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Evaluating the bone-implant interface (BII) properties of osseointegrated transfemoral (TFA) implants is important for early failure detection and prescribing loads during rehabilitation. The objective of this work is to derive and validate a 1D finite element (FE) model of the Osseointegrated Prosthetic Limb (OPL) TFA system that can: (1) model its dynamic behaviour and (2) extract the BII properties. The model was validated by: (1) comparing the 1D FE formulation to the analytical and 3D FE solutions for a simplified cylinder, (2) comparing the vibration modes of the actual TFA geometry using 1D and 3D FE models, and (3) evaluating the BII properties for three extreme conditions (LOW, INTERMEDIATE, and HIGH) generated using 3D FE and experimental (where the implant was embedded, using different adhesives, in synthetic femurs) signals for additional validation. The modes predicted by the 1D FE model converged to the analytical and the 3D FE solutions for the cylinder. The 1D model also matched the 3D FE solution with a maximum frequency difference of 2.02% for the TFA geometry. Finally, the 1D model extracted the BII stiffness and the system's damping properties for the three conditions generated using the 3D FE simulations and the experimental INTERMEDIATE and HIGH signals. The agreement between the 1D FE and the 3D FE solutions for the TFA geometry indicates that the 1D model captures the system's dynamic behaviour. Distinguishing between the different BII conditions demonstrates the 1D model's potential use for the non-invasive clinical evaluation of the TFA BII properties.
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Upper limb robotic (myoelectric) prostheses are technologically advanced, but challenging to use. In response, substantial research is being done to develop person-specific prosthesis controllers that can predict a user's intended movements. Most studies that test and compare new controllers rely on simple assessment measures such as task scores (e.g., number of objects moved across a barrier) or duration-based measures (e.g., overall task completion time). These assessment measures, however, fail to capture valuable details about: the quality of device arm movements; whether these movements match users' intentions; the timing of specific wrist and hand control functions; and users' opinions regarding overall device reliability and controller training requirements. In this work, we present a comprehensive and novel suite of myoelectric prosthesis control evaluation metrics that better facilitates analysis of device movement details-spanning measures of task performance, control characteristics, and user experience. As a case example of their use and research viability, we applied these metrics in real-time control experimentation. Here, eight participants without upper limb impairment compared device control offered by a deep learning-based controller (recurrent convolutional neural network-based classification with transfer learning, or RCNN-TL) to that of a commonly used controller (linear discriminant analysis, or LDA). The participants wore a simulated prosthesis and performed complex functional tasks across multiple limb positions. Analysis resulting from our suite of metrics identified 16 instances of a user-facing problem known as the "limb position effect". We determined that RCNN-TL performed the same as or significantly better than LDA in four such problem instances. We also confirmed that transfer learning can minimize user training burden. Overall, this study contributes a multifaceted new suite of control evaluation metrics, along with a guide to their application, for use in research and testing of myoelectric controllers today, and potentially for use in broader rehabilitation technologies of the future.
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Miembros Artificiales , Electromiografía , Humanos , Masculino , Femenino , Adulto , Diseño de Prótesis , Extremidad Superior/fisiología , Robótica , Movimiento/fisiología , Redes Neurales de la Computación , Adulto Joven , Aprendizaje ProfundoRESUMEN
Prosthesis rejection is a significant barrier to rehabilitation of persons with upper limb difference. Many individual factors can affect device rejection, including a person's sex or gender. The objective of this narrative review was to explore the reported differences between the sexes and genders in upper limb prosthesis rejection. This review considered peer-reviewed, published research studies in which the study population were adults (aged 18 and older) who had unilateral or bilateral limb difference (any level) of any etiology with current, past, or no history of prosthetic device usage. Using identified keywords, index terms, and a peer-reviewed search filter, the literature was searched in MEDLINE, Embase, and PsycInfo. The reasons for rejection, disuse, or abandonment of prosthetic devices were extracted, with the focus on reported differences between sex and genders. After searching, 29 articles were selected for full-text review and 15 were included. Only 5 of 15 articles examined differences between the sexes. Women tend to reject upper extremity prostheses more than men both before and after being fit with a device; device characteristics, such as weight and cosmesis, do not appear to be appropriately designed for women; and there may not be adequate consideration of the goals for women with limb difference(s). There is inadequate reporting of sex and gender in the literature on prosthesis rejection; future studies should report and explore these factors to determine whether the needs of the full population with limb loss are being met.
