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Zbinden J, Earley EJ, Ortiz-Catalan M. Intuitive control of additional prosthetic joints via electro-neuromuscular constructs improves functional and disability outcomes during home use-a case study. J Neural Eng 2024; 21:036021. [PMID: 38489845 DOI: 10.1088/1741-2552/ad349c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Accepted: 03/15/2024] [Indexed: 03/17/2024]
Abstract
Objective.The advent of surgical reconstruction techniques has enabled the recreation of myoelectric controls sites that were previously lost due to amputation. This advancement is particularly beneficial for individuals with higher-level arm amputations, who were previously constrained to using a single degree of freedom (DoF) myoelectric prostheses due to the limited number of available muscles from which control signals could be extracted. In this study, we explore the use of surgically created electro-neuromuscular constructs to intuitively control multiple bionic joints during daily life with a participant who was implanted with a neuromusculoskeletal prosthetic interface.Approach.We sequentially increased the number of controlled joints, starting at a single DoF allowing to open and close the hand, subsequently adding control of the wrist (2 DoF) and elbow (3 DoF).Main results.We found that the surgically created electro-neuromuscular constructs allow for intuitive simultaneous and proportional control of up to three degrees of freedom using direct control. Extended home-use and the additional bionic joints resulted in improved prosthesis functionality and disability outcomes.Significance.Our findings indicate that electro-neuromuscular constructs can aid in restoring lost functionality and thereby support a person who lost their arm in daily-life tasks.
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Affiliation(s)
- Jan Zbinden
- Center for Bionics and Pain Research, Mölndal, Sweden
- Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden
| | - Eric J Earley
- Center for Bionics and Pain Research, Mölndal, Sweden
- Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden
- Bone-Anchored Limb Research Group, University of Colorado, Aurora, CO, United States of America
- Department of Orthopedics, University of Colorado School of Medicine, Aurora, CO, United States of America
| | - Max Ortiz-Catalan
- Center for Bionics and Pain Research, Mölndal, Sweden
- Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden
- Bionics Institute, Melbourne, Australia
- Medical Bionics Department, University of Melbourne, Melbourne, Australia
- Prometei Pain Rehabilitation Center, Vinnytsia, Ukraine
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Tian Y, Vaskov AK, Adidharma W, Cederna PS, Kemp SW. Merging Humans and Neuroprosthetics through Regenerative Peripheral Nerve Interfaces. Semin Plast Surg 2024; 38:10-18. [PMID: 38495064 PMCID: PMC10942838 DOI: 10.1055/s-0044-1779028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
Limb amputations can be devastating and significantly affect an individual's independence, leading to functional and psychosocial challenges in nearly 2 million people in the United States alone. Over the past decade, robotic devices driven by neural signals such as neuroprostheses have shown great potential to restore the lost function of limbs, allowing amputees to regain movement and sensation. However, current neuroprosthetic interfaces have challenges in both signal quality and long-term stability. To overcome these limitations and work toward creating bionic limbs, the Neuromuscular Laboratory at University of Michigan Plastic Surgery has developed the Regenerative Peripheral Nerve Interface (RPNI). This surgical construct embeds a transected peripheral nerve into a free muscle graft, effectively amplifying small peripheral nerve signals to provide enhanced control signals for a neuroprosthetic limb. Furthermore, the RPNI has the potential to provide sensory feedback to the user and facilitate neuroprosthesis embodiment. This review focuses on the animal studies and clinical trials of the RPNI to recapitulate the promising trajectory toward neurobionics where the boundary between an artificial device and the human body becomes indistinct. This paper also sheds light on the prospects of the improvement and dissemination of the RPNI technology.
