SYSTEM AND METHOD TO DETECT ALERTNESS OF MACHINE OPERATOR

• US 20170231546A1
• Filed: 05/01/2017
• Published: 08/17/2017
• Est. Priority Date: 03/18/2014
• Status: Active Grant

• Current Assignee: J. Kimo Arbas
• Original Assignee: J. Kimo Arbas
• Inventors: Arbas, J. Kimo
• Granted Patent: US 10,383,563 B2
• Time in Patent Office: Days
• CPC Class Codes: A61B 2560/0242 adapted to measure environmental factors, e.g. temperature, pollution
• CPC Class Codes: A61B 2562/0219 Inertial sensors, e.g. accelerometers, gyroscopes, tilt switches
• CPC Class Codes: A61B 5/0205 Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
• CPC Class Codes: A61B 5/024 Detecting, measuring or recording pulse rate or heart rate A61B5/0205, A61B5/021 take precedence
• CPC Class Codes: A61B 5/082 Evaluation by breath analysis, e.g. determination of the chemical composition of exhaled breath A61B5/083, A61B5/091 take precedence
• CPC Class Codes: A61B 5/11 Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb for measuring pulse A61B5/02 ;A61B5/1038 takes precedence; motion detection to correct for motion artifacts in physiological signals A61B5/721
• CPC Class Codes: A61B 5/165 Evaluating the state of mind, e.g. depression, anxiety
• CPC Class Codes: A61B 5/18 for vehicle drivers or machine operators
• CPC Class Codes: A61B 5/369 Electroencephalography [EEG] devices for psychotechnics A61B5/16
• CPC Class Codes: A61B 5/389 Electromyography [EMG]
• CPC Class Codes: A61B 5/4806 Sleep evaluation A61B5/4821 takes precedence; devices for inducing sleep A61M21/02
• CPC Class Codes: A61B 5/4809 Sleep detection, i.e. determining whether a subject is asleep or not
• CPC Class Codes: A61B 5/4845 Toxicology, e.g. by detection of alcohol, drug or toxic products A61B5/4848 takes precedence
• CPC Class Codes: A61B 5/6803 Head-worn items, e.g. helmets, masks, headphones or goggles
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: A61B 5/7405 using sound
• CPC Class Codes: A61B 5/742 using visual displays A61B5/339 takes precedence
• CPC Class Codes: A61B 5/7455 characterised by tactile indication, e.g. vibration or electrical stimulation
• CPC Class Codes: A61B 5/746 Alarms related to a physiological condition, e.g. details of setting alarm thresholds or avoiding false alarms alarms per se G08B

Abstract

A system and method relate to receiving, by a processing device, at least one stream of data captured by at least one sensor monitoring a human subject, wherein the at least one stream of data comprises sensor measurements, comparing the sensor measurements to at least one model of a mental state to estimate the mental state of the human subject, determining whether to trigger an alarm based on the estimated mental state, and in response to determining to trigger the alarm, generating an instruction to trigger the alarm.

Claims

1-20. -20. (canceled)

21. A method comprising:

receiving, by a processing device, at least one stream of data captured by at least one sensor monitoring a human subject, wherein the at least one stream of data comprises sensor measurements;

comparing the sensor measurements to at a threshold to determine whether the human subject is in at least one of a rage state or a depression state;

determining whether to trigger an alarm based on the comparison; and

in response to determining to trigger the alarm, generating an instruction to trigger the alarm.

22. The method of claim 21, wherein the at least one sensor comprises at least one of a brain wave monitor, a sleep monitor, a camera, a breath analyzer, a health monitor, an accelerometer, or an environmental monitor.

23. The method of claim 22, wherein the brain wave monitor comprises an electroencephalography (EEG) monitor, and wherein the EEG monitor is to measure voltage potentials on scalp of the human subject.

24. The method of claim 22, wherein the sleep monitor comprises an electromyography (EMG) monitor, and wherein the EMG monitor is to measure an electrical activity caused by eye blinks by the human subject.

25. The method of claim 22, wherein the accelerometer is to measure an acceleration of a head nod by the human subject.

26. The method of claim 22, wherein the health monitor comprises a heart rate monitor, and wherein the heart rate monitor is to measure a heart rate of the human subject.

27. The method of claim 21, wherein the human subject is a truck driver driving a truck.

28. The method of claim 21, further comprising:

transmitting the instruction to trigger the alarm to an alarm receiver, wherein, in response to receiving the instruction, the alarm receiver is to generate the alarm.

29. The method of claim 28, wherein the alarm comprises at least one of a sound alarm, a flash light, a vibration, or text.

30. The method of claim 21, wherein the at least one model is built using machine learning.

31. A non-transitory machine-readable storage medium storing instructions which, when executed, cause a processing device to:

receive, by the processing device, at least one stream of data captured by at least one sensor monitoring a human subject, wherein the at least one stream of data comprises sensor measurements;

comparing the sensor measurements to at a threshold to determine whether the human subject is in at least one of a rage state or a depression state based;

determining whether to trigger an alarm based on the comparison; and

in response to determining to trigger the alarm, generating an instruction to trigger the alarm.

32. A device comprising:

an electroencephalography (EEG) sensor to detect a brain wave data of a human subject;

a heart rate sensor to detect a heart rate data of the human subject;

an electromyography (EMG) sensor to detect an electrical activity data relating to eye blinks by the human subject;

an accelerometer to detect an acceleration data of the human subject; and

a warning device to generate an alarm in response to determining the human subject is in at least one of a rage state or a depression state based on at least one of the brain wave data, the heart rate data, the electrical activity data, or the acceleration data and associated thresholds.

33. The device of claim 32, wherein the wearable device is a headband mountable on a head of the human subject.

34. The device of claim 33, wherein the human subject is a machine operator operating a machine.

35. The device of claim 32, wherein the mental state further comprises comprises one of a drowsiness state, an intoxication state, or a meditative state.

36. The device of claim 32, further comprising:

communication device to transmit the at least one of the brain wave data, the heart rate data, the electrical activity data, or the acceleration data to a processing device, wherein the communication device receives an indication indicating the occurrence of the mental state.

37. The device of claim 36, wherein in response to receiving the indication indicating the occurrence of the mental state, the communication device is to transmit an instruction to the warning device.

38. The device of claim 37, wherein in response to receiving the instruction from the communication device, the warning device is to generate the alarm.

39. The device of claim 38, wherein the alarm comprises at least one of a sound alarm, a flash light, or a vibration.