬆快速地檢測是否酒駕。
第1圖為本發明實施例一酒駕評判系統1的功能方塊圖。酒駕評判系統1包含一影像擷取模組10、一生理參數計算模組11以及一酒精偵測運算單元12。
影像擷取模組10用於持續地拍攝一受測者(例如連續拍攝3~5分鐘),以連續獲得多張相關於受測者之影像以及多張連續的色光影像。影像擷取模組13例如是可提供影像之前置鏡頭,舉例而言包含網路攝影機、筆記型電腦影像頭,但不限於上述模組。
生理參數計算模組11耦接於影像擷取模組10和酒精偵測運算單元12,用來根據多張相關於受測者之影像,產生至少一生理參數到酒精偵測運算單元12。生理參數主要包含但不限於遠程光體積變化描記(Remote PhotoPlethysmoGraphy,簡稱rPPG)、心率(Heart rate,HR)、心律變異(Heart rate variability,HRV)、血氧、呼吸速率、血壓等。
酒精偵測運算單元12耦接於生理參數計算模組11,用來根據至少一生理參數,產生一酒駕判斷結果,以指示受測者是否酒駕。判斷是否酒駕的方法包含但不限於模糊理論與類神經網路演算法(artificial neural network algorithm)等方法。例如,酒精偵測運算單元12可事先根據已知生理參數之特性,使用模糊理論建立一酒駕預測規則,將至少一生理參數輸入到已建立好的酒駕預測規則中,即可得到是否酒駕的判斷結果;亦或事先根據多種已知的學習樣本,預先訓練類神經網路演算法並建立一酒駕預測模型,將至少一生理參數輸入到已訓練好的酒駕預測模型時,即可得到是否酒駕的判斷結果。
生理參數計算模組11包含一光體積變化描記轉換模組110、一心率分析模組112以及一心律變異分析模組114。光體積變化描記轉換模組110耦接於影像擷取模組10,用來將多張相關於受測者之影像轉換為遠程光體積變化描記。遠程光體積變化描記是利用光感測元件吸收光線能量的原理,記錄光線在血管中受血流脈動的變化而偵測出來的訊號,因在皮膚表層就可量測到訊號,所以為一種非侵入式的量測方式,且具有架設容易、使用簡單、價格低廉等優點。
心率分析模組112耦接於光體積變化描記轉換模組110,用來根據遠程光體積變化描記,判斷受測者的心率。第2圖為心電圖與遠程光體積變化描記的示意圖。心電圖的波峰與波峰間的間隔稱之為R-R區間(R-R interval)或心跳節拍間隔(InterBeat Interval,IBI),藉由計算每分鐘的平均R-R區間,即可得到每分鐘的平均心率。平均心率簡稱為心率,可作為衡量受測者是否酒駕的生理參數之一,例如,酒駕駕駛受到酒精作用影響而心跳速率,使其心率參數所對應的範圍與未酒駕駕駛有所差異。遠程光體積變化描記的波峰與波峰間的間隔稱之為P-P區間(Peak-to-Peak interval),藉由計算每分鐘的平均P-P區間,即可得到每分鐘的平均心率。因此,本發明使用遠程光體積變化描記的量測方式來取代傳統心電圖,對駕駛的生理參數進行分析,以在不接觸使用者的情況下評斷使用者的酒醉程度。
心律變異分析模組114耦接於光體積變化描記轉換模組110,用來根據遠程光體積變化描記,判斷受測者的心律變異。於一實施例中,生理參數計算模組11還包含一分析模組,用來根據遠程光體積變化描記,判斷受測者的血氧、呼吸速率和血壓,但不限於此。
於一實施例中,影響心律變異的因素可分為時域(time domain)及頻域(frequency domain)二大類型。例如,影響心律變異的時域指標包含但不限於一正常竇性心搏間期之標準差(standard deviation of all normal to normal intervals,SDNN)、一相鄰值平方和的均方根(root mean square successive differences,RMSSD)以及一相鄰正常心跳間期差值在20毫秒到50毫秒的比例(簡稱P20~P50)。
