Localization strategies for robotic endoscopic capsules: a review

Figures & data

Figure 1. Examples of magnetic-based localization systems. (a) Scheme and cubic magnetic array of sensors presented by Hu et al. in [21]. (b) Wearable magnetic localization array of sensors presented by Hu et al. in [23]. (c) Multicoils electromagnetic tracking system presented by Plotkin et al. in [25]. (d) Electromagnetic locomotion and sensors array localization system proposed by Turan et al. in [37]. (e) Application scenario of active magnetic manipulation of a capsule endoscope using a permanent magnet mounted at the end-effector of a robot manipulator presented by Taddese et al. in [38]. (f) Modelling principle used by Popek et al. in [45] that use a magnetic field magnitude generated by a rotating permanent magnetic dipole.

Figure 2. Examples of some electromagnetic waves-based localization systems. (a) Design of an RFID localization system composed by reader, tag and computer proposed by Zhang et al. in [63]. (b) Design of a ToA localization system composed by the capsule and the array of sensors, mounted on body surface presented by Pourhomayoun et al. in [68]. (c) Circular arrays and inertial measurement unit for DoA/ToA/TDoA-based endoscopy capsule localization presented by Nafchi et al. in [69]. (d) Overview of the cyber physical system for localization and distance travelled inside the small intestine, presented by Pahlavan et al. in [71]. (e) Illustration of a FCN-VGG for polyp detection presented by Brandao et al. in [75]. (f) Visual geometric odometry of wireless capsule endoscopes aided by artificial neural networks presented by Dimas et al. in [78].

Table A1. Summary table of magnetic field-based localization strategies.

