Estimation of lower back muscle force in a lifting task using wearable IMUs.

Low back pain is commonly reported in occupational settings due to factors such as heavy lifting and poor ergonomic practices, often resulting in significant healthcare expenses and lowered productivity. Assessment tools for human motion and ergonomic risk at the workplace are still limited. Therefore, this study aimed to assess lower back muscle and joint reaction forces in laboratory conditions using wearable inertial measurement units (IMUs) during weight lifting, a frequently high-risk workplace task. Ten able-bodied participants were instructed to lift a 28 lbs. box while surface electromyography sensors, IMUs, and a camera-based motion capture system recorded their muscle activity and body motion. The data recorded by IMUs and motion capture system were used to estimate lower back muscle and joint reaction forces via musculoskeletal modeling. Lower back muscle patterns matched well with electromyography recordings. The normalized mean absolute differences between muscle forces estimated based on measurements of IMUs and cameras were less than 25 %, and the statistical parametric mapping results indicated no significant difference between the forces estimated by both systems. However, abrupt changes in motion, such as lifting initiation, led to significant differences (p < 0.05) between the muscle forces. Furthermore, the maximum L5-S1 joint reaction force estimated using IMU data was significantly lower (p < 0.05) than those estimated by cameras during weight lifting and lowering. The study showed how kinematic errors from IMUs propagated through the musculoskeletal model and affected the estimations of muscle forces and joint reaction forces. Our findings showed the potential of IMUs for in-field ergonomic risk evaluations.

Kinematic Alignment Technique Outperforms Mechanical Alignment in Simultaneous Bilateral Total Knee Arthroplasty: A Randomized Controlled Trial.

BACKGROUND: The aim of this study was to compare the clinical results of kinematic alignment (KA) with those of mechanical alignment (MA) in single-stage bilateral total knee arthroplasty. METHODS: In this double-blinded randomized controlled trial, 65 patients who had bilateral knee osteoarthritis underwent simultaneous bilateral total knee arthroplasty. One knee was randomly selected to be operated on with the calipered-KA technique and the other with MA. The participants were assessed via the Oxford Knee Score, Western Ontario and McMaster Universities Osteoarthritis Index questionnaire, and visual analog scale before the surgery and the same plus the Forgotten Joint Score at their last follow-up visit, 2 years postoperatively. Maximum knee flexion and the time reaching maximum knee flexion, named the recovery time, were also recorded. Hip-knee-ankle angle, medial proximal tibial angle, and lateral distal femoral angle were measured before and after the surgery using 3-joint-view radiographs. RESULTS: At 2 years, there were significant differences between the KA and MA techniques in terms of duration of surgery, recovery time, and final Western Ontario and McMaster Universities Osteoarthritis Index, Forgotten Joint Score, and maximum flexion range in favor of KA (P < .05), but no significant difference in visual analog scale score or Oxford Knee Score. In patients who have a preferred knee, the KA knee was preferred over the MA knee by most patients. No prosthetic failure or revision was reported in either group. CONCLUSIONS: The KA technique yields acceptable functional outcomes compared to the MA technique. The KA technique was associated with a shorter surgery time, a faster recovery time, and higher patient satisfaction in 2-year follow-ups. Larger multicenter studies with longer follow-ups are warranted to confirm these findings. LEVEL OF EVIDENCE: I.

Enhancing skill learning with dual-user haptic feedback: insights from a task-specific approach.

Introduction: This study was to examine whether inter-user haptic feedback would have a differential impact on skill acquisition based on the nature of the surgical task involved. Specifically, we hypothesized that haptic feedback would facilitate target orientation more than cutting tasks in the context of laparoscopic surgery. Methods: Ten novice participants were recruited and assigned to one of two training groups. Each group underwent six half-hour training sessions dedicated to laparoscopic pattern-cutting tasks. In the haptic group, five participants received expert guidance during the training sessions, whereas the remaining five participants in the control group engaged in self-practice. All trials were recorded on video, enabling a comparative analysis of task performance between the participants' left hand (target manipulation) and right hand (cutting task). Additionally, the number of haptic feedback instances provided to the trainees in the haptic group was recorded. Results: Practice led to a reduction in total task time, grasping time, and cutting errors. However, no significant differences were observed between the two training groups, except for the grasping time, where haptic feedback significantly reduced the grasping time compared to the control group. Moreover, the frequency of haptic feedback instances provided to the trainees was notably higher for the grasping than for the cutting task. Discussion: Our study suggests that haptic feedback has a more substantial impact on orientation tasks than on cutting tasks in laparoscopic surgery training. However, we acknowledge that a larger sample size would provide a more robust evaluation of this effect.