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Affiliation(s)
- Yucheng Tian
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan
| | - Alex K. Vaskov
- Section of Plastic Surgery, Department of Surgery, University of Michigan, Ann Arbor, Michigan
| | - Widya Adidharma
- Section of Plastic Surgery, Department of Surgery, University of Michigan, Ann Arbor, Michigan
| | - Paul S. Cederna
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan
- Section of Plastic Surgery, Department of Surgery, University of Michigan, Ann Arbor, Michigan
| | - Stephen W.P. Kemp
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan
- Section of Plastic Surgery, Department of Surgery, University of Michigan, Ann Arbor, Michigan
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Taghlabi KM, Cruz-Garza JG, Hassan T, Potnis O, Bhenderu LS, Guerrero JR, Whitehead RE, Wu Y, Luan L, Xie C, Robinson JT, Faraji AH. Clinical outcomes of peripheral nerve interfaces for rehabilitation in paralysis and amputation: a literature review. J Neural Eng 2024; 21:011001. [PMID: 38237175 DOI: 10.1088/1741-2552/ad200f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Accepted: 01/18/2024] [Indexed: 02/02/2024]
Abstract
Peripheral nerve interfaces (PNIs) are electrical systems designed to integrate with peripheral nerves in patients, such as following central nervous system (CNS) injuries to augment or replace CNS control and restore function. We review the literature for clinical trials and studies containing clinical outcome measures to explore the utility of human applications of PNIs. We discuss the various types of electrodes currently used for PNI systems and their functionalities and limitations. We discuss important design characteristics of PNI systems, including biocompatibility, resolution and specificity, efficacy, and longevity, to highlight their importance in the current and future development of PNIs. The clinical outcomes of PNI systems are also discussed. Finally, we review relevant PNI clinical trials that were conducted, up to the present date, to restore the sensory and motor function of upper or lower limbs in amputees, spinal cord injury patients, or intact individuals and describe their significant findings. This review highlights the current progress in the field of PNIs and serves as a foundation for future development and application of PNI systems.
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Affiliation(s)
- Khaled M Taghlabi
- Department of Neurological Surgery, Houston Methodist Hospital, Houston, TX 77030, United States of America
- Center for Neural Systems Restoration, Houston Methodist Research Institute, Houston, TX 77030, United States of America
- Clinical Innovations Laboratory, Houston Methodist Research Institute, Houston, TX 77030, United States of America
| | - Jesus G Cruz-Garza
- Department of Neurological Surgery, Houston Methodist Hospital, Houston, TX 77030, United States of America
- Center for Neural Systems Restoration, Houston Methodist Research Institute, Houston, TX 77030, United States of America
- Clinical Innovations Laboratory, Houston Methodist Research Institute, Houston, TX 77030, United States of America
| | - Taimur Hassan
- Department of Neurological Surgery, Houston Methodist Hospital, Houston, TX 77030, United States of America
- Center for Neural Systems Restoration, Houston Methodist Research Institute, Houston, TX 77030, United States of America
- Clinical Innovations Laboratory, Houston Methodist Research Institute, Houston, TX 77030, United States of America
- School of Medicine, Texas A&M University, Bryan, TX 77807, United States of America
| | - Ojas Potnis
- Department of Neurological Surgery, Houston Methodist Hospital, Houston, TX 77030, United States of America
- Center for Neural Systems Restoration, Houston Methodist Research Institute, Houston, TX 77030, United States of America
- Clinical Innovations Laboratory, Houston Methodist Research Institute, Houston, TX 77030, United States of America
- School of Engineering Medicine, Texas A&M University, Houston, TX 77030, United States of America
| | - Lokeshwar S Bhenderu
- Department of Neurological Surgery, Houston Methodist Hospital, Houston, TX 77030, United States of America
- Center for Neural Systems Restoration, Houston Methodist Research Institute, Houston, TX 77030, United States of America
- Clinical Innovations Laboratory, Houston Methodist Research Institute, Houston, TX 77030, United States of America
- School of Medicine, Texas A&M University, Bryan, TX 77807, United States of America
| | - Jaime R Guerrero
- Department of Neurological Surgery, Houston Methodist Hospital, Houston, TX 77030, United States of America
- Center for Neural Systems Restoration, Houston Methodist Research Institute, Houston, TX 77030, United States of America
- Clinical Innovations Laboratory, Houston Methodist Research Institute, Houston, TX 77030, United States of America
| | - Rachael E Whitehead
- Department of Academic Affairs, Houston Methodist Academic Institute, Houston, TX 77030, United States of America
