An augmented reality home-training system based on the mirror training and imagery approach.
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ABSTRACT:
SUBMITTER: Trojan J
PROVIDER: S-EPMC4105586 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BACKGROUND:Digital rectal examination is a difficult examination to learn and teach because of limited opportunities for practice; however, the main challenge is that students and tutors cannot see the finger when it is palpating the anal canal and prostate gland inside the patients. OBJECTIVE:This paper presents an augmented reality system to be used with benchtop models commonly available in medical schools with the aim of addressing the problem of lack of visualization. The system enables visualization of the examining finger, as well as of the internal organs when performing digital rectal examinations. Magnetic tracking sensors are used to track the movement of the finger, and a pressure sensor is used to monitor the applied pressure. By overlaying a virtual finger on the real finger and a virtual model on the benchtop model, students can see through the examination and finger maneuvers. METHODS:The system was implemented in the Unity game engine (Unity Technologies) and uses a first-generation HoloLens (Microsoft Inc) as an augmented reality device. To evaluate the system, 19 participants (9 clinicians who routinely performed digital rectal examinations and 10 medical students) were asked to use the system and answer 12 questions regarding the usefulness of the system. RESULTS:The system showed the movement of an examining finger in real time with a frame rate of 60 fps on the HoloLens and accurately aligned the virtual and real models with a mean error of 3.9 mm. Users found the movement of the finger was realistic (mean 3.9, SD 1.2); moreover, they found the visualization of the finger and internal organs were useful for teaching, learning, and assessment of digital rectal examinations (finger: mean 4.1, SD 1.1; organs: mean 4.6, SD 0.8), mainly targeting a novice group. CONCLUSIONS:The proposed augmented reality system was designed to improve teaching and learning of digital rectal examination skills by providing visualization of the finger and internal organs. The initial user study proved its applicability and usefulness.
| S-EPMC7453322 | biostudies-literature
Project description:In video surgery, and more specifically in arthroscopy, one of the major problems is positioning the camera and instruments within the anatomic environment. The concept of computer-guided video surgery has already been used in ear, nose, and throat (ENT), gynecology, and even in hip arthroscopy. These systems, however, rely on optical or mechanical sensors, which turn out to be restricting and cumbersome. The aim of our study was to develop and evaluate the accuracy of a navigation system based on electromagnetic sensors in video surgery.We used an electromagnetic localization device (Aurora, Northern Digital Inc., Ontario, Canada) to track the movements in space of both the camera and the instruments. We have developed a dedicated application in the Python language, using the VTK library for the graphic display and the OpenCV library for camera calibration.A prototype has been designed and evaluated for wrist arthroscopy. It allows display of the theoretical position of instruments onto the arthroscopic view with useful accuracy.The augmented reality view represents valuable assistance when surgeons want to position the arthroscope or locate their instruments. It makes the maneuver more intuitive, increases comfort, saves time, and enhances concentration.