Evaluating Efficiency of a Provincial Telerehabilitation Service in Improving Access to Care During the COVID-19 Pandemic.

Scope: Early in the COVID-19 pandemic, community rehabilitation stakeholders from a provincial health system designed a novel telerehabilitation service. The service provided wayfinding and self-management advice to individuals with musculoskeletal concerns, neurological conditions, or post-COVID-19 recovery needs. This study evaluated the efficiency of the service in improving access to care. Methodology: We used multiple methods including secondary data analyses of call metrics, narrative analyses of clinical notes using artificial intelligence (AI) and machine learning (ML), and qualitative interviews. Conclusions: Interviews revealed that the telerehabilitation service had the potential to positively impact access to rehabilitation during the COVID-19 pandemic, for individuals living rurally, and for individuals on wait lists. Call metric analyses revealed that efficiency may be enhanced if call handling time was reduced. AI/ML analyses found that pain was the most frequently-mentioned keyword in clinical notes, suggesting an area for additional telerehabilitation resources to ensure efficiency.

Robotics in Nursing: Protocol for a Scoping Review.

BACKGROUND: Globally, health care systems are challenged with the shortage of health care professionals, particularly nurses. The decline in the nursing workforce is primarily attributed to an aging population, increased demand for health care services, and a shortage of qualified nurses. Stressful working conditions have also increased the physical and emotional demands and perceptions of burnout, leading to attrition among nurses. Robotics has the potential to alleviate some of the workforce challenges by augmenting and supporting nurses in their roles; however, the impact of robotics on nurses is an understudied topic, and limited literature exists. OBJECTIVE: We aim to understand the extent and type of evidence in relation to robotics integration in nursing practice. METHODS: The Joanna Briggs Institute methodology and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist will guide the scoping review. The MEDLINE (Ovid), Embase (Ovid), CINAHL Plus with Full Text (EBSCOhost), Scopus, Cochrane Library, and IEEE Xplore electronic bibliographic databases will be searched to retrieve papers. In addition, gray literature sources, including Google Scholar, dissertations, theses, registries, blogs, and relevant organizational websites will be searched. Furthermore, the reference lists of included studies retrieved from the databases and the gray literature will be hand-searched to ensure relevant papers are not missed. In total, 2 reviewers will independently screen retrieve papers at each stage of the screening process and independently extract data from the included studies. A third reviewer will be consulted to help decision-making if conflicts arise. Data analysis will be completed using both descriptive statistics and content analysis. The results will be presented using tabular and narrative formats. RESULTS: The review is expected to describe the current evidence on the integration and impact of robots and robotics into nursing clinical practice, provide insights into the current state and knowledge gaps, identify a direction for future research, and inform policy and practice. The authors expect to begin the data searches in late January 2024. CONCLUSIONS: The robotics industry is evolving rapidly, providing different solutions that promise to revamp health care delivery with possible improvements to nursing practice. This review protocol outlines the steps proposed to systematically investigate this topic and provides an opportunity for more insights from scholars and researchers working in the field. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/50626.

Surgical tooltip motion metrics assessment using virtual marker: an objective approach to skill assessment for minimally invasive surgery.