| | - Yu Wu
- Rice Neuroengineering Initiative, Rice University, Houston, TX 77005, United States of America
- Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005, United States of America
| | - Lan Luan
- Rice Neuroengineering Initiative, Rice University, Houston, TX 77005, United States of America
- Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005, United States of America
| | - Chong Xie
- Rice Neuroengineering Initiative, Rice University, Houston, TX 77005, United States of America
- Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005, United States of America
| | - Jacob T Robinson
- Rice Neuroengineering Initiative, Rice University, Houston, TX 77005, United States of America
- Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005, United States of America
| | - Amir H Faraji
- Department of Neurological Surgery, Houston Methodist Hospital, Houston, TX 77030, United States of America
- Center for Neural Systems Restoration, Houston Methodist Research Institute, Houston, TX 77030, United States of America
- Clinical Innovations Laboratory, Houston Methodist Research Institute, Houston, TX 77030, United States of America
- Rice Neuroengineering Initiative, Rice University, Houston, TX 77005, United States of America
- Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005, United States of America
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González-Prieto J, Cristóbal L, Arenillas M, Giannetti R, Muñoz Frías JD, Alonso Rivas E, Sanz Barbero E, Gutiérrez-Pecharromán A, Díaz Montero F, Maldonado AA. Regenerative Peripheral Nerve Interfaces (RPNIs) in Animal Models and Their Applications: A Systematic Review. Int J Mol Sci 2024; 25:1141. [PMID: 38256216 PMCID: PMC10816042 DOI: 10.3390/ijms25021141] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Revised: 01/05/2024] [Accepted: 01/10/2024] [Indexed: 01/24/2024] Open
Abstract
Regenerative Peripheral Nerve Interfaces (RPNIs) encompass neurotized muscle grafts employed for the purpose of amplifying peripheral nerve electrical signaling. The aim of this investigation was to undertake an analysis of the extant literature concerning animal models utilized in the context of RPNIs. A systematic review of the literature of RPNI techniques in animal models was performed in line with the PRISMA statement using the MEDLINE/PubMed and Embase databases from January 1970 to September 2023. Within the compilation of one hundred and four articles employing the RPNI technique, a subset of thirty-five were conducted using animal models across six distinct institutions. The majority (91%) of these studies were performed on murine models, while the remaining (9%) were conducted employing macaque models. The most frequently employed anatomical components in the construction of the RPNIs were the common peroneal nerve and the extensor digitorum longus (EDL) muscle. Through various histological techniques, robust neoangiogenesis and axonal regeneration were evidenced. Functionally, the RPNIs demonstrated the capability to discern, record, and amplify action potentials, a competence that exhibited commendable long-term stability. Different RPNI animal models have been replicated across different studies. Histological, neurophysiological, and functional analyses are summarized to be used in future studies.
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Affiliation(s)
- Jorge González-Prieto
- Peripheral Nerve Unit, Department of Plastic Surgery, University Hospital of Getafe, 28905 Madrid, Spain; (J.G.-P.); (L.C.)
- Department of Medicine, Faculty of Biomedical Science and Health, Universidad Europea de Madrid, 28670 Madrid, Spain
| | - Lara Cristóbal
- Peripheral Nerve Unit, Department of Plastic Surgery, University Hospital of Getafe, 28905 Madrid, Spain; (J.G.-P.); (L.C.)
- Department of Medicine, Faculty of Biomedical Science and Health, Universidad Europea de Madrid, 28670 Madrid, Spain
| | - Mario Arenillas
- Animal Medicine and Surgery Department, Complutense University of Madrid, 28040 Madrid, Spain;
| | - Romano Giannetti
- Institute for Research in Technology, ICAI School of Engineering, Comillas Pontifical University, 28015 Madrid, Spain; (R.G.); (J.D.M.F.)
| | - José Daniel Muñoz Frías
- Institute for Research in Technology, ICAI School of Engineering, Comillas Pontifical University, 28015 Madrid, Spain; (R.G.); (J.D.M.F.)
| | - Eduardo Alonso Rivas
- Institute for Research in Technology, ICAI School of Engineering, Comillas Pontifical University, 28015 Madrid, Spain; (R.G.); (J.D.M.F.)
| | - Elisa Sanz Barbero
- Peripheral Nerve Unit, Neurophysiology Department, University Hospital of Getafe, 28905 Madrid, Spain;
| | - Ana Gutiérrez-Pecharromán
- Peripheral Nerve Unit, Pathological Anatomy Department, University Hospital of Getafe, 28905 Madrid, Spain;
| | - Francisco Díaz Montero
- Department of Design, BAU College of Arts & Design of Barcelona, 28036 Barcelona, Spain;
| | - Andrés A. Maldonado
- Peripheral Nerve Unit, Department of Plastic Surgery, University Hospital of Getafe, 28905 Madrid, Spain; (J.G.-P.); (L.C.)
