System, device, and method for vehicle post-crash support

1. A system for providing medical information of at least one occupant in a vehicle cabin, the system comprising:

a sensing module comprising:

an illuminator comprising one or more illumination sources configured to project light in a predefined light pattern on the vehicle cabin;

at least one image sensor configured to capture sensory data of the vehicle cabin, wherein said sensory data comprises a sequence of two dimensional (2D) images and three dimensional (3D) images of the vehicle cabin, wherein at least one of the 2D images comprises reflections of said predefined light pattern from the one or more occupants in the cabin; and

a control module comprising at least one processor, said processor is configured to:

receive said sensory data from said image sensor;

detect an imminent crash of the vehicle, wherein said sensory data is captured prior to said detection of imminent crash, during said crash and following said crash; and

analyze said sensory data including the sequence of 2D images and 3D images using one or more analysis methods to provide the medical information of said at least one occupant; and

assess a medical status of said at least one vehicle occupant following the crash based on said analyzed sensory data.

2. The system of claim 1 , wherein said light source comprises one or more optical elements for splitting a single light beam generated by said light source, said one or more optical elements are selected from the group consisting of:

diffractive optical element (DOE); split mirrors; and diffuser.

3. The system of claim 1 , wherein said sensing module comprises a depth sensor.

4. The system of claim 3 , wherein said depth sensor is configured to capture depth data by projecting a light pattern onto the vehicle cabin and wherein the at least one processor is configured to analyze the location of known light pattern elements in said depth data.

5. The system of claim 4 wherein the pose of said at least one occupant is estimated by analyzing the depth data using said computer vision methods.

6. The system of claim 1 , wherein the sensing module comprises a micro-vibration sensor.

7. The system of claim 6 , wherein the micro-vibration sensor is configured to:

project light onto the vehicle cabin scene;

capture a plurality of images, wherein each image of said plurality of images comprises reflected diffused light elements; and

wherein the processor is configured to:

receive the captured images; and

analyze one or more temporal changes in the speckle pattern of at least one of the plurality of reflected diffused light elements in at least some consecutive images of the plurality of images to yield micro-vibration data.

8. The system of claim 1 , wherein the sensing module comprises a combination of the image sensor and at least one sensor selected from a group consisting of:

a depth sensor and a micro-vibration sensor.

9. The system of claim 1 , wherein the at least one processor is further configured to classify the at least one vehicle occupant using said computer vision methods by visually analyzing at least one 2D or 3D image of the sequence of images captured by the at least one image sensor.

10. The system of claim 1 , wherein the detection of an imminent crash is performed by one or more of:

vehicle impact sensor; hectic movement detection sensor; and external sensory system.

11. A system for estimating the medical state of one or more occupants in a vehicle cabin following an accident of the vehicle, the system comprising;

a sensing module comprising:

an illuminator comprising one or more illumination sources configured to project light in a predefined light pattern on the vehicle cabin;

at least one image sensor configured to capture sensory data prior to, during and following a crash of said vehicle, said sensory data comprising a sequence of two dimensional (2D) images and three dimensional (3D) images of the vehicle cabin wherein at least one of the 2D images comprise reflections of said predefined light pattern from the one or more occupants in the cabin;

a control module comprising:

a memory module; and

at least one processor, said at least one processor is configured to:

receive said captured sensory data from the sensing module;

receive an impact detection signal of an imminent crash of the vehicle;

store the received sensory data, captured prior to receiving said impact detection signal, in said memory module;

analyze said received sensory data including the sequence of 2D images and 3D images using computer vision or machine learning algorithm to yield pre-crash assessment data comprising an identification of the one or more occupant's state prior to the crash;

receive sensory data captured during said crash from the sensing module;

analyze the received sensory data including the sequence of 2D images and 3D images captured during said crash to yield during-crash assessment data comprising body trajectories of the one or more occupants; and

provide medical information of said one or more occupants following the crash based on said during-crash assessment data and pre-crash assessment data.

12. The system of claim 11 wherein said at least one processor is further configured to:

receive sensory data captured following the crash; and

analyze the received sensory data captured following the crash data using computer vision or machine learning algorithm to yield one or more of post-crash assessment data of said one or more occupants.

13. The system of claim 12 wherein said post-crash assessment data comprises one or more of: heartbeat; respiration rate; body pose; body motion; visible wounds.

14. The system of claim 12 wherein said processor is further configured to combine said post-crash assessment data with said during crash assessment data and said pre-crash assessment data to yield said medical information of said one or more occupants following the crash.

15. The system of claim 13 wherein the heartbeat or respiration rate are identified by:

analyzing one or more changes in one or more speckle patterns of at least one of the reflections of said predefined light pattern in at least some consecutive images of the plurality of images; and

identifying the vibrations of the one or more occupants based on said speckle pattern analysis.

16. The system of claim 11 , wherein said one or more of the body pose, body motion, and visible wounds are detected by analyzing the sequence of 2D images or 3D images of the vehicle cabin.