Myoelectric Research Articles

Secondary amputation: a qualitative study of quality of life in patients after primary limb salvage surgery and after later ablative sarcoma treatment.

This study focuses on how patients experience the time following amputation after primary limb salvage surgery due to musculoskeletal malignancies. Limb salvage is state of the art in the treatment of musculoskeletal tumours. Nonetheless, in some cases, limb salvage can become problematic over time, resulting in poorer limb function and septic outcomes. This raises the question of whether amputation is indicated sooner rather than later. Patients who have undergone secondary amputation might retrospectively prefer a different approach. Interview study. Patients who underwent primary limb salvage surgery followed by later ablative sarcoma treatment. Semi-structured interviews and the standardized "Prosthetic Limb Users Survey of Mobility" questionnaire were conducted. Interviews were analysed according to Mayring content analysis method. Amputation is perceived as an improvement after a long course of illness with little quality of life. By enhancing the amputation environment and providing detailed information regarding quality of life afterwards, emotional pressure could be reduced and patient satisfaction improved. Surgical options for ablation should be openly communicated earlier when consulting patients experiencing recurrent complications that might eventually lead to amputation. Supporting factors that subsequently may help to improve quality of life after amputation were further identified.

Improved primary stability and load transfer of a customized osseointegrated transfemoral prosthesis compared to a commercial one

BackgroundTransfemoral osseointegrated prostheses, like other uncemented prostheses experience the risk of aseptic loosening and post-operative periprosthetic fractures, with an incidence between 3% and 30%. To date, however, osseointegrated off-the-shelf prostheses are manufactured in a limited number of sizes, and some patients do not meet the strict eligibility criteria of commercial devices. A customized osseointegrated stem was developed and a pre-clinical in vitro investigation of the stem was performed, to evaluate its biomechanical performance.Materials and methodsSix human cadaveric femurs were implanted with commercial stems, while the six contralateral were implanted with customized stems. Three more femurs that did not meet the eligibility criteria for the commercial stems were implanted with the customized stems. Two different loading scenarios (compression-flexion, and torsion) were simulated to measure the primary implant stability and the load transfer. For both loading scenarios, the displacements of the implant with respect to the host bone, and the strains on the bone surface were measured using digital image correlation (DIC). To measure the pull-out force, a tensile force was applied to the prostheses.ResultsThe translational inducible micromotions during the compression-flexion test of the OsteoCustom stem were more than 4 times smaller than the commercial one (p < 0.05). The rotational inducible micromotions of the OsteoCustom stem were more than 3 times smaller than the commercial one (p < 0.05). Similar results were found from the torsional test. The full-field strain distribution of the commercial stem showed a slightly higher strain concentration near the stem tip (maximum principal strain = 1928±127 µɛ) than the OsteoCustom (maximum principal strain = 1758±130 µɛ). Similar results were found for the femurs that did not meet the eligibility criteria for the commercial stems and could be implanted with the OsteoCustom. No statistically significant difference was found in the extraction force between the two groups.Discussion and conclusionThese results support the hypothesis that the OsteoCustom stem can offer better primary stability and load distribution compared to commercial implants. The outcome highlighted the potential benefits of the OsteoCustom prosthesis, which is capable of including a wider range of femoral anatomies than the current standard.

Finite Element Analysis of Custom Designed and Additive Manufactured Total Surface Bearing Prosthesis for Trans-Tibial Amputees

Our limb prostheses aim to restore Activities of Daily Living (ADLs) for amputees, with the socket being a critical component of trans-tibial prostheses influencing both comfort and functionality. Despite technological advancements, challenges such as fit, weight, and durability remain. This study investigates an additive manufacturing method for Total Surface Bearing (TSB) sockets, leveraging CT scans to create a Computer-Aided Design (CAD) and finite element (FE) model. Biomechanical behavior under static loading conditions were analyzed using FE analysis and resistive-based pressure sensors. The study found consistent pressure distribution across the residual limb, with deviations of 8.53 kPa and 4.46 kPa between FE analysis and experimental measurements. Mean pressures of 44.6 kPa and 22.11 kPa were observed under Full Body Weight (FBW) and Half Body Weight (HBW) conditions, respectively. The FE analysis demonstrated a uniform stress distribution in the prosthetic socket, with a maximum stress of 0.15 MPa and a deformation of 0.008 mm, highlighting the effectiveness of this approach in enhancing socket design.

A low-cost transhumeral prosthesis operated via an ML-assisted EEG-head gesture control system.

