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DEVELOPMENT OF A MULTISENSORY ACQUISITION
SYSTEM FOR FLS TRAINING ASSESSMENT
M.Sc. Candidate: Andrea Panaccio Advisors: Prof. Elena De Momi
(853459) Prof. Marc Garbey
Co-Advisors: Prof. Ahmet Omurtag
Guillaume Joerger, PhD
Center for Computational Surgery
Houston Methodist Research Institute
(Houston, TX)
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Andrea Panaccio, 21/12/2017
Laparoscopy
Laparoscopy is a minimally invasive surgical procedure used to examine the organs inside the abdomen. It can be usedfor both diagnostic and operational purposes.
× Loss of tactile feedback× Fulcrum effect× Lower mobility, no wrist-like movement× The lack of depth perception
✓ Less pain and scaring✓ Reduced recovery time✓ Reduced intraoperative blood loss✓ Reduced infection and complications
SPECIAL TRAINING REQUIRED
N. Mortensen, “Does laparoscopic surgery spell the end of the open surgeon?,” 2003.
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Andrea Panaccio, 21/12/2017
Laparoscopic Training – FLS program
“The Fundamentals of Laparoscopic Surgery” (FLS) is an educational program created by SAGES and aimed to teach the fundamental knowledge and skills required in a basic laparoscopic surgery.
The FLS program is:• a joint educational offering of SAGES and ACS. • a standard of validated surgical training for residency education in
America (CME accredited)
Training/Exam
Knowledge test
Hands-onskills
FLS, “FLS Manual Skills Written Instructions and Performance Guidelines.”, 2014
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Andrea Panaccio, 21/12/2017
Laparoscopic Training – FLS program
“The Fundamentals of Laparoscopic Surgery” (FLS) is an educational program created by SAGES and aimed to teach the fundamental knowledge and skills required in a basic laparoscopic surgery.
The FLS program is:• a joint educational offering of SAGES and ACS. • a standard of validated surgical training for residency education in
America (CME accredited)
Training/Exam
Knowledge test
Hands-onskills
5 tasks of increasing complexity:A. Peg TransferB. Precision CuttingC. Ligating LoopD. Suture with
Extracorporeal KnotE. Suture with
Intracorporeal Knot
Evaluation criteria:• Time• Accuracy
FLS, “FLS Manual Skills Written Instructions and Performance Guidelines.”, 2014
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Andrea Panaccio, 21/12/2017
Stress impact on the performance
SURGICAL FIELD MILITARY AND CIVIL AVIATION FIELDS
Laparoscopy is more stressful than open and robotic surgery
Electrooculogram (↑ Blink Rate)
Stress has effect on decision making (e.g. attentional
tunnelling)
Eye Tracking (↓ SWR)
ambulatory monitoring system (↑ Heart Rate)
Self-assessment questionnaires (MWL)
Heart monitoring (↑ Heart Rate)
Performance evaluation
N. Sharma et al., “Objective measures , sensors and computational techniques for stress recognition and classification : A survey”, 2012.S. Arora et al., “The impact of stress on surgical performance : A systematic review of the literature”, 2010R. Nicolas et al., “Formal Detection of Attentional Tunneling in Human Operator – Automation Interactions”, 2014.
