An Instrumented Glove to Assess Manual Dexterity in Simulation-Based Neurosurgical Education

Use of a Composed Simulator by Veterinarian Non-Experts in Minimally Invasive Surgery for Training and Acquisition of Surgical Skills for Laparoscopic Ovariectomy in Dogs

This study aims to assess the acquisition of surgical skills for laparoscopic ovariectomy (LOE) in dogs by veterinary surgeons with no experience in minimally invasive surgery using the CALMA Veterinary Lap-trainer simulator (CVLTS) in an experimental and analytical setting. Veterinary surgeons with no experience in minimally invasive surgery (MIS) (experimental, n = 5), and MIS experts (experts, n = 3) were evaluated. Experimental and expert group participants watched an instructional video (initial time) before practicing the LOE on uterine tissues and ovaries freshly reconstituted after elective ovariohysterectomy (initial time evaluation). Then, the experimental group practiced five training sessions on the composite simulator with permanent feedback and then performed the LOE again (final time evaluation). Surgical performances in initial and final evaluations were video recorded and further evaluated by three external MIS experts using Global objective assessment of laparoscopic skills (GOALS) and LOE-specific rating scales (SRSs) in a double-blinded schedule. In addition, a hands movement assessment system (HMAS) attached to the back of the hands was used to quantitatively measure completion time, angularity, and movement smoothness. Data were analyzed with one-factor ANOVA and Tukey's contrast test. No statistically significant differences were found between the novice group's performance after training and the expert group's performance according to the GOALS (p < 0.01) and SRS (p < 0.05) scores. Moreover, the novices had significantly improved time, number of movements, and angularity in the final time compared with the initial time (p < 0.05), with no significant differences compared to the expert group (p > 0.05). LOE training using a composed simulator resulted in significantly improved laparoscopic skills and time, number, and angularity of movements data, providing evidence of the usefulness and reliability of CVLTS in training LOE.

Hand-worn devices for assessment and rehabilitation of motor function and their potential use in BCI protocols: a review

Introduction

Various neurological conditions can impair hand function. Affected individuals cannot fully participate in activities of daily living due to the lack of fine motor control. Neurorehabilitation emphasizes repetitive movement and subjective clinical assessments that require clinical experience to administer.

Methods

Here, we perform a review of literature focused on the use of hand-worn devices for rehabilitation and assessment of hand function. We paid particular attention to protocols that involve brain-computer interfaces (BCIs) since BCIs are gaining ground as a means for detecting volitional signals as the basis for interactive motor training protocols to augment recovery. All devices reviewed either monitor, assist, stimulate, or support hand and finger movement.

Results

A majority of studies reviewed here test or validate devices through clinical trials, especially for stroke. Even though sensor gloves are the most commonly employed type of device in this domain, they have certain limitations. Many such gloves use bend or inertial sensors to monitor the movement of individual digits, but few monitor both movement and applied pressure. The use of such devices in BCI protocols is also uncommon.

Discussion

We conclude that hand-worn devices that monitor both flexion and grip will benefit both clinical diagnostic assessment of function during treatment and closed-loop BCI protocols aimed at rehabilitation.

Analysis and Clustering of Upper Limb Motion during the Hand Dexterity Pegboard Test using Inertial Sensor Systems

Maintaining hand and upper limb mobility is important from the viewpoint of freedom in daily life and high performance in work. Few studies on the mobility and dexterity of the upper limb have focused on detailed hand and finger movements. Therefore, we measured the motion of the upper limbs during a general hand dexterity pegboard test using inertial sensor systems and our previous measuring method. To clarify the characteristics of each purpose of motion, we divided the peg-in-hole motion in the pegboard test into its three sections, focusing on two sections: the pinch section, and the carry and insert section. In addition, the obtained joint angles were grouped into arm group and finger group, and singular value decomposition was performed for each joint group in each section. By clustering the decomposition results across five subjects' multiple right and left arm tests, and averaging the singular vectors in the same cluster, the joint distributions and combinations could be clarified. In addition, by recalculating joint angles from averaged SVD results and applying them to the rigid link model, we obtained motion animation with characteristics that made it possible to more clearly understand the requirements for greater dexterity. These results suggested high dexterity motion characteristics in the pinch section, and the carry and insert section of the pegboard test.

