Analysis of the video motion tracking system "Kinovea" to assess surgical movements during robot-assisted radical prostatectomy

Development of a simultaneous and noninvasive measuring method using high-frame rate videography and motion analysis software for the assessment of facial palsy recovery in a rat model

BACKGROUND

For the development of new therapeutic and reconstructive methods for facial nerve palsy, it is critical to validate them in animal models. This study developed a novel evaluation method using a high-speed camera and motion analysis software for rat facial paralysis models. The validity of the new method was verified using normal rats and rats with facial paralysis.

METHODS

The whisker movement was recorded using a high-frame video camera. The video files were processed using motion analysis software, and the angular velocities were measured. The score was calculated as the percentage of movement on the side that had palsy compared with the movement on the normal side. Normal rats were used to examine which of the four indices of angular velocity is appropriate for this evaluation method. Using this method, two types of facial nerve palsy models were compared. Furthermore, the three agents that were predicted to promote axon regeneration from previous studies were evaluated.

RESULTS

The two averages of the protraction and retraction movement velocities of the whiskers were considered as the most appropriate indicators for this new method. Compared with the saline group, all agent groups showed significant differences in the improvement of facial palsy recovery.

CONCLUSIONS

This method is an evaluation method for the effects of therapeutic intervention for facial nerve paralysis in real time without sacrificing animals.

An Automated Skill Assessment Framework Based on Visual Motion Signals and a Deep Neural Network in Robot-Assisted Minimally Invasive Surgery

Surgical skill assessment can quantify the quality of the surgical operation via the motion state of the surgical instrument tip (SIT), which is considered one of the effective primary means by which to improve the accuracy of surgical operation. Traditional methods have displayed promising results in skill assessment. However, this success is predicated on the SIT sensors, making these approaches impractical when employing the minimally invasive surgical robot with such a tiny end size. To address the assessment issue regarding the operation quality of robot-assisted minimally invasive surgery (RAMIS), this paper proposes a new automatic framework for assessing surgical skills based on visual motion tracking and deep learning. The new method innovatively combines vision and kinematics. The kernel correlation filter (KCF) is introduced in order to obtain the key motion signals of the SIT and classify them by using the residual neural network (ResNet), realizing automated skill assessment in RAMIS. To verify its effectiveness and accuracy, the proposed method is applied to the public minimally invasive surgical robot dataset, the JIGSAWS. The results show that the method based on visual motion tracking technology and a deep neural network model can effectively and accurately assess the skill of robot-assisted surgery in near real-time. In a fairly short computational processing time of 3 to 5 s, the average accuracy of the assessment method is 92.04% and 84.80% in distinguishing two and three skill levels. This study makes an important contribution to the safe and high-quality development of RAMIS.

Does an Adjusted Kinematic Model Predict the Relative Eccentric Force During Nordic Curl?

This study aimed to assess the combination of video-based kinematic variables adjusted by intrinsic covariates to predict the relative eccentric force (RelF) during the Nordic curl. The participants (n = 21) performed Nordic curls (3 trials; 3-min rest) on a device measuring the eccentric force. The peaks were normalized by body weight. Kinovea software was used to track angular and linear velocity and acceleration from recorded videos. Two prediction models with multiple linear regression equations associated kinematic, anthropometric, and age variables to adjust the actual RelF. The equations obtained the predicted RelF. The actual RelF was inversely correlated with height (r = -.52), tangential (r = -.50) and centripetal accelerations (r = -.715), and angular velocity (r = -.70). The best prediction models combined angular velocity with age (F2,18 = 15.1, P = .001, r = .792, r2 = .627) and with height (F2,18 = 14.5, P = .001, r = .785, r2 = .616). No differences were observed between actual and predicted values (P = .993-.994), with good levels of agreement and consistency (intraclass correlation coefficient = .77-.78; Cronbach α = .86-.87). Bland-Altman results showed high levels of agreement and low biases. The standard error of measurement and minimal detectable change ranges were 0.46 to 0.49 N/kg and 1.28 to 1.36 N/kg, respectively. Also, the percentage of standard error of measurement was below 10% (7.92%-8.35%). The coefficient of variation analysis returned a 14.54% and 15.13% for each model, respectively. Kinematic analysis offers portability and low cost to current expensive or technical impaired dynamometry-based techniques to assess the RelF.