影響心律變異的頻域指標包含但不限於一低頻(Low Frequency,LF)指標、一高頻(High Frequency,HF)指標以及一低頻/高頻比值(LF/HF)。第3圖為心律變異頻譜圖的示意圖。如第3圖所示,低頻指標為遠程光體積變化描記轉換為頻域時,截取其頻率為0.04~0.15Hz的波形。高頻指標為遠程光體積變化描記轉換為頻域時,截取其頻率為0.15~0.4Hz的波形。低頻/高頻比值用來作為反應交感/副交感神經平衡的指標或代表交感神經調控的指標。時域指標及頻域指標的具體計算方式乃本領域所熟知,於此不贅述。
簡言之,影響心律變異之因素可包含時域指標(SDNN、RMSSD、P20~P50)及頻域指標(LF、HF、LF/HF),酒精偵測運算單元12可根據心率和心律變異相關之指標來評斷受測者是否酒駕,其中心率和心律變異相關之指標可藉由受測者的影像來取得。因此,在酒駕評判系統1的架構下,本發明可以在不接觸使用者的情況下,輕鬆快速地檢測是否酒駕。
舉例而言,酒精偵測運算單元12可根據已知生理參數之特性如低頻之頻域指標(LF)下降時與喝酒成高度相關,但不限於此生理參數以及此特性,酒精偵測運算單元12使用模糊理論並透過至少一生理參數之特性建立一酒駕預測規則,將至少一生理參數輸入到已建立好的酒駕預測規則中,即可得到是否酒駕的判斷結果。
舉例而言,酒精偵測運算單元12可根據已知有無喝酒的學習樣本,預先訓練類神經網路演算法並建立一酒駕預測模型,其中學習樣本包括與喝酒成高度相關之生理參數如心率、心律變異、血氧、呼吸速率和血壓等等但不限於上述之生理參數,酒精偵測運算單元12將至少一生理參數輸入到已訓練好的酒駕預測模型時,即可得到是否酒駕的判斷結果。
上述模糊理論及類神經網路演算法僅止於範例而酒精偵測運算單元12之實作方法並不局限於此作法。
關於酒駕評判系統1的操作方式可歸納為一酒駕評判流程4,如第4圖所示,酒駕評判流程4包含以下步驟。
步驟40:影像擷取模組10獲得多張相關於受測者之影像。
步驟41:生理參數計算模組11將多張相關於受測者之影像轉換為遠程光體積變化描記。
步驟42:生理參數計算模組11根據遠程光體積變化描記,產生至少一生理參數,其中至少一生理參數包含遠程光體積變化描記、心率、心律變異、血氧、呼吸速率、血壓。
步驟43:酒精偵測運算單元12根據至少一生理參數,產生一酒駕判斷結果,以指示受測者是否酒駕。
關於酒駕評判流程40的詳細操作方式可參考第1圖到第3圖的相關說明,於此不贅述。
綜上所述,本發明將受測者的影像轉換為遠程光體積變化描記,以進行心率、心律變異、血氧、呼吸速率、血壓等生理參數之分析,據此判斷受測者是否酒駕。如此一來,在酒駕評判系統的架構下,本發明可以在不接觸使用者的情況下,輕鬆快速地檢測是否酒駕。
以上所述僅為本發明之較佳實施例,凡依本發明申請專利範圍所做之均等變化與修飾,皆應屬本發明之涵蓋範圍。
1:酒駕評判系統
10:影像擷取模組
11:生理參數計算模組
110:光體積變化描記轉換模組
112:心率分析模組
114:心律變異分析模組
12:酒精偵測運算單元
4:酒駕評判流程
40、41、42、43:步驟
第1圖為本發明實施例一酒駕評判系統的功能方塊圖。
第2圖為心電圖與遠程光體積變化描記的示意圖。
第3圖為心律變異頻譜圖的示意圖。
第4圖為本發明實施例一酒駕評判流程的流程圖。
1:酒駕評判系統
10:影像擷取模組
11:生理參數計算模組
110:光體積變化描記轉換模組
112:心率分析模組
114:心律變異分析模組
12:酒精偵測運算單元