- Department of Medicine, Faculty of Biomedical Science and Health, Universidad Europea de Madrid, 28670 Madrid, Spain
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Jiang X, Ma C, Nazarpour K. One-shot random forest model calibration for hand gesture decoding. J Neural Eng 2024; 21:016006. [PMID: 38225863 DOI: 10.1088/1741-2552/ad1786] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Accepted: 12/20/2023] [Indexed: 01/17/2024]
Abstract
Objective.Most existing machine learning models for myoelectric control require a large amount of data to learn user-specific characteristics of the electromyographic (EMG) signals, which is burdensome. Our objective is to develop an approach to enable the calibration of a pre-trained model with minimal data from a new myoelectric user.Approach.We trained a random forest (RF) model with EMG data from 20 people collected during the performance of multiple hand grips. To adapt the decision rules for a new user, first, the branches of the pre-trained decision trees were pruned using the validation data from the new user. Then new decision trees trained merely with data from the new user were appended to the pruned pre-trained model.Results.Real-time myoelectric experiments with 18 participants over two days demonstrated the improved accuracy of the proposed approach when compared to benchmark user-specific RF and the linear discriminant analysis models. Furthermore, the RF model that was calibrated on day one for a new participant yielded significantly higher accuracy on day two, when compared to the benchmark approaches, which reflects the robustness of the proposed approach.Significance.The proposed model calibration procedure is completely source-free, that is, once the base model is pre-trained, no access to the source data from the original 20 people is required. Our work promotes the use of efficient, explainable, and simple models for myoelectric control.
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Affiliation(s)
- Xinyu Jiang
- School of Informatics, The University of Edinburgh, Edinburgh, United Kingdom
| | - Chenfei Ma
- School of Informatics, The University of Edinburgh, Edinburgh, United Kingdom
| | - Kianoush Nazarpour
- School of Informatics, The University of Edinburgh, Edinburgh, United Kingdom
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Gonzalez MA, Nwokeabia C, Vaskov AK, Vu PP, Lu CW, Patil PG, Cederna PS, Chestek CA, Gates DH. Electrical Stimulation of Regenerative Peripheral Nerve Interfaces (RPNIs) Induces Referred Sensations in People With Upper Limb Loss. IEEE Trans Neural Syst Rehabil Eng 2024; 32:339-349. [PMID: 38145529 PMCID: PMC10938368 DOI: 10.1109/tnsre.2023.3345164] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2023]
Abstract
Individuals with upper limb loss lack sensation of the missing hand, which can negatively impact their daily function. Several groups have attempted to restore this sensation through electrical stimulation of residual nerves. The purpose of this study was to explore the utility of regenerative peripheral nerve interfaces (RPNIs) in eliciting referred sensation. In four participants with upper limb loss, we characterized the quality and location of sensation elicited through electrical stimulation of RPNIs over time. We also measured functional stimulation ranges (sensory perception and discomfort thresholds), sensitivity to changes in stimulation amplitude, and ability to differentiate objects of different stiffness and sizes. Over a period of up to 54 months, stimulation of RPNIs elicited sensations that were consistent in quality (e.g. tingling, kinesthesia) and were perceived in the missing hand and forearm. The location of elicited sensation was partially-stable to stable in 13 of 14 RPNIs. For 5 of 7 RPNIs tested, participants demonstrated a sensitivity to changes in stimulation amplitude, with an average just noticeable difference of 45 nC. In a case study, one participant was provided RPNI stimulation proportional to prosthetic grip force. She identified four objects of different sizes and stiffness with 56% accuracy with stimulation alone and 100% accuracy when stimulation was combined with visual feedback of hand position. Collectively, these experiments suggest that RPNIs have the potential to be used in future bi-directional prosthetic systems.