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Best way to proceed:• Non-invasive and unobtrusive sensors• More than one source of information• Don’t disregard an evaluation of the subject performance
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Andrea Panaccio, 21/12/2017
Aim of the project
Setup of the acquisition system
Data acquisition
Algorithm for blinking detection
Algorithm for the 2D reconstruction of the movement of the tool
Validation Validation
Preliminary analysis
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4 video cameras• 2 Trocar’s camera• Laparoscopic camera• Face camera
HexoskinEEG
Eye Tracker
Offline extractionand synchronization
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Andrea Panaccio, 21/12/2017
Workflow
Setup of the acquisitionsystem
Data acquisition
Algorithm for blinking detection
Algorithm for the 2D reconstruction of the movement of the tool
Validation Validation
Preliminary analysis
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Andrea Panaccio, 21/12/2017
Setup of the acquisition system
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Andrea Panaccio, 21/12/2017
Setup of the acquisition system
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Andrea Panaccio, 21/12/2017
Setup of the acquisition system
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Andrea Panaccio, 21/12/2017
Setup of the acquisition system
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Andrea Panaccio, 21/12/2017
Workflow
Setup of the acquisitionsystem
Data acquisition
Algorithm for blinking detection
Algorithm for the 2D reconstruction of the movement of the tool
Validation Validation
Preliminary analysis
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Andrea Panaccio, 21/12/2017
Algorithm for blinking detection
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Eye Tracker Gaze analysis: ET blink candidates
EEG analysis on Fp1 and Fp2: EEG blink candidates
Candidates comparison:Final blinks
Blinking is a semi-autonomic, reflexive, rapid closing of both the eyes.
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Andrea Panaccio, 21/12/2017
Algorithm for blinking detection
P. Manoilov et al., “EEG Eye-Blinking Artefacts Power Spectrum Analysis,”, 2006.M. Haak et al., “Detecting stress using eye blinks and brain activity from eeg signals.”, 2014
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Detection criteria:intervals of eyes not captured < 400 ms
GAZE ANALYSIS
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Andrea Panaccio, 21/12/2017
Algorithm for blinking detection
P. Manoilov et al., “EEG Eye-Blinking Artefacts Power Spectrum Analysis,”, 2006.M. Haak et al., “Detecting stress using eye blinks and brain activity from eeg signals.”, 2014
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AMPLITUDE ANALYSIS – PEAK ESTIMATION
Fp1
Fp2
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Andrea Panaccio, 21/12/2017
Algorithm for blinking detection
P. Manoilov et al., “EEG Eye-Blinking Artefacts Power Spectrum Analysis,”, 2006.M. Haak et al., “Detecting stress using eye blinks and brain activity from eeg signals.”, 2014
SPECTRAL ANALYSIS – PEAK ESTIMATION
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Andrea Panaccio, 21/12/2017
Algorithm for blinking detection
P. Manoilov et al., “EEG Eye-Blinking Artefacts Power Spectrum Analysis,”, 2006.M. Haak et al., “Detecting stress using eye blinks and brain activity from eeg signals.”, 2014
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Andrea Panaccio, 21/12/2017
Algorithm for blinking detection
P. Manoilov et al., “EEG Eye-Blinking Artefacts Power Spectrum Analysis,”, 2006.M. Haak et al., “Detecting stress using eye blinks and brain activity from eeg signals.”, 2014
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Validations:100% of blinking detection (little and slow movementsof the subject during the performance)
Main limits:• Fast and rough movements of the subject (lots of
motion artifacts)• Subject on the edge of the tracker volume of the ET
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Andrea Panaccio, 21/12/2017
Workflow
Setup of the acquisitionsystem
Data acquisition
Algorithm for blinking detection
Algorithm for the 2D reconstruction of the movement of the tool
Validation Validation
Preliminary analysis
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Andrea Panaccio, 21/12/2017
Algorithm for 2D reconstruction of the movement of the tool
Identification criteria:
• # circles close to 1 vertex
• # circles close to 2 vertexes
• Presence of circle in the center of
the square
e.g. feature vector [2 0 1]
Flat patterns on the ceilingi-th FRAME ANALYSIS
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Andrea Panaccio, 21/12/2017
Algorithm for 2D reconstruction of the movement of the tool
i-th Frame HSV – V channel Thresholding
Fill and candidate labeling
Features detectionPattern extraction
Square labeling
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Andrea Panaccio, 21/12/2017
Algorithm for 2D reconstruction of the movement of the tool
Frame by frame additive error
Frame (i+1)Frame (i)
Model Data
𝒊𝑴𝒐𝒅𝒆𝒍𝑻𝑫𝒂𝒕𝒂
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Andrea Panaccio, 21/12/2017
Algorithm for 2D reconstruction of the movement of the tool
Frame (i+1)Frame (i)
Model Data
𝒊𝑴𝒐𝒅𝒆𝒍𝑻𝑫𝒂𝒕𝒂
Registration error: M = 0.81px Std = 0.67 pxMax registration error: 4 pixelError depends on image’s quality.