Synergy-Based Sensor Reduction for Recording the Whole Hand Kinematics

Simultaneous measurement of the kinematics of all hand segments is cumbersome due to sensor placement constraints, occlusions, and environmental disturbances. The aim of this study is to reduce the number of sensors required by using kinematic synergies, which are considered the basic building blocks underlying hand motions. Synergies were identified from the public KIN-MUS UJI database (22 subjects, 26 representative daily activities). Ten synergies per subject were extracted as the principal components explaining at least 95% of the total variance of the angles recorded across all tasks. The 220 resulting synergies were clustered, and candidate angles for estimating the remaining angles were obtained from these groups. Different combinations of candidates were tested and the one providing the lowest error was selected, its goodness being evaluated against kinematic data from another dataset (KINE-ADL BE-UJI). Consequently, the original 16 joint angles were reduced to eight: carpometacarpal flexion and abduction of thumb, metacarpophalangeal and interphalangeal flexion of thumb, proximal interphalangeal flexion of index and ring fingers, metacarpophalangeal flexion of ring finger, and palmar arch. Average estimation errors across joints were below 10% of the range of motion of each joint angle for all the activities. Across activities, errors ranged between 3.1% and 16.8%.

Validation of Training and Acquisition of Surgical Skills in Veterinary Laparoscopic Surgery: A Review

At present, veterinary laparoscopic surgery training is lacking in experiences that provide a controlled and safe environment where surgeons can practice specific techniques while receiving experts' feedback. Surgical skills acquired using simulators must be certified and transferable to the operating room. Most models for practicing laparoscopic skills in veterinary minimally invasive surgery are general task trainers and consist of boxes (simulators) designed for training human surgery. These simulators exhibit several limitations, including anatomic species and procedural differences, as well as general psychomotor training rather than in vivo skill recreation. In this paper, we review the existing methods of training, evaluation, and validation of technical skills in veterinary laparoscopic surgery. Content includes global and specific scales, and the conditions a structured curriculum should meet for improving the performance of novice surgeons during and after training. A focus on trainee-specific assessment and tailored-technical instruction should influence training programs. We provide a comprehensive analysis of current theories and concepts related to the evaluation and validation of simulators for training laparoscopic surgery in small animal surgery. We also highlight the need to develop new training models and complementary evaluation scales for the validation of training and acquisition of basic and advanced skills in veterinary laparoscopic surgery.

Neurophysiological changes associated with training in laparoscopic surgery using EEG: a pilot study

Laparoscopy is a minimally invasive technique that requires surgeons to acquire special motor skills derived from an extensive training. This work focuses on exploring the neurophysiological changes associated with motor learning. Electroencephalographic (EEG) signals were recorded from eight subjects while performing a bimanual coordination task in a laparoscopic simulator. Spectral power measurements in theta, alpha and beta bands during four training sessions were calculated. Power indices, task score and perception of mental workload were evaluated using analysis of variance to show the effect of training session. Results show improvements in task performance and changes in power measurements associated with the training process. This work opens the possibility to assess the training performance of surgical residents using electrophysiological recordings.

Effect on manual skills of wearing instrumented gloves during manipulation

Instrumented gloves are motion capture systems that are widely used due to the simplicity of the setup required and the absence of occlusion problems when manipulating objects. Nevertheless, the effect of their use on manipulation capabilities has not been studied to date. Therefore, the aim of this work is to quantify the effect of wearing CyberGlove instrumented gloves on these capabilities when different levels of precision are required. Thirty healthy subjects were asked to perform three standardised dexterity tests twice: bare-handed and wearing instrumented gloves. The tests were the Sollerman Hand Function Test (to evaluate capability of performing activities of daily living), the Box and Block Test (to evaluate gross motor skills) and the Purdue Pegboard Test (to evaluate fine motor skills). Scores obtained in the test evaluating fine motor skills decreased by an average of 29% when wearing gloves, while scores obtained on those evaluating gross motor skills and capability to perform activities of daily living were reduced by an average of 8% and 3%, respectively. The use of instrumented gloves to record hand kinematics is only recommended when performing tasks requiring medium and gross motor skills.

