Riheng Wu from Olathe, KS, age 51

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Drowsy Driver Detection System
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US Patent:

20120169503, Jul 5, 2012
Filed:

Jun 23, 2010
Appl. No.:

13/379763
Inventors:

Riheng Wu - Carthage MO, US
Jason Turner - Joplin MO, US
Caleb Browning - Carthage MO, US
Travis Brummett - Carthage MO, US
International Classification:

G08B 23/00
US Classification:

340575
Abstract:

A method of detecting impairment of a driver of a vehicle. The method includes sensing, using a sensor, a position of the driver's head at a plurality of time points; determining, using a microprocessor, changes in the position of the driver's head between the plurality of time points; evaluating, using a microprocessor, whether the changes in the position of the driver's head between the plurality of time points exhibit at least one of a periodic and a quasi-periodic pattern; determining whether the driver is impaired based on the pattern of the changes in the position of the driver' s head; and if the driver is impaired, alerting the driver using an alarm.

Non-Contact Detection Of Physiological Data Using Stochastic Resonance
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US Patent:

20110196243, Aug 11, 2011
Filed:

Feb 5, 2010
Appl. No.:

12/701402
Inventors:

Riheng Wu - Carthage MO, US
Jason Turner - Joplin MO, US
Travis Brummett - Carthage MO, US
Caleb Browning - Carthage MO, US
International Classification:

A61B 5/0205
US Classification:

600484
Abstract:

Obtaining physiological data from a living being using non-contact sensors is disclosed. The non-contact sensors are disposed within, for example, a vehicle seat or bed. Signals detected by the non-contacting sensors, which include both physiological signals and ambient noise, are transmitted to a processing device which is positioned nearby; such as in the vehicle seat or bed. The processing device employs a stochastic resonance function whereby a signal-to-noise ratio of the physiological signals is improved. A wavelet multi-scale decomposition function and an adaptive threshold function are then used to identify the physiological signals and distinguish them from the ambient noise. The resulting signals are measured and then made available at an output of the processing device for transmission to and use by a human-machine interface.

Riheng Wu