Femoral neck fracture during physical therapy following surface replacement arthroplasty: a preventable complication? A case report

This case report describes two cases of peri-prosthetic fracture during physical therapy in patients who underwent a hip resurfacing, or surface replacement arthroplasty. The fractures occurred with forceful passive combined flexion and external rotation. Functional results were ultimately obtained in both cases, requiring conversion to total hip arthroplasty. Recognizing patient risk factors and cautioning therapists about the possibility of fracture may have prevented these complications

Objective evaluation of expert and novice performance during robotic surgical training tasks

Background - Robotic laparoscopic surgery has revolutionized minimally invasive surgery for the treatment of abdominal pathologies. However, current training techniques rely on subjective evaluation. The authors sought to identify objective measures of robotic surgical performance by comparing novices and experts during three training tasks. Methods - Five novices (medical students) were trained in three tasks with the da Vinci Surgical System. Five experts trained in advanced laparoscopy also performed the three tasks. Time to task completion (TTC), total distance traveled (D), speed (S), curvature (Ƙ), and relative phase (Φ) were measured. Results - Before training, TTC, D, and Ƙ were significantly smaller for experts than for novices (p \u3c 0.05), whereas S was significantly larger for experts than for novices before training (p \u3c 0.05). Novices performed significantly better after training, as shown by smaller TTC, D, and Ƙ, and larger S. Novice performance after training approached expert performance. Conclusion - This study clearly demonstrated the ability of objective kinematic measures to distinguish between novice and expert performance and training effects in the performance of robotic surgical training tasks

Enhanced Robotic Surgical Training Using Augmented Visual Feedback

The goal of this study was to enhance robotic surgical training via real-time augmented visual feedback. Thirty novices (medical students) were divided into 5 feedback groups (speed, relative phase, grip force, video, and control) and trained during 1 session in 3 inanimate surgical tasks with the da Vinci Surgical System. Task completion time, distance traveled, speed, curvature, relative phase, and grip force were measured immediately before and after training and during a retention test 2 weeks after training. All performance measures except relative phase improved after training and were retained after 2 weeks. Feedback-specific effects showed that the speed group was faster than other groups after training, and the grip force group applied less grip force. This study showed that the real-time augmented feedback during training can enhance the surgical performance and can potentially be beneficial for both training and surgery

Electromyographic response is altered during robotic surgical training with augmented feedback

There is a growing prevalence of robotic systems for surgical laparoscopy. We previously developed quantitative measures to assess robotic surgical proficiency, and used augmented feedback to enhance training to reduce applied grip force and increase speed. However, there is also a need to understand the physiological demands of the surgeon during robotic surgery, and if training can reduce these demands. Therefore, the goal of this study was to use clinical biomechanical techniques via electromyography (EMG) to investigate the effects of real-time augmented visual feedback during short-term training on muscular activation and fatigue. Twenty novices were trained in three inanimate surgical tasks with the da Vinci Surgical System. Subjects were divided into five feedback groups (speed, relative phase, grip force, video, and control). Time- and frequency-domain EMG measures were obtained before and after training. Surgical training decreased muscle work as found from mean EMG and EMG envelopes. Grip force feedback further reduced average and total muscle work, while speed feedback increased average muscle work and decreased total muscle work. Training also increased the median frequency response as a result of increased speed and/or reduced fatigue during each task. More diverse motor units were recruited as revealed by increases in the frequency bandwidth post-training. We demonstrated that clinical biomechanics using EMG analysis can help to better understand the effects of training for robotic surgery. Real-time augmented feedback during training can further reduce physiological demands. Future studies will investigate other means of feedback such as biofeedback of EMG during robotic surgery training

Electromyographic response is altered during robotic surgical training with augmented feedback