Development of a performance model for virtual reality tumor resections

OBJECTIVE

Previous work from the authors has shown that hand ergonomics plays an important role in surgical psychomotor performance during virtual reality brain tumor resections. In the current study they propose a hypothetical model that integrates the human and task factors at play during simulated brain tumor resections to better understand the hand ergonomics needed for optimal safety and efficiency. They hypothesize that 1) experts (neurosurgeons), compared to novices (residents and medical students), spend a greater proportion of their time in direct contact with critical tumor areas; 2) hand ergonomic conditions (most favorable to unfavorable) prompt participants to adapt in order to optimize tumor resection; and 3) hand ergonomic adaptation is acquired with increasing expertise.

METHODS

In an earlier study, experts (neurosurgeons) and novices (residents and medical students) were instructed to resect simulated brain tumors on the NeuroVR (formerly NeuroTouch) virtual reality neurosurgical simulation platform. For the present study, the simulated tumors were divided into four quadrants (Q1 to Q4) to assess hand ergonomics at various levels of difficulty. The spatial distribution of time expended, force applied, and tumor volume removed was analyzed for each participant group (total of 22 participants).

RESULTS

Neurosurgeons spent a significantly greater percentage of their time in direct contact with critical tumor areas. Under the favorable hand ergonomic conditions of Q1 and Q3, neurosurgeons and senior residents spent significantly more time in Q1 than in Q3. Although forces applied in these quadrants were similar, neurosurgeons, having spent more time in Q1, removed significantly more tumor in Q1 than in Q3. In a comparison of the most favorable (Q2) to unfavorable (Q4) hand ergonomic conditions, neurosurgeons adapted the forces applied in each quadrant to resect similar tumor volumes. Differences between Q2 and Q4 were emphasized in measures of force applied per second, tumor volume removed per second, and tumor volume removed per unit of force applied. In contrast, the hand ergonomics of medical students did not vary across quadrants, indicating the existence of an “adaptive capacity” in neurosurgeons.

CONCLUSIONS

The study results confirm the experts’ (neurosurgeons) greater capacity to adapt their hand ergonomics during simulated neurosurgical tasks. The proposed hypothetical model integrates the study findings with various human and task factors that highlight the importance of learning in the acquisition of hand ergonomic adaptation.

Automatic Outcome in Manual Dexterity Assessment Using Colour Segmentation and Nearest Neighbour Classifier

Objective assessment of motor function is an important component to evaluating the effectiveness of a rehabilitation process. Such assessments are carried out by clinicians using traditional tests and scales. The Box and Blocks Test (BBT) is one such scale, focusing on manual dexterity evaluation. The score is the maximum number of cubes that a person is able to displace during a time window. In a previous paper, an automated version of the Box and Blocks Test using a Microsoft Kinect sensor was presented, and referred to as the Automated Box and Blocks Test (ABBT). In this paper, the feasibility of ABBT as an automated tool for manual dexterity assessment is discussed. An algorithm, based on image segmentation in CIELab colour space and the Nearest Neighbour (NN) rule, was developed to improve the reliability of automatic cube counting. A pilot study was conducted to assess the hand motor function in people with Parkinson’s disease (PD). Three functional assessments were carried out. The success rate in automatic cube counting was studied by comparing the manual (BBT) and the automatic (ABBT) methods. The additional information provided by the ABBT was analysed to discuss its clinical significance. The results show a high correlation between manual (BBT) and automatic (ABBT) scoring. The lowest average success rate in cube counting for ABBT was 92%. Additionally, the ABBT acquires extra information from the cubes’ displacement, such as the average velocity and the time instants in which the cube was detected. The analysis of this information can be related to indicators of health status (coordination and dexterity). The results showed that the ABBT is a useful tool for automating the assessment of unilateral gross manual dexterity, and provides additional information about the user’s performance.

Design of an Inertial-Sensor-Based Data Glove for Hand Function Evaluation

Capturing hand motions for hand function evaluations is essential in the medical field. Various data gloves have been developed for rehabilitation and manual dexterity assessments. This study proposed a modular data glove with 9-axis inertial measurement units (IMUs) to obtain static and dynamic parameters during hand function evaluation. A sensor fusion algorithm is used to calculate the range of motion of joints. The data glove is designed to have low cost, easy wearability, and high reliability. Owing to the modular design, the IMU board is independent and extensible and can be used with various microcontrollers to realize more medical applications. This design greatly enhances the stability and maintainability of the glove.