Objective&#xD;Key challenges in upper limb prosthetics include a lack of effective control systems, the often invasive surgical requirements of brain-controlled limbs, and prohibitive costs. As a result, disuse rates remain high despite potential for increased quality of life. To address these concerns, this project developed a low cost, noninvasive transhumeral neuroprosthesis-operated via a combination of electroencephalography (EEG) signals and head gestures. &#xD;&#xD;Approach&#xD;To address the shortcomings of current noninvasive neural monitoring techniques-namely, single-channel EEG-we leveraged machine learning (ML), creating a neural network-based EEG interpretation algorithm. ML generation was guided by two underlying goals: (1) to improve overall system performance by combining discrete models using a prediction voting scheme, and (2) to favor model diversity within these new neural network ensembles, as opposed to individual model performance. EEG data from eight frequency bands was collected from human subjects to train a machine learning algorithm employing a hierarchical mixture-of-experts (MoE) structure. We also implemented head gesture-based control to assist in the generation of additional stable classes for the control system.&#xD;&#xD;Main Results&#xD;The final model performs competitively with existing EEG interpretation systems. IMU-based head gestures supplement the neural control system, with 270° actuation of synovial elbow and radial wrist joints driven by intuitive corresponding head gestures. The brain-controlled prosthesis presented in this study costs US$300 to manufacture and achieved competitive performance on a Box and Block Test (BBT). &#xD;&#xD;Significance&#xD;These results suggest proof-of-concept for potential application as an alternative to current prosthetics, but it is important to note that the demonstration in this study remains exploratory. Future work includes broader clinical testing and exploring further uses for the developed ML system.

A lightweight prosthetic hand with 19-DOF dexterity and human-level functions

A human hand has 23-degree-of-freedom (DOF) dexterity for managing activities of daily living (ADLs). Current prosthetic hands, primarily driven by motors or pneumatic actuators, fall short in replicating human-level functions, primarily due to limited DOF. Here, we develop a lightweight prosthetic hand that possesses biomimetic 19-DOF dexterity by integrating 38 shape-memory alloy (SMA) actuators to precisely control five fingers and the wrist. The prosthetic hand features real-time sensing of joint angles in each finger, feeding data into a control module for selectively heating or cooling SMA actuators in a closed-loop manner, mimicking the functioning of human muscles. Enabled by the high-power density of SMAs, the hand part (from the wrist to the fingertip) only weighs 0.22 kg, much lower than existing products. We also integrate an onboard power management module that provides electricity for operating the entire system. In addition to 33 standard grasping modes, this prosthetic hand supports 6 advanced grasping modes designed for enhanced dexterity evaluation, expanding the range of achievable ADLs for amputees while facilitating standard prosthesis function tests and validation in real-world scenarios. This innovation offers a significant advancement in prosthetic hand functions, promising improved quality of life for users.

Grasp Pattern Recognition Using Surface Electromyography Signals and Bayesian-Optimized Support Vector Machines for Low-Cost Hand Prostheses

Every year, thousands of people undergo amputations due to trauma or medical conditions. The loss of an upper limb, in particular, has profound physical and psychological consequences for patients. One potential solution is the use of externally powered prostheses equipped with motorized artificial hands. However, these commercially available prosthetic hands are prohibitively expensive for most users. In recent years, advancements in 3D printing and sensor technologies have enabled the design and production of low-cost, externally powered prostheses. This paper presents a pattern-recognition-based human–prosthesis interface that utilizes surface electromyography (sEMG) signals, captured by an affordable device, the Myo armband. A Support Vector Machine (SVM) algorithm, optimized using Bayesian techniques, is trained to classify the user’s intended grasp from among nine common grasping postures essential for daily life activities and functional prosthetic performance. The proposal is viable for real-time implementations on low-cost platforms with 85% accuracy in grasping posture recognition.

3D printable and myoelectrically sensitive hydrogel for smart prosthetic hand control

Surface electromyogram (sEMG) serves as a means to discern human movement intentions, achieved by applying epidermal electrodes to specific body regions. However, it is difficult to obtain high-fidelity sEMG recordings in areas with intricate curved surfaces, such as the body, because regular sEMG electrodes have stiff structures. In this study, we developed myoelectrically sensitive hydrogels via 3D printing and integrated them into a stretchable, flexible, and high-density sEMG electrodes array. This electrode array offered a series of excellent human-machine interface (HMI) features, including conformal adherence to the skin, high electron-to-ion conductivity (and thus lower contact impedance), and sustained stability over extended periods. These attributes render our electrodes more conducive than commercial electrodes for long-term wearing and high-fidelity sEMG recording at complicated skin interfaces. Systematic in vivo studies were used to investigate its efficacy to control a prosthetic hand by decoding sEMG signals from the human hand via a multiple-channel readout circuit and a sophisticated artificial intelligence algorithm. Our findings demonstrate that the 3D printed gel myoelectric sensing system enables real-time and highly precise control of a prosthetic hand.

