Article
Psychology, Multidisciplinary
Satoshi Shibuya, Satoshi Unenaka, Yukari Ohki
Summary: The rubber hand illusion is a perceptual illusion that can also occur with delayed visual feedback, causing proprioceptive drift. The study found that hand ownership and localization are caused by distinct multisensory integration processes.
FRONTIERS IN PSYCHOLOGY
(2021)
Article
Neurosciences
Arran T. Reader, Victoria S. Trifonova, H. Henrik Ehrsson
Summary: The study showed that manipulating body ownership through the rubber hand illusion has little impact on basic motor control, as subjective sensations of rubber hand ownership did not convincingly correlate with kinematic variables according to experimental results.
EUROPEAN JOURNAL OF NEUROSCIENCE
(2021)
Article
Chemistry, Analytical
Emre Sariyildiz, Fergus Hanss, Hao Zhou, Manish Sreenivasa, Lucy Armitage, Rahim Mutlu, Gursel Alici
Summary: This study proposes a new hybrid multi-modal sensory feedback system for prosthetic hands that can provide haptic and proprioceptive feedback and facilitate object recognition without vision. The system performance was evaluated in three experiments and showed effectiveness in haptic perception, proprioceptive feedback, and object recognition.
Article
Behavioral Sciences
Arran T. T. Reader, Sara Coppi, Victoria S. S. Trifonova, H. Henrik Ehrsson
Summary: In this study, the researchers attempted to replicate the reduction in MEP amplitude associated with the rubber hand illusion (RHI) and identify the components of the illusion that might explain these changes. Despite participants reporting the presence of the illusion and shifts in perceived real hand position towards the fake limb, no reduction in MEP amplitude was observed.
BRAIN AND BEHAVIOR
(2023)
Article
Psychology, Multidisciplinary
Arran T. Reader, Victoria S. Trifonova, H. Henrik Ehrsson
Summary: The study found that in the rubber hand illusion, participants who reported feeling ownership also tended to report touch referral, showing a moderately strong positive relationship between the two. Touch referral was often reported more strongly and frequently than ownership, indicating implications for the experimental paradigm.
FRONTIERS IN PSYCHOLOGY
(2021)
Article
Neurosciences
Rafael Morand, Tobia Brusa, Nina Schnueriger, Sabrina Catanzaro, Martin Berli, Volker M. Koch
Summary: This study investigates the redirection of force feedback from prosthetic hands to the foot to overcome the drawbacks of adding a feedback system in the prosthetic socket. A vibrotactile insole was developed, and a pilot trial involving experienced users of myoelectric prostheses was conducted. The results showed positive effects in the sorting task with vibrotactile feedback, but varied outcomes in manipulation tasks. The redirection of feedback to the feet aligns with previous studies applied to the residual arm.
FRONTIERS IN NEUROSCIENCE
(2022)
Article
Engineering, Biomedical
Jack Tchimino, Marko Markovic, Jakob Lund Dideriksen, Strahinja Dosen
Summary: This study investigated the impact of cutoff frequency and normalization value on the quality of closed-loop control with EMG feedback. The experiments showed that lower cutoff frequency and higher normalization value resulted in better control performance for EMG feedback, with the optimal combination being 40% MVC and 0.5 Hz cutoff frequency.
JOURNAL OF NEURAL ENGINEERING
(2021)
Article
Biotechnology & Applied Microbiology
Daniele Esposito, Sergio Savino, Emilio Andreozzi, Chiara Cosenza, Vincenzo Niola, Paolo Bifulco
Summary: 3D-printed hand prostheses offer a cost-effective and efficient solution for hand restoration, with muscle contraction monitoring and differential mechanical system for hand control. The force sensor provides advantages over EMG, with fast activation speed and low cost.
BIOENGINEERING-BASEL
(2021)
Article
Multidisciplinary Sciences
Michel Akselrod, Bogdan Vigaru, Julio Duenas, Roberto Martuzzi, James Sulzer, Andrea Serino, Olaf Blanke, Roger Gassert
Summary: This study found that active movement generation has a greater impact on the sense of hand agency compared to the sense of hand ownership. The experimental paradigms utilized were successful in manipulating the sense of hand ownership and agency. Additionally, it was demonstrated that the sense of hand ownership and agency interact beyond their common multisensory basis.
