Robotic systems for navigation of luminal networks that compensate for physiological noise

1. A method of navigating a luminal network of a patient, the method comprising:

generating an electromagnetic (EM) field;

accessing a preoperative model representative of the luminal network;

accessing a registration mapping between a coordinate frame of the EM field and a coordinate frame of the preoperative model;

receiving an EM data signal from a set of one or more EM sensors at a distal end of a steerable instrument within the EM field;

calculating a frequency of respiration of the patient based on a respiration data signal from a set of respiration sensors configured to be placed on the patient;

applying a predictive filter to the EM data signal and the respiration data signal, the predictive filter configured to predict respiration motion due to the respiration;

removing components of the EM data signal attributable to the predicted respiration motion;

calculating, based on the EM data signal with the components removed, at least one position of the set of EM sensors within the EM field;

determining a position of the distal end of the steerable instrument relative to the preoperative model via transforming the at least one position of the set of EM sensors within the EM field using the registration mapping;

determining at least one position of the set of EM sensors relative to the set of respiration sensors;

calculating at least one positional displacement of the set of EM sensors between inspiration and expiration phases of the respiration of the patient based on (i) the determined at least one position of the set of EM sensors relative to the set of respiration sensors and (ii) at least one magnitude of displacement of the set of respiration sensors between the inspiration and expiration phases; and

determining a position of the distal end of the steerable instrument relative to the preoperative model based on the calculated at least one positional displacement of the set of EM sensors between the inspiration and expiration phases.

2. The method of claim 1 , further comprising:

transforming one or more data signals from the set of respiration sensors into a frequency domain representation of the one or more data signals; and

identifying the frequency of respiration from the frequency domain representation of the one or more data signals.

3. The method of claim 1 , wherein the set of respiration sensors comprises a first additional EM sensor positioned, in use, at a first position on a body surface of the patient and a second additional EM sensor positioned, in use, at a second position of the body surface, wherein the second position is spaced apart from the first position such that a first magnitude of displacement of the first additional EM sensor is greater than a second magnitude of displacement of the second additional EM sensor between the inspiration and expiration phases.

4. The method of claim 3 , further comprising:

determining a relative positioning of the set of EM sensors with respect to the first and second additional EM sensors; and

interpolating between the first and second magnitudes of displacement based on the determined relative positioning of the set of EM sensors, wherein the calculation of the positional displacement of the set of EM sensors between the inspiration and the expiration phases is based on the interpolated magnitude.

5. The method of claim 3 , further comprising:

estimating a movement vector for at least a portion of the preoperative model based on the at least one magnitude of displacement;

translating the preoperative model within the coordinate frame of the EM field based on the estimated movement vector; and

determining the position of the distal end of the steerable instrument based on the translated preoperative model.

6. The method of claim 5 , wherein the translating the preoperative model within the coordinate frame of the EM field comprises:

moving a first portion of the preoperative model to first new coordinates based on the first magnitude of displacement; and

moving a second portion of the preoperative model to second new coordinates based on the second magnitude of displacement.

7. The method of claim 1 , further comprising:

generating a graphical representation of the position of the distal end of the steerable instrument relative to the preoperative model; and

rendering the generated graphical representation on a display.

8. A system configured to navigate a luminal network of a patient, the system comprising:

a field generator configured to generate an electromagnetic (EM) field;

a set of one or more EM sensors at a distal end of a steerable instrument;

a set of one or more respiration sensors configured to be placed on the patient;

at least one computer-readable memory having stored thereon executable instructions; and

one or more processors in communication with the at least one computer-readable memory and configured to execute the instructions to cause the system to at least:

access a preoperative model representative of the luminal network;

access a registration mapping between a coordinate frame of the EM field and a coordinate frame of the preoperative model;

receive an EM data signal from the set of EM sensors within the EM field;

calculate a frequency of respiration of the patient based on a respiration data signal from the set of respiration sensors;

according to a first process:

apply a predictive filter configured to predict respiration motion due to the respiration to the EM data signal and the respiration data signal;

remove components of the EM data signal attributable to the predicted respiration motion;

calculate, based on the EM data signal with the components removed, at least one position of the set of EM sensors within the EM field; and

determine a position of the distal end of the steerable instrument relative to the preoperative model via transforming the at least one position of the set of EM sensors within the EM field using the registration mapping; and

according to a second process:

calculate at least one positional displacement of the set of EM sensors between inspiration and expiration phases of the respiration of the patient based on (i) at least one position of the set of EM sensors relative to the set of respiration sensors and (ii) at least one magnitude of displacement of the set of respiration sensors between the inspiration and expiration phases; and

determine the position of the distal end of the steerable instrument relative to the preoperative model based on the calculated at least one positional displacement of the set of EM sensors between the inspiration and expiration phases.

9. The system of claim 8 , wherein the one or more processors are configured to execute the instructions to cause the system to at least:

transform one or more data signals from the set of respiration sensors into a frequency domain representation of the one or more data signals; and

identify the frequency of respiration from the frequency domain representation of the one or more data signals.