PURPOSE: Surgical skill assessment has primarily been performed using checklists or rating scales, which are prone to bias and subjectivity. To tackle this shortcoming, assessment of surgical tool motion can be implemented to objectively classify skill levels. Due to the challenges involved in motion tracking of surgical tooltips in minimally invasive surgeries, formerly used assessment approaches may not be feasible for real-world skill assessment. We proposed an assessment approach based on the virtual marker on surgical tooltips to derive the tooltip's 3D position and introduced a novel metric for surgical skill assessment. METHODS: We obtained the 3D tooltip position based on markers placed on the tool handle. Then, we derived tooltip motion metrics to identify the metrics differentiating the skill levels for objective surgical skill assessment. We proposed a new tooltip motion metric, i.e., motion inconsistency, that can assess the skill level, and also can evaluate the stage of skill learning. In this study, peg transfer, dual transfer, and rubber band translocation tasks were included, and nine novices, five surgical residents and five attending general surgeons participated. RESULTS: Our analyses showed that tooltip path length (p [Formula: see text] 0.007) and path length along the instrument axis (p [Formula: see text] 0.014) differed across the three skill levels in all the tasks and decreased by skill level. Tooltip motion inconsistency showed significant differences among the three skill levels in the dual transfer (p [Formula: see text] 0.025) and the rubber band translocation tasks (p [Formula: see text] 0.021). Lastly, bimanual dexterity differed across the three skill levels in all the tasks (p [Formula: see text] 0.012) and increased by skill level. CONCLUSION: Depth perception ability (indicated by shorter tooltip path lengths along the instrument axis), bimanual dexterity, tooltip motion consistency, and economical tooltip movements (shorter tooltip path lengths) are related to surgical skill. Our findings can contribute to objective surgical skill assessment, reducing subjectivity, bias, and associated costs.

A framework for evaluation and adoption of industrial exoskeletons.

Work-related Musculoskeletal Disorders (WMSDs) account for a significant portion of worker illnesses and injuries, resulting in high costs and productivity losses to employers globally. In recent years, there has been an increased interest in the use of exoskeleton technology to reduce rates of WMSDs in industrial worksites. Despite the potential of exoskeletons to mitigate the risks of WMSDs, the required steps to properly assess and implement the technology for industrial applications are not clear. This paper proposes a framework that can help organizations successfully evaluate and adopt industrial exoskeletons. Through a focus group of industry professionals, researchers, and exoskeleton experts, and by building on existing literature, an overarching adoption framework is developed. The identified stages and tasks within the framework enable an organization to evaluate and adopt exoskeletons through a systematic approach and to identify the existing gaps in their technology adoption process. The findings also highlight the areas where further studies are needed to promote the adoption of industrial exoskeletons, including large-scale field studies and long-term monitoring.

A Dynamic Procedure to Detect Maximum Voluntary Contractions in Low Back.

Surface electromyography (sEMG) is generally used to measure muscles' activity. The sEMG signal can be affected using several factors and vary among individuals and even measurement trials. Thus, to consistently evaluate data among individuals and trials, the maximum voluntary contraction (MVC) value is usually calculated and used to normalize sEMG signals. However, the sEMG amplitude collected from low back muscles can be frequently larger than that found when conventional MVC measurement procedures are used. To address this limitation, in this study, we proposed a new dynamic MVC measurement procedure for low back muscles. Inspired by weightlifting, we designed a detailed dynamic MVC procedure, and then collected data from 10 able-bodied participants and compared their performances using several conventional MVC procedures by normalizing the sEMG amplitude for the same test. The sEMG amplitude normalized by our dynamic MVC procedure showed a much lower value than those obtained using other procedures (Wilcoxon signed-rank test, with p < 0.05), indicating that the sEMG collected during dynamic MVC procedure had a larger amplitude than those of conventional MVC procedures. Therefore, our proposed dynamic MVC obtained sEMG amplitudes closer to its physiological maximum value and is thus more capable of normalizing the sEMG amplitude for low back muscles.

Motion Smoothness-Based Assessment of Surgical Expertise: The Importance of Selecting Proper Metrics.

The smooth movement of hand/surgical instruments is considered an indicator of skilled, coordinated surgical performance. Jerky surgical instrument movements or hand tremors can cause unwanted damages to the surgical site. Different methods have been used in previous studies for assessing motion smoothness, causing conflicting results regarding the comparison among surgical skill levels. We recruited four attending surgeons, five surgical residents, and nine novices. The participants conducted three simulated laparoscopic tasks, including peg transfer, bimanual peg transfer, and rubber band translocation. Tooltip motion smoothness was computed using the mean tooltip motion jerk, logarithmic dimensionless tooltip motion jerk, and 95% tooltip motion frequency (originally proposed in this study) to evaluate their capability of surgical skill level differentiation. The results revealed that logarithmic dimensionless motion jerk and 95% motion frequency were capable of distinguishing skill levels, indicated by smoother tooltip movements observed in high compared to low skill levels. Contrarily, mean motion jerk was not able to distinguish the skill levels. Additionally, 95% motion frequency was less affected by the measurement noise since it did not require the calculation of motion jerk, and 95% motion frequency and logarithmic dimensionless motion jerk yielded a better motion smoothness assessment outcome in distinguishing skill levels than mean motion jerk.

