Virtual Prosthesis Research Articles

Is there a role for acromioplasty and tuberoplasty in reverse shoulder arthroplasty to improve impingement-free range of motion?

Hypothesis and BackgroundLateralizing the center of rotation in reverse shoulder arthroplasty (RSA) decreases the risk of scapular notching due to inferior impingement but may limit range of motion (ROM) in abduction and forward flexion related to superior acromial impingement. Our primary hypothesis was that, using a 3-dimensional (3D) computer model, a virtual acromioplasty (with or without tuberoplasty) could improve abduction and forward flexion following RSA for cuff tear arthritis (CTA) or massive cuff tear. Our secondary hypothesis was that, based on the virtual planning, a surgical acromioplasty could be performed safely during RSA, without increasing the risk of postoperative acromial fracture. MethodsEighty seven patients with CTA scheduled for RSA were analyzed with a 3D software and impingement-free ROM was measured. After virtual prosthesis implantation, early acromio-humeral impingement (abduction ≤ 80° or forward flexion ≤ 120°) was observed in 25% of the cases (22/87). A virtual acromioplasty (with or without tuberoplasty) was then performed and glenohumeral ROM was measured again. Based on this 3D planning, a surgical acromioplasty (with or without tuberoplasty) was performed to improve ROM in the vertical plane in these 22 patients with early acromial impingement. Patients were followed with minimum 24 months of follow-up to assess final shoulder ROM and complications. ResultsAfter virtual acromioplasty alone (n = 11) or acromioplasty with tuberoplasty (n = 11), glenohumeral abduction significantly increased from 75° ± 6.9 before to 89.5° ± 23.4, and forward flexion from 119.3° ± 12 to 135.2° ± 10 (P < .001). After surgical acromioplasty/tuberoplasty, the final mean global forward flexion was 148° ± 5 and mean global abduction 150° ± 8 in these patients. At last follow-up, no acromial fracture was observed. ConclusionIn a 3D model, early acromial impingement may limit abduction (≤80°) or forward flexion (≤120°) after virtual RSA implantation for CTA or massive cuff tear. Virtual acromioplasty (with or without tuberoplasty) shows improved ROM in abduction and flexion. In patients with early impingement, a surgical acromioplasty can be performed safely during RSA, through a deltopectoral approach, without increasing the risk of postoperative acromial fracture.

Implications of EMG channel count: enhancing pattern recognition online prosthetic testing.

Myoelectric pattern recognition systems have shown promising control of upper limb powered prostheses and are now commercially available. These pattern recognition systems typically record from up to 8 muscle sites, whereas other control systems use two-site control. While previous offline studies have shown 8 or fewer sites to be optimal, real-time control was not evaluated. Six individuals with no limb absence and four individuals with a transradial amputation controlled a virtual upper limb prosthesis using pattern recognition control with 8 and 16 channels of EMG. Additionally, two of the individuals with a transradial amputation performed the Assessment for Capacity of Myoelectric Control (ACMC) with a multi-articulating hand and wrist prosthesis with the same channel count conditions. Users had significant improvements in control when using 16 compared to 8 EMG channels including decreased classification error (p = 0.006), decreased completion time (p = 0.019), and increased path efficiency (p = 0.013) when controlling a virtual prosthesis. ACMC scores increased by more than three times the minimal detectable change from the 8 to the 16-channel condition. The results of this study indicate that increasing EMG channel count beyond the clinical standard of 8 channels can benefit myoelectric pattern recognition users.

An Interactive Digital-Twin Model for Virtual Reality Environments to Train in the Use of a Sensorized Upper-Limb Prosthesis

In recent years, the boost in the development of hardware and software resources for building virtual reality environments has fuelled the development of tools to support training in different disciplines. The purpose of this work is to discuss a complete methodology and the supporting algorithms to develop a virtual reality environment to train the use of a sensorized upper-limb prosthesis targeted at amputees. The environment is based on the definition of a digital twin of a virtual prosthesis, able to communicate with the sensors worn by the user and reproduce its dynamic behaviour and the interaction with virtual objects. Several training tasks are developed according to standards, including the Southampton Hand Assessment Procedure, and the usability of the entire system is evaluated, too.

