DROWSINESS ONSET DETECTION

DROWSINESS ONSET DETECTION

Drowsiness onset detection implementations are presented that predict when a person transitions from a state of wakefulness to a state of drowsiness based on heart rate information. Appropriate action is then taken to stimulate the person to a state of wakefulness or notify other people of their sta...

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Bibliographische Detailangaben
Hauptverfasser: AVINASH GUJJAR, AADHARSH KANNAN, GOVIND RAMASWAMY, SRINIVAS BHASKAR
Format: Patent
Sprache:eng
Schlagworte:
ARRANGEMENT OR MOUNTING OF PLURAL DIVERSE PRIME-MOVERS INVEHICLES
ARRANGEMENT OR MOUNTING OF PROPULSION UNITS OR OFTRANSMISSIONS IN VEHICLES
ARRANGEMENTS IN CONNECTION WITH COOLING, AIR INTAKE, GASEXHAUST OR FUEL SUPPLY OF PROPULSION UNITS, IN VEHICLES
AUXILIARY DRIVES FOR VEHICLES
DIAGNOSIS
HUMAN NECESSITIES
HYGIENE
IDENTIFICATION
INSTRUMENTATION OR DASHBOARDS FOR VEHICLES
MEDICAL OR VETERINARY SCIENCE
PERFORMING OPERATIONS
SURGERY
TRANSPORTING
VEHICLES IN GENERAL
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Beschreibung
Zusammenfassung:Drowsiness onset detection implementations are presented that predict when a person transitions from a state of wakefulness to a state of drowsiness based on heart rate information. Appropriate action is then taken to stimulate the person to a state of wakefulness or notify other people of their state (with respect to drowsiness/alertness). This generally involves capturing a person's heart rate information over time using one or more heart rate (HR) sensors (102, 302) and then computing a heart-rate variability (HRV) signal (122, 328) from the captured heart rate information. The HRV signal is analyzed to extract features that are indicative of an individual's transition from a wakeful state to a drowsy state. The extracted features are input (206) into an artificial neural net (ANN) that has been trained using the same features to identify when an individual makes the aforementioned transition to drowsiness. Whenever an onset (208) of drowsiness is detected, a warning (210) is initiated. (Figure 2)