Article
Engineering, Biomedical
Masahiro Yoshikawa, Kazunori Ogawa, Shunji Yamanaka, Noritaka Kawashima
Summary: This paper presents the Finch, a lightweight prosthetic arm with three opposing fingers controlled by muscle bulge. It is easy to wear and use, and allows for intuitive control based on the degree of muscle contraction. The Finch showed practical functionality in daily activities.
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING
(2023)
Review
Chemistry, Analytical
Siu-Teing Ko, Fredrik Asplund, Begum Zeybek
Summary: This investigation focused on a scoping review of sensor systems in transfemoral sockets to identify potential breakthroughs in improving prosthetic socket design. The study highlighted the importance of interdisciplinary cooperation and open research data generation in advancing sensor design for amputees.
Review
Engineering, Biomedical
Michael Baldock, Nicolaas Pickard, Michael Prince, Sarah Kirkwood, Alix Chadwell, David Howard, Alex Dickinson, Laurence Kenney, Niamh Gill, Sam Curtin
Summary: This paper reviews the designs of adjustable prosthetic sockets and finds that adjustable sockets have become more prevalent in recent years. There are clear differences in design focus between industry and researchers in terms of adjustable range and design principles.
JOURNAL OF NEUROENGINEERING AND REHABILITATION
(2023)
Article
Engineering, Biomedical
Jennifer Olsen, Sarah Day, Sigrid Dupan, Kianoush Nazarpour, Matthew Dyson
Summary: Limited progress has been made in modernising the way upper-limb prosthetic sockets are made, with current techniques still heavily reliant on outdated casting methods and manual labor. While digital methods such as 3D scanning and printing hold promise for improving efficiency and patient satisfaction, challenges exist in implementing them in clinical settings. There is a disconnect between technology developers and the actual needs of clinicians and patients, highlighting the need for expert knowledge to guide the use of digital tools in prosthetic socket manufacturing.
IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING
(2021)
Review
Chemistry, Analytical
Vaheh Nazari, Yong-Ping Zheng
Summary: This paper presents a critical review and comparison of recently published studies on human-machine interface and the use of sonomyography (SMG) for upper limb prosthesis control. The results show that ultrasound sensing can be used as a viable human-machine interface and various ultrasound modes, machine learning algorithms, and feature extraction methods can enhance the accuracy of controlling bionic hands.
Article
Rehabilitation
Tonya L. Rich, Greg Voss, Stuart Fairhurst, Mary Matsumoto, Steven Brielmaier, Karl Koester, Theoden Netoff, Andrew H. Hansen, John E. Ferguson
Summary: This study describes the design and testing of a novel sensor system for measuring distal end weight bearing in prosthetic sockets and alerting users of poor socket fit. The results show consistent relationships between the sensor measurements and socket fit, and users expressed interest in the device, highlighting its potential benefits during early prosthesis training.
DISABILITY AND REHABILITATION
(2023)
Review
Engineering, Mechanical
Kai Xu, Shengfeng Qin
Summary: This review explores the possibilities and challenges of interdisciplinary research in upper limb prosthetic socket design and manufacturing, which is crucial for enhancing the lives of individuals with limb loss. By integrating various fields like engineering, materials science, biomechanics, and healthcare, along with emerging technologies such as 3D printing, artificial intelligence (AI), and virtual reality (VR), interdisciplinary collaboration can promote innovative solutions that meet the diverse needs of users. Despite its immense potential, interdisciplinary research faces challenges in communication, collaboration, and evaluation. This review analyzes relevant case studies and discusses the implications of interdisciplinary research, emphasizing the importance of fostering shared understanding, open communication, and institutional innovation. By examining technological advancements, user satisfaction, and prosthetic device usage in various interdisciplinary research examples, valuable insights and guidance are provided for researchers and professionals aiming to contribute to this transformative field.
Article
Engineering, Biomedical
Florian Grimm, Jelena Kraugmann, Georgios Naros, Alireza Gharabaghi
Summary: The study demonstrated the validity of a device-assisted approach in assessing severely impaired stroke patients' upper limb movements. Shoulder internal/external rotation was found to be a significant predictor in the clinical status, suggesting its relevance in the evaluation of stroke patients. These findings provide a promising new method for assessing severely impaired stroke patients and should be further validated in larger patient cohorts.
