Article
Engineering, Biomedical
Ann M. Simon, Kristi L. Turner, Laura A. Miller, Benjamin K. Potter, Mark D. Beachler, Gregory A. Dumanian, Levi J. Hargrove, Todd A. Kuiken
Summary: This study is the first multi-user study to investigate the control and use of a multi-grip hand prosthesis at home. It found that participants demonstrated broader usage of grips in pattern recognition compared to direct control. After the home trial, participants showed significant improvements in myoelectric control using pattern recognition.
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING
(2023)
Article
Robotics
Daniele D'Accolti, Francesco Clemente, Andrea Mannini, Enzo Mastinu, Max Ortiz-Catalan, Christian Cipriani
Summary: Decoding human motor intentions through processing electrophysiological signals remains an unsolved challenge for effective upper limb prostheses. This study proposes a method for decoding wrist and hand movements by processing transient electromyographic (EMG) signals, instead of relying on steady-state EMGs. The approach was tested online and showed promising results, with non-amputees displaying a significant learning trend and completing 95% of trials, and the amputee completing about 80% of trials. The outcomes suggest that transient EMG signals could be a viable alternative to steady-state pattern recognition approaches.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2023)
Article
Engineering, Biomedical
Luke E. Osborn, Courtney W. Moran, Matthew S. Johannes, Erin E. Sutton, Jared M. Wormley, Christopher Dohopolski, Michelle J. Nordstrom, Josef A. Butkus, Albert Chi, Paul F. Pasquina, Adam B. Cohen, Brock A. Wester, Matthew S. Fifer, Robert S. Armiger
Summary: The study monitored a participant with a transhumeral amputation using a dexterous Modular Prosthetic Limb controlled through pattern recognition of electromyography (EMG) over one year, showing continuous increase in prosthesis usage, improved functional metrics, and enhanced control performance. The participant was able to control the prosthetic limb efficiently with decreased EMG signal magnitude, demonstrating the potential of advanced prosthesis technology for rehabilitation.
JOURNAL OF NEURAL ENGINEERING
(2021)
Article
Engineering, Biomedical
Christopher Copeland, Claudia Cortes Reyes, Jean L. Peck, Rakesh Srivastava, Jorge M. Zuniga
Summary: This study compared functional outcomes and patient satisfaction between a standard transradial prosthesis and a 3D-printed prosthesis, finding that the 3D printed prosthesis had better functional performance but lower overall patient satisfaction.
BIOMEDICAL ENGINEERING ONLINE
(2022)
Article
Computer Science, Information Systems
Muhammad Usman Qadir, Izhar Ul Haq, Muhammad Awais Khan, Mian Naveed Ahmad, Kamran Shah, Nizar Akhtar
Summary: The study focuses on designing a novel and cost-effective externally powered prosthesis to help amputees transition from body-powered devices. The control system relies on muscle signals acquired through force myography technique. Integration of force-sensitive resistor inside the socket has improved measurement of muscle activity.
Article
Computer Science, Information Systems
Md. Johirul Islam, Shamim Ahmad, Fahmida Haque, Mamun Bin Ibne Reaz, Mohammad A. S. Bhuiyan, Md. Rezaul Islam
Summary: The authors proposed a scheme to normalize EMG signals across channels before feature extraction, significantly enhancing force invariant EMG-PR performance compared to previous studies. The proposed method achieved the highest F1 scores when using different classifiers, suggesting its potential for practical application.
Article
Medicine, General & Internal
Md. Johirul Islam, Shamim Ahmad, Fahmida Haque, Mamun Bin Ibne Reaz, Mohammad Arif Sobhan Bhuiyan, Md. Rezaul Islam
Summary: The improved force-invariant feature extraction method proposed in the study uses nonlinear transformation, changes in amplitude, signal amplitude, and spatial correlation coefficients to extract information from electromyogram signals across different force levels. This method shows higher pattern recognition performance, robustness, and efficiency compared to existing feature extraction methods.