EMG Dataset for Gesture Recognition with Arm Translation

Myoelectric control has emerged as a promising approach for a wide range of applications, including controlling limb prosthetics, teleoperating robots and enabling immersive interactions in the Metaverse. However, the accuracy and robustness of myoelectric control systems are often affected by various factors, including muscle fatigue, perspiration, drifts in electrode positions and changes in arm position. The latter has received less attention despite its significant impact on signal quality and decoding accuracy. To address this gap, we present a novel dataset of surface electromyographic (EMG) signals captured from multiple arm positions. This dataset, comprising EMG and hand kinematics data from 8 participants performing 6 different hand gestures, provides a comprehensive resource for investigating position-invariant myoelectric control decoding algorithms. We envision this dataset to serve as a valuable resource for both training and benchmark arm position-invariant myoelectric control algorithms. Additionally, to expand the publicly available data capturing the variability of EMG signals across diverse arm positions, we propose a novel data acquisition protocol that can be utilized for future data collection.

Kinematics, kinetics, and muscle activations during human locomotion over compliant terrains

Walking on compliant terrains, like carpets, grass, and soil, presents a unique challenge, especially for individuals with mobility impairments. In contrast to rigid-ground walking, compliant surfaces alter movement dynamics and increase the risk of falls. Understanding and modeling gait control across such soft and deformable surfaces is thus crucial for maintaining daily mobility. However, access to the necessary equipment for modeling compliant surface walking is limited. Therefore, in this paper, we present the first publicly available biomechanics dataset of 20 individuals walking on terrains of varying compliance, using a unique robotic device, the Variable Stiffness Treadmill 2 (VST 2), designed to simulate walking on adjustable compliant terrain. VST 2 provides a consistent and reproducible environment for studying the biomechanics of walking on such surfaces within laboratory settings. The goal of this dataset is to provide insights into the muscular, kinematic, and kinetic adaptations that occur when humans walk on compliant terrain in order to design better controllers for prosthetic limbs, improve rehabilitation protocols, and develop adaptive assistive devices that can enhance mobility on compliant surfaces.

Impact of Antithrombotic Therapy on Thrombotic and Bleeding Complications after Elective Endovascular Repair of Abdominal Aortic Aneurysms.

To investigate the influence of antithrombotic therapy on occurrence of thrombotic and bleeding complications after endovascular aneurysm repair (EVAR). In this retrospective single-center cohort study, patients who underwent elective endovascular aneurysm repair for abdominal aortic aneurysm were categorized into three antithrombotic groups: single antiplatelet therapy (SAPT), anticoagulants, or dual antiplatelet therapy (DAPT). Outcome measures were the incidence of major adverse cardiovascular events (MACE), prosthetic limb occlusions, and bleeding complications during follow-up. Among 616 patients (SAPT: n = 450, anticoagulants: n = 84, and DAPT: n = 82), Kaplan-Meier analysis showed no significant difference (log-rank p = 0.37) in incidence of MACE between patients receiving SAPT (20.9%), anticoagulants (25.0%), and DAPT (14.6%) during a median follow-up of almost 4years. In multivariable Cox regression analysis, only age (HR = 1.03; 95% CI 1.01-1.06, p = 0.01) and American Society of Anesthesiologists (ASA) classification (HR = 1.46; 95% CI 1.12-1.91; p = 0.01) were significant predictors for MACE. Prosthetic limb occlusion was observed in 38 patients during a median follow-up of 4years; incidence between patients receiving SAPT (5.8%), anticoagulants (10.7%), and DAPT (3.7%) was not significantly different (log-rank p = 0.08). Age (HR = 0.96; 95% CI 0.92-1.00; p = 0.03) and use of anticoagulants (HR = 3.79, 95% CI 1.46-9.83; p < 0.01) were significant predictors for prosthetic limb occlusion. Bleeding complications occurred in 73 patients during median follow-up of almost 4years, without significant difference (log rank p = 0.06) in incidence between patients receiving SAPT (10.7%), anticoagulants (19.0%), and DAPT (11.0%). ASA classification (HR = 1.74; 95% CI 1.23-2.46; p < 0.01) was a significant predictor for bleeding complications. Use of anticoagulants after EVAR appears to be associated with a higher risk of prosthetic limb occlusion compared to the use of single or dual antiplatelet therapy.