Main Limit:• Blurring introduced by fast movements
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Andrea Panaccio, 21/12/2017
Workflow
Setup of the acquisitionsystem
Data acquisition
Algorithm for blinking detection
Algorithm for the 2D reconstruction of the movement of the tool
Validation Validation
Preliminary analysis
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Andrea Panaccio, 21/12/2017
Acquisition
Acquisition Protocol:
1. Calibration
2. Signals quality check
3. Acquisitions
– Task 0: Rest
– Task 1: Peg Transfer
– Task 2: Circle Cut
– Task 3: Intracorporeal Knot (only R and E)
Participants:• 4 Beginners (B)• 5 Residents (R)• 3 Experts (E)
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Andrea Panaccio, 21/12/2017
Workflow
Setup of the acquisitionsystem
Data acquisition
Algorithm for blinking detection
Algorithm for the 2D reconstruction of the movement of the tool
Validation Validation
Preliminary analysis
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Andrea Panaccio, 21/12/2017
Performance evaluation
Criteria:- Task’s initial score = 700 pts- Subtract the % of completion time required to complete the task- Penalties for each not completed phase- Penalties for errors (small, big, very big)
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Andrea Panaccio, 21/12/2017
Performance evaluation
Task 2: main discriminative task among B and R,E
Task 3: main discriminative task among R and E
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Task 3
Task 2
Task 1
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Andrea Panaccio, 21/12/2017
Preliminary analysis – Gaze observations (ET)
Loss of attention
Initialdifficulty
Correlation with events
Reaction to error
Reaction to error
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Task 1
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Andrea Panaccio, 21/12/2017
Preliminary analysis – Gaze observations (ET)
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Task 3
Smoother signals better performance
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Andrea Panaccio, 21/12/2017
Task 2:
Preliminary analysis – Gaze observations (ET)
Level of focus
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HIGHER DISPERSION
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Andrea Panaccio, 21/12/2017
Task 3:
Preliminary analysis – Gaze observations (ET)
Level of focus
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HIGHER DISPERSION
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Andrea Panaccio, 21/12/2017
Preliminary analysis – Gaze observations (ET)
High
Low
High
Low
Level of focus - Analysis on Gaze displacements vectors’ module
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Outliers
Task 2
Task 3
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Andrea Panaccio, 21/12/2017
Preliminary analysis – Hexoskin, Blinking, Pupil observations
Hexoskin:• Heart activity: almost 1/3 of the
data present errors• Respiratory activity: irregular
respiration during hard phases
Blinking Rate:• Drop from rest to exercise• In some, it increases in hard phases
Low BR High BR
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Task 3
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Andrea Panaccio, 21/12/2017
Preliminary analysis – Hexoskin, Blinking, Pupil observations
Hexoskin:• Heart activity: almost 1/3 of the
data present errors• Respiratory activity: irregular
respiration during hard phases
Blinking Rate:• Drop from rest to exercise• In some, it increases in hard phases
Low BR High BR
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Tunnel Effect (sound): No impact on the performance
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Andrea Panaccio, 21/12/2017
Conclusions
The goals achieved:• Creation of a multisensory platform for signals acquisition during FLS training• Algorithm for blinking detection• Algorithm for 2D reconstruction of the tool motion• Observations on preliminary analysis on subset of signals: ET, respiration and Blinking represent signals
of interest
Future development:• Include a new device for heart monitoring and enlarge the number of participants• More in depth analysis for all the other signals to find relevant parameters for a wider performance
evaluation• Add external events such as the rotation of the laparoscopic view and the appearance of smoke in the
FOV
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Andrea Panaccio, 21/12/2017
Thank you for your attention
Contact InformationAndrea Panaccio