JOURNAL OF NEUROENGINEERING AND REHABILITATION
(2021)
Review
Engineering, Electrical & Electronic
Kevin Wendo, Olivier Barbier, Xavier Bollen, Thomas Schubert, Thierry Lejeune, Benoit Raucent, Raphael Olszewski
Summary: Upper limb loss has a significant impact on individuals' personal and professional lives. However, commercial prosthetic devices are often unaffordable or inaccessible to underprivileged individuals. Additive manufacturing, particularly 3D printing, offers a potential solution by providing higher availability and accessibility for prosthetic manufacturing. This study aims to evaluate the current status of reliable open-source upper limb 3D-printed prostheses, highlighting the need for further research to validate their usage and prove their clinical efficacy, as well as the importance of guidelines to unify contributions from different sources.
Article
Materials Science, Multidisciplinary
Minhyeok Ha, Jihun Lee, Yongbeom Cho, Minwoo Lee, Hyunwoo Baek, Jungmin Lee, Jongmin Seo, Sejoon Chun, Kisoo Kim, Jin-Gyun Kim, Won Gu Lee
Summary: This study presents a hybrid upper-arm guided exoskeleton system that combines tangible virtual reality technology, anatomical digital-twin model, and mixed reality remote healthcare monitoring. The device can simulate physical interactions and has the potential to provide tangible metaverse feedback and communication in remote healthcare monitoring in the post-pandemic era.
ADVANCED MATERIALS TECHNOLOGIES
(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
Rehabilitation
Marluce Lopes Basilio, Giane Amorim Ribeiro Samora, Danielle Aparecida Gomes Pereira, Veronica Franco Parreira, Louise Ada, Luci Fuscaldi Teixeira-Salmela
Summary: The study revealed that individuals with stroke had higher energy demand in the paretic upper limb during unilateral arm crank submaximal exercise testing compared to the nonparetic side and controls. There was a strong relationship between energy demand and upper limb activity in stroke patients, indicating the potential impact of energy demand on real-life upper limb activity post-stroke.
ARCHIVES OF PHYSICAL MEDICINE AND REHABILITATION
(2021)
Article
Engineering, Multidisciplinary
Antonio Perez-Gonzalez, Victor Roda-Casanova, Javier Sabater-Gazulla
Summary: Automation of wrist rotations in upper limb prostheses simplifies the human-machine interface and reduces compensatory movements. This study investigated the prediction of wrist rotations in pick-and-place tasks using kinematic information from other arm joints. By recording the position and orientation of the hand, forearm, arm, and back, rotation angles were obtained and used to train feed-forward neural networks (FFNNs) and time-delay neural networks (TDNNs). Correlation coefficients of 0.88 for FFNN and 0.94 for TDNN were achieved. Improvements in correlation were observed when object information or subject-specific training was implemented. These results indicate the feasibility of reducing compensatory movements in prosthetic hands by automating wrist rotations based on kinematic information.
Article
Computer Science, Information Systems
Preet Parag Modi, Md Samiul Haque Sunny, Md Mahafuzur Rahaman Khan, Helal Uddin Ahmed, Mohammad H. Rahman
Summary: This research introduces an interactive telerehabilitation system that integrates the IIoT platform with a robotic manipulator, aiming to provide rehabilitation therapies for individuals with upper limb dysfunctions. The system demonstrates stable communication architecture and low teleoperation latency.
Article
Rheumatology
Susan L. Murphy, Mary Barber, Suiyuan Huang, Maya Sabbagh, Gary Cutter, Dinesh Khanna
Summary: The study examined the effects of two occupational therapy interventions on hand disability in patients with diffuse cutaneous systemic sclerosis, indicating both interventions were beneficial for hand disability. At 18 weeks, participants in the App Alone group showed improvement equal to the Intensive group. The findings support further research into telehealth rehabilitation approaches.