Claims (12)
- 一種酒駕評判系統,包含: 一影像擷取模組,用來獲得多張相關於一受測者之影像; 一生理參數計算模組,耦接於該影像擷取模組,用來根據該多張相關於一受測者之影像,產生至少一生理參數,其中該至少一生理參數包含一遠程光體積變化描記、一心率、一心律變異、一血氧、一呼吸速率和一血壓中的至少一者;以及 一酒精偵測運算單元,耦接於該生理參數計算模組,用來根據該至少一生理參數,產生一酒駕判斷結果,以指示該受測者是否酒駕。
- 如請求項1所述的酒駕評判系統,其中該生理參數計算模組包含: 一光體積變化描記轉換模組,耦接於該影像擷取模組,用來將該多張相關於受測者之影像轉換為該遠程光體積變化描記; 一心率分析模組,耦接於該光體積變化描記轉換模組,用來根據該遠程光體積變化描記,判斷該受測者的該心率;以及 一心律變異分析模組,耦接於該光體積變化描記轉換模組,用來根據該遠程光體積變化描記,判斷該受測者的該心律變異。
- 如請求項1所述的酒駕評判系統,其中該心律變異包含至少一時域指標,該至少一時域指標包含一正常竇性心搏間期之標準差、一相鄰值平方和的均方根以及一相鄰正常心跳間期差值在20毫秒到50毫秒的比例。
- 如請求項1所述的酒駕評判系統,其中該心律變異包含至少一頻域指標,該至少一頻域指標包含一低頻指標、一高頻指標以及一低頻/高頻比值。
- 如請求項1所述的酒駕評判系統,其中該酒精偵測運算單元根據生理參數計算模組產生之至少一生理參數之特性,使用模糊理論建立一酒駕預測規則,將至少一生理參數輸入到該酒駕預測規則,以產生該酒駕判斷結果。
- 如請求項1所述的酒駕評判系統,其中該酒精偵測運算單元根據多個學習樣本,預先訓練一類神經網路演算法並建立一酒駕預測模型,將生理參數計算模組產生之至少一生理參數輸入到該酒駕預測模型,以產生該酒駕判斷結果。
- 一種酒駕評判方法,包含: 獲得多張相關於一受測者之影像; 將該多張相關於一受測者之影像輸入至一生理參數計算單元,以產生至少一生理參數,其中該至少一生理參數包含一遠程光體積變化描記、一心率、一心律變異、一血氧、一呼吸速率和一血壓中的至少一者;以及 將該至少一生理參數輸入至一酒精偵測運算單元,以產生一酒駕判斷結果,以指示該受測者是否酒駕。
- 如請求項7所述的酒駕評判方法,其中根據該多張相關於該受測者之影像,產生該至少一生理參數的步驟包含: 將該多張相關於受測者之影像轉換為該遠程光體積變化描記; 根據該遠程光體積變化描記,判斷該受測者的該心率;以及 根據該遠程光體積變化描記,判斷該受測者的該心律變異。
- 如請求項7所述的酒駕評判方法,其中該心律變異包含至少一時域指標,該至少一時域指標包含一正常竇性心搏間期之標準差、一相鄰值平方和的均方根以及一相鄰正常心跳間期差值在20毫秒到50毫秒的比例。
- 如請求項7所述的酒駕評判方法,其中該心律變異包含至少一頻域指標,該至少一頻域指標包含一低頻指標、一高頻指標以及一低頻/高頻比值。
- 如請求項7所述的酒駕評判方法中的酒精偵測運算單元,其中根據生理參數計算單元產生之至少一生理參數,產生該酒駕判斷結果的步驟包含: 根據至少一生理參數之特性,使用模糊理論建立一酒駕預測規則,將該至少一生理參數輸入到該酒駕預測規則,以產生該酒駕判斷結果。
- 如請求項7所述的酒駕評判方法中的酒精偵測運算單元,其中根據生理參數計算單元產生之至少一生理參數,產生該酒駕判斷結果的步驟包含: 根據多個學習樣本,預先訓練一類神經網路演算法來並建立一酒駕預測模型; 將生理參數計算單元產生之至少一生理參數但不限於上述之生理參數輸入到該酒駕預測模型,以產生該酒駕判斷結果。
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