There is a growing prevalence of robotic systems for surgical laparoscopy. We previously developed quantitative measures to assess robotic surgical proficiency, and used augmented feedback to enhance training to reduce applied grip force and increase speed. However, there is also a need to understand the physiological demands of the surgeon during robotic surgery, and if training can reduce these demands. Therefore, the goal of this study was to use clinical biomechanical techniques via electromyography (EMG) to investigate the effects of real-time augmented visual feedback during short-term training on muscular activation and fatigue. Twenty novices were trained in three inanimate surgical tasks with the da Vinci Surgical System. Subjects were divided into five feedback groups (speed, relative phase, grip force, video, and control). Time- and frequency-domain EMG measures were obtained before and after training. Surgical training decreased muscle work as found from mean EMG and EMG envelopes. Grip force feedback further reduced average and total muscle work, while speed feedback increased average muscle work and decreased total muscle work. Training also increased the median frequency response as a result of increased speed and/or reduced fatigue during each task. More diverse motor units were recruited as revealed by increases in the frequency bandwidth post-training. We demonstrated that clinical biomechanics using EMG analysis can help to better understand the effects of training for robotic surgery. Real-time augmented feedback during training can further reduce physiological demands. Future studies will investigate other means of feedback such as biofeedback of EMG during robotic surgery training

Robotic Surgery and Training: Electromyographic correlates of robotic laparoscopic training

Background: Robotic laparoscopic surgery has been shown to decrease task completion time, reduce errors, and decrease training time when compared to manual laparoscopic surgery. However, current literature has not addressed physiological effects, in particular muscle responses, to training with a robotic surgical system. We seek to determine the frequency response of electromyographic (EMG) signals of specific arm and hand muscles with training using the da Vinci Surgical System (dVSS). Methods: Seven right-handed medical students were trained in three tasks with da Vinci Surgical System over four weeks. These subjects, along with eight controls, were tested before and after training. Electromyographic (EMG) signals were collected from four arm and hand muscles during the testing sessions and the median EMG frequency and bandwidth were computed. Results: The median frequency and frequency bandwidth both increased after training for two of the three tasks. Conclusion: The results suggested that training reduces muscle fatigue as a result of faster and more deliberate movements. These changes occurred predominantly in muscles that were the dominant muscles for each task, whereas the more demanding task recruited more diverse motor units. An evaluation of the physiological demands of robotic laparoscopic surgery using electromyography can provide us with a meaningful quantitative way to examine performance and skill acquisition

\u3ci\u3eMedicine Meets Virtual Reality 14\u3c/i\u3e

Chapter, Real-Time Augmented Feedback Benefits Robotic Laparoscopic Training, co-authored by Nicholas Steriou, UNO faculty member. Machine intelligence will eclipse human intelligence within the next few decades - extrapolating from Moore’s Law - and our world will enjoy limitless computational power and ubiquitous data networks. Today’s iPod® devices portend an era when biology and information technology will fuse to create a human experience radically different from our own. Already, our healthcare system now appears on the verge of crisis; accelerating change is part of the problem. Each technological upgrade demands an investment of education and money, and a costly infrastructure more quickly becomes obsolete. Practitioners can be overloaded with complexity: therapeutic options, outcomes data, procedural coding, drug names etc. Furthermore, an aging global population with a growing sense of entitlement demands that each medical breakthrough be immediately available for its benefit: what appears in the morning paper is expected simultaneously in the doctor’s office. Meanwhile, a third-party payer system generates conflicting priorities for patient care and stockholder returns. The result is a healthcare system stressed by scientific promise, public expectation, economic and regulatory constraints and human limitations. Change is also proving beneficial, of course. Practitioners are empowered by better imaging methods, more precise robotic tools, greater realism in training simulators, and more powerful intelligence networks. The remarkable accomplishments of the IT industry and the Internet are trickling steadily into healthcare. The Medicine Meets Virtual Reality series can readily see the progress of the past fourteen years: more effective healthcare at a lower overall cost, driven by cheaper and better computers.https://digitalcommons.unomaha.edu/facultybooks/1236/thumbnail.jp

Peripheral Arterial Disease Affects the Frequency Response of Ground Reaction Forces During Walking