Discrete-Time Control Barrier Function: High-Order Case and Adaptive Case.

This article proposes the novel concepts of the high-order discrete-time control barrier function (CBF) and adaptive discrete-time CBF. The high-order discrete-time CBF is used to guarantee forward invariance of a safe set for discrete-time systems of high relative degree. An optimization problem is then established unifying high-order discrete-time CBFs with discrete-time control Lyapunov functions to yield a safe controller. To improve the feasibility of such optimization problems, the adaptive discrete-time CBF is designed, which can relax constraints on system control input through time-varying penalty functions. The effectiveness of the proposed methods in dealing with high relative degree constraints and improving feasibility is verified on the discrete-time system of a three-link manipulator.

Machine-learned Adaptive Switching in Voluntary Lower-limb Exoskeleton Control: Preliminary Results.

Lower-limb exoskeletons utilize fixed control strategies and are not adaptable to user's intention. To this end, the goal of this study was to investigate the potential of using temporal-difference learning and general value functions for predicting the next possible walking mode that will be selected by users wearing exoskeletons in order to reduce the effort and cognitive load while switching between different modes of walking. Experiments were performed with a user wearing the Indego exoskeleton and given the authority to switch between five walking modes that were different in terms of speed and turn direction. The user's switching preferences were learned and predicted from device-centric and room-centric measurements by considering similarities in the movements being performed. A switching list was updated to show the most probable future next modes to be selected by the user. In contrast to other approaches that either can only predict a single time-step or require intensive offline training, this work used a computationally inexpensive method for learning and has the potential of providing temporally extended sets of predictions in real-time. Comparing the number of required manual switches between the machine-learned switching list and the best possible static lists showed an average decrease of 42.44% in the required switches for the machine-learned adaptive strategy. These promising results will facilitate the path for real-time application of this technique.

Haptic virtual surgery simulation system under field programmable analogue array-based hybrid control.

In this paper, a bilateral haptic virtual surgery simulation system under a hybrid controller was studied. An analogue controller realized by a field programmable analogue array (FPAA) was paralleled in the operator robot side, which reduced the impact of controller discretisation on the system. A system stability conditions under hybrid control with multiple-operators were deduced. The stability analysis indicates that the addition of analogue derivative term widens the range of haptic controls gains that satisfy the multiple-users' stability conditions. Finally, the human's performance of a stiffness discrimination task was studied in an independently developed minimally invasive surgical (MIS) platform. The experiment results show that, human operators under the hybrid controller achieve the highest task success rates.

Dual Mode pHRI-teleHRI Control System with a Hybrid Admittance-Force Controller for Ultrasound Imaging.

The COVID-19 pandemic has brought unprecedented extreme pressure on the medical system due to the physical distance policy, especially for procedures such as ultrasound (US) imaging, which are usually carried out in person. Tele-operation systems are a promising way to avoid physical human-robot interaction (pHRI). However, the system usually requires another robot on the remote doctor side to provide haptic feedback, which makes it expensive and complex. To reduce the cost and system complexity, in this paper, we present a low-cost, easy-to-use, dual-mode pHRI-teleHRI control system with a custom-designed hybrid admittance-force controller for US imaging. The proposed system requires only a tracking camera rather than a sophisticated robot on the remote side. An audio feedback is designed for replacing haptic feedback on the remote side, and its sufficiency is experimentally verified. The experimental results indicate that the designed hybrid controller can significantly improve the task performance in both modes. Furthermore, the proposed system enables the user to conduct US imaging while complying with the physical distance policy, and allows them to seamlessly switch modes from one to another in an online manner. The novel system can be easily adapted to other medical applications beyond the pandemic, such as tele-healthcare, palpation, and auscultation.

Evaluating the impact of a novel telerehabilitation service to address neurological, musculoskeletal, or coronavirus disease 2019 rehabilitation concerns during the coronavirus disease 2019 pandemic.