An evaluation of temporal and club angle parameters during golf swings using low cost video analyses packages

The purpose of this study was to compare swing time and golf club angle parameters during golf swings using three, two dimensional (2D) low cost, Augmented-Video-based-Portable-Systems (AVPS) (Kinovea, SiliconCoach Pro, SiliconCoach Live). Twelve right-handed golfers performed three golf swings whilst being recorded by a high-speed 2D video camera. Footage was then analysed using AVPS-software and the results compared using both descriptive and inferential statistics. There were no significant differences for swing time and the golf phase measurements between the 2D and 3D software comparisons. In general, the results showed a high Intra class Correlation Coefficient (ICC > 0.929) and Cronbach’s Coefficient Alpha (CCA > 0.924) reliability for both the kinematic and temporal parameters. The inter-rater reliability test for the swing time and kinematic golf phase measurements on average were strong. Irrespective of the AVPS software investigated, the cost effective AVPS can produce reliable output measures that benefit golf analyses.

A new method for assessing lung tumor motion in radiotherapy using dynamic chest radiography

Dynamic chest radiography (DCR) is a recent advanced modality to acquire dynamic and functional images. We developed a new method using DCR and the free analysis software, Kinovea, to assess lung tumor motion. This study aimed to demonstrate the usefulness of our method. Phantom and clinical studies were performed. In the phantom study, dynamic images of a moving lead sphere were acquired using DCR, and the motion of the phantom was tracked using Kinovea in a DCR video. The amplitude of phantom motion was measured and compared with a predetermined baseline amplitude. In a clinical study, DCR and respiratory‐gated four‐dimensional computed tomography (4D‐CT) were performed on 15 patients who underwent stereotactic body radiation therapy for lung tumors. The amplitudes of tumor motion in DCR and 4D‐CT were measured in the superior‐inferior (SI), left‐right (LR), and anterior‐posterior (AP) directions, and the square root of the sum of squares (SRSS) of the amplitude was calculated in all directions. Spearman's rank correlation and the Wilcoxon signed‐rank test were performed to determine the correlations of the amplitudes of tumor motion obtained using DCR and 4D‐CT. In the phantom study, the absolute mean error between the measured and predetermined amplitudes was 0.60 mm (range: 0.061.53 mm). In the clinical study, the amplitudes of tumor motion obtained using DCR correlated significantly with those of 4D‐CT in the SI and LR directions, as did the SRSS values. The median amplitudes for DCR were significantly higher than those for 4D‐CT in all (SI, LR, and AP) directions, as were the SRSS values. Our proposed method based on DCR and Kinovea is useful for assessing lung tumor motion, visually and quantitatively. Therefore, DCR has potential as a new modality for evaluating lung tumor motion in radiotherapy.

Do It by Yourself: Larval Locomotion in the Black Soldier Fly Hermetia illucens, with a Novel “Self-Harvesting” Method to Separate Prepupae

Simple Summary

The black soldier fly Hermetia illucens is a widespread species of fly of American origins, which is increasingly used to develop sustainable waste recycling processes as it is able to develop by consuming a wide variety of wastes as food, while both its body and the residuals of its feeding activity can be re-used in a variety of processes. However, many aspects of its larval biology remain unknown. Among these, there is larval movement and its variation in response to external stimuli and environmental conditions. Larvae of the black soldier fly eventually reach the prepupal stage, during which they stop feeding and seek a shelter to pupate. Sorting prepupae from the younger larvae and feeding substratum can be important in rearing processes, since they are used to obtain adults but are also particularly rich in protein and lipids. We focused our study on behavioural differences between prepupae and younger larvae, describing tonic immobility as an anti-predatory response of both, but also their very different ways of locomotion and reactions to stress. Finally, we developed a practical system to exploit these differences, inducing prepupae to move away from the substratum and other larvae to be efficiently collected.