Merging motoneuron and postural synergies in prosthetic hand design for natural bionic interfacing.

Despite the advances in bionic reconstruction of missing limbs, the control of robotic limbs is still limited and, in most cases, not felt to be as natural by users. In this study, we introduce a control approach that combines robotic design based on postural synergies and neural decoding of synergistic behavior of spinal motoneurons. We developed a soft prosthetic hand with two degrees of actuation that realizes postures in a two-dimensional linear manifold generated by two postural synergies. Through a manipulation task in nine participants without physical impairment, we investigated how to map neural commands to the postural synergies. We found that neural synergies outperformed classic muscle synergies in terms of dimensionality and robustness. Leveraging these findings, we developed an online method to map the decoded neural synergies into continuous control of the two-synergy prosthetic hand, which was tested on 11 participants without physical impairment and three prosthesis users in real-time scenarios. Results demonstrated that combined neural and postural synergies allowed accurate and natural control of coordinated multidigit actions (>90% of the continuous mechanical manifold could be reached). The target hit rate for specific hand postures was higher with neural synergies compared with muscle synergies, with the difference being particularly pronounced for prosthesis users (prosthesis users, 82.5% versus 35.0%; other participants, 79.5% versus 54.5%). This demonstration of codesign of multisynergistic robotic hands and neural decoding algorithms enabled users to achieve natural modular control to span infinite postures across a two-dimensional space and to execute dexterous tasks, including in-hand manipulation, not feasible with other approaches.

Spatiotemporal gait parameters influencing functional mobility of people with lower limb amputation.

Walking speed is a measure of functional mobility that is relatively easy to quantify. In people with lower limb amputation, reduced walking speed has been linked with specific atypical spatiotemporal gait parameters. However, the influence of atypical spatiotemporal gait parameters on the walking speed of people with unilateral transtibial amputation (TTA) and transfemoral amputation (TFA) remains unclear. To identify spatiotemporal gait parameters influencing walking speed of people with unilateral TTA or TFA. Cross-sectional. The 10-meter walk test (10mWT) was used to measure walking speed, and an instrumented walkway was used to record spatiotemporal gait parameters. Regression analyses were used to determine the best subset of spatiotemporal gait parameters that influence the walking speed of people with TTA and TFA. The study included 43 people with TTA and 49 with TFA. In the TTA group, spatiotemporal gait parameters accounted for 65.5% of the variance in walking speed, with prosthetic single limb support accounting for 52.2%, prosthetic terminal double limb support accounting for 8.9%, and stride width accounting for 4.4%. In the TFA group, intact swing accounted for 46.7% of the variance in walking speed. There was no significant difference in walking speed between the TTA and the TFA groups (p > 0.05). The study's results highlight specific spatiotemporal gait parameters that affect the walking speed of people with unilateral TTA and TFA. In addition, results suggest that walking speed over short distances is not confounded by amputation level (i.e., TTA and TFA).

Physical activity patterns following major lower limb amputation

Introduction and aim of study: Lower limb amputation is one of the most common acquired disabilities. The main aim of the study was to assess global trends regarding the procedure, investigate the current trends in post-amputation care, particularly in terms of returning to physical fitness, and identify potential fields of interest in order to improve the everyday life of people with lower limb amputation. Materials and methods: The authors based this review paper on a widespread analysis of scientific articles published in Science Direct, PubMed, UpToDate, Cochrane, Springer, and Google Scholar, the 2021 Global Burden of Disease Study, and government platforms. Results: The collected information emphasizes the existence of numerous barriers discouraging from participating in sports. The post-amputation care is crucial and requires a multidisciplinary team approach. Chronic pain restricts physical activity significantly. Different types of movement focused on specific muscle groups improve functionality. Conclusions: Disability as a result of lower limb amputation is a significant social issue requiring more action to improve its visibility. New strategies ought to be implemented to educate people with disabilities on the importance of physical activity. The new technologies that are currently under investigation may bring some novelty to the topic in the future. Keywords: Amputation, Artificial limbs, Rehabilitation, Para-Sports

Development of a Cable-Driven Bionic Spherical Joint for a Robot Wrist.