Magnetic field-based localization
Reference(s)	Compatibility with magnetic locomotion [YES/NO]	Update rate	Main components of the localization system	Passive/active components embedded into the device	Test conditions	DoFs	Position Accuracy (PA) Orientation Accuracy (OA)	Notes
Hu et al., 2005 [13]	NO	~137 ms	Circular IPM; #16 3-axis Hall-effect array of sensors	Passive, sensing magnetic field of IPM	Simulations and free-space validation	3D position; 2D orientation (pitch/yaw)	PA: 5.6 mm; and OA: 4.26% unit orientation vector	Linear optimizer
Hu et al., 2005 [16]	NO	<10.6 ms	Circular IPM; #16 3-axis Hall-effect array of sensors	Passive, sensing magnetic field of IPM	Simulations and free-space validation	3D position; 2D orientation (pitch/yaw)	PA: 5.6 mm; and OA: 4.26% unit orientation vector	Linear optimizer
Wang et al. [17]	NO	100–200 ms	Circular IPM; #16 3-axis magneto-resistive array of sensors	Passive, sensing magnetic field of IPM	Simulations and free-space validation (100 mm above the array of sensors)	3D position; 2D orientation (pitch/yaw)	PA: 3.3 mm (max. 10 mm); and OA: 4.5° (max. 5.7°)	Linear optimizer
Hu et al., 2008 [18]	NO	N/A	Circular IPM; #16 3-axis magnetic array of sensors	Passive, sensing magnetic field of IPM	Simulations and free-space validation (240x240 mm^2)	3D position; 2D orientation (pitch/yaw)	PA: 2 mm; OA: 1.6°	2-step localization: rough estimation with linear algorithm and fine estimation with nonlinear optimizer
Yang et al. [19]	NO	t1*: 170 ms; t2**: 630 ms	Rectangular IPM; #16 3-axis magneto-resistive array of sensors	Passive, sensing magnetic field of IPM	Simulations	3D position; 3D orientation	PA: 3.9 mm* and 0.59 mm**; OA: 5.06°* and 0.66°**	Particle swarm optimizer (PSO)
Hu et al. [21]	NO	~100 ms	Rectangular IPM; cubic magnetic array of sensors composed by #64 HMC1043 3-axis magnetic sensors	Passive, sensing magnetic field of IPM	Simulations and free-space validation (up to 250 mm between the sensor and the capsule)	3D position; 3D orientation	PA: 1.82 mm; OA: 1.62°	Particle swarm optimizer (PSO); improved performance compared to Yang et al. [18]
Song et al. [22]	NO	830 s	Annular IPM; cubic magnetic array of sensors composed by HMC1043 3-axis magnetic sensors	Passive, sensing magnetic field of IPM	Simulations (360 × 370 × 300 mm^3)	3D position; 3D orientation	PA: 0.003 mm; OA: 0.036°	Particle swarm optimizer (PSO) and derived mathematical model (analytical magnetic model)
Hu et al. [23]	NO	N/A	Ring-shape IPM; wearable magnetic array of sensors of #32 3-axis magnetic sensors	Passive, sensing magnetic field of IPM	Simulation and free-space validation	3D position; 3D orientation	PA: 3.82 mm; OA: 2.2°	Another 2 permanent magnets attached to the surface of the human body used as reference sources for body motion compensation
Plotkin et al. [24,25]	NO	20 ms	Sub-miniature induction coil embedded in the capsule as sensor; 8 × 8 of circular coplanar transmitting coils	Active, magnetic field generated by external sources detected by an embedded coil	Free-space validation (200 mm distance between the coaxial receiving and transmitting coils)	3D position; 3D orientation	PA: ~0.75 mm; OA: 0.6°	Maximum operative range of 200 mm; Levenberg-Marquardt algorithm
Nagaoka and Uchiyama [26]	NO	66 ms	Internal coil (secondary) used for FM signal generation; 5 alternating magnetic fields generated outside from solenoid coils (primary)	Active, magnetic field generated by external sources detected by an internal coil	Free-space validation (up to 500 mm to the magnetic field generator)	3D position	PA: 2.8 ± 2.2 mm; OA: 13.4°± 20.9°	Maximum operative range of 500 mm; flat band between 50 and 500kHz obtained through characterization of living tissue
Islam and Fleming [27]	NO	N/A	3-orthogonal rectangular coils inside a capsule and used as tri-axial sensor	Active, magnetic field generated by external sources detected by an internal coil	Free-space validation (up to 257 mm to the magnetic field generator)	3D position; 3D orientation	PA: 6 ± 0.28 mm; OA: 1.11° ± 0.04°	Optimization of coil-shaped sensor volume inside the WCE
Ciuti et al. [29]	YES	50 ms	6-DoFs robotic arm with an EPM; a capsule device with IPMs; IEEE 802.15.4 module; 3-axis accelerometer	Active, localization based on impulse signals obtained from the accelerometer	Ex-vivo experiments	2D position; 2D orientation (pitch/roll)	PA: 30 mm; OA: 6°	For orientation accuracy see STM LIS331DL sensor datasheet
Salerno et al. [31]	YES	27 s	6-DoFs robotic arm with an EPM; capsule device with IPMs and embedded Hall-effect sensors	Active, sensing magnetic field of EPM	Free-space validation (150x150x200 mm^3)	3D position	PA: −3.2 ± 18 mm along X; 5.4 ± 15 mm along Y: and −13 ± 19 mm along Z	Analytical charge-model of external and internal magnetic field
Di Natali et al. [33,34]	YES	7 ms	6-DoFs robotic arm with an EPM; capsule device with IPMs; embedded Hall-effect sensors; 3-axis accelerometer	Active, sensing magnetic field of EPM	Free-space validation (200×200×60-120 mm^3)	3D position; 3D orientation	PA: 6.2 ± 4.4 mm radial; 6.9 ± 3.9 mm axial; 5.4° ± 7.9° azimuth; OA: 0.27° ± 0.17° pitch; 0.34° ± 0.18° yaw; 1.8° ± 1.1° roll	Maximum operating range of 150 mm; pitch and roll angle obtained from accelerometer
Son et al. [36]	YES	5 ms	2D array (8x8) of monoaxial Hall-effect sensors and an omnidirectional electromagnet made of three box-shaped orthogonal coils and a soft iron core	Passive, sensing magnetic field of IPM	Free-space validation (70×70×50 mm^3)	3D position; 2D orientation	PA: 2.1 ± 0.8 mm; OA: 6.7° ± 4.3°	2-step algorithm for reducing the influence of the magnetic locomotion module interference acting with electromagnetic-based fields
Taddese et al. [38]	YES	10 ms	6-DoFs robotic arm with an EPM and an electromagnet fixed around the EPM; a capsule device with IPMs; Hall-effect sensors; 3-axis accelerometer	Active, sensing magnetic field of EPM	Free-space validation (radii of the hemisphere: 150–200 mm, 10 mm step)	3D position; 3D orientation	PA: <5 mm; OA: <6° (static tests along a spiral trajectory)	Hybrid permanent magnet/electromagnet-based model (point-dipole model) with particle filtering method
Abbott et al. [43–47]	YES	3400 ms	6-DoFs robotic arm with a rotational permanent magnet; Maxon motor for controlling the magnetic end-effector; capsule device with an IPM and six mono-axial Hall-effect sensors	Active, sensing magnetic field of EPM	Simulations and free-space validation (spherical shell from 3ρ to 8ρ – ρ: 25.4 mm, i.e., radius of the external spherical magnet)	3D position; 3D orientation	PA: 4.9 ± 2.7 mm; OA: 3.3° ± 1.7°	Dipole-dipole analytical magnetic model with Levenberg-Marquardt method