SCIENTIFIC REPORTS
(2021)
Article
Biochemistry & Molecular Biology
Greta Preatoni, Giacomo Valle, Francesco M. Petrini, Stanisa Raspopovic
Summary: The study found that providing intraneural sensory feedback can significantly reduce amputees' perception of prosthetic weight, while increasing embodiment and confidence in walking with the prosthesis. Sensory feedback also helps alleviate the reduction in walking speed and accuracy caused by increased cognitive load.
Article
Chemistry, Analytical
Zhaolong Gao, Rongyu Tang, Qiang Huang, Jiping He
Summary: The study proposed a controller for finger joint angle estimation using sEMG, with training data gathered from a commercial EMG sensor, the Myo armband. Results showed that the proposed model had good performance across all test subjects, demonstrating accuracy and generalization abilities in daily life movements.
Article
Neurosciences
Kota Ataka, Tamami Sudo, Ryoji Otaki, Eizaburo Suzuki, Shin-Ichi Izumi
Summary: Long-term non-use of body parts due to physical dysfunction may decrease the sense of body ownership. This study induced a sense of disownership using the rubber hand illusion and found that disownership led to a decrease in tactile sensitivity.
FRONTIERS IN SYSTEMS NEUROSCIENCE
(2022)
Article
Engineering, Biomedical
Romain Valette, Jose Gonzalez-Vargas, Strahinja Dosen
Summary: This study evaluated the psychometric properties of multichannel electrotactile stimulation during sitting and walking. The results showed that sitting provided better perception of the stimulation compared to walking, which can be affected by motion and physical coupling. Calibration of the stimulation is particularly important for individuals with lower-limb loss.
JOURNAL OF NEUROENGINEERING AND REHABILITATION
(2023)
Article
Computer Science, Artificial Intelligence
Noemi Gozzi, Lorenzo Malandri, Fabio Mercorio, Alessandra Pedrocchi
Summary: This study applies explainable artificial intelligence algorithms to EMG hand gesture classification in order to understand the results of machine learning models in relation to physiological processes. The findings show that AI models recognize hand gestures by mapping and fusing high amplitude activity of synergic muscles, and that classification performance can be improved by reducing the number of electrodes and selecting key features.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Chemistry, Multidisciplinary
Guoying Gu, Ningbin Zhang, Chen Chen, Haipeng Xu, Xiangyang Zhu
Summary: The development and implementation of neuroprosthetic hands aim to replace the sensorimotor function of upper-limb amputees. Soft robotics technology shows promise in addressing design complexity and integration difficulty, especially in personalized applications. This review explores the evolution of neuroprosthetic hands with soft robotics, discussing anthropomorphic design and bidirectional neural interactions. Future opportunities include revolutionized mechanisms, high-performance sensors, and compliant neural-interaction interfaces.
Article
Multidisciplinary Sciences
Nebojsa Malesevic, Anders Bjorkman, Gert S. Andersson, Ana Matran-Fernandez, Luca Citi, Christian Cipriani, Christian Antfolk
Article
Biology
Alexander E. Olsson, Anders Bjorkman, Christian Antfolk
COMPUTERS IN BIOLOGY AND MEDICINE
(2020)
Article
Chemistry, Analytical
Nebojsa Malesevic, Vladimir Petrovic, Minja Belic, Christian Antfolk, Veljko Mihajlovic, Milica Jankovic
Article
Neurosciences
Ulrika Wijk, Ingela K. Carlsson, Christian Antfolk, Anders Bjorkman, Birgitta Rosen
FRONTIERS IN NEUROSCIENCE
(2020)
Article
Engineering, Electrical & Electronic
Pamela Svensson, Christian Antfolk, Nebojsa Malesevic, Fredrik Sebelius
IEEE SENSORS JOURNAL
(2020)
Article
Engineering, Biomedical
Alexander E. Olsson, Nebojsa Malesevic, Anders Bjorkman, Christian Antfolk
Summary: The proposed Myoelectric Representation Learning (MRL) framework outperformed the standard Linear Discriminant Analysis (LDA) framework in terms of online performance metrics and temporal stability when applied to myoelectric control interfaces. The results suggest that MRL can generate stable mappings from EMG to kinematics, enabling real-time myoelectric control with superior performance compared to LDA, indicating its potential practical utility for muscle-computer interfaces.
JOURNAL OF NEUROENGINEERING AND REHABILITATION
(2021)
Article
Multidisciplinary Sciences
Nebojsa Malesevic, Alexander Olsson, Paulina Sager, Elin Andersson, Christian Cipriani, Marco Controzzi, Anders Bjoerkman, Christian Antfolk
Summary: This study aims to provide an annotated database of high-density surface electromyographic signals to aid in designing robust and versatile electromyographic control interfaces for prosthetic hands. Participants performed 65 different hand gestures while various quantitative assessments were conducted to evaluate the quality of the recorded signals, including frequency content analysis, channel crosstalk, and detection of poor skin-electrode contacts.
Article
Chemistry, Analytical
Pamela Svensson, Christian Antfolk, Anders Bjorkman, Nebojsa Malesevic
Summary: This study investigates the use of a microphone and electrotactile feedback to identify various textures. Results show that participants were able to differentiate between textures with an accuracy of 85% using only electrotactile feedback.
Article
Chemistry, Analytical
Nebojsa Malesevic, Anders Bjorkman, Gert S. Andersson, Christian Cipriani, Christian Antfolk
Summary: This paper evaluates fourteen common algorithms for the direct and proportional control of a prosthetic hand. The estimation of forces generated in the hand using different algorithms is compared to the measured forces, providing a baseline performance metric for more advanced algorithms.
Article
Computer Science, Interdisciplinary Applications
Jonathan Lundsberg, Anders Bjorkman, Nebojsa Malesevic, Christian Antfolk
Summary: This study proposes a new automatic decomposition method for high-density surface electromyography (HDsEMG) that can better estimate the distribution of motor unit action potentials (MUAP) and identify more motor units. By using compression and clustering techniques, the method significantly improves the decomposition performance. Validation results demonstrate good performance of the proposed method on both simulated data and experimental data.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2023)
Article
Neurosciences
Robin Rohlen, Christian Antfolk, Christer Gronlund
Summary: This study optimized and evaluated the methods for identifying and analyzing motor units (MUs) using imaging techniques. The results showed that the Haar wavelet transform (HWM) is a better method for estimating spikes compared to the band-pass filter (BPM), as it demonstrated higher agreement with simulated and experimental spikes, as well as less bias and variation.
JOURNAL OF ELECTROMYOGRAPHY AND KINESIOLOGY
(2022)
Article
Physiology
Tanya Subash, Ann David, StephenSukumaran ReetaJanetSurekha, Sankaralingam Gayathri, Selvaraj Samuelkamaleshkumar, Henry Prakash Magimairaj, Nebojsa Malesevic, Christian Antfolk, Varadhan Skm, Alejandro Melendez-Calderon, Sivakumar Balasubramanian
Summary: This study compares and analyzes various measures for quantifying upper limb use and finds that machine learning methods perform better than traditional methods in detecting upper limb use. Additionally, the study reveals the information used by machine learning methods and the influence of data on their performance.
FRONTIERS IN PHYSIOLOGY
(2022)
Proceedings Paper
Engineering, Biomedical
Alexander E. Olsson, Nebojsa Malesevic, Anders Bjorkman, Christian Antfolk
Summary: This study introduces a technique to synthesize electromyography (EMG) data related to multi-degrees of freedom (DoF) motions using generative deep learning models, aiming to simplify the calibration process for multifunctional prosthetic hands. Experimental results show that this method significantly improves the performance of classifiers, demonstrating the potential to simulate real-time training data for multi-articulate motions.
2021 43RD ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE & BIOLOGY SOCIETY (EMBC)
(2021)
Article
Neurosciences
Alexander E. Olsson, Nebojsa Malesevic, Anders Bjoerkman, Christian Antfolk
Summary: Surgically implanted electrodes offer a viable option for long-term acquisition of precise intramuscular electromyography (iEMG) measurements. Different deep learning models show significant advantages in transforming raw forearm iEMG signals into representations correlating with forces exerted at the level of the hand. Among them, the All-to-All and All-to-One strategies outperform the One-to-One strategy.
FRONTIERS IN NEUROSCIENCE
(2021)
Meeting Abstract
Rehabilitation
Nebojsa M. Malesevic, Cheng Feng Wang, Katherine Rich, Christian Antfolk
ASSISTIVE TECHNOLOGY
(2019)