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Miembros Artificiales , Extremidad Superior , Humanos , Femenino , Masculino , Factores Sexuales , Diseño de Prótesis , Amputados/rehabilitaciónRESUMEN
Introduction: Bone-anchored prostheses (BAP) are an advanced reconstructive surgical approach for individuals who had transfemoral amputation and are unable to use the conventional socket-suspension systems for their prostheses. Access to this technology has been limited in part due to the lag between the start of a new procedure and the availability of evidence that is required before making decisions about widespread provision. This systematic review presents as a single resource up-to-date information on aspects most relevant to decision makers, i.e., clinical efficacy, safety parameters, patient experiences, and health economic outcomes of this technology. Methods: A systematic search of the literature was conducted by an information specialist in PubMed, MEDLINE, Embase, CINAHL, Cochrane Library, the Core Collection of Web of Science, CADTH's Grey Matters, and Google Scholar up until May 31, 2023. Peer-reviewed original research articles on the outcomes of clinical effectiveness (health-related quality of life, mobility, and prosthesis usage), complications and adverse events, patient experiences, and health economic outcomes were included. The quality of the studies was assessed using the Oxford Centre for Evidence-Based Medicine Levels of Evidence and ROBINS-I, as appropriate. Results: Fifty studies met the inclusion criteria, of which 12 were excluded. Thirty-eight studies were finally included in this review, of which 21 reported on clinical outcomes and complications, 9 case series and 1 cohort study focused specifically on complications and adverse events, and 2 and 5 qualitative studies reported on patient experience and health economic assessments, respectively. The most common study design is a single-arm trial (pre-/post-intervention design) with varying lengths of follow-up. Discussion: The clinical efficacy of this technology is evident in selected populations. Overall, patients reported increased health-related quality of life, mobility, and prosthesis usage post-intervention. The most common complication is a superficial or soft-tissue infection, and more serious complications are rare. Patient-reported experiences have generally been positive. Evidence indicates that bone-anchored implants for prosthesis fixation are cost-effective for those individuals who face significant challenges in using socket-suspension systems, although they may offer no additional advantage to those who are functioning well with their socket-suspended prostheses.
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Virtual reality (VR) technology has advanced significantly in recent years, with many potential applications. However, it is unclear how well VR simulations mimic real-world experiences, particularly in terms of eye-hand coordination. This study compares eye-hand coordination from a previously validated real-world object interaction task to the same task re-created in controller-mediated VR. We recorded eye and body movements and segmented participants' gaze data using the movement data. In the real-world condition, participants wore a head-mounted eye tracker and motion capture markers and moved a pasta box into and out of a set of shelves. In the VR condition, participants wore a VR headset and moved a virtual box using handheld controllers. Unsurprisingly, VR participants took longer to complete the task. Before picking up or dropping off the box, participants in the real world visually fixated the box about half a second before their hand arrived at the area of action. This 500-ms minimum fixation time before the hand arrived was preserved in VR. Real-world participants disengaged their eyes from the box almost immediately after their hand initiated or terminated the interaction, but VR participants stayed fixated on the box for much longer after it was picked up or dropped off. We speculate that the limited haptic feedback during object interactions in VR forces users to maintain visual fixation on objects longer than in the real world, altering eye-hand coordination. These findings suggest that current VR technology does not replicate real-world experience in terms of eye-hand coordination.
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Realidad Virtual , Humanos , Movimiento , Mano , Fijación Ocular , OjoRESUMEN
Position-aware myoelectric prosthesis controllers require long, data-intensive training routines. Transfer Learning (TL) might reduce training burden. A TL model can be pre-trained using forearm muscle signal data from many individuals to become the starting point for a new user. A recurrent convolutional neural network (RCNN)-based classifier has already been shown to benefit from TL in offline analysis (95% accuracy). The present real-time study tested whether an RCNN-based classification controller with TL (RCNN-TL) could reduce training burden, offer improved device control (per functional task performance metrics), and mitigate what is known as the "limb position effect". 27 participants without amputation were recruited. 19 participants performed wrist/hand movements across multiple limb positions, with resulting forearm muscle signal data used to pre-train RCNN-TL. 8 other participants donned a simulated prosthesis, retrained (calibrated) and tested RCNN-TL, plus trained and tested a conventional linear discriminant analysis classification controller (LDA-Baseline). Results confirmed that TL reduces user training burden. RCNN-TL yielded improved task performance durations over LDA-Baseline (in specific Grasp and Release phases), yet other metrics worsened. Overall, this work contributes training condition factors necessary for TL success, identifies metrics needed for comprehensive control analysis, and contributes insights towards improved position-aware control.