TechnoSapiens: merging humans with technology in augmented reality

We present a marker-less AR/DR system that can replace the arm of the user with a virtual bionic prosthesis in real time including finger tracking. For this, we use a mixed reality HMD that provides the user with a stereo image based on video-see-through (VST). We apply chroma-keying to remove the user’s arm from each captured image and input reconstructed background information into the removed pixels. Before rendering the prosthesis model into the image, we re-target motion capture data of the user’s hand to the kinematic skeleton of the prosthesis to match the current hand pose. This system opens new research possibilities on self- and other-perception of bionic bodies. In a first evaluation study of the system, we propose that users perceive the virtual prosthesis model as a part of their body (i.e., that they experience a sense of ownership). We tested this assumption in a laboratory study with 27 individuals who used the system to perform a series of simple tasks in AR with their prosthesis. We measured body ownership and other measures with self-reports. In support of the hypothesis, users experienced a sense of body ownership. Also, a feeling of self-presence is induced during the task, and participants rated the overall experience as positive.

Limb loading enhances skill transfer between augmented and physical reality tasks during limb loss rehabilitation

BackgroundVirtual and augmented reality (AR) have become popular modalities for training myoelectric prosthesis control with upper-limb amputees. While some systems have shown moderate success, it is unclear how well the complex motor skills learned in an AR simulation transfer to completing the same tasks in physical reality. Limb loading is a possible dimension of motor skill execution that is absent in current AR solutions that may help to increase skill transfer between the virtual and physical domains.MethodsWe implemented an immersive AR environment where individuals could operate a myoelectric virtual prosthesis to accomplish a variety of object relocation manipulations. Intact limb participants were separated into three groups, the load control (CGLD; N=4), the AR control (CGAR; N=4), and the experimental group (EG; N=4). Both the CGAR and EG completed a 5-session prosthesis training protocol in AR while the CGLD performed simple muscle training. The EG attempted manipulations in AR while undergoing limb loading. The CGAR attempted the same manipulations without loading. All participants performed the same manipulations in physical reality while operating a real prosthesis pre- and post-training. The main outcome measure was the change in the number of manipulations completed during the physical reality assessments (i.e. completion rate). Secondary outcomes included movement kinematics and visuomotor behavior.ResultsThe EG experienced a greater increase in completion rate post-training than both the CGAR and CGLD. This performance increase was accompanied by a shorter motor learning phase, the EG’s performance saturating in less sessions of AR training than the CGAR.ConclusionThe results demonstrated that limb loading plays an important role in transferring complex motor skills learned in virtual spaces to their physical reality analogs. While participants who did not receive limb loading were able to receive some functional benefit from AR training, participants who received the loading experienced a greater positive change in motor performance with their performance saturating in fewer training sessions.

Electromyography biofeedback system with visual and vibratory feedbacks designed for lower limb rehabilitation