Background—Walking is problematic for patients with Peripheral Arterial Disease. The purpose of this study was to investigate the frequency domain of the ground reaction forces during walking to further elucidate the ambulatory impairment of these patients. Methods—Nineteen bilateral peripheral arterial disease patients and nineteen controls were included in this study. Subjects were matched for age and gait speed. Participants walked over a force plate sampling at 600Hz. PAD patients were tested before (pain-free condition) after the onset of claudication symptoms (pain). We calculated median frequency, frequency bandwidth, and frequency containing 99.5% of the signal for the vertical and anterior-posterior ground reaction forces. Findings—Our results showed reduced median frequency in the vertical and anterior-posterior components of the ground reaction forces between the control group and both peripheral arterial disease conditions. We found reduced frequency bandwidth in the anterior-posterior direction between controls and the peripheral arterial disease pain-free condition. There were no differences in median frequency or bandwidth between peripheral arterial disease pain-free and pain conditions, but an increase in the frequency content for 99.5% of the signal was observed in the pain condition. Interpretation—Reduced frequency phenomena during gait in peripheral arterial disease patients compared to velocity-matched controls suggests more sluggish activity within the neuromotor system. Increased frequency phenomena due to pain in these patients suggests a more erratic application of propulsive forces when walking. Frequency domain analysis thus offers new insights into the gait impairments associated with this patient population

\u3ci\u3eMedicine Meets Virtual Reality 15\u3c/i\u3e

Chapter, Virtual Reality for Robotic Laparoscopic Surgical Training, co-authored by Nicholas Stergiou, UNO faculty member. Our culture is obsessed with design. Sometimes designers can fuse utility and fantasy to make the mundane appear fresh—a cosmetic repackaging of the same old thing. Because of this, medicine—grounded in the unforgiving realities of the scientific method and peer review, and of flesh, blood, and pain—can sometimes confuse “design” with mere “prettifying.” Design solves real problems, however. This collection of papers underwrites the importance of design for the MMVR community, within three different environments: in vivo, in vitro and in silico. in vivo: we design machines to explore our living bodies. Imaging devices, robots, and sensors move constantly inward, operating within smaller dimensions: system, organ, cell, DNA. in vitro: Using test tubes and Petri dishes, we isolate in vivo to better manipulate and measure biological conditions and reactions. in silico: We step out of the controlled in vitro environment and into a virtual reality. The silica mini-worlds of test tubes and Petri dishes are translated into mini-worlds contained within silicon chips. The future of medicine remains within all three environments: in vivo, in vitro, and in silico. Design is what makes these pieces fit together—the biological, the informational, the physical/material—into something new and more useful.https://digitalcommons.unomaha.edu/facultybooks/1235/thumbnail.jp

Skills Learning in Robot-Assisted Surgery Is Benefited by Task-Specific Augmented Feedback

Background: Providing augmented visual feedback is one way to enhance robot-assisted surgery (RAS) training. However, it is unclear whether task specificity should be considered when applying augmented visual feedback. Methods: Twenty-two novice users of the da Vinci Surgical System underwent testing and training in 3 tasks: simple task, bimanual carrying (BC); intermediate task, needle passing (NP); and complex task, suture tying (ST). Pretraining (PRE), training, and posttraining (POST) trials were performed during the first session. Retention trials were performed 2 weeks later (RET). Participants were randomly assigned to 1 of 4 feedback training groups: relative phase (RP), speed, grip force, and video feedback groups. Performance measures were time to task completion (TTC), total distance traveled (D), speed (S), curvature, relative phase, and grip force (F). Results: Significant interaction for TTC and curvature showed that the RP feedback training improved temporal measures of complex ST task compared to simple BC task. Speed feedback training significantly improved the performance in simple BC task in terms of TTC, D, S, curvature, and F even after retention. There was also a lesser long-term effect of speed feedback training on complex ST task. Grip force feedback training resulted in significantly greater improvements in TTC and curvature for complex ST task. For the video feedback training group, the improvements in most of the outcome measures were evident only after RET. Conclusions: Task-specific augmented feedback is beneficial to RAS skills learning. Particularly, the RP and grip force feedback could be useful for training complex tasks