{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T16:14:50Z","timestamp":1776442490300,"version":"3.51.2"},"reference-count":87,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2025,9,3]],"date-time":"2025-09-03T00:00:00Z","timestamp":1756857600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001871","name":"Funda\u00e7\u00e3o para a Ci\u00eancia e Tecnologia","doi-asserted-by":"publisher","award":["UIDB\/00151\/2020"],"award-info":[{"award-number":["UIDB\/00151\/2020"]}],"id":[{"id":"10.13039\/501100001871","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Machines"],"abstract":"<jats:p>Neuromuscular robotic prostheses have emerged as a critical convergence point between biomedical engineering, machine learning, and human\u2013machine interfaces. This work provides a narrative state-of-the-art review regarding recent developments in robotic prosthetic technology, emphasizing sensor integration, actuator architectures, signal acquisition, and algorithmic strategies for intent decoding. Special focus is given to non-invasive biosignal modalities, particularly surface electromyography (sEMG), as well as invasive approaches involving direct neural interfacing. Recent developments in AI-driven signal processing, including deep learning and hybrid models for robust classification and regression of user intent, are also examined. Furthermore, the integration of real-time adaptive control systems with surgical techniques like Targeted Muscle Reinnervation (TMR) is evaluated for its role in enhancing proprioception and functional embodiment. Finally, this review highlights the growing importance of modular, open-source frameworks and additive manufacturing in accelerating prototyping and customization. Progress in this domain will depend on continued interdisciplinary research bridging artificial intelligence, neurophysiology, materials science, and real-time embedded systems to enable the next generation of intelligent prosthetic devices.<\/jats:p>","DOI":"10.3390\/machines13090804","type":"journal-article","created":{"date-parts":[[2025,9,4]],"date-time":"2025-09-04T08:08:46Z","timestamp":1756973326000},"page":"804","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Robotic Prostheses and Neuromuscular Interfaces: A Review of Design and Technological Trends"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5484-7755","authenticated-orcid":false,"given":"Pedro Garcia","family":"Batista","sequence":"first","affiliation":[{"name":"Department of Electromechanical Engineering, University of Beira Interior, Rua Marqu\u00eas d\u2019\u00c1vila e Bolama, 6201-001 Covilh\u00e3, Portugal"},{"name":"Cova da Beira University Hospital Center (ULS Cova da Beira), 6200-251 Covilh\u00e3, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6165-8899","authenticated-orcid":false,"given":"Andr\u00e9 Costa","family":"Vieira","sequence":"additional","affiliation":[{"name":"Department of Electromechanical Engineering, University of Beira Interior, Rua Marqu\u00eas d\u2019\u00c1vila e Bolama, 6201-001 Covilh\u00e3, Portugal"},{"name":"C-MAST\u2014Center for Mechanical and Aerospace Science and Technologies, 6201-001 Covilh\u00e3, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1691-1709","authenticated-orcid":false,"given":"Pedro Dinis","family":"Gaspar","sequence":"additional","affiliation":[{"name":"Department of Electromechanical Engineering, University of Beira Interior, Rua Marqu\u00eas d\u2019\u00c1vila e Bolama, 6201-001 Covilh\u00e3, Portugal"},{"name":"C-MAST\u2014Center for Mechanical and Aerospace Science and Technologies, 6201-001 Covilh\u00e3, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2025,9,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"595","DOI":"10.1146\/annurev-control-071020-104336","article-title":"Current solutions and future trends for robotic prosthetic hands","volume":"4","author":"Mendez","year":"2021","journal-title":"Annu. Rev. Control. Robot. Auton. Syst."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Hargrove, L.J., Miller, L.A., Turner, K., and Kuiken, T.A. (2017). Myoelectric pattern recognition outperforms direct control for transhumeral amputees with targeted muscle reinnervation: A randomized clinical trial. Sci. Rep., 7.","DOI":"10.1038\/s41598-017-14386-w"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Zheng, J.Z., De La Rosa, S., and Dollar, A.M. (2011, January 9\u201313). An investigation of grasp type and frequency in daily household and machine shop tasks. Proceedings of the 2011 IEEE International Conference on Robotics and Automation, Shanghai, China.","DOI":"10.1109\/ICRA.2011.5980366"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1151","DOI":"10.1016\/S0736-0266(03)00114-1","article-title":"Quantifying thumb rotation during circumduction utilizing a video technique","volume":"21","author":"Coert","year":"2003","journal-title":"J. Orthop. Res."