| S-EPMC3858680 | biostudies-other
Project description:Key factors positively influencing rehabilitation and functional recovery after spinal cord injury (SCI) include training variety, intensive movement repetition, and motivating training tasks. Systems supporting these aspects may provide profound gains in rehabilitation, independent of the subject's treatment location. In the present study, we test the hypotheses that virtual reality (VR)-augmented training at home (i.e., unsupervised) is feasible with subjects with an incomplete SCI (iSCI) and that it improves motor functions such as lower limb muscle strength, balance, and functional mobility. In the study, 12 chronic iSCI subjects used a home-based, mobile version of a lower limb VR training system. The system included motivating training scenarios and combined action observation and execution. Virtual representations of the legs and feet were controlled via movement sensors. The subjects performed home-based training over 4?weeks, with 16-20 sessions of 30-45?min each. The outcome measures assessed were the Lower Extremity Motor Score (LEMS), Berg Balance Scale (BBS), Timed Up and Go (TUG), Spinal Cord Independence Measure mobility, Walking Index for Spinal Cord Injury II, and 10?m and 6?min walking tests. Two pre-treatment assessment time points were chosen for outcome stability: 4?weeks before treatment and immediately before treatment. At post-assessment (i.e., immediately after treatment), high motivation and positive changes were reported by the subjects (adapted Patients' Global Impression of Change). Significant improvements were shown in lower limb muscle strength (LEMS, P?=?0.008), balance (BBS, P?=?0.008), and functional mobility (TUG, P?=?0.007). At follow-up assessment (i.e., 2-3?months after treatment), functional mobility (TUG) remained significantly improved (P?=?0.005) in contrast to the other outcome measures. In summary, unsupervised exercises at home with the VR training system led to beneficial functional training effects in subjects with chronic iSCI, suggesting that it may be useful as a neurorehabilitation tool. Trial registration:Canton of Zurich ethics committee (EK-24/2009, PB_2016-00545), ClinicalTrials.gov: NCT02149186. Registered 24 April 2014.
| S-EPMC5712347 | biostudies-literature
Project description:The effect of rehabilitative training after stroke is dose-dependent. Out-patient rehabilitation training is often limited by transport logistics, financial resources and a lack of motivation/compliance. We studied the feasibility of an unsupervised arm therapy for self-directed rehabilitation therapy in patients' homes.An open-label, single group study involving eleven patients with hemiparesis due to stroke (27?±?31.5 months post-stroke) was conducted. The patients trained with an inertial measurement unit (IMU)-based virtual reality system (ArmeoSenso) in their homes for six weeks. The self-selected dose of training with ArmeoSenso was the principal outcome measure whereas the Fugl-Meyer Assessment of the upper extremity (FMA-UE), the Wolf Motor Function Test (WMFT) and IMU-derived kinematic metrics were used to assess arm function, training intensity and trunk movement. Repeated measures one-way ANOVAs were used to assess differences in training duration and clinical scores over time.All subjects were able to use the system independently in their homes and no safety issues were reported. Patients trained on 26.5?±?11.5 days out of 42 days for a duration of 137?±?120 min per week. The weekly training duration did not change over the course of six weeks (p?=?0.146). The arm function of these patients improved significantly by 4.1 points (p?=?0.003) in the FMA-UE. Changes in the WMFT were not significant (p?=?0.552). ArmeoSenso based metrics showed an improvement in arm function, a high number of reaching movements (387 per session), and minimal compensatory movements of the trunk while training.Self-directed home therapy with an IMU-based home therapy system is safe and can provide a high dose of rehabilitative therapy. The assessments integrated into the system allow daily therapy monitoring, difficulty adaptation and detection of maladaptive motor patterns such as trunk movements during reaching.Unique identifier: NCT02098135 .
| S-EPMC4982313 | biostudies-literature
Project description:BackgroundHand amputation can have a truly debilitating impact on the life of the affected person. A multifunctional myoelectric prosthesis controlled using pattern classification can be used to restore some of the lost motor abilities. However, learning to control an advanced prosthesis can be a challenging task, but virtual and augmented reality (AR) provide means to create an engaging and motivating training.MethodsIn this study, we present a novel training framework that integrates virtual elements within a real scene (AR) while allowing the view from the first-person perspective. The framework was evaluated in 13 able-bodied subjects and a limb-deficient person divided into intervention (IG) and control (CG) groups. The IG received training by performing simulated clothespin task and both groups conducted a pre- and posttest with a real prosthesis. When training with the AR, the subjects received visual feedback on the generated grasping force. The main outcome measure was the number of pins that were successfully transferred within 20 min (task duration), while the number of dropped and broken pins were also registered. The participants were asked to score the difficulty of the real task (posttest), fun-factor and motivation, as well as the utility of the feedback.ResultsThe performance (median/interquartile range) consistently increased during the training sessions (4/3 to 22/4). While the results were similar for the two groups in the pretest, the performance improved in the posttest only in IG. In addition, the subjects in IG transferred significantly more pins (28/10.5 versus 14.5/11), and dropped (1/2.5 versus 3.5/2) and broke (5/3.8 versus 14.5/9) significantly fewer pins in the posttest compared to CG. The participants in IG assigned (mean ± std) significantly lower scores to the difficulty compared to CG (5.2 ± 1.9 versus 7.1 ± 0.9), and they highly rated the fun factor (8.7 ± 1.3) and usefulness of feedback (8.5 ± 1.7).ConclusionThe results demonstrated that the proposed AR system allows for the transfer of skills from the simulated to the real task while providing a positive user experience. The present study demonstrates the effectiveness and flexibility of the proposed AR framework. Importantly, the developed system is open source and available for download and further development.
