scholarly journals Real-Time EMG Based Pattern Recognition Control for Hand Prostheses: A Review on Existing Methods, Challenges and Future Implementation

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4596 ◽  
Author(s):  
Nawadita Parajuli ◽  
Neethu Sreenivasan ◽  
Paolo Bifulco ◽  
Mario Cesarelli ◽  
Sergio Savino ◽  
...  
Keyword(s):  
Pattern Recognition ◽  
Real Time ◽  
Upper Limb ◽  
Real World ◽  
Healthcare Sector ◽  
Limb Amputation ◽  
Future Research ◽  
Myoelectric Prosthesis ◽  
Upper Limb Prosthesis ◽  
Maximum Utility

Upper limb amputation is a condition that significantly restricts the amputees from performing their daily activities. The myoelectric prosthesis, using signals from residual stump muscles, is aimed at restoring the function of such lost limbs seamlessly. Unfortunately, the acquisition and use of such myosignals are cumbersome and complicated. Furthermore, once acquired, it usually requires heavy computational power to turn it into a user control signal. Its transition to a practical prosthesis solution is still being challenged by various factors particularly those related to the fact that each amputee has different mobility, muscle contraction forces, limb positional variations and electrode placements. Thus, a solution that can adapt or otherwise tailor itself to each individual is required for maximum utility across amputees. Modified machine learning schemes for pattern recognition have the potential to significantly reduce the factors (movement of users and contraction of the muscle) affecting the traditional electromyography (EMG)-pattern recognition methods. Although recent developments of intelligent pattern recognition techniques could discriminate multiple degrees of freedom with high-level accuracy, their efficiency level was less accessible and revealed in real-world (amputee) applications. This review paper examined the suitability of upper limb prosthesis (ULP) inventions in the healthcare sector from their technical control perspective. More focus was given to the review of real-world applications and the use of pattern recognition control on amputees. We first reviewed the overall structure of pattern recognition schemes for myo-control prosthetic systems and then discussed their real-time use on amputee upper limbs. Finally, we concluded the paper with a discussion of the existing challenges and future research recommendations.

ElectroMyoGram Pattern Recognition for Real-Time Control of Upper Limb Prosthesis

2016 ◽  
Vol 6 (8) ◽  
pp. 1872-1880 ◽  
Author(s):  
Enas Abdulhay ◽  
Ruba Khnouf ◽  
Abeer Bakeir ◽  
Razan Al-Asasfeh ◽  
Heba Khader
Keyword(s):  
Pattern Recognition ◽  
Real Time ◽  
Upper Limb ◽  
Real Time Control ◽  
Time Control ◽  
Upper Limb Prosthesis ◽  
Limb Prosthesis

scholarly journals Intermanual Transfer in Training With an Upper-Limb Myoelectric Prosthesis Simulator: A Mechanistic, Randomized, Pretest-Posttest Study

2013 ◽  
Vol 93 (1) ◽  
pp. 22-31 ◽  
Author(s):  
Sietske Romkema ◽  
Raoul M. Bongers ◽  
Corry K. van der Sluis
Keyword(s):  
Upper Limb ◽  
Force Control ◽  
Movement Time ◽  
Limb Amputation ◽  
Control Group ◽  
Intermanual Transfer ◽  
Initiation Time ◽  
Myoelectric Prosthesis ◽  
Upper Limb Prosthesis ◽  
Experimental Group