PurposeOne of the main causes of long-term prosthetic abandonment is the lack of ownership over the prosthesis, which was caused mainly by the absence of sensory information regarding the lost limb. The period where the patient learns how to interact with a prosthetic device is critical in rehabilitation. This ideally happens within the first months after amputation, which is also a period associated with the consolidation of brain changes. Different studies have shown that the introduction of feedback mechanisms can be crucial to bypass the lack of sensorial information. To develop a biofeedback system for the rehabilitation of transfemoral amputees – controlled via electromyographic (EMG) activity from the leg muscles – that can provide real-time visual and/or vibratory feedback for the user.Design/methodology/approachThe system uses surface EMG to control two feedback mechanisms, which are the knee joint of a prosthetic leg of a humanoid avatar in a virtual reality (VR) environment (visual feedback) and a matrix of 16 vibrotactile actuators placed in the back of the user (vibratory feedback). Data acquisition was inside a Faraday Cage using an OpenEphys® acquisition board for the surface EMG recordings. The tasks were performed on able-bodied participants, with no amputation, and for this, the dominant leg of the user was immobilized using an orthopedic boot fixed on the chair, allowing only isometric contractions of target muscles, according to the Surface EMG for Non-Invasive Assessment of Muscles (SENIAM) standard. The authors test the effectiveness of combining vibratory and visual feedback and how task difficulty affects overall performance.FindingsThe authors' results show no negative interference combining both feedback modalities and that performance peaked at the intermediate difficulty. These results provide powerful insights of what can be accomplished with the population of amputee people. By using this biofeedback system, the authors expect to engage another sensory modality in the process of spatial representation of a virtual leg, bypassing the lack of information associated with the disruption of afferent pathways following amputation.Research limitations/implicationsThe authors developed a showcase with a new protocol and feedback mechanisms showing the protocol's safety, efficiency and reliability. However, since this system is designed for patients with leg amputation, the full extent of the effects of the biofeedback training can only be assessed after the evaluation with the amputees, and the results obtained so far establish a safe and operational protocol to accomplish this.Practical implicationsIn this study, the authors proposed a new biofeedback device intended to be used in the preprosthetic rehabilitation phase for people with transfemoral amputation. With this new system, the authors propose a mechanism to bypass the lack of sensory information from a virtual prosthesis and help to assimilate visual and vibrotactile stimuli as a cue for movement representation.Social implicationsWith this new system, the authors propose a mechanism to bypass the lack of sensory information from a virtual prosthesis and help to assimilate visual and vibrotactile stimuli as a cue for movement representation.Originality/valueThe authors' results show that all users were capable of recognizing both feedback modalities, both separate and combined, being able to respond accordingly throughout the tasks. The authors also show that for a one-session protocol, the last difficulty level imposed a greater challenge for most users, explained by the significant drop in performance disregarding the feedback modality. Lastly, the authors believe this paradigm can provide a better process for the embodiment of prosthetic devices, fulfilling the lack of sensory information for the users.

A digital workflow to predict facial aesthetics in patients with maxillofacial trauma with implant retained prostheses.

Purpose To introduce a digital workflow for the prediction of facial aesthetics, especially in patients with dentation deformity caused by maxillofacial trauma.Methods Cone-beam computed tomography (CBCT) and three-dimensional facial scans of patients with radiographic prostheses were collected. The aforementioned data were uploaded to ProPlan CMF software and merged to generate a virtual patient with craniofacial hard tissue, realistic facial soft tissue, and remaining dentition. The radiographic prostheses were scanned to form a digital cast, which was fitted with its CBCT image to create the virtual prostheses. Postoperative facial soft tissue was simulated according to the movement of the virtual prostheses. An appropriate virtual diagnostic prosthesis plan was selected by the patient and dentist. Subsequently, prosthetically driven implant guide and restoration were designed and fabricated.Conclusions A virtual patient was successfully constructed. A 4-mm protrusion of the virtual prosthesis was chosen. Subsequently, implant surgery was performed, and dental prostheses were fabricated based on this location. The fusion of the postoperative facial scan and preoperative facial prediction was found to be coincident. This technique can effectively predict facial aesthetic features of patients with maxillofacial trauma, facilitate communication with patients, reduce chairside time, and guide the multidisciplinary design of implant placement and restoration fabrication.

Learning in a closed-loop brain-machine interface with distributed optogenetic cortical feedback