Wrist movements play a crucial role in upper-limb motor tasks. As prosthetic and robotic hand technologies have evolved, increasing attention has been focused on replicating the anatomy and functionality of the wrist. Closely imitating the biomechanics and movement mechanisms of human limbs is expected to enhance the overall performance of bionic robotic hands. This study presents the design of a tendon-driven bionic spherical robot wrist, utilizing two pairs of cables that mimic antagonist muscle pairs. The cables are actuated by pulleys driven by servo motors, allowing for two primary wrist motions: flexion-extension and ulnar-radial deviation. The performance Please confirm if the "1583 Iiyama" is necessary. Same as belowof the proposed robot wrist is validated through manipulation experiments using a prototype, demonstrating its capability to achieve a full range of motion for both ulnar and radial deviation. This wrist mechanism is expected to be integrated into robotic systems, enabling greater flexibility and more human-like movement capabilities.

Study of Bionic Tactile Sensors in Flexible Robots

This research investigates the advancement and implementation of bio-inspired tactile and mechanosensory systems, drawing inspiration from sophisticated biological mechanisms found in nature, particularly human sensory networks and the Venus flytrap's rapid response system. The study demonstrates significant progress in developing highly sensitive and precise sensor technologies that effectively mimic natural sensing capabilities. Through innovative material combinations and structural designs, including hybrid graphene-based platforms and advanced piezoelectric tactile arrays, these sensing systems achieve enhanced detection of mechanical forces, subtle vibrations, and environmental fluctuations. The research findings indicate substantial improvements in sensor performance metrics, including response time, sensitivity threshold, and signal-to-noise ratio. Current challenges in manufacturing scalability and cost-effectiveness are addressed, with proposed solutions for large-scale production and seamless system integration. The study outlines promising applications across multiple fields, from advanced prosthetic limbs with enhanced tactile feedback to sophisticated robotic systems capable of precise environmental interaction. Future research directions emphasize the development of more robust and adaptable sensing platforms, focusing on improved durability, reduced power consumption, and enhanced integration capabilities for next-generation biosensing applications.

Assessment of the Oropharyngeal Space Using CBCT and Its Impact on Volume of Airway Prior and after Denture Placement: In Vivo Study.

The current study aimed to assess the oropharyngeal space using cone-beam computed tomography (CBCT) and its effect on airway volume both before and after denture placement. For this investigation, a total of 15 individuals with fully edentulous upper and lower ridges, ranging in age from 40 to 70, were taken into consideration. A recording of the pulmonary function test was made both prior to and following full denture recovery. Prior to finishing denture therapy, the patient underwent a CBCT scan while standing erect and wearing a cephalostat. For one patient, two tomographs were recorded. The initial skull tomography was obtained prior to the rehabilitation of prosthetic limbs. After receiving prosthetic rehabilitation, the second tomograph was taken. On Demand 3D and CS 3D imaging software were used to take the measurements. The maxillary and mandibular complete dentures were fabricated using standardized techniques. Following prosthesis insertion, a CBCT scan of the skull was performed, and the results were recorded and analyzed. The mean oropharyngeal space measurement before and after complete denture rehabilitation was 9.18 mm and 10.20 mm, respectively. It was discovered that there was a statistically significant difference (p = 0.001). The oropharynx's mean volume before complete denture rehabilitation was 5533.50 mm3, and it was 6562.39 mm3 after denture rehabilitation was finished. A statistically significant difference was discovered (p = 0.028). On conclusion, a statistically significant difference was found between the airway volume and oropharyngeal space prior to and following denture rehabilitation. Reducing apnea-hypopnea episodes can be achieved by minimizing pharyngeal collapsibility in patients by providing complete dentures that are created with acceptable and potentially improved vertical dimension of occlusion within the limits of permissible tissues. The CBCT image enables it to be simple to distinguish between empty space and soft tissues. One benefit of wearing a denture while sleeping for edentulous patients with obstructive sleep apnea is that it helps decrease apnea-hypopnea episodes. This happens because wearing a denture causes changes to the soft tissue, pharyngeal airway space, jaw, and tongue positions. How to cite this article: Raj K, Soni M, Hatila S, et al. Assessment of the Oropharyngeal Space Using CBCT and Its Impact on Volume of Airway Prior and after Denture Placement: In Vivo Study. J Contemp Dent Pract 2024;25(10):936-940.