BackgroundIntermanual transfer may improve prosthetic handling and acceptance if used in training soon after an amputation.ObjectiveThe purpose of this study was to determine whether intermanual transfer effects can be detected after training with a myoelectric upper-limb prosthesis simulator.DesignA mechanistic, randomized, pretest-posttest design was used.ParticipantsA total of 48 right-handed participants (25 women, 23 men) who were able-bodied were randomly assigned to an experimental group or a control group.InterventionThe experimental group performed a training program of 5 days' duration using the prosthesis simulator. To determine the improvement in skill, a test was administered before, immediately after, and 6 days after training. The control group only performed the tests. Training was performed with the unaffected arm, and tests were performed with the affected arm (the affected arm simulating an amputated limb). Half of the participants were tested with the dominant arm and half with the nondominant arm.MeasurementsInitiation time was defined as the time from starting signal until start of the movement, movement time was defined as the time from the beginning of the movement until completion of the task, and force control was defined as the maximal applied force on a deformable object.ResultsThe movement time decreased significantly more in the experimental group (F2,92=7.42, P=.001, ηG2=.028) when compared with the control group. This finding is indicative of faster handling of the prosthesis. No statistically significant differences were found between groups with regard to initiation time and force control. We did not find a difference in intermanual transfer between the dominant and nondominant arms.LimitationsThe training utilized participants who were able-bodied in a laboratory setting and focused only on transradial amputations.ConclusionsIntermanual transfer was present in the affected arm after training the unaffected arm with a myoelectric prosthesis simulator, and this effect did not depend on laterality. This effect may improve rehabilitation of patients with an upper-limb amputation.

INTELLIGENT UPPER-LIMB PROSTHETIC CONTROL (iULP) WITH NOVEL FEATURE EXTRACTION METHOD FOR PATTERN RECOGNITION USING EMG

2021 ◽  
pp. 2150043
Author(s):  
SIDHARTH PANCHOLI ◽  
AMIT M. JOSHI
Keyword(s):  
Pattern Recognition ◽  
Upper Limb ◽  
Classification Accuracy ◽  
Time Derivative ◽  
Machine Learning Algorithms ◽  
Prosthetic Control ◽  
Myoelectric Prosthesis ◽  
Feature Extraction Method ◽  
Similar Work ◽  
Emg Signal

EMG signal-based pattern recognition (EMG-PR) techniques have gained lots of focus to develop myoelectric prosthesis. The performance of the prosthesis control-based applications mainly depends on extraction of eminent features with minimum neural information loss. The machine learning algorithms have a significant role to play for the development of Intelligent upper-limb prosthetic control (iULP) using EMG signal. This paper proposes a new technique of extracting the features known as advanced time derivative moments (ATDM) for effective pattern recognition of amputees. Four heterogeneous datasets have been used for testing and validation of the proposed technique. Out of the four datasets, three datasets have been taken from the standard NinaPro database and the fourth dataset comprises data collected from three amputees. The efficiency of ATDM features is examined with the help of Davies–Bouldin (DB) index for separability, classification accuracy and computational complexity. Further, it has been compared with similar work and the results reveal that ATDM features have excellent classification accuracy of 98.32% with relatively lower time complexity. The lower values of DB criteria prove the good separation of features belonging to various classes. The results are carried out on 2.6[Formula: see text]GHz Intel core i7 processor with MATLAB 2015a platform.

Neurorehabilitation in Adults With Traumatic Upper Extremity Amputation: A Scoping Review

2021 ◽  
pp. 154596832110702
Author(s):  
Jake Rydland ◽  
Stephanie Spiegel ◽  
Olivia Wolfe ◽  
Bennett Alterman ◽  
John T Johnson ◽  
...  
Keyword(s):  
Upper Extremity ◽  
Upper Limb ◽  
Current Literature ◽  
Scoping Review ◽  
Neural Mechanisms ◽  
Limb Amputation ◽  
Future Research ◽  
Prosthetic Devices ◽  
Scoping Reviews ◽  
Extremity Amputation