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Jawad T, Koh RGL, Zariffa J. Selective peripheral nerve recording using simulated human median nerve activity and convolutional neural networks. Biomed Eng Online 2023; 22:118. [PMID: 38062509 PMCID: PMC10704747 DOI: 10.1186/s12938-023-01181-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Accepted: 11/23/2023] [Indexed: 12/18/2023] Open
Abstract
BACKGROUND It is difficult to create intuitive methods of controlling prosthetic limbs, often resulting in abandonment. Peripheral nerve interfaces can be used to convert motor intent into commands to a prosthesis. The Extraneural Spatiotemporal Compound Action Potentials Extraction Network (ESCAPE-NET) is a convolutional neural network (CNN) that has previously been demonstrated to be effective at discriminating neural sources in rat sciatic nerves. ESCAPE-NET was designed to operate using data from multi-channel nerve cuff arrays, and use the resulting spatiotemporal signatures to classify individual naturally evoked compound action potentials (nCAPs) based on differing source fascicles. The applicability of this approach to larger and more complex nerves is not well understood. To support future translation to humans, the objective of this study was to characterize the performance of this approach in a computational model of the human median nerve. METHODS Using a cross-sectional immunohistochemistry image of a human median nerve, a finite-element model was generated and used to simulate extraneural recordings. ESCAPE-NET was used to classify nCAPs based on source location, for varying numbers of sources and noise levels. The performance of ESCAPE-NET was also compared to ResNet-50 and MobileNet-V2 in the context of classifying human nerve cuff data. RESULTS Classification accuracy was found to be inversely related to the number of nCAP sources in ESCAPE-NET (3-class: 97.8% ± 0.1%; 10-class: 89.3% ± 5.4% in low-noise conditions, 3-class: 70.3% ± 0.1%; 10-class: 52.5% ± 0.3% in high-noise conditions). ESCAPE-NET overall outperformed both MobileNet-V2 (3-class: 96.5% ± 1.1%; 10-class: 84.9% ± 1.7% in low-noise conditions, 3-class: 86.0% ± 0.6%; 10-class: 41.4% ± 0.9% in high-noise conditions) and ResNet-50 (3-class: 71.2% ± 18.6%; 10-class: 40.1% ± 22.5% in low-noise conditions, 3-class: 81.3% ± 4.4%; 10-class: 31.9% ± 4.4% in high-noise conditions). CONCLUSION All three networks were found to learn to differentiate nCAPs from different sources, as evidenced by performance levels well above chance in all cases. ESCAPE-NET was found to have the most robust performance, despite decreasing performance as the number of classes increased, and as noise was varied. These results provide valuable translational guidelines for designing neural interfaces for human use.
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Affiliation(s)
- Taseen Jawad
- KITE Research Institute, Toronto Rehabilitation Institute-University Health Network, Toronto, Canada
- Institute of Biomedical Engineering, University of Toronto, Toronto, Canada
| | - Ryan G L Koh
- KITE Research Institute, Toronto Rehabilitation Institute-University Health Network, Toronto, Canada
| | - José Zariffa
- KITE Research Institute, Toronto Rehabilitation Institute-University Health Network, Toronto, Canada.
- Institute of Biomedical Engineering, University of Toronto, Toronto, Canada.
- Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto, Toronto, Canada.
- Rehabilitation Sciences Institute, University of Toronto, Toronto, Canada.
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Huynh THN, Kuruvilla DR, Nester MD, Zervoudakis G, Letson GD, Joyce DM, Binitie OT, Lazarides AL. Limb Amputations in Cancer: Modern Perspectives, Outcomes, and Alternatives. Curr Oncol Rep 2023; 25:1457-1465. [PMID: 37999825 DOI: 10.1007/s11912-023-01475-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/07/2023] [Indexed: 11/25/2023]
Abstract
PURPOSE OF REVIEW This review summarizes current findings regarding limb amputation within the context of cancer, especially in osteosarcomas and other bony malignancies. We seek to answer the question of how amputation is utilized in the contemporary management of cancer as well as explore current advances in limb-sparing techniques. RECENT FINDINGS The latest research on amputation has been sparse given its extensive history and application. However, new research has shown that rotationplasty, osseointegration, targeted muscle reinnervation (TMR), and regenerative peripheral nerve interfaces (RPNI) can provide patients with better functional outcomes than traditional amputation. While limb-sparing surgeries are the mainstay for managing musculoskeletal malignancies, limb amputation is useful as a palliative technique or as a primary treatment modality for more complex cancers. Currently, rotationplasty and osseointegration have been valuable limb-sparing techniques with osseointegration continuing to develop in recent years. TMR and RPNI have also been of interest in the modern management of patients requiring full or partial amputations, allowing for better control over myoelectric prostheses.
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Affiliation(s)
- Thien Huong N Huynh
- University of South Florida Health Morsani College of Medicine, Tampa, FL, USA
| | - Davis R Kuruvilla
- University of South Florida Health Morsani College of Medicine, Tampa, FL, USA
| | - Matthew D Nester
- University of South Florida Health Morsani College of Medicine, Tampa, FL, USA
| | | | | | - David M Joyce
- Department of Sarcoma, Moffitt Cancer Center, Tampa, FL, USA
| | - Odion T Binitie
- Department of Sarcoma, Moffitt Cancer Center, Tampa, FL, USA
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Dosen S. Toward self-contained bidirectional bionic limbs with high information throughput. Sci Robot 2023; 8:eadk6086. [PMID: 37820005 DOI: 10.1126/scirobotics.adk6086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/13/2023]
Abstract
Surgical neural engineering and human-machine interfacing enable bionic limbs with dexterous control and sensory feedback.
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Affiliation(s)
- Strahinja Dosen
- Department of Health Science and Technology, Faculty of Medicine, Aalborg University, Aalborg, Denmark
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