A sensory neuroprosthesis enhances recovery from treadmill-induced stumbles for individuals with lower limb loss

Over 50% of individuals with lower limb loss report a fear of falling and avoiding daily activities partly due to a lack of plantar sensation. Providing direct somatosensory feedback via neural stimulation holds promise for addressing this issue. In this study, three individuals with lower limb loss received a sensory neuroprosthesis (SNP) that provided plantar somatosensory feedback corresponding to prosthesis-floor interactions perceived as arising from the missing foot generated by electrically activating the peripheral nerves in the residuum. Participants walked on a treadmill while receiving perturbations involving brief increases in the belt speed. Perturbations were initiated during early stance and randomly delivered to intact and prosthetic sides with the SNP active or inactive. With the SNP active, participants exhibited decreased trunk angular sway and peak trunk flexion angular velocity during recovery from both prosthetic and intact side perturbations. For prosthetic side perturbations, peak ground reaction force magnitudes decreased when the SNP was active. For intact side perturbations, peak ground reaction force magnitudes increased on the prosthetic side’s first recovery step after the perturbation, which resulted in a more symmetric recovery because the force approached the response on the intact side’s first recovery step following a prosthetic side perturbation. These results suggest participants integrated the feedback from the SNP into their sensorimotor control for maintaining stability and gained confidence in relying on their prosthetic limb during recovery. Restoring plantar sensation with a SNP for individuals with lower limb loss could lead to reduced risk of falling by improving recovery from trips.

Restoration of Genuine Sensation and Proprioception of Individual Fingers Following Transradial Amputation with Targeted Sensory Reinnervation as a Mechanoneural Interface.

Background/Objectives: Tactile gnosis derives from the interplay between the hand's tactile input and the memory systems of the brain. It is the prerequisite for complex hand functions. Impaired sensation leads to profound disability. Various invasive and non-invasive sensory substitution strategies for providing feedback from prostheses have been unsuccessful when translated to clinical practice, since they fail to match the feeling to genuine sensation of the somatosensory cortex. Methods: Herein, we describe a novel surgical technique for upper-limb-targeted sensory reinnervation (ulTSR) and report how single digital nerves selectively reinnervate the forearm skin and restore the spatial sensory capacity of single digits of the amputated hand in a case series of seven patients. We explore the interplay of the redirected residual digital nerves and the interpretation of sensory perception after reinnervation of the forearm skin in the somatosensory cortex by evaluating sensory nerve action potentials (SNAPs), somatosensory evoked potentials (SEPs), and amputation-associated pain qualities. Results: Digital nerves were rerouted and reliably reinnervated the forearm skin after hand amputation, leading to somatotopy and limb maps of the thumb and four individual fingers. SNAPs were obtained from the donor digital nerves after stimulating the recipient sensory nerves of the forearm. Matching SEPs were obtained after electrocutaneous stimulation of the reinnervated skin areas of the forearm where the thumb, index, and little fingers are perceived. Pain incidence was significantly reduced or even fully resolved. Conclusions: We propose that ulTSR can lead to higher acceptance of prosthetic hands and substantially reduce the incidence of phantom limb and neuroma pain. In addition, the spatial restoration of lost-hand sensing and the somatotopic reinnervation of the forearm skin may serve as a machine interface, allowing for genuine sensation and embodiment of the prosthetic hand without the need for complex neural coding adjustments.

Muscle activity mapping by single peak localization from HDsEMG.

Human-machine interfaces using electromyography (EMG) offer promising applications in control of prosthetic limbs, rehabilitation assessment, and assistive technologies. These applications rely on advanced algorithms that decode the activation patterns of muscles contractions. This paper presents a new approach to assess and decode muscle activity by localizing the origin of individual temporal peaks in high-density surface EMG recordings from the dorsal forearm during low force finger extensions. Localization was performed using a surface Gaussian fit applied in the spatial domain to the varying amplitudes across the channels of the electrode grids. Localized EMG peaks were used to estimate different muscle volumes for each finger, showing high consistency across 10 subjects. The results suggest that muscle regions generating each action are highly distinct and indicate potential structural differences of muscle fibres between digits. The estimated volumes were further used to classify individual EMG peaks into each corresponding action. The percentage of correctly classified peaks for each action across 10 participants were 79±18, 84±9, 76±13, and 79±9 percent for index, middle, ring, and little finger extension, respectively. The presented volume analysis provides a new approach to assessing the spatial activation patterns in compact muscle anatomies; and the single peak classification approach opens up possibilities for near-instantaneous identification of muscle activations.

Grasping control using 2D and 3D visual integration for robotic prosthetic hand

Grasping control using 2D and 3D visual integration for robotic prosthetic hand