Background Most of the current literature around amputation focuses on lower extremity amputation or engineering aspects of prosthetic devices. There is a need to more clearly understand neurobehavioral mechanisms related to upper extremity amputation and how such mechanisms might influence recovery and utilization of prostheses. Objective This scoping review aims to identify and summarize the current literature on adult traumatic upper limb amputation in regard to recovery and functional outcomes and how neuroplasticity might influence these findings. Methods We identified appropriate articles using Academic Search Complete EBSCO, OVID Medline, and Cochrane databases. The resulting articles were then exported, screened, and reviewed based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Scoping Reviews (PRISMA-ScR) guidelines. Results Eleven (11) studies met the study criteria. Of these studies, 7 focused on sensory involvement, 3 focused on neuroplastic changes post-amputation related to functional impact, and 1 study focused on motor control and learning post-amputation. Overall, these studies revealed an incomplete understanding of the neural mechanisms involved in motor rehabilitation in the central and peripheral nervous systems, while also demonstrating the value of an individualized approach to neurorehabilitation in upper limb loss. Conclusions There is a gap in our understanding of the role of neurorehabilitation following amputation. Overall, focused rehabilitation parameters, demographic information, and clarity around central and peripheral neural mechanisms are needed in future research to address neurobehavioral mechanisms to promote functional recovery following traumatic upper extremity amputation.

Can We Induce a Cognitive Representation of a Prosthetic Arm by Means of Crossmodal Stimuli?

2020 ◽  
pp. 1653-1674
Author(s):  
Mateus Franco ◽  
Tiago V. Ortiz ◽  
Henrique A. Amorim ◽  
Jean Faber
Keyword(s):  
Real Time ◽  
Upper Limb ◽  
Tactile Stimulation ◽  
Body Schema ◽  
Cognitive Representation ◽  
Experimental Protocol ◽  
Main Hypothesis ◽  
Upper Limb Prosthesis ◽  
Limb Prosthesis ◽  
Feedback Responses

The ownership feeling of our body occurs mainly due to feedback responses in real-time from environment stimuli to our own body. These constant feedbacks induce a neuronal arrangement, generating a representative map and, consequently, an ownership and unity feeling, named as a body schema. Although there is a relative well knowing of the sensorial mapping about each part of our body, there are still several gaps about how the integration of all this representation is indeed accomplished. Many researchers have shown high rates of prosthesis non-acceptance due to different reasons. Here, the authors discuss an experimental protocol to induce optimally the ownership feeling associated with upper limb prosthesis, by means of a crossmodal vibro-tactile stimulation over the individual's body. The main hypothesis is that through this procedure the participant will extend their proprioception and achieve an ownership feeling of the prosthesis.

Adjustment and Satisfaction with Prosthesis Among People after Upper Limb Amputation in Slovenia

2020 ◽  
Vol 22 (2) ◽  
pp. 85-93
Author(s):  
Klara Šosterič ◽  
Helena Burger ◽  
Gaj Vidmar
Keyword(s):  
Upper Limb ◽  
Limb Amputation ◽  
Cross Sectional ◽  
Upper Limb Amputation ◽  
Upper Limb Prosthesis ◽  
Activity Restrictions ◽  
Univariate Analyses ◽  
Limb Prosthesis ◽  
Large Representative ◽  
Representative Samples

Background. There is a lack of studies on adjustment to upper limb prosthesis with large representative samples that would compare different prosthesis types and use standardised outcome measures. Hence, we wanted to assess satisfaction with, and level of adjustment to, an upper-limb prosthesis among people after an upper limb amputation in our country. Material and methods. We conducted a cross-sectional descriptive study. The TAPES-R questionnaire was mailed to 431 patients identified from electronic health records at national specialist outpatient clinics for rehabilitation of people after upper limb amputation. Results. 191 patients (44%) responded and were subsequently ascertained to be a representative sample of the population of upper limb amputees in our country. Univariate analyses and multiple regression models indicated that, on average, overall satisfaction is lower among those who have received their current prosthesis more recently, women might be more satisfied with prosthesis than men, above-elbow amputees experience more activity restrictions than those with amputation at a lower level, patients with amputated fingers or palm are more satisfied with the prosthesis than others, and so are those who had amputation following an accident as compared to other reasons. Conclusion. We reliably identified some systematic factors, but it is individual factors and experience that largely determine adjustment to and satisfaction with a prosthesis following an upper limb amputation.

