Method and system for detecting pilot incompetence based on vital signs and head mounted sensors

• US 10,568,558 B2
• Filed: 08/27/2018
• Issued: 02/25/2020
• Est. Priority Date: 10/08/2013
• Status: Active Grant

• Current Assignee: Elbit Systems Limited
• Original Assignee: Elbit Systems Limited
• Inventors: Kranz, Yaron, Oron, Zvi, Ophir, Yoav
• Primary Examiner(s): Swarthout, Brent
• Application Number:
  US16/112,831
• Publication Number:
  US 20190008438A1
• Time in Patent Office: 547 Days
• Field of Search: None
• CPC Class Codes: A61B 2503/22 Motor vehicles operators, e.g. drivers, pilots, captains
• CPC Class Codes: A61B 2560/0242 adapted to measure environmental factors, e.g. temperature, pollution
• CPC Class Codes: A61B 2560/0257 using atmospheric pressure
• CPC Class Codes: A61B 2560/0475 Special features of memory means, e.g. removable memory cards
• CPC Class Codes: A61B 3/113 for determining or recording eye movement
• CPC Class Codes: A61B 5/0059 using light, e.g. diagnosis by transillumination, diascopy, fluorescence A61B5/0093, A61B5/1455, A61B5/02416 and A61B5/0261 take precedence
• 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 5/02416 using photoplethysmograph signals, e.g. generated by infrared radiation A61B5/14552 takes precedence
• CPC Class Codes: A61B 5/02438 with portable devices, e.g. worn by the patient
• CPC Class Codes: A61B 5/026 Measuring blood flow A61B3/1233, A61B3/1241 take precedence
• CPC Class Codes: A61B 5/1103 Detecting eye twinkling
• CPC Class Codes: A61B 5/1114 Tracking parts of the body
• CPC Class Codes: A61B 5/14542 for measuring blood gases A61B5/14551 takes precedence
• CPC Class Codes: A61B 5/163 by tracking eye movement, gaze, or pupil change
• 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 5/4519 Muscles A61B5/389, A61B5/224 take precedence
• CPC Class Codes: A61B 5/6803 Head-worn items, e.g. helmets, masks, headphones or goggles
• CPC Class Codes: A61B 5/7275 Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
• CPC Class Codes: A61B 5/7445 Display arrangements, e.g. multiple display units
• 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
• CPC Class Codes: B60W 2040/0827 : due to sleepiness
• CPC Class Codes: B60W 2040/0872 : Driver physiology
• CPC Class Codes: B60W 40/09 : Driving style or behaviour
• CPC Class Codes: G08B 21/06 : indicating a condition of sleep, e.g. anti-dozing alarms
• CPC Class Codes: G08B 29/188 : Data fusion; cooperative systems, e.g. voting among different detectors
• CPC Class Codes: G16H 50/30 : for calculating health indices; for individual health risk assessment
• CPC Class Codes: G16Z 99/00 : Subject matter not provided for in other main groups of this subclass

Abstract

A system for monitoring a pilot'"'"'s health is provided herein. The system may include: a head mounted device mountable to a head of a pilot; at least one vital signs sensor couplable to a body portion of said pilot and configured to obtain vital signs data associated with said pilot; at least one head sensor configured to obtain head-related data associated with the head of said pilot; and a computer processor configured to receive the vital signs data and the head-related data as an input and generate as an output, an indication of pilot incompetence, based on predefined criteria.

Claims

1. A system comprising:

a head mounted device mountable to a head of a pilot;

at least one vital signs sensor couplable to a body part of said pilot and configured to repeatedly obtain in real time, vital signs data associated with said pilot;

at least one accelerometer embedded within said head mounted device and configured to repeatedly obtain in real time, head-related data associated with position and orientation of the head of said pilot; and

a computer processor configured to;

simultaneously receive the vital signs data and the head-related data as an input to a decision function; and

generate, as an output of the decision function, a prediction of pilot incompetence, before the pilot incompetence has occurred, based on said input and predefined criteria,

wherein the at least one vital signs sensor comprises at least one Dynamic Light Scattering (DLS) sensor and at least one reflective photoplethysmograph (PPG) sensor.

2. The system according to claim 1, wherein the vital signs data is indicative of at least one:

heartbeat rate, saturation of peripheral oxygen, perfusion level, and Electroencephalogram (EEG), associated with said pilot.

3. The system according to claim 1, wherein the head-related data further comprises at least one of:

head inertial data and muscle tone level of a neck of the pilot.

4. The system according to claim 1, wherein the input further comprises real-time platform data comprising at least one of:

cockpit pressure, platform altitude, platform attitude, and platform accelerations.

5. The system according to claim 1, further comprising a database configured to store pilot-specific data indicative of historical vital signs and head behavior of the pilot vis à

vis platform data recorded over previous flights, and wherein the computer processor is further configured to receive as an input said pilot-specific data and generate said prediction further based on said pilot-specific data.

6. The system according to claim 1, wherein the computer processor further receives as an input G-affected flights history of said pilot from a database, and further generates said pilot incompetence prediction based on said G-affected flights history.

7. The system according to claim 5, wherein the computer processor is further configured to update the database based on data obtained in real time that comprises at least one of:

platform data, head-related data, and vital signs data.

8. The system according to claim 1, wherein the computer processor is further configured to determine an action to be taken based on a type of the detected pilot incompetence.

9. The system according to claim 1, wherein the pilot incompetence comprises at least one of:

Hypoxia, loss of consciousness (LOC), G-force induced pilot incompetence, and drowsiness.

10. The system according to claim 1, wherein the head mounted device comprises a head or helmet mounted display (HMD).

11. A method comprising:

repeatedly obtaining in real time, vital signs data associated with a pilot, via at least one vital signs sensor couplable to a body part of said pilot;

repeatedly obtaining in real time, head-related data associated with position and orientation of a head of said pilot, via at least one accelerometer embedded within a head mounted device mountable to the head of said pilot;

simultaneously receiving the vital signs data and the head-related data as an input to a decision function; and

generating as an output of the decision function, a prediction of pilot incompetence, before the pilot incompetence has occurred, based on said input and predefined criteria,

wherein the at least one vital signs sensor comprises at least one Dynamic Light Scattering (DLS) sensor and at least one reflective photoplethysmograph (PPG) sensor.

12. The method according to claim 11, wherein the vital signs data is indicative of at least:

heartbeat rate, saturation of peripheral oxygen, perfusion level, and Electroencephalogram (EEG), associated with said pilot.

13. The method according to claim 11, wherein the head-related data further comprises at least one of:

head inertial data and muscle tone level of a neck of the pilot.

14. The method according to claim 11, further comprising storing pilot-specific data indicative of historical vital signs and head behavior of the pilot visa vis platform data recorded over previous flights, and further receiving as an input the pilot-specific data and generating said prediction further based on said pilot-specific data.

15. The method according to claim 11, further comprising receiving as an input G-affected flights history of said pilot from a database, and generating said pilot incompetence prediction based on said G-affected flights history.

16. The method according to claim 15, further comprising updating the database based on:

platform data, head-related data, and vital signs data obtained in real time.

17. The method according to claim 11, further comprising determining an action to be taken based on a type of the detected pilot incompetence.

18. The method according to claim 11, wherein the pilot incompetence comprises at least one of:

Hypoxias, loss of consciousness (LOC), G-force induced pilot incompetence, and drowsiness.