Objective. Distributed microstimulations at the cortical surface can efficiently deliver feedback to a subject during the manipulation of a prosthesis through a brain-machine interface (BMI). Such feedback can convey vast amounts of information to the prosthesis user and may be key to obtain an accurate control and embodiment of the prosthesis. However, so far little is known of the physiological constraints on the decoding of such patterns. Here, we aimed to test a rotary optogenetic feedback that was designed to encode efficiently the 360° movements of the robotic actuators used in prosthetics. We sought to assess its use by mice that controlled a prosthesis joint through a closed-loop BMI. Approach. We tested the ability of mice to optimize the trajectory of a virtual prosthesis joint in order to solve a rewarded reaching task. They could control the speed of the joint by modulating the activity of individual neurons in the primary motor cortex. During the task, the patterned optogenetic stimulation projected on the primary somatosensory cortex continuously delivered information to the mouse about the position of the joint. Main results. We showed that mice are able to exploit the continuous, rotating cortical feedback in the active behaving context of the task. Mice achieved better control than in the absence of feedback by detecting reward opportunities more often, and also by moving the joint faster towards the reward angular zone, and by maintaining it longer in the reward zone. Mice controlling acceleration rather than speed of the joint failed to improve motor control. Significance. These findings suggest that in the context of a closed-loop BMI, distributed cortical feedback with optimized shapes and topology can be exploited to control movement. Our study has direct applications on the closed-loop control of rotary joints that are frequently encountered in robotic prostheses.

A Virtual Prosthesis for Morality? Experiential Learning through XR Technologies for Autonomy Enhancement of Psychiatric Offenders.

A Virtual Prosthesis for Morality? Experiential Learning through XR Technologies for Autonomy Enhancement of Psychiatric Offenders.

An EMG-Based Deep Learning Approach for Multi-DOF Wrist Movement Decoding

In robotics, decoding complex human movements of multiple degrees of freedom from surface electromyography (sEMG) remains challenging. Recently, the rapid development of artificial intelligence (AI) technology provides a new solution to this problem. In this article, we propose an AI-based framework that consists of a series of deep learning approaches for achieving a precise and robust decoding on three-dimensional (3-D) wrist movements. A previously developed device (wrist movement detector) was utilized to tag the myoelectric signals with 3-D kinematic labels. A public dataset (HIT-SimCo) was established, wherein the sEMG signals were collected from diverse wrist movements and multiple subjects. A lightweight convolutional neural network was constructed, which can extract the motion-related features directly from raw sEMG, and make motion predictions in an end-to-end manner. In addition, several data augmentation strategies were explored to improve the robustness of the model against environmental variations; and a fine-tuning policy was proposed to further improve the subject-specific accuracy. The decoding model was finally tested in three scenarios: a robotic arm&#x002F;hand system performing daily-living tasks (pouring, screwing, etc.), a supernumerary robotic hand playing blocks-building, and a virtual prosthesis conducting motor rehabilitation training.

Improving Automatic Control of Upper-Limb Prosthesis Wrists Using Gaze-Centered Eye Tracking and Deep Learning.

Many upper-limb prostheses lack proper wrist rotation functionality, leading to users performing poor compensatory strategies, leading to overuse or abandonment. In this study, we investigate the validity of creating and implementing a data-driven predictive control strategy in object grasping tasks performed in virtual reality. We propose the idea of using gaze-centered vision to predict the wrist rotations of a user and implement a user study to investigate the impact of using this predictive control. We demonstrate that using this vision-based predictive system leads to a decrease in compensatory movement in the shoulder, as well as task completion time. We discuss the cases in which the virtual prosthesis with the predictive model implemented did and did not make a physical improvement in various arm movements. We also discuss the cognitive value in implementing such predictive control strategies into prosthetic controllers. We find that gaze-centered vision provides information about the intent of the user when performing object reaching and that the performance of prosthetic hands improves greatly when wrist prediction is implemented. Lastly, we address the limitations of this study in the context of both the study itself as well as any future physical implementations.

Extended Reality "X-Reality" for Prosthesis Training of Upper-Limb Amputees: A Review on Current and Future Clinical Potential.