| S-EPMC7860185 | biostudies-literature
Project description:Augmented reality (AR), mixed reality (MR), and virtual reality devices are enabling technologies that may facilitate effective communication in healthcare between those with information and knowledge (clinician/specialist; expert; educator) and those seeking understanding and insight (patient/family; non-expert; learner). Investigators initiated an exploratory program to enable the study of AR/MR use-cases in acute care clinical and instructional settings.Academic clinician educators, computer scientists, and diagnostic imaging specialists conducted a proof-of-concept project to 1) implement a core holoimaging pipeline infrastructure and open-access repository at the study institution, and 2) use novel AR/MR techniques on off-the-shelf devices with holoimages generated by the infrastructure to demonstrate their potential role in the instructive communication of complex medical information.The study team successfully developed a medical holoimaging infrastructure methodology to identify, retrieve, and manipulate real patients' de-identified computed tomography and magnetic resonance imagesets for rendering, packaging, transfer, and display of modular holoimages onto AR/MR headset devices and connected displays. Holoimages containing key segmentations of cervical and thoracic anatomic structures and pathology were overlaid and registered onto physical task trainers for simulation-based "blind insertion" invasive procedural training. During the session, learners experienced and used task-relevant anatomic holoimages for central venous catheter and tube thoracostomy insertion training with enhanced visual cues and haptic feedback. Direct instructor access into the learner's AR/MR headset view of the task trainer was achieved for visual-axis interactive instructional guidance.Investigators implemented a core holoimaging pipeline infrastructure and modular open-access repository to generate and enable access to modular holoimages during exploratory pilot stage applications for invasive procedure training that featured innovative AR/MR techniques on off-the-shelf headset devices.
| S-EPMC5785186 | biostudies-literature
Project description:PurposeIn laparoscopic surgery training, experts guide novice physicians to desired instrument positions or indicate relevant areas of interest. These instructions are usually given via verbal communication or using physical pointing devices. To facilitate a sterile work flow and to improve training, new guiding methods are needed. This work proposes to use optical see-through augmented reality to visualize an interactive virtual pointer on the laparoscopic.MethodsAfter an interdisciplinary development, the pointer's applicability and feasibility for training was evaluated and it was compared to a standard condition based on verbal and gestural communication only. In this study, ten surgical trainees were guided by an experienced trainer during cholecystectomies on a laparoscopic training simulator. All trainees completed a virtual cholecystectomy with and without the interactive virtual pointer in alternating order. Measures included procedure time, economy of movement and error rates.ResultsResults of standardized variables revealed significantly improved economy of movement (p = 0.047) and error rates (p = 0.047), as well as an overall improved user performance (Total z-score; p = 0.031) in conditions using the proposed method.ConclusionThe proposed HoloPointer is a feasible and applicable tool for laparoscopic surgery training. It improved objective performance metrics without prolongation of the task completion time in this pre-clinical setup.