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Miembros Artificiales , Músculo Esquelético , Humanos , Electromiografía/métodos , Músculo Esquelético/fisiología , Redes Neurales de la Computación , Aprendizaje AutomáticoRESUMEN
Many clinical measurement tools for balance have ceiling effects. Technology-based assessments using virtual reality systems such as the Computer-Assisted Rehabilitation Environment (CAREN) may provide a way to develop objective, quantitative measures that scale from low to high levels of difficulty. Our objective was to: (1) develop a performance assessment tool (PAT) for the CAREN; (2) quantify the reliability of the tool; (3) validate the scores against clinical balance measures; and (4) compare the scores from a population with balance impairments to those from able-bodied individuals in a cross-sectional validation study. Three games were developed on the CAREN and tested on 49 participants (36 able-bodied and 13 with impaired mobility). For each module, the corresponding measures were transformed into scores using a series of functions such that ceiling and flooring effects would be minimized. The results showed an association between scores and age, an overlap in scores from impaired high-performance individuals and able-bodied low performance individuals, and a correlation of PAT scores with other clinical tests. Several of the limitations of current clinical tools, including floor and ceiling effects, were overcome by the PAT, suggesting that the PAT can be used to monitor the effect of rehabilitation and training.
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Medicina , Humanos , Estudios Transversales , Reproducibilidad de los Resultados , Interfaz Usuario-Computador , TecnologíaRESUMEN
INTRODUCTION: A key determinant of prosthesis use is the quality of fit of the prosthetic socket. The socket surrounds the residual limb and applies the appropriate force distribution to the soft tissues to maintain suspension, support, and stabilization as well as translate limb movement to prosthesis movement. The challenge in socket fabrication lays in achieving geometry that provides the appropriate force distribution at physiologically appropriate locations; a task dependent on the understanding of interface tissue-mechanics. AREAS COVERED: In the last 20 years substantial advancements in sensor innovation and computational power have allowed researchers to quantify the socket-residual limb interface; this paper reviews prominent measurement and sensing techniques described in literature over this time frame. Advantages and short comings of each technique are discussed with a focus on translation to clinical environments. EXPERT OPINION: Prosthetic sockets directly influence comfort, device use, user satisfaction, and tissue health. Advancements in instrumentation technology have unlocked the possibility of sophisticated measurement systems providing quantitative data that may work in tandem with a clinician's heuristic expertise during socket fabrication. If validated, many of the emerging sensing technologies could be implemented into a clinical setting to better characterize how patients interact with their device and help inform prosthesis fabrication and assessment techniques.
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Miembros Artificiales , Implantación de Prótesis , Humanos , Diseño de Prótesis , Fenómenos Mecánicos , Extremidades , Muñones de AmputaciónRESUMEN
BACKGROUND: Osseointegration (OI) is an emerging technique that allows a direct connection between the bone and a titanium metal implant, allowing the direct attachment of bone-anchored prostheses (BAP) to address the problems associated with socket prostheses. This review article aims to compare the biomechanical features of gait when using a transfemoral BAP in comparison to healthy gait, and in comparison to the gait of traditional transfemoral socket prosthesis users. METHODS: A computer-based literature search of electronic databases since inception (ranging from 1967 to 2004 depending on the database) to June 14, 2022, identified peer-reviewed articles focusing on the temporal-spatial, kinematic, kinetic, and electromyography data related to transfemoral BAP gait. Eight articles were included that focused on these biomechanical features of gait in adults with BAP and were compared with socket prosthesis users or healthy gait. RESULTS: Compared with healthy participants, prosthesis users after OI surgery have slower speed and cadence, lower symmetry, longer duration of swing phase, increased pelvic and trunk motion, more hip extension, larger moments on the intact limb, and lower forces on the prosthetic side. Compared with transfemoral socket prosthesis gait, BAP gait shows faster cadence and longer duration of support phase. There are limited and inconsistent data on changes in trunk, pelvic, and hip motion with OI. CONCLUSION: Based on this review, transfemoral BAP improve spatial-temporal parameters closer to normal gait when compared to socket gait, but there are persisting deficits compared with healthy gait. Additional studies are needed to confirm the changes in kinematics and kinetics when walking with a BAP.