Self-Correcting Pattern Recognition System of Surface EMG Signals for Upper Limb Prosthesis Control

2014 ◽  
Vol 61 (4) ◽  
pp. 1167-1176 ◽  
Author(s):  
Sebastian Amsuss ◽  
Peter M. Goebel ◽  
Ning Jiang ◽  
Bernhard Graimann ◽  
Liliana Paredes ◽  
...  
Keyword(s):  
Pattern Recognition ◽  
Upper Limb ◽  
Recognition System ◽  
Surface Emg ◽  
Pattern Recognition System ◽  
Upper Limb Prosthesis ◽  
Prosthesis Control ◽  
Limb Prosthesis

scholarly journals Myoelectric Prosthesis Users and Non-Disabled Individuals Wearing A Simulated Prosthesis Exhibit Similar Compensatory Movement Strategies

2020 ◽  
Author(s):  
Heather E. Williams ◽  
Craig S. Chapman ◽  
Patrick M. Pilarski ◽  
Albert H. Vette ◽  
Jacqueline S. Hebert
Keyword(s):  
Upper Limb ◽  
Performance Metrics ◽  
Upper Body ◽  
Kinematic Data ◽  
Myoelectric Prosthesis ◽  
Myoelectric Prostheses ◽  
Compensatory Movement ◽  
Upper Limb Prosthesis ◽  
Movement Strategies ◽  
Shoulder Motion

Abstract Background: Research studies on upper limb prosthesis function often rely on the use of simulated myoelectric prostheses (attached to and operated by individuals with intact limbs), primarily to increase participant sample size. However, it is not known if these devices elicit the same movement strategies as myoelectric prostheses (operated by individuals with amputation). The objective of this study was to compare compensatory movement strategies, measured by hand and upper body kinematics, of twelve non-disabled individuals wearing a simulated prosthesis to those of three individuals with transradial amputation using their custom-fitted myoelectric devices. Methods: Motion capture was used to obtain kinematic data as participants performed a standardized functional task. Performance metrics, end effector movements and angular kinematics were analyzed. Results: Results show that participants using a simulated or actual myoelectric prosthesis had similar differences in phase durations, hand velocities, hand trajectories, movement units, grip aperture plateaus, and trunk and shoulder motion when compared to normative behaviour. Conclusions: This study suggests that the use of a simulated device in upper limb research offers a reasonable approximation of compensatory movement strategies employed by a novice to mid-skilled transradial myoelectric prosthesis user.

Can We Induce a Cognitive Representation of a Prosthetic Arm by Means of Crossmodal Stimuli?

2017 ◽  
pp. 182-204
Author(s):  
Mateus Franco ◽  
Tiago V. Ortiz ◽  
Henrique A. Amorim ◽  
Jean Faber
Keyword(s):  
Real Time ◽  
Upper Limb ◽  
Tactile Stimulation ◽  
Body Schema ◽  
Cognitive Representation ◽  
Experimental Protocol ◽  
Main Hypothesis ◽  
Upper Limb Prosthesis ◽  
Limb Prosthesis ◽  
Feedback Responses

The ownership feeling of our body occurs mainly due to feedback responses in real-time from environment stimuli to our own body. These constant feedbacks induce a neuronal arrangement, generating a representative map and, consequently, an ownership and unity feeling, named as a body schema. Although there is a relative well knowing of the sensorial mapping about each part of our body, there are still several gaps about how the integration of all this representation is indeed accomplished. Many researchers have shown high rates of prosthesis non-acceptance due to different reasons. Here, the authors discuss an experimental protocol to induce optimally the ownership feeling associated with upper limb prosthesis, by means of a crossmodal vibro-tactile stimulation over the individual's body. The main hypothesis is that through this procedure the participant will extend their proprioception and achieve an ownership feeling of the prosthesis.

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