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Belter, J.T., and Dollar, A.M. Performance characteristics of anthropomorphic prosthetic hands. In Proceedings of the 2011 IEEE International Conference on Rehabilitation Robotics, Zurich, Switzerland, 29 June\u20131 July 2011.","DOI":"10.1109\/ICORR.2011.5975476"},{"key":"ref_6","first-page":"77","article-title":"Underactuation in Robotic Grasping Hands","volume":"4","author":"Birglen","year":"2002","journal-title":"Jpn. J. Mach. Intell. Robot. Control"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Yoder, Z., Kellaris, N., Chase-Markopoulou, C., Ricken, D., Mitchell, S.K., Emmett, M.B., Weir, R.F.F., Segil, J., and Keplinger, C. (2020). Design of a High-Speed Prosthetic Finger Driven by Peano-HASEL Actuators. Front. Robot. AI, 7.","DOI":"10.3389\/frobt.2020.586216"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1089\/soro.2016.0029","article-title":"Soft Pneumatic Actuator Fascicles for High Force and Reliability","volume":"4","author":"Robertson","year":"2017","journal-title":"Soft Robot."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Huang, F., Sun, X., Xu, Q., Cheng, W., Shi, Y., and Pan, L. (2025). Recent Developments and Applications of Tactile Sensors with Biomimetic Microstructures. Biomimetics, 10.","DOI":"10.3390\/biomimetics10030147"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Navaraj, W.T., Nassar, H., and Dahiya, R. (2019, January 26\u201329). Prosthetic hand with biomimetic tactile sensing and force feedback. Proceedings of the 2019 IEEE International Symposium on Circuits and Systems (ISCAS), Sapporo, Japan.","DOI":"10.1109\/ISCAS.2019.8702732"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"115332","DOI":"10.1016\/j.measurement.2024.115332","article-title":"Tactile Sensors: A Review","volume":"238","author":"Mahmoud","year":"2024","journal-title":"Measurement"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Pirozzi, S. (2020). Tactile Sensors for Robotic Applications. Sensors, 20.","DOI":"10.3390\/s20247009"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"032001","DOI":"10.1088\/2634-4386\/adf091","article-title":"Neuromorphic touch for robotics\u2014A review","volume":"5","author":"Liu","year":"2025","journal-title":"Neuromorphic Comput. Eng."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"e00478","DOI":"10.1016\/j.ohx.2023.e00478","article-title":"BioIn-Tacto: A compliant multi-modal tactile sensing module for robotic tasks","volume":"16","author":"Oliveira","year":"2023","journal-title":"HardwareX"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Lang, L., Antunes, R., Dutra, T.A., Aguiar, M.L.d., Pereira, N., and Gaspar, P.D. (2025). Mechanical Characterization and Computational Analysis of TPU 60A: Integrating Experimental Testing and Simulation for Performance Optimization. Materials, 18.","DOI":"10.3390\/ma18020240"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Antunes, R., Lang, L., de Aguiar, M.L., Dutra, T.A., and Gaspar, P.D. (2024, January 2\u20134). Design of Fin Ray Effect Soft Robotic Gripper for Improved Mechanical Performance and Adaptability: Numerical Simulations and Experimental Validation. Proceedings of the 2024 20th IEEE\/ASME International Conference on Mechatronic and Embedded Systems and Applications (MESA), Genova, Italy.","DOI":"10.1109\/MESA61532.2024.10704855"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Antunes, R., Lang, L., de Aguiar, M.L., Dutra, T.A., and Gaspar, P.D. (2024, January 18\u201319). Enhancing the Performance of Fin Ray Effect Soft Robotic Finger via Computational Design and Simulation. Proceedings of the 2024 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC), Paredes de Coura, Portugal.","DOI":"10.1109\/ICARSC61747.2024.10535939"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"353","DOI":"10.1016\/j.carbon.2017.06.006","article-title":"Low-dimensional carbon-based sensors and sensing network for wearable health and environmental monitoring","volume":"121","author":"Wang","year":"2017","journal-title":"Carbon"},{"key":"ref_19","first-page":"418","article-title":"McKibben artificial muscles: Pneumatic actuators with biomechanical intelligence","volume":"7","author":"Klute","year":"1999","journal-title":"IEEE\/ASME Trans. Mechatron."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"90","DOI":"10.1109\/70.481753","article-title":"Measurement and modeling of McKibben pneumatic artificial muscles","volume":"12","author":"Chou","year":"1996","journal-title":"IEEE Trans. Robot. Autom."