Table A2. Summary table of electromagnetic field-based localization strategies.

Electromagnetic field-based localization
Reference(s)	Compatibility with magnetic locomotion [YES/NO]	Update rate	Main components of the localization system	Passive/active components embedded into the device	Test conditions	DoFs	Position Accuracy (PA) Orientation Accuracy (OA)	Notes
[53–56]	N/A	N/A	Capsule device with RF transmitting antenna	Active strategy, localization based on transmitted RF signals	Simulations	N/A	N/A	Studies focused on modelling propagation of RF waves through human body
Chandra et al. [57]	N/A	From 3 s to 17 s (cell size)	Capsule device with RF transmitting antenna; 4 receiving antennas on the human body surface	Active strategy, localization based on transmitted RF signals	Simulations and test on different phantoms (realistic phantom* and circular phantom**)	3D position	PA: 9mm*; 3 mm**	The authors proposed to acquire an image of the human body before the procedure in order to obtain electrical properties
Li et al. [58]	N/A	N/A	Capsule device with RF transmitting antenna; 4 receiving antennas on human body surface	Active strategy, localization based on transmitted RF signals	Simulations (400 ×200×350 mm^3)	3D position	PA: range 80–110 mm	Localization based on Cramer Rao Lower Bound (CRLB); used signal propagation model developed by NIST
Ye et al. [60]	N/A	N/A	Capsule device with RF transmitting antenna; array of 32 receiving antennas on human body surface	Active strategy, localization based on transmitted RF signals	Simulations (268×323×312 mm^3)	3D position	PA: range 45–50 mm	Localization based on Cramer Rao Lower Bound (CRLB); frequency depends by dielectric properties of more than 300 parts of a male human body; modification of NIST propagation loss model
Hou et al. [62]	N/A	N/A	Capsule device with RFID tag; 3D array of antennas surrounding human body	Hybrid	Simulations and ex-vivo tests	3D position	PA: 20 mm	No need of signal attenuation model of the human body
Hekimian-Williams et al. [64]	N/A	N/A	3D array of antennas surrounding the human body	Hybrid, based on phase difference of receiving antennas (RFID)	Simulation	3D position	PA: 1.8 mm	Localization based on maximum likelihood estimation algorithm
Wille et al. [65]	N/A	N/A	Capsule device with RF transmitting antenna; 3D array of antennas surrounding the human body	Active, based on phase difference of receiving antennas (RFID)	Simulation (500×900×200 mm^3)	3D position	PA: 1.6 ± 1.2 mm @grid 5 mm, 7.8 ± 5.2 mm @grid 10 mm	Localization based on support Vector Regression Algorithm (VRA)
Liu et al. [67]	N/A	N/A	Capsule device with RF transmitting antenna; 3D array of antennas surrounding the human body	Active, based on Time of Arrival (ToA)	Simulations (597x21.6x203 mm^3)	3D position	N/A	Mathematical model derived by experimental tests and compared with SEMCAD X software simulations
Pourhomayoun et al [68]	N/A	10 s for 16 sensors and 3 s for 4 sensors	Capsule device with RF transmitting antenna; 3D array of antennas surrounding the human body	Active, based on spatial diversity of transmitting antenna	Simulations	3D position	PA: <8.8 mm	Mathematical model derived by extensive Monte Carlo simulations for radiofrequency emission signals
Nafchi et al. [69]	N/A	1 s (sampling time); 1 ms processing time	Capsule device with RF transmitting antenna; 3D array of antennas surrounding the human body; Inertial Measurement Unit (IMU)	Active, based on both DoA and ToA	Simulations	3D position	PA: 10 mm with 16 sensors	Extended Kalman filter for position estimation
Duda et al. [72]	N/A	N/A	Endoscopic device with an integrated camera	Active, based on computer vision	Analysis of acquired images	3D position/classification	N/A	Comparative analysis of ANN, VQ and VQ + PCA classification algorithms
Bao et al. [74]	N/A	N/A	Capsule device with an integrated camera	Active, based on computer vision	Analysis of acquired images	3D position/classification	N/A	Region-Based Kernel Support Machine Vector (K-SVM) classifier proposed to estimate endoscopic capsule motion
Brandao et al. [75]	N/A	N/A	Endoscopic device with an integrated camera	Active, based on computer vision	Analysis of acquired images	3D position/classification	N/A	Polyps detection through Fully Convolutional Neural Network algorithm
Aghanouri et al. [76]	N/A	N/A	Capsule device with an integrated camera	Active, based on computer vision	Analysis of acquired images	3D position 3D orientation	OA: 0.3°	Evaluation of travelled distance and orientation change from consecutive image frames
Iakovidis et al. [77,78,85]	N/A	N/A	Capsule device with an integrated camera; 6-DoFs Mitsubishi RV3SB robotic arm as benchmark	Active, based on computer vision	Analysis of acquired data from in-vitro experiments	3D position	PA: 1 mm	Evaluation of travelled distance (visual odometry)
Geng et al. [88]	N/A	N/A	Capsule device with an integrated camera and a transmitting antenna	Active, based on computer vision and RF data fusion	Simulations	3D position	PA: <30 mm	Localization based on Cramer Rao Lower Bound (CRLB)