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BACKGROUND: Painful conditions such as residual limb pain (RLP) and phantom limb pain (PLP) can manifest after amputation. The mechanisms underlying such postamputation pains are diverse and should be addressed accordingly. Different surgical treatment methods have shown potential for alleviating RLP due to neuroma formation - commonly known as neuroma pain - and to a lesser degree PLP. Two reconstructive surgical interventions, namely targeted muscle reinnervation (TMR) and regenerative peripheral nerve interface (RPNI), are gaining popularity in postamputation pain treatment with promising results. However, these two methods have not been directly compared in a randomised controlled trial (RCT). Here, we present a study protocol for an international, double-blind, RCT to assess the effectiveness of TMR, RPNI, and a non-reconstructive procedure called neuroma transposition (active control) in alleviating RLP, neuroma pain, and PLP. METHODS: One hundred ten upper and lower limb amputees suffering from RLP will be recruited and assigned randomly to one of the surgical interventions (TMR, RPNI, or neuroma transposition) in an equal allocation ratio. Complete evaluations will be performed during a baseline period prior to the surgical intervention, and follow-ups will be conducted in short term (1, 3, 6, and 12 months post-surgery) and in long term (2 and 4 years post-surgery). After the 12-month follow-up, the study will be unblinded for the evaluator and the participants. If the participant is unsatisfied with the outcome of the treatment at that time, further treatment including one of the other procedures will be discussed in consultation with the clinical investigator at that site. DISCUSSION: A double-blind RCT is necessary for the establishment of evidence-based procedures, hence the motivation for this work. In addition, studies on pain are challenging due to the subjectivity of the experience and the lack of objective evaluation methods. Here, we mitigate this problem by including different pain evaluation methods known to have clinical relevance. We plan to analyse the primary variable, mean change in NRS (0-10) between baseline and the 12-month follow-up, using the intention-to-treat (ITT) approach to minimise bias and keep the advantage of randomisation. The secondary outcomes will be analysed on both ITT and per-protocol (PP). An adherence protocol (PP population) analysis will be used for estimating a more realistic effect of treatment. TRIAL REGISTRATION: ClincialTrials.gov NCT05009394.
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Amputados , Neuroma , Miembro Fantasma , Humanos , Miembro Fantasma/diagnóstico , Miembro Fantasma/etiología , Miembro Fantasma/cirugía , Amputación Quirúrgica/efectos adversos , Neuroma/cirugía , Extremidad Inferior , Ensayos Clínicos Controlados Aleatorios como AsuntoRESUMEN
BACKGROUND: The Helen Hayes anatomical model is commonly used in clinical gait analysis with standard medial/lateral knee and thigh markers. METHODS: To quantify soft-tissue artifacts associated with the thigh marker following osseointegration surgery, we added an "implant marker" on the implant extending from the femur, with the objective of identifying the differences in the angular kinematics when using the standard versus implant marker. One female adult with an osseointegrated transfemoral prosthesis walked overground for three trials, and common kinematic measures were calculated from motion capture data. FINDINGS: The results indicated that, when using the thigh marker, a peak of knee varus occurred during the swing phase on the prosthetic side, which is unusual during gait and not feasible for hinge joint prostheses. When using the implant marker, knee varus/valgus was closer to normative. Using the thigh marker, the results showed an internal hip rotation at the start of stance and during the mid and terminal swing phases. In contrast, external hip rotation occurred in both stance and swing phases using the implant marker. Moreover, when selecting the medial knee marker instead of the thigh marker, the angular kinematics and range of motion of knee varus/valgus and hip rotation were comparable to those for the implant marker. INTERPRETATION: This finding suggests that when studying osseointegration gait, using an implant marker will result in more accurate femoral and knee joint motion than using the thigh marker. Changing the selection of markers can reduce the errors of knee varus/valgus and hip kinematics in osseointegrated transfemoral prosthetic gait.