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1109\/3516.653050","article-title":"Application of Rubber Artificial Muscle Manipulator as a Rehabilitation Robot","volume":"2","author":"Noritsugu","year":"1997","journal-title":"IEEE\/ASME Trans. Mechatron."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Gong, D., and Yu, J. (2022). Design and Control of the McKibben Artificial Muscles Actuated Humanoid Manipulator. IntechOpen.","DOI":"10.5772\/intechopen.101761"},{"key":"ref_23","unstructured":"Repperger, D.W., Phillips, C.A., and Krier, M. (1999, January 22\u201327). Controller design involving gain scheduling for a large scale pneumatic muscle actuator. Proceedings of the 1999 IEEE International Conference on Control Applications, Kohala Coast, HI, USA."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"247","DOI":"10.2147\/MDER.S91102","article-title":"Myoelectric control of prosthetic hands: State-of-the-art review","volume":"9","author":"Geethanjali","year":"2016","journal-title":"Med. Devices Evid. Res."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Kamavuako, E.N., Brown, M., Bao, X., Chihi, I., Pitou, S., and Howard, M. (2021). Affordable Embroidered EMG Electrodes for Myoelectric Control of Prostheses: A Pilot Study. Sensors, 21.","DOI":"10.3390\/s21155245"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Ribeiro, J., Fernandes, H., Lopes, C., Magalh\u00e3es, F., and Teixeira, S. (2019). Analysis of Man-Machine Interfaces in Upper-Limb Prosthesis: A Review. Robotics, 8.","DOI":"10.3390\/robotics8010016"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"738","DOI":"10.1109\/TNSRE.2022.3159186","article-title":"Sensory Feedback for Upper-Limb Prostheses: Opportunities and Barriers","volume":"30","author":"Jabban","year":"2022","journal-title":"IEEE Trans. Neural Syst. Rehabil."},{"key":"ref_28","unstructured":"Konrad, P. (2005). The ABC of EMG: A Practical Introduction to Kinesiological Electromyography, Version 1.0, Noraxon Inc."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Naik, G. (2019). Biomedical Signal Processing: Advances in Theory, Algorithms and Applications, Springer.","DOI":"10.1007\/978-981-13-9097-5"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"361","DOI":"10.1016\/S1050-6411(00)00027-4","article-title":"Development of recommendations for SEMG sensors and sensor placement procedures","volume":"10","author":"Hermens","year":"2000","journal-title":"J. Electromyogr. Kinesiol."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1361","DOI":"10.1007\/s12551-020-00770-w","article-title":"Review on electromyography signal acquisition and processing","volume":"12","author":"Gohel","year":"2020","journal-title":"Biophys Rev."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Valentinuzzi, M.E., S\u00f6rnmo, L., Laguna, P., Merletti, R., and Parker, P. (2007). Bioelectrical Signal Processing in Cardiac and Neurological Applications. Biomed. Eng. Online, 6.","DOI":"10.1186\/1475-925X-6-27"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1016\/j.jneumeth.2014.07.016","article-title":"First-in-man demonstration of a fully implanted myoelectric sensors system to control an advanced electromechanical prosthetic hand","volume":"244","author":"Pasquina","year":"2015","journal-title":"J. Neurosci. Methods"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1111\/j.1525-1594.2011.01219.x","article-title":"Development of an Implantable Myoelectric Sensor for Advanced Prosthesis Control","volume":"35","author":"Merrill","year":"2011","journal-title":"Artif. Organs"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"036023","DOI":"10.1088\/1741-2560\/8\/3\/036023","article-title":"Comparative Analysis of Transverse Intrafascicular Multichannel, Longitudinal Intrafascicular and Multipolar Cuff Electrodes for the Selective Stimulation of Nerve Fascicles","volume":"8","author":"Badia","year":"2011","journal-title":"J. Neural Eng."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"103550","DOI":"10.1016\/j.isci.2021.103550","article-title":"Recent advances in recording and modulation technologies for next-generation neural interfaces","volume":"24","author":"Hong","year":"2021","journal-title":"iScience"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1007\/s40137-013-0044-8","article-title":"Prosthetic Myoelectric Control Strategies: A Clinical Perspective","volume":"2","author":"Roche","year":"2014","journal-title":"Curr. Surg. Rep."