Article
Clinical Neurology
Matthew Stephen Fifer, David P. McMullen, Luke E. Osborn, Tessy M. Thomas, Breanne P. Christie, Robert W. Nickl, Daniel N. Candrea, Eric A. Pohlmeyer, Margaret C. Thompson, Manuel Alejandro Anaya, Wouter Schellekens, Nick F. Ramsey, Sliman J. Bensmaia, William S. Anderson, Brock A. Wester, Nathan E. Crone, Pablo A. Celnik, Gabriela L. Cantarero, Francesco Tenore
Summary: This study demonstrates the possibility of restoring fingertip sensations through intracortical microstimulation, which could be used to control neuroprostheses for object manipulation. The participant was able to reliably identify stimulation sites and perceive the intensity of the stimulation based on the stimulation amplitude.
Article
Clinical Neurology
Breanne Christie, Luke E. Osborn, David P. McMullen, Ambarish S. Pawar, Tessy M. Thomas, Sliman J. Bensmaia, Pablo A. Celnik, Matthew S. Fifer, Francesco Tenore
Summary: This study evaluated the relative latency of intensity-matched vibration and ICMS perception. The results showed that the perception of ICMS lagged behind mechanical stimulation, but the latency differences were small, especially when the stimulus intensities were matched. This suggests that ICMS-based somatosensory feedback is rapid enough to be effective in neuroprosthetic applications.
Article
Engineering, Biomedical
Luke E. Osborn, Courtney W. Moran, Lauren D. Dodd, Erin E. Sutton, Nicolas Norena Acosta, Jared M. Wormley, Connor O. Pyles, Kelles D. Gordge, Michelle J. Nordstrom, Josef A. Butkus, Jonathan A. Forsberg, Paul F. Pasquina, Matthew S. Fifer, Robert S. Armiger
Summary: In this case study, the use of an onboard system to monitor prosthesis usage is demonstrated to provide better understanding of how prostheses are incorporated into daily life, supporting the long-term goal of restoring independence and quality of life for individuals with upper limb amputation.
JOURNAL OF NEURAL ENGINEERING
(2022)
Article
Automation & Control Systems
Dapeng Yang, Hong Liu
Summary: In this article, an AI-based framework is proposed for decoding three-dimensional wrist movements, and it is tested in various scenarios.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2022)
Article
Computer Science, Artificial Intelligence
Chenglong Yu, Zhiqi Li, Dapeng Yang, Hong Liu
Summary: This paper proposes a novel modeling framework based on sparsity and feature learning for approximating inverse dynamics of multi-DOF manipulators. The framework identifies and selects features and their weights from the analytical form of the dynamical equation and improves time and space efficiency using a matrix-free procedure. Experimental results demonstrate the superior performance of the learning framework in torque prediction and control.
JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS
(2022)
Article
Multidisciplinary Sciences
Korine A. Ohiri, Connor O. Pyles, Leslie H. Hamilton, Megan M. Baker, Matthew T. McGuire, Eric Q. Nguyen, Luke E. Osborn, Katelyn M. Rossick, Emil G. McDowell, Leah M. Strohsnitter, Luke J. Currano
Summary: This article presents a novel design for an e-textile based sEMG suit, which utilizes stretchable conductive textiles as electrodes and interconnects. The fabrication process is cost effective and can be done in a typical research environment. The suit provides comparable sEMG signal quality to traditional adhesive electrodes, but with improved comfort and reusability. The embedded electronics allow for signal conditioning and processing to estimate joint movements. The approach is also applicable to other electrophysiological sensors.
SCIENTIFIC REPORTS
(2022)
Article
Multidisciplinary Sciences
Robert W. Nickl, Manuel A. Anaya, Tessy M. Thomas, Matthew S. Fifer, Daniel N. Candrea, David P. McMullen, Margaret C. Thompson, Luke E. Osborn, William S. Anderson, Brock A. Wester, Francesco Tenore, Nathan E. Crone, Gabriela L. Cantarero, Pablo A. Celnik
Summary: The study focused on characterizing the spatial organization and stability of sensorimotor maps in a participant with spinal cord injury using MEAs. Stability of firing strength within electrodes decreased over time, with differences observed between sensory and motor cortex, as well as contralateral and ipsilateral hemispheres. However, no differences were found at the network level, suggesting overall stability in decoding wrist motions.