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Prótesis Articulares , Muslo , Adulto , Humanos , Femenino , Fenómenos Biomecánicos , Oseointegración , Articulación de la Rodilla/cirugía , Marcha , Rango del Movimiento ArticularRESUMEN
Advanced upper limb prostheses aim to restore coordinated hand and arm function. However, this objective can be difficult to quantify as coordinated movements require an intact visuomotor system. Eye tracking has recently been applied to study the visuomotor behaviours of upper limb prosthesis users by enabling the calculation of eye movement metrics. This scoping review aims to characterize the visuomotor behaviours of upper limb prosthesis users as described by eye tracking metrics, to summarize the eye tracking metrics used to describe prosthetic behaviour, and to identify gaps in the literature and potential areas for future research. A review of the literature was performed to identify articles that reported eye tracking metrics to evaluate the visual behaviours of individuals using an upper limb prosthesis. Data on the level of amputation, type of prosthetic device, type of eye tracker, primary eye metrics, secondary outcome metrics, experimental task, aims, and key findings were extracted. Seventeen studies were included in this scoping review. A consistently reported finding is that prosthesis users have a characteristic visuomotor behaviour that differs from that of individuals with intact arm function. Visual attention has been reported to be directed more towards the hand and less towards the target during object manipulation tasks. A gaze switching strategy and delay to disengage gaze from the current target has also been reported. Differences in the type of prosthetic device and experimental task have revealed some distinct gaze behaviours. Control factors have been shown to be related to gaze behaviour, while sensory feedback and training interventions have been demonstrated to reduce the visual attention associated with prosthesis use. Eye tracking metrics have also been used to assess the cognitive load and sense of agency of prosthesis users. Overall, there is evidence that eye tracking is an effective tool to quantitatively assess the visuomotor behaviour of prosthesis users and the recorded eye metrics are sensitive to change in response to various factors. Additional studies are needed to validate the eye metrics used to assess cognitive load and sense of agency in upper limb prosthesis users.
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Miembros Artificiales , Humanos , Tecnología de Seguimiento Ocular , Benchmarking , Extremidad Superior , Mano/fisiología , Diseño de PrótesisRESUMEN
BACKGROUND: Virtual 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. METHODS: We 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; [Formula: see text]), the AR control (CGAR; [Formula: see text]), and the experimental group (EG; [Formula: see text]). 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. RESULTS: The 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. CONCLUSION: The 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.
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Amputados , Realidad Aumentada , Humanos , Amputados/rehabilitación , Extremidad Superior , Destreza Motora , Examen FísicoRESUMEN
Upper limb prosthesis users have disruptions in hand-eye coordination, with increased fixations towards the hand and less visual allocation for feedforward planning. The purpose of this study was to explore whether improved motor planning, as reflected by eye gaze behaviour, was associated with more efficient hand movement patterns. Able-bodied participants wore a simulated prosthesis while performing a functional object movement task. Motion and eye tracking data were collected to quantify the eye gaze and hand movement during object interaction. The results of this study demonstrated that the latency of the eye to precede the hand at pick-up was correlated with measures of hand function, including hand variability, movement units, and grasp time, but not reach time. During transport and release, longer latency to disengage gaze from the grasped object and look ahead towards the target was correlated to hand kinematics of hand variability, distance travelled, and transport time. In addition, the latency of the eye to disengage the drop-off location was correlated to release time. Together these may point to control issues with opening and closing the prosthetic hand. Overall, increased feedforward fixations towards the target and reduced feedback fixations towards the hand were related to improved measures of hand function. Hence, coordination between eye and hand movements when using a myoelectric prosthesis may prove to be a useful metric to assess motor planning.
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Movimientos Oculares , Desempeño Psicomotor , Fijación Ocular , Mano , Fuerza de la Mano , Humanos , Movimiento , Extremidad SuperiorRESUMEN
To mitigate the "limb position effect" that hinders myoelectric upper limb prosthesis control, pattern recognition-based models must accurately predict user-intended movements across a multitude of limb positions. Such models can use electromyography (EMG) and inertial measurement units to capture necessary multi-position data. However, this data capture solution requires lengthy user-performed model training routines, with movements in many limb positions, plus retraining thereafter due to inherent signal variations over time. While a general-purpose control model (trained with a dataset that represents numerous device users) eliminates the user-training requirement altogether, it yields low movement predictive accuracy. Conversely, a user-specific control model (trained with a smaller dataset from an individual) yields high predictive accuracy, but requires retraining over time. This study capitalizes on the benefits offered by both such control options, and contributes an alternative control solution-a novel recurrent convolutional neural network (RCNN)-based Composite Model that combines the representation portion of a general-purpose model, with the decision portion of a user-specific model. The resulting Composite Model offers moderate movement predictive accuracy across various limb positions and a reduction in user training routine requirements, suggesting a new research direction to help mitigate the limb position effect along with model training burden.