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Calado, A., Soares, F., and Matos, D. (2019, January 24\u201326). A Review on Commercially Available Anthropomorphic Myoelectric Prosthetic Hands, Pattern-Recognition-Based Microcontrollers and sEMG Sensors Used for Prosthetic Control. Proceedings of the 2019 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC), Paredes, Portugal.","DOI":"10.1109\/ICARSC.2019.8733629"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Moore, J.E., and Maitland, D.J. (2013). Biomedical Technology and Devices, CRC Press. [2nd ed.].","DOI":"10.1201\/b15085"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Secco, E.L., and Noh, Y. (2024). Editorial: Human-like Robotic Hands for Biomedical Applications and Beyond. Front. Robot. AI, 11.","DOI":"10.3389\/frobt.2024.1414971"},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Madusanka, D.G.K., Wijayasingha, L.N.S., Gopura, R.A.R.C., Amarasinghe, Y.W.R., and Mann, G.K.I. (2015, January 7\u20138). A Review on Hybrid Myoelectric Control Systems for Upper Limb Prosthesis. Proceedings of the 2015 Moratuwa Engineering Research Conference (MERCon), Moratuwa, Sri Lanka.","DOI":"10.1109\/MERCon.2015.7112334"},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Ke, A., Huang, J., Wang, J., and He, J. (2022). Improving the Robustness of Human-Machine Interactive Control for Myoelectric Prosthetic Hand during Arm Position Changing. Front. Neurorobot., 16.","DOI":"10.3389\/fnbot.2022.853773"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"9938","DOI":"10.1109\/LRA.2024.3451388","article-title":"Long-Term Upper-Limb Prosthesis Myocontrol via High-Density sEMG and Incremental Learning","volume":"9","author":"Domenico","year":"2024","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"2200063","DOI":"10.1002\/aisy.202200063","article-title":"Use of Advanced Materials and Artificial Intelligence in Electromyography Signal Detection and Interpretation","volume":"4","author":"Gao","year":"2022","journal-title":"Adv. Intell. Syst."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"eabq3665","DOI":"10.1126\/scitranslmed.abq3665","article-title":"Improved Control of a Prosthetic Limb by Surgically Creating Electro-Neuromuscular Constructs with Implanted Electrodes","volume":"15","author":"Zbinden","year":"2023","journal-title":"Sci. Transl. Med."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"AlQahtani, N.J., Al-Naib, I., and Althobaiti, M. (2024). Recent Progress on Smart Lower Prosthetic Limbs: A Comprehensive Review on Using EEG and fNIRS Devices in Rehabilitation. Front. Bioeng. Biotechnol., 12.","DOI":"10.3389\/fbioe.2024.1454262"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"2010","DOI":"10.1038\/s41591-024-02994-9","article-title":"Continuous Neural Control of a Bionic Limb Restores Biomimetic Gait After Amputation","volume":"30","author":"Song","year":"2024","journal-title":"Nat. Med."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1038\/s43856-022-00162-z","article-title":"Agonist\u2013Antagonist Muscle Strain in the Residual Limb Preserves Motor Control and Perception After Amputation","volume":"2","author":"Song","year":"2022","journal-title":"Commun. Med."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Xu, B., Zhong, L., Zhang, G., Liang, X., Virtue, D., Madan, R., and Bhattacharjee, T. (2024). CushSense: Soft, Stretchable and Comfortable Tactile-Sensing Skin for Physical Human\u2013Robot Interaction. arXiv.","DOI":"10.1109\/ICRA57147.2024.10610014"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"5535918","DOI":"10.1155\/2024\/5535918","article-title":"Design and Application of Flexible Sensors in Human\u2013Machine Interaction","volume":"2024","author":"Zheng","year":"2024","journal-title":"Adv. Polym. Technol."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"101865","DOI":"10.1016\/j.measen.2025.101865","article-title":"Wearable sensor-based intent recognition for adaptive control of intelligent ankle-foot prosthetics","volume":"39","author":"Kumar","year":"2025","journal-title":"Meas. Sens."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"3051","DOI":"10.1109\/TBME.2022.3160618","article-title":"Artificial Intelligence Enables Real-Time and Intuitive Control of Prostheses via Nerve Interface","volume":"69","author":"Luu","year":"2022","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"697","DOI":"10.1080\/19475411.2024.2417834","article-title":"Recent Advances in Flexible Bending Sensors and Their Applications","volume":"15","author":"Liu","year":"2024","journal-title":"Int. J. Smart Nano Mater."},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Varghese, R.J., Pizzi, M., Kundu, A., Grison, A., Burdet, E., and Farina, D. (2024). Design, Fabrication and Evaluation of a Stretchable High-Density Electromyography Array. Sensors, 24.","DOI":"10.3390\/s24061810"},{"key":"ref_55","unstructured":"Schultz Feuser, A.E., and Barlow, A.K. (2013). Targeted Muscle Reinnervation: A Neural Interface for Artificial Limbs, CRC Press. [1st ed.]."