The rejection rates of upper-limb prosthetic devices in adults are high, currently averaging 26% and 23% for body-powered and electric devices, respectively. While many factors influence acceptance, prosthesis training methods relying on novel virtual reality systems have been cited as a critical factor capable of increasing the likelihood of long-term, full-time use. Despite that, these implementations have not yet garnered widespread traction in the clinical setting, and their use remains immaterial. This review aims to explore the reasons behind this situation by identifying trends in existing research that seek to advance Extended Reality "X-Reality" systems for the sake of upper-limb prosthesis rehabilitation and, secondly, analyzing barriers and presenting potential pathways to deployment for successful adoption in the future. The search yielded 42 research papers that were divided into two categories. The first category included articles that focused on the technical aspect of virtual prosthesis training. Articles in the second category utilize user evaluation procedures to ensure applicability in a clinical environment. The review showed that 75% of articles that conducted whole system testing experimented with non-immersive virtual systems. Furthermore, there is a shortage of experiments performed with amputee subjects. From the large-scale studies analyzed, 71% of those recruited solely non-disabled participants. This paper shows that X-Reality technologies for prosthesis rehabilitation of upper-limb amputees carry significant benefits. Nevertheless, much still must be done so that the technology reaches widespread clinical use.

Evaluating the Ability of Congenital Upper Extremity Amputees to Control a Multi-Degree of Freedom Myoelectric Prosthesis

To determine whether children and adults with unilateral congenital upper limb amputation can control myoelectric prostheses with multiple degrees of freedom (DOF) using pattern recognition (PR) technology. Seven participants (age 9-62 years) with unilateral congenital transradial amputation were tested on both their residual and sound side limbs to determine proficiency in controlling a virtual prosthesis using electromyographic signals captured by an array of surface electrodes that were processed using PR technology. Proficiency was measured through a virtual environment game called the target achievement control test, in which the testing protocol asked participants to match increasingly complex prosthesis postures with 1,2, and 3 DOF. All the participants successfully created a PR calibration at 1, 2, and 3 DOF with their residual limb during testing, and no differences in calibration accuracy were observed when comparing the residual versus sound upper limbs. No differences were noted in the mean completion rate on the target achievement control test between the residual and sound limbs. Participants with a congenital upper limb amputation achieved PR control calibration of multi-DOF prostheses with proficiency and quality results of PR calibration that were comparable to those of their sound limb. This capability was observed in children as well as in adults. This demonstrates the potential for children and adults with a unilateral congenital transradial amputation to benefit from myoelectric prostheses with PR control. The results from this study highlight the potential for patients in this population to benefit from myoelectric prostheses with PR control. Persons with unilateral congenital upper limb amputations can be considered for provision of this technology andenrollment in future research activities.

A Wearable Ultrasound System for Sensing Muscular Morphological Deformations

Noninvasive monitoring of muscle contraction, which provides information about muscle morphological deformations, has a great potential in medical applications, such as stroke rehabilitation and prosthesis control. This paper presents a wearable multichannel A-mode ultrasound system for the multiperspective muscle contraction detection against its existing bulky ultrasound sensing counterpart. The system consists of a waveform generator and a waveform amplifier for ultrasound excitation, as well as a signal processing module for echo receiving, amplifying, and transmitting. In addition, a miniaturized transducer was optimized for muscle contraction monitoring using 1-3 piezoelectric composite. The system's superiorities on excitation pulse, detection depth, and axial resolution were validated by the evaluation experiments. And in vivo muscle deformation detection and virtual prosthesis control experiments (target achievement control test) demonstrated its ability in rehabilitation applications, with a task completion rate of 100% and path efficiency of 93.30%. These results confirmed the reliability of the proposed ultrasound system and paved the way for its applications in rehabilitation treatment and prosthesis research.

Comparison of Dexterous Task Performance in Virtual Reality and Real-World Environments

Virtual reality is being used to aid in prototyping of advanced limb prostheses with anthropomorphic behavior and user training. A virtual version of a prosthesis and testing environment can be programmed to mimic the appearance and interactions of its real-world counterpart, but little is understood about how task selection and object design impact user performance in virtual reality and how it translates to real-world performance. To bridge this knowledge gap, we performed a study in which able-bodied individuals manipulated a virtual prosthesis and later a real-world version to complete eight activities of daily living. We examined subjects' ability to complete the activities, how long it took to complete the tasks, and number of attempts to complete each task in the two environments. A notable result is that subjects were unable to complete tasks in virtual reality that involved manipulating small objects and objects flush with the table, but were able to complete those tasks in the real world. The results of this study suggest that standardization of virtual task environment design may lead to more accurate simulation of real-world performance.