Abstract

The neotropical insect Hermetia illucens has become a cosmopolite species, and it is considered a highly promising insect in circular and sustainable economic processes. Being able to feed on a wide variety of organic substrates, it represents a source of lipids and proteins for many uses and produces recyclable waste. We investigated the characteristics and differences in the poorly-known locomotory behaviour of larvae of different instars, paying particular attention to the unique characteristics of the prepupal stage, key to farming and industrial processes. Moreover, we attempted to develop a “self-harvesting” system relying on the behavioural traits of prepupae to obtain their separation from younger larvae under rearing condition with minimum effort. Prepupae differ from younger larvae in their response to physical disturbance in the form of tonic immobility and significantly differ in their locomotory movements. Both prepupae and younger larvae reacted similarly to heat or light-induced stress, but low light and high moisture induced only prepupae to migrate away, which resulted in the development of a highly efficient separation methodology. The new data on the behaviour of H. illucens not only shed new light on some unexplored aspects of its biology, but also led to develop an inexpensive self-harvesting system that can be implemented in small-scale and industrial farming.

Review of automated performance metrics to assess surgical technical skills in robot-assisted laparoscopy

INTRODUCTION

Robot-assisted laparoscopy is a safe surgical approach with several studies suggesting correlations between complication rates and the surgeon's technical skills. Surgical skills are usually assessed by questionnaires completed by an expert observer. With the advent of surgical robots, automated surgical performance metrics (APMs)-objective measures related to instrument movements-can be computed. The aim of this systematic review was thus to assess APMs use in robot-assisted laparoscopic procedures. The primary outcome was the assessment of surgical skills by APMs and the secondary outcomes were the association between APM and surgeon parameters and the prediction of clinical outcomes.

METHODS

A systematic review following the PRISMA guidelines was conducted. PubMed and Scopus electronic databases were screened with the query "robot-assisted surgery OR robotic surgery AND performance metrics" between January 2010 and January 2021. The quality of the studies was assessed by the medical education research study quality instrument. The study settings, metrics, and applications were analysed.

RESULTS

The initial search yielded 341 citations of which 16 studies were finally included. The study settings were either simulated virtual reality (VR) (4 studies) or real clinical environment (12 studies). Data to compute APMs were kinematics (motion tracking), and system and specific events data (actions from the robot console). APMs were used to differentiate expertise levels, and thus validate VR modules, predict outcomes, and integrate datasets for automatic recognition models. APMs were correlated with clinical outcomes for some studies.

CONCLUSIONS

APMs constitute an objective approach for assessing technical skills. Evidence of associations between APMs and clinical outcomes remain to be confirmed by further studies, particularly, for non-urological procedures. Concurrent validation is also required.

Audio and panoramic video recording in the operating room: legal and ethical perspectives

INTRODUCTION

The idea of video recording (VR) in the operating room (OR) with panoramic cameras and microphones is a new concept that is changing the approach to medical activities in the OR. However, VR in the OR has brought up many concerns regarding patient privacy and has highlighted legal and ethical issues that were never previously exposed.

AIM

To review the literature concerning these aspects and provide a better ethical and legal understanding of the new challenges concerning VR in the OR.

CONCLUSIONS

There is a disparity between the two main legal models concerning VR in the OR, namely the European legal system (General Data Protection Regulation (GDPR)) and the American legal framework (Health Insurance Portability and Accountability Act (HIPAA)). This difference mainly deals with two distinct bioethical paradigms: GDPR places a strong emphasis on protecting patients' privacy to improve the public health system, whereas HIPAA indicates the need to generate protocols to safeguard the risks connected to medical activity and patient privacy. Following from this point, we may argue that, at the ethical and bioethical level, GDPR and HIPAA depend mainly on two different ethical models: a perspective based on moral acquaintances and weak proceduralism, respectively. It is worth noting the importance of developing additional guidelines concerning different world regions to avoid the ethical problems that may emerge when simply applying a foreign paradigm to a very different culture.