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Miembros Artificiales , Electromiografía/métodos , Humanos , Movimiento , Redes Neurales de la Computación , Reconocimiento de Normas Patrones Automatizadas/métodosRESUMEN
Assessing gaze behavior during real-world tasks is difficult; dynamic bodies moving through dynamic worlds make gaze analysis difficult. Current approaches involve laborious coding of pupil positions. In settings where motion capture and mobile eye tracking are used concurrently in naturalistic tasks, it is critical that data collection be simple, efficient, and systematic. One solution is to combine eye tracking with motion capture to generate 3D gaze vectors. When combined with tracked or known object locations, 3D gaze vector generation can be automated. Here we use combined eye and motion capture and explore how linear regression models generate accurate 3D gaze vectors. We compare spatial accuracy of models derived from four short calibration routines across three pupil data inputs: the efficacy of calibration routines was assessed, a validation task requiring short fixations on task-relevant locations, and a naturalistic object interaction task to bridge the gap between laboratory and "in the wild" studies. Further, we generated and compared models using spherical and Cartesian coordinate systems and monocular (left or right) or binocular data. All calibration routines performed similarly, with the best performance (i.e., sub-centimeter errors) coming from the naturalistic task trials when the participant is looking at an object in front of them. We found that spherical coordinate systems generate the most accurate gaze vectors with no differences in accuracy when using monocular or binocular data. Overall, we recommend 1-min calibration routines using binocular pupil data combined with a spherical world coordinate system to produce the highest-quality gaze vectors.
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A commonly cited reason for the high abandonment rate of myoelectric prostheses is a lack of grip force sensory feedback. Researchers have attempted to restore grip force sensory feedback by stimulating the residual limb's skin surface in response to the prosthetic hand's measured grip force. Recent work has focused on restoring natural feedback to the missing digits directly through invasive surgical procedures. However, the functional benefit of utilizing somatotopically matching feedback has not been evaluated. In this paper, we propose an experimental protocol centered on a fragile object grasp and lift task using a sensorized myoelectric prosthesis to evaluate sensory feedback techniques. We formalized a suite of outcome measures related to task success, timing, and strategy. A pilot study (n = 3) evaluating the effect of utilizing a somatotopically accurate feedback stimulation location in able-bodied participants was conducted to evaluate the feasibility of the standardized platform, and to inform future studies on the role of feedback stimulation location in prosthesis use. Large between-participant effect sizes were observed in all outcome measures, indicating that the feedback location likely plays a role in myoelectric prosthesis performance. The success rate decreased, and task timing and task focus metrics increased, when using somatotopically-matched feedback compared to non-somatotopically-matched feedback. These results were used to conduct a power analysis, revealing that a sample size of n = 8 would be sufficient to achieve significance in all outcome measures.
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Miembros Artificiales , Retroalimentación , Mano , Humanos , Proyectos Piloto , Diseño de PrótesisRESUMEN
OBJECTIVE: Persons with normal arm function can perform complex wrist and hand movements over a wide range of limb positions. However, for those with transradial amputation who use myoelectric prostheses, control across multiple limb positions can be challenging, frustrating, and can increase the likelihood of device abandonment. In response, the goal of this research was to investigate convolutional neural network (RCNN)-based position-aware myoelectric prosthesis control strategies. METHODS: Surface electromyographic (EMG) and inertial measurement unit (IMU) signals, obtained from 16 non-disabled participants wearing two Myo armbands, served as inputs to RCNN classification and regression models. Such models predicted movements (wrist flexion/extension and forearm pronation/supination), based on a multi-limb-position training routine. RCNN classifiers and RCNN regressors were compared to linear discriminant analysis (LDA) classifiers and support vector regression (SVR) regressors, respectively. Outcomes were examined to determine whether RCNN-based control strategies could yield accurate movement predictions, while using the fewest number of available Myo armband data streams. RESULTS: An RCNN classifier (trained with forearm EMG data, and forearm and upper arm IMU data) predicted movements with 99.00% accuracy (versus the LDA's 97.67%). An RCNN regressor (trained with forearm EMG and IMU data) predicted movements with R2 values of 84.93% for wrist flexion/extension and 84.97% for forearm pronation/supination (versus the SVR's 77.26% and 60.73%, respectively). The control strategies that employed these models required fewer than all available data streams. CONCLUSION: RCNN-based control strategies offer novel means of mitigating limb position challenges. SIGNIFICANCE: This research furthers the development of improved position-aware myoelectric prosthesis control.