Introduction: A novel telerehabilitation service provides wayfinding and self-management advice to persons with neurological, musculoskeletal, or coronavirus disease 2019 related rehabilitation needs. Method: We utilized multiple methods to evaluate the impact of the service. Surveys clarified health outcomes (quality of life, self-efficacy, social support) and patient experience (telehealth usability; general experience) 3-months post-call. We analysed associations between, and within, demographics and survey responses. Secondary analyses described health care utilization during the first 6 months. Results: Sixty-eight callers completed the survey (42% response rate). Self-efficacy was significantly related to quality of life, interpersonal support and becoming productive quickly using the service. Becoming productive quickly was significantly related to quality of life. Education level was related to ethnicity. Survey respondents' satisfaction and whether they followed the therapist's recommendations were not significantly associated with demographics. Administrative data indicated there were 124 callers who visited the emergency department before, on, or after their call. The average (SD) frequency of emergency department visits before was 1.298 times (1.799) compared to 0.863 times (1.428) after. Discussion: This study offers insights into the potential impact of the telerehabilitation service amidst pandemic restrictions. Usability measurements showed that callers were satisfied, corroborating literature from pre-pandemic contexts. The satisfaction and acceptability of the service does not supplant preferences for in-person visits. The survey sample reported lower quality of life compared with the provincial population, conflicting with pre-pandemic research. Findings may be due to added stressors associated with the pandemic. Future research should include population-level comparators to better clarify impact.

A Systematic Review of Industrial Exoskeletons for Injury Prevention: Efficacy Evaluation Metrics, Target Tasks, and Supported Body Postures.

Industrial workplaces expose workers to a high risk of injuries such as Work-related Musculoskeletal Disorders (WMSDs). Exoskeletons are wearable robotic technologies that can be used to reduce the loads exerted on the body's joints and reduce the occurrence of WMSDs. However, current studies show that the deployment of industrial exoskeletons is still limited, and widespread adoption depends on different factors, including efficacy evaluation metrics, target tasks, and supported body postures. Given that exoskeletons are not yet adopted to their full potential, we propose a review based on these three evaluation dimensions that guides researchers and practitioners in properly evaluating and selecting exoskeletons and using them effectively in workplaces. Specifically, evaluating an exoskeleton needs to incorporate: (1) efficacy evaluation metrics based on both subjective (e.g., user perception) and objective (e.g., physiological measurements from sensors) measures, (2) target tasks (e.g., manual material handling and the use of tools), and (3) the body postures adopted (e.g., squatting and stooping). This framework is meant to guide the implementation and assessment of exoskeletons and provide recommendations addressing potential challenges in the adoption of industrial exoskeletons. The ultimate goal is to use the framework to enhance the acceptance and adoption of exoskeletons and to minimize future WMSDs in industrial workplaces.

Preliminary testing of eye gaze interfaces for controlling a haptic system intended to support play in children with physical impairments: Attentive versus explicit interfaces.

INTRODUCTION: Children with physical impairments may face challenges to play because of their motor impairments, which could lead to negative impacts in their development. The objective of this article was to compare two eye gaze interfaces that identified the desired toy a user wanted to reach with a haptic-enabled telerobotic system in a play activity. METHODS: One of the interfaces was an attentive user interface predicted the toy that children wanted to reach by observing where they incidentally focused their gaze. The other was an explicit eye input interface determined the toy after the child dwelled for 500 ms on a selection point. Five typically developing children, an adult with cerebral palsy (CP) and a child with CP participated in this study. They controlled the robotic system to play a whack-a-mole game. RESULTS: The prediction accuracy of the attentive interface was higher than 89% in average, for all participants. All participants did the activity faster with the attentive interface than with the explicit interface. CONCLUSIONS: Overall, the attentive interface was faster and easier to use, especially for children. Children needed constant prompting and were not 100% successful at using the explicit interface.

A feasibility study of eye gaze with biofeedback in a human-robot interface.

Play is a vital activity in which children learn skills and explore the environment through object manipulation. Assistive robots have been used to provide access to play, and Forbidden Region Virtual Fixture (FRVF) guidance at the user interface could help the users make the robot traverse the play environment more efficiently because it behaves like virtual walls to follow. Eye gaze was used to indicate the user's intended target and generate the location of the virtual walls in a card sorting task. We eliminated the typical computer screen required for visual feedback to confirm gaze location, and examined the use of alternative feedback. In this feasibility study, first a group of adults without physical impairment tested the system with auditory and vibrotactile feedback modalities for the gaze fixation and with the virtual walls on and off for robot movement. Then case studies with children and individuals with physical impairments were performed. Even though gaze fixation feedback and the virtual wall did not improve the performance of adult participants without impairment, the feedback increased the speed and accuracy of the gaze fixation and the virtual walls improved the movement efficiency for the participants with impairment and a 6-year-old child without impairment.