| S-EPMC7822765 | biostudies-literature
Project description:BackgroundAugmented reality (AR), a form of 3D imaging technology, has been preliminarily applied in tumor surgery of the head and spine, both are rigid bodies. However, there is a lack of research evaluating the clinical value of AR in tumor surgery of the brachial plexus, a non-rigid body, where the anatomical position varies with patient posture.MethodsPrior to surgery in 8 patients diagnosed with brachial plexus tumors, conventional MRI scans were performed to obtain conventional 2D MRI images. The MRI data were then differentiated automatically and converted into AR-based 3D models. After point-to-point relocation and registration, the 3D models were projected onto the patient's body using a head-mounted display for navigation. To evaluate the clinical value of AR-based 3D models compared to the conventional 2D MRI images, 2 senior hand surgeons completed questionnaires on the evaluation of anatomical structures (tumor, arteries, veins, nerves, bones, and muscles), ranging from 1 (strongly disagree) to 5 (strongly agree).ResultsSurgeons rated AR-based 3D models as superior to conventional MRI images for all anatomical structures, including tumors. Furthermore, AR-based 3D models were preferred for preoperative planning and intraoperative navigation, demonstrating their added value. The mean positional error between the 3D models and intraoperative findings was approximately 1 cm.ConclusionsThis study evaluated, for the first time, the clinical value of an AR-based 3D navigation system in preoperative planning and intraoperative navigation for brachial plexus tumor surgery. By providing more direct spatial visualization, compared with conventional 2D MRI images, this 3D navigation system significantly improved the clinical accuracy and safety of tumor surgery in non-rigid bodies.
| S-EPMC10792838 | biostudies-literature
Project description:This review aims to provide an update on the role of augmented reality (AR) in surgical training and investigate whether the use of AR improves performance measures compared to traditional approaches in surgical trainees.PUBMED, EMBASE, Google Scholar, Cochrane Library, British Library and Science Direct were searched following PRIMSA guidelines. All English language original studies pertaining to AR in surgical training were eligible for inclusion. Qualitative analysis was performed and results were categorised according to simulator models, subsequently being evaluated using Messick's framework for validity and McGaghie's translational outcomes for simulation-based learning.Of the 1132 results retrieved, 45 were included in the study. 29 platforms were identified, with the highest 'level of effectiveness' recorded as 3. In terms of validity parameters, 10 AR models received a strong 'content validity' score of 2.15 models had a 'response processes' score ≥ 1. 'Internal structure' and 'consequences' were largely not discussed. 'Relations to other variables' was the best assessed criterion, with 9 platforms achieving a high score of 2. Overall, the Microsoft HoloLens received the highest level of recommendation for both validity and level of effectiveness.Augmented reality in surgical education is feasible and effective as an adjunct to traditional training. The Microsoft HoloLens has shown the most promising results across all parameters and produced improved performance measures in surgical trainees. In terms of the other simulator models, further research is required with stronger study designs, in order to validate the use of AR in surgical training.
| S-EPMC10331622 | biostudies-literature
Project description:Motor imagery offers an excellent opportunity as a stimulus-free paradigm for brain-machine interfaces. Conventional electroencephalography (EEG) for motor imagery requires a hair cap with multiple wired electrodes and messy gels, causing motion artifacts. Here, a wireless scalp electronic system with virtual reality for real-time, continuous classification of motor imagery brain signals is introduced. This low-profile, portable system integrates imperceptible microneedle electrodes and soft wireless circuits. Virtual reality addresses subject variance in detectable EEG response to motor imagery by providing clear, consistent visuals and instant biofeedback. The wearable soft system offers advantageous contact surface area and reduced electrode impedance density, resulting in significantly enhanced EEG signals and classification accuracy. The combination with convolutional neural network-machine learning provides a real-time, continuous motor imagery-based brain-machine interface. With four human subjects, the scalp electronic system offers a high classification accuracy (93.22 ± 1.33% for four classes), allowing wireless, real-time control of a virtual reality game.
| S-EPMC8498913 | biostudies-literature