A virtual approach to orthopedic systems based on implants and prostheses

In the parameterized virtual environments almost all the joints in the human body have been defined. The geometric models of the bone components were generated from different tomographic images taken from many patients. A revolutionary technique was used to identify the different tissues in the human body, based on the specific shades of gray. Special CAD techniques and specific three-dimensional scanning methods were used whereby the initial “point cloud” was transformed into virtual solids. But, this database, which consists of the joint geometries, can be considered ideal, because the pathology is different for each patient. Different pathological situations were created on these ideal models, which required elements of implant or prosthesis. The surgical techniques specific to each pathological situation were considered, so that the bone components were virtually prepared for virtual prosthesis or implantation. The virtual prosthetic joint was tested using the finite element method for different loads determined under normal situations. These results were compared with those obtained in the normal joint. Finally, different conclusions were pointed out.

Precise tooth preparation technique guided by 3D printing guide plate with quantitative hole

The minimum amount of tooth preparation that can be fully controlled is crucial in achieving long-term, stable, and effective aesthetic restoration, which is also a major difficulty in aesthetic restoration. The tooth preparation can be imple-mented efficiently and accurately through digital technology based on the fixed-deep hole guiding technology. Prior the actual tooth preparation, the technology first designs the virtual contour, layering, and virtual occlusion of the prosthesis on the computer. Then, virtual tooth preparation is carried out by cutting back according to the virtual prosthesis. Next, the virtual drilling operation plan is designed according to the shape of the virtual tooth preparation and the contour of the abutment tooth. Finally, the tooth preparation guide plate is designed and printed in 3D. It realizes the whole process of quantitative and precise guidance of dental preparation, visualizes the restoration space, reduces the clinical operation time, and guarantees the quality of dental preparation. It also promotes the improvement of the teaching quality of digital practical exercises.

Aesthetic restoration of anterior teeth with monolithic self-glazed zirconia crowns via a completely digital workflow: a clinical case report

ABSTRACT This case represents aesthetic restoration by full-contour monolithic zirconia crowns without porcelain veneer via a completely digital workflow. Virtual prostheses were designed following intraoral scanning and digital smile design (DSD) process. Polymethyl methacrylate (PMMA)-based provisional restorations were used and adjusted as guide for aesthetic and occlusal evaluation. Definite self-glazed zirconia crowns were delivered by superimposing the abutment teeth and modified temporary crowns in situ. Such novel zirconia crowns were formed by net-shape manufacturing process following biogeneric copying of the provisional crowns. The restorations represented functionally tailored hierarchical structures exhibiting superior smoothness on the surface without conventional manual work of grinding, polishing and veneering. The application of full-contour monolithic zirconia restorations in the anterior region via a completely digital workflow indicates a reliable treatment option.

Improved Control of a Virtual Prosthesis Using a Pattern Recognition Algorithm and an Interactive Training Environment in a Transhumeral Amputee Demonstrating Local Reinnervation

Contemporary advances in amputation care include the development of myoelectric prostheses. .

Virtual Reality Provides an Effective Platform for Functional Evaluations of Closed-Loop Neuromyoelectric Control.

Although recent advances in neuroprostheses offer opportunities for improved and intuitive control of advanced motorized and sensorized robotic arms, practical complications associated with such hardware can impede the research necessary for clinical translation. These hurdles potentially can be reduced with virtual reality environments (VREs) with embedded physics engines using virtual models of physical robotic hands. These software suites offer several advantages over physical prototypes, including high repeatability, reduced human error, elimination of many secondary sensory cues, and others. There are limited demonstrations of closed-loop prostheses in the VRE, and it is unclear whether VRE performance translates to the physical world. Here we describe how two trans-radial amputees with neural and intramuscular implants identified objects and performed activities of daily living with closed-loop control of prostheses in the VRE. Our initial evidence further suggests that capabilities with virtual prostheses may be predictors of physical prosthesis performance, demonstrating the utility of VREs for neuroprosthetic research.