Article
Behavioral Sciences
Chenglin Li, A. Mike Burton, Geza Gergely Ambrus, Gyula Kovacs
Summary: The study reveals that the neural representations of face familiarity emerge between 400-600 msec post-stimulus onset, especially for famous individuals. The correlation between decoding performance and behavioral familiarity was more reliable, occurred earlier and lasted longer when personally familiar faces and viewers' own faces were included in the analysis.
Article
Chemistry, Multidisciplinary
Irati Rasines, Miguel Prada, Viacheslav Bobrov, Dhruv Agrawal, Leire Martinez, Pedro Iriondo, Anthony Remazeilles, Joseph McIntyre
Summary: This study evaluates different combinations of features and algorithms for controlling a prosthetic hand, focusing on detecting intended force variation and gestures in EMG signals from upper-limb amputees. Experiment results show that a logarithmically scaled version of the current window plus previous window achieves the highest classification accuracy, with 88% accuracy for classic features and 89% for TD-PSD features when using LDA as a classifier and majority-voting strategy.
APPLIED SCIENCES-BASEL
(2021)
Article
Computer Science, Artificial Intelligence
Ejay Nsugbe, Ali H. Al-Timemy
Summary: By studying shoulder girdle recognition, it was confirmed that combining EMG and accelerometer signals can improve classification accuracy, providing practical evidence for prosthetic control for amputees, and offering a framework for integrating shoulder motion recognition with neuromuscular reprogramming to ease cognitive burden during the process.
CAAI TRANSACTIONS ON INTELLIGENCE TECHNOLOGY
(2022)
Article
Orthopedics
Brian Kaluf, Michael S. Gart, Bryan J. Loeffler, Glenn Gaston
Summary: This study aimed to investigate whether children and adults with unilateral congenital upper limb amputation can control myoelectric prostheses with multiple degrees of freedom using pattern recognition technology. The results demonstrated that participants successfully calibrated the prostheses with proficiency, and there were no significant differences between their residual and sound limbs. This suggests that individuals with unilateral congenital upper limb amputations can benefit from myoelectric prostheses with pattern recognition control.
JOURNAL OF HAND SURGERY-AMERICAN VOLUME
(2022)
Review
Chemistry, Analytical
Federico Mereu, Francesca Leone, Cosimo Gentile, Francesca Cordella, Emanuele Gruppioni, Loredana Zollo
Summary: The evolution of technological and surgical techniques allows for more intuitive control of multiple joints with advanced prosthetic systems. Targeted Muscle Reinnervation (TMR) is considered an innovative surgical technique for improving prosthetic control for people with different levels of limb amputation.
Article
Engineering, Biomedical
Bin Yang, Chunyuan Shi, Ziqi Liu, Yawen Hu, Ming Cheng, Li Jiang
Summary: This study proposed a method using a fingertip proximity sensor and neural network-based classifier to predict an appropriate grasping pattern for multigrasp prosthesis in transradial amputees. By utilizing fingertip proximity sensing instead of EMG signals, the proposed method achieved a high accuracy of 96% in predicting grasping patterns. Testing on non-disabled subjects and one transradial amputee showed that the proposed method enabled faster completion of reach-and-pick up tasks compared to the traditional EMG methods, reducing the dependency on EMG sources.
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING
(2023)
Article
Computer Science, Artificial Intelligence
Elif Hocaoglu, Volkan Patoglu
Summary: In this paper, a natural human-machine control interface is proposed that achieves tele-impedance control for a variable stiffness transradial hand prosthesis through surface electromyography (sEMG) signals. The interface allows an amputee to modulate the impedance of the prosthetic limb to match task requirements, while controlling the position intentionally. The approach is advantageous as it does not require amputees' attention and does not interfere with intact body segments.
FRONTIERS IN NEUROROBOTICS
(2022)
Article
Engineering, Electrical & Electronic
Shiyu Lin, Yanfei Cao, Zhiqiang Wang, Yan Yan, Tingna Shi, Changliang Xia
Summary: This article proposes a new decoupling 2DOF control structure that reduces the complexity of controller design and parameter tuning and increases the flexibility of controller design. The experimental results confirm the effectiveness of the proposed method.
IEEE TRANSACTIONS ON POWER ELECTRONICS
(2023)