Table A3. Summary table of other types of localization strategies.

Other types of localization strategies
Reference(s)	Compatibility with magnetic locomotion [YES/NO]	Update Rate	Main components of the localization system	Passive/active components embedded into the device	Test conditions	DoFs	Position Accuracy (PA) Orientation Accuracy (OA)	Notes
Boese et al. [89]	YES (not mentioned)	N/A	X-Ray beam; detector plane	Passive, based on the shadow of radiation pattern	N/A	3D position; 3D orientation	N/A	Test conditions not provided (patent)
Kurth et al. [90]	YES	N/A	Capsule device with IPM; X-Ray beam; detector plane; electromagnetic coils for steering	Passive, based on the shadow of radiation pattern	N/A	3D position; 3D orientation	N/A	Test conditions not provided (patent)
Carpi et al. [91]	YES	N/A	Magnetic driven capsule device (Stereotaxis system); RF signal triangulation complemented with X-ray imaging.	Hybrid, based on the shadow of radiation pattern and RF signal triangulation	In-vivo tests on domestic pig	3D position;	PA: 1 mm; OA: N/A	Hybrid localization strategy: signal triangulation (rough 2D localization) and X-ray imaging (finer 2D and 3D localization)
Krieger et al. [93]	YES (not mentioned)	N/A	Biopsy needle; Magnetic Resonance Pulse generator; RF coils for pulse detection	Passive, based on Magnetic Resonance Pulse	In-vitro, in-vivo canine model and in-vivo clinical trials	3D position; 3D orientation	PA: 0.19 ± 0.25 mm; OA: 0.33°±0.42° (in-vitro)	Method applied for needle prostate biopsy but applicable to WCE
Fluckiger et al. [97]	YES (not mentioned)	N/A	Capsule device with ultrasound emitter; ultrasounds receiver on the human body surface	Active, based on ultrasound transmitted by the capsule	In-vitro tests (circular area of 140 mm in diameter)	3D position	PA: 748 ± 310 µm	Algorithm based on FEM simulations with heterogeneous media

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