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"3717","DOI":"10.1007\/s00590-023-03736-2","article-title":"Targeted Muscle Reinnervation in Upper Extremity Amputations","volume":"34","author":"Le","year":"2024","journal-title":"Eur. J. Orthop. Surg. Traumatol."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"373","DOI":"10.1016\/j.bjps.2024.10.017","article-title":"What to Expect Following Targeted Muscle Reinnervation\/Regenerative Peripheral Nerve Interface: Pain Outcomes in an Amputee Population","volume":"99","author":"Lauzon","year":"2024","journal-title":"J. Plast. Reconstr. Aesthetic Surg."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"238","DOI":"10.1097\/SLA.0000000000003088","article-title":"Targeted Muscle Reinnervation Treats Neuroma and Phantom Pain in Major Limb Amputees: A Randomized Clinical Trial","volume":"270","author":"Dumanian","year":"2019","journal-title":"Ann. Surg."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1007\/s11552-014-9602-5","article-title":"Targeted Muscle Reinnervation in the Initial Management of Traumatic Upper Extremity Amputation Injury","volume":"9","author":"Cheesborough","year":"2014","journal-title":"Hand"},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"2984","DOI":"10.1007\/s11999-014-3528-7","article-title":"Targeted Muscle Reinnervation: A Novel Approach to Postamputation Neuroma Pain","volume":"472","author":"Souza","year":"2014","journal-title":"Clin. Orthop. Relat. Res."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1097\/BTO.0000000000000194","article-title":"Targeted Muscle Reinnervation for the Upper and Lower Extremity","volume":"32","author":"Kuiken","year":"2017","journal-title":"Tech. Orthop."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"644","DOI":"10.1097\/XCS.0000000000000778","article-title":"Outcomes of Targeted Muscle Reinnervation and Regenerative Peripheral Nerve Interfaces for Chronic Pain Control in the Oncologic Amputee Population","volume":"237","author":"Roubaud","year":"2023","journal-title":"J. Am. Coll. Surg."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"681","DOI":"10.2106\/JBJS.20.01005","article-title":"Practice Patterns and Pain Outcomes for Targeted Muscle Reinnervation: An Informed Approach to TMR Use in the Acute Amputation Setting","volume":"103","author":"Hoyt","year":"2021","journal-title":"J. Bone Joint Surg. Am."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1177\/22925503221107462","article-title":"Targeted Muscle Reinnervation and Regenerative Peripheral Nerve Interfaces versus Standard Management in the Treatment of Limb Amputation: A Systematic Review and Meta-Analysis","volume":"32","author":"Yuan","year":"2024","journal-title":"Plast. Surg."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1038\/s44182-025-00018-3","article-title":"High-density electromyography for effective gesture-based control of physically assistive mobile manipulators","volume":"3","author":"Yang","year":"2025","journal-title":"Npj Robot."},{"key":"ref_66","doi-asserted-by":"crossref","unstructured":"Hwang, S., Kwon, N., Lee, D., Kim, J., Yang, S., Youn, I., Moon, H.-J., Sung, J.-K., and Han, S. (2025). A Multimodal Fatigue Detection System Using sEMG and IMU Signals with a Hybrid CNN-LSTM-Attention Model. Sensors, 25.","DOI":"10.3390\/s25113309"},{"key":"ref_67","unstructured":"Ciuffreda, M. (2022). The Role of Osseointegration in Bionic Prostheses of the Upper Limb. [Doctoral Dissertation, Universit\u00e0 Campus Bio-Medico di Roma]."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"e0043","DOI":"10.2106\/JBJS.RVW.19.00043","article-title":"Osseointegration for Amputees: Current Implants, Techniques and Future Directions","volume":"8","author":"Hoellwarth","year":"2020","journal-title":"JBJS Rev."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1302\/0301-620X.96B1.31905","article-title":"A Novel Osseointegrated Percutaneous Prosthetic System for the Treatment of Patients with Transfemoral Amputation","volume":"96-B","author":"Berlin","year":"2014","journal-title":"Bone Jt. J."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1007\/s42399-023-01629-3","article-title":"Current Challenges and Future Prospects of Osseointegration Limb Reconstruction for Amputees","volume":"6","author":"Akhtar","year":"2024","journal-title":"SN Compr. Clin. Med."},{"key":"ref_71","doi-asserted-by":"crossref","unstructured":"Sun, Y., Xu, J., Lv, S., Xu, Z., Li, L., Li, Y., and Li, Y. (2022). Extramedullary Osseointegration\u2014A Novel Design of Percutaneous Osseointegration Prosthesis for Amputees. Front. Bioeng. Biotechnol., 10.","DOI":"10.3389\/fbioe.2022.811128"},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"116","DOI":"10.1177\/1753193410382720","article-title":"Long-term outcomes of osseointegrated digital prostheses for proximal amputations","volume":"36","author":"Sierakowski","year":"