10. The system of claim 8 , wherein the set of respiration sensors comprises a first additional EM sensor positioned, in use, at a first position on a body surface of the patient and a second additional EM sensor positioned, in use, at a second position of the body surface, wherein the second position is spaced apart from the first position such that a first magnitude of displacement of the first additional EM sensor is greater than a second magnitude of displacement of the second additional EM sensor between the inspiration and expiration phases.

11. The system of claim 10 , wherein the one or more processors are configured to execute the instructions to cause the system to at least:

determine a relative positioning of the set of EM sensors with respect to the first and second additional EM sensors; and

interpolate between the first and second magnitudes of displacement based on the determined relative positioning of the set of EM sensors, wherein the calculation of the positional displacement of the set of EM sensors between the inspiration and the expiration phases is based on the interpolated magnitude.

12. The system of claim 10 , wherein the one or more processors are configured to execute the instructions to cause the system to at least:

estimate a movement vector for at least a portion of the preoperative model based on the at least one magnitude of displacement;

translate the preoperative model within the coordinate frame of the EM field based on the estimated movement vector; and

determine the position of the distal end of the steerable instrument based on the translated preoperative model.

13. The system of claim 12 , wherein, to translate the preoperative model within the coordinate frame of the EM field, the one or more processors are configured to execute the instructions to cause the system to at least:

move a first portion of the preoperative model to first new coordinates based on the first magnitude of displacement; and

move a second portion of the preoperative model to second new coordinates based on the second magnitude of displacement.

14. The system of claim 8 , further comprising a display, wherein the one or more processors are configured to execute the instructions to cause the system to at least:

activate a safety mode for navigation based on one or more of the frequency of respiration or one or more safety zones; and

render information associated with the safety mode on the display.

15. A non-transitory computer readable storage medium having stored thereon instructions that, when executed, cause at least one computing device to at least:

receive a first data signal from an electromagnetic (EM) sensor on an instrument inserted, in use, in a tissue site of a patient within an EM field;

access a registration mapping between coordinate frames of the EM field and the tissue site;

receive a second data signal from at least one additional sensor configured to detect movement of the tissue site, the at least one additional sensor configured to be placed on the patient;

calculate, based on the first data signal, a position of the EM sensor within the EM field disposed around the tissue site;

calculate, based on the second data signal, a frequency of cyclic movement of the tissue site;

according to a first process;

apply a predictive filter configured to predict respiration motion due to respiration of the patient to the first data signal and the second data signal;

remove components of the first data signal attributable to the predicted respiration motion;

calculate, based on the first data signal with the components removed, a position of the EM sensor within the EM field; and

determine a position of the instrument relative to the tissue site via transforming the position of the EM sensor within the EM field using the registration mapping; and

according to a second process:

calculate a positional displacement of the EM sensor between inspiration and expiration phases of the respiration of the patient based on (i) a position of the EM sensor relative to the at least one additional sensor and (ii) at least one magnitude of displacement of the at least one additional sensor between the inspiration and expiration phases; and

determine the position of the instrument based on the calculated positional displacement of the EM sensor between the inspiration and expiration phases.

16. The non-transitory computer readable storage medium of claim 15 , wherein the instructions, when executed, cause the at least one computing device to:

transform the second data signal from the at least one additional sensor into a frequency domain representation; and

identify the frequency of the cyclic movement from the frequency domain representation.

17. The non-transitory computer readable storage medium of claim 15 , wherein the at least one additional sensor comprises a first additional EM sensor positioned, in use, at a first position on the patient and a second additional EM sensor positioned, in use, at a second position of the patient, wherein the second position is spaced apart from the first position such that a first magnitude of displacement of the first additional EM sensor is greater than a second magnitude of displacement of the second additional EM sensor between the inspiration and expiration phases, and wherein the instructions, when executed, cause the at least one computing device to:

determine a position of the EM sensor relative to the first and second additional EM sensors; and

interpolate between the first and second magnitudes of displacement based on the determined position of the EM sensor relative to the first and second additional EM sensors, wherein the calculation of the positional displacement of the EM sensor between the inspiration and the expiration phases is based on the interpolated magnitude.

18. The non-transitory computer readable storage medium of claim 17 , wherein the instructions, when executed, cause the at least one computing device to:

access data representing a model representing a topography of the tissue site,

where the registration mapping is further between the coordinate frame of the EM field and a coordinate frame of the model,

wherein determining the position of the instrument is based on the registration mapping, the frequency, and the position of the EM sensor within the EM field.

19. The non-transitory computer readable storage medium of claim 18 , wherein the tissue site comprises respiratory airways, and wherein the instructions, when executed, cause the at least one computing device to:

estimate a movement vector for at least a portion of the model based on the at least one magnitude of displacement;

translate the model within the coordinate frame of the EM field based on the estimated movement vector; and

determine the position of the instrument based on the translated model.

20. The non-transitory computer readable storage medium of claim 19 , wherein, to translate the model within the coordinate frame, the instructions, when executed, cause the at least one computing device to:

move a first portion of the model to first new coordinates based on the first magnitude of displacement; and

move a second portion of the model to second new coordinates based on the second magnitude of displacement.