A finite-time adaptive order estimation approach for non-integer order nonlinear systems.

This paper proposes some methods for estimating the order of nonlinear systems having non-integer order. First, the stability of time-varying order systems is studied. Afterward, the multivariable systems with time-varying incommensurate order are studied and an estimation scheme is proposed to approximate the order. In the next step, considering the pseudo-states of a system to be unknown, an order/pseudo-state estimator is designed for a category of nonlinear systems. It is shown that the method is extendible to form order/pseudo-state estimators for other classes of nonlinear systems using other traditional nonlinear observers. One of the advantages of the proposed methods is that a compact time interval is enough to guarantee bounded estimation error.

Impedance Variation and Learning Strategies in Human-Robot Interaction.

In this survey, various concepts and methodologies developed over the past two decades for varying and learning the impedance or admittance of robotic systems that physically interact with humans are explored. For this purpose, the assumptions and mathematical formulations for the online adjustment of impedance models and controllers for physical human-robot interaction (HRI) are categorized and compared. In this systematic review, studies on: 1) variation and 2) learning of appropriate impedance elements are taken into account. These strategies are classified and described in terms of their objectives, points of view (approaches), and signal requirements (including position, HRI force, and electromyography activity). Different methods involving linear/nonlinear analyses (e.g., optimal control design and nonlinear Lyapunov-based stability guarantee) and the Gaussian approximation algorithms (e.g., Gaussian mixture model-based and dynamic movement primitives-based strategies) are reviewed. Current challenges and research trends in physical HRI are finally discussed.

Evaluating Community-Facing Virtual Modalities to Support Complex Neurological Populations During the COVID-19 Pandemic: Protocol for a Mixed Methods Study.

BACKGROUND: The COVID-19 pandemic and concomitant governmental responses have created the need for innovative and collaborative approaches to deliver services, especially for populations that have been inequitably affected. In Alberta, Canada, two novel approaches were created in Spring 2020 to remotely support patients with complex neurological conditions and rehabilitation needs. The first approach is a telehealth service that provides wayfinding and self-management advice to Albertans with physical concerns related to existing neurological or musculoskeletal conditions or post-COVID-19 recovery needs. The second approach is a webinar series aimed at supporting self-management and social connectedness of individuals living with spinal cord injury. OBJECTIVE: The study aims to evaluate the short- and long-term impacts and sustainability of two virtual modalities (telehealth initiative called Rehabilitation Advice Line [RAL] and webinar series called Alberta Spinal Cord Injury Community Interactive Learning Seminars [AB-SCILS]) aimed at advancing self-management, connectedness, and rehabilitation needs during the COVID-19 pandemic and beyond. METHODS: We will use a mixed-methods evaluation approach. Evaluation of the approaches will include one-on-one semistructured interviews and surveys. The evaluation of the telehealth initiative will include secondary data analyses and analysis of call data using artificial intelligence. The evaluation of the webinar series will include analysis of poll questions collected during the webinars and YouTube analytics data. RESULTS: The proposed study describes unique pandemic virtual modalities and our approaches to evaluating them to ensure effectiveness and sustainability. Implementing and evaluating these virtual modalities synchronously allows for the building of knowledge on the complementarity of these methods. At the time of submission, we have completed qualitative and quantitative data collection for the telehealth evaluation. For the webinar series, so far, we have distributed the evaluation survey following three webinars and have conducted five attendee interviews. CONCLUSIONS: Understanding the impact and sustainability of the proposed telehealth modalities is important. The results of the evaluation will provide data that can be actioned and serve to improve other telehealth modalities in the future, since health systems need this information to make decisions on resource allocation, especially in an uncertain pandemic climate. Evaluating the RAL and AB-SCILS to ensure their effectiveness demonstrates that Alberta Health Services and the health system care about ensuring the best practice even after a shift to primarily virtual care. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/28267.