SCIENTIFIC REPORTS
(2022)
Article
Computer Science, Artificial Intelligence
David A. Handelman, Luke E. Osborn, Tessy M. Thomas, Andrew R. Badger, Margaret Thompson, Robert W. Nickl, Manuel A. Anaya, Jared M. Wormley, Gabriela L. Cantarero, David McMullen, Nathan E. Crone, Brock Wester, Pablo A. Celnik, Matthew S. Fifer, Francesco V. Tenore
Summary: Advancements in intelligent robotic systems and brain-machine interfaces have improved the functionality and independence of individuals with sensorimotor deficits. A collaborative shared control strategy allows for coordinated bimanual movements and fine manipulation tasks.
FRONTIERS IN NEUROROBOTICS
(2022)
Article
Engineering, Electrical & Electronic
Le Qi, Dapeng Yang, Baoshi Cao, Zhiqi Li, Hong Liu
Summary: The study proposes a ring-type bearingless torque sensor (RBL-TS) structure design and data fusion method, which effectively reduces crosstalk error and increases flexural stiffness. The structure is simple and can be easily integrated into modular robot joints with various speed reducers. The proposed data fusion method further reduces crosstalk error and avoids crosstalk anisotropy of the flexural moments, making RBL-TS suitable for use in robot joints without CRBs.
IEEE SENSORS JOURNAL
(2022)
Article
Robotics
Liangliang Zhao, Jingdong Zhao, Ziyi Liu, Dapeng Yang, Hong Liu
Summary: This paper presents a novel algorithm for real-time motion planning of non-holonomic robots in dynamic scenes. The algorithm decomposes the robot and obstacles into superquadric objects and uses expanded Minkowski sums to construct the velocity obstacle. It also extends to collision avoidance for different types and numbers of obstacles.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Article
Automation & Control Systems
XueAi Li, Honghao Yue, Dapeng Yang, Kui Sun, Hong Liu
Summary: This article presents a lightweight and portable inflatable robotic arm (IRA) for inspecting sensitive environments. The IRA utilizes antagonist pneumatic artificial muscles to achieve 10 degrees of freedom and employs a custom-designed joystick input interface for human-in-the-loop teleoperation. Experimental results demonstrate the promising performance of the developed IRA.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Surgery
Baoshan Niu, Dapeng Yang, Peng Wang, Haonan Yang, Le Zhang, Yikun Gu, Li Jiang
Summary: This paper proposes an improved artificial potential field method that uses an artificial neural network to predict the target position, guiding the operator to track the optimal scanning plane in tumor surgery. Experimental results show that this method effectively reduces trajectory redundancy, shortens the time of OSP discovery and tracking, and decreases the deviation between the scanning position and the OSP. The method is significant for accurate localization and successful removal of tumors.
INTERNATIONAL JOURNAL OF MEDICAL ROBOTICS AND COMPUTER ASSISTED SURGERY
(2023)
Article
Computer Science, Interdisciplinary Applications
Chunhao Peng, Dapeng Yang, Zhe Ge, Hong Liu
Summary: Incorporating an electrically powered wrist improves the dexterity of a prosthetic hand but also increases the difficulty of its operation. This paper explores the concept of multi-joint synergy in human body movements to address this issue. The study collects and analyzes upper-limb joint angles, establishes a regression model to predict wrist rotation angle, and conducts experiments to evaluate task completion time and compensatory movements. The results demonstrate that the synergy-based wrist autonomy method effectively enhances efficiency and reduces compensatory movements compared to traditional prostheses.
MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING
(2023)
Article
Robotics
Chunyuan Shi, Dapeng Yang, Siyang Qiu, Jingdong Zhao
Summary: We propose an eye-tracking based grasp switching interface (i-GSI) that integrates augmented reality to enable the control of multi-grasp prosthetic hands. The interface is implemented in HoloLens 2 and allows users to switch between six grasp types by simply glancing at GazeButtons. Experimental results demonstrate its successful performance and adaptability to different users with amputation levels.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2023)
Article
Computer Science, Artificial Intelligence
Haonan Yang, Dapeng Yang
Summary: In this paper, a pyramid structure network combining a convolutional neural network and Swin Transformer is proposed for automatic segmentation of breast tumors. The network improves the performance of breast lesion segmentation by using interactive channel attention and supplementary feature fusion modules, and introduces a boundary detection module to enhance the boundary quality of segmentation results. Experimental results demonstrate the superiority of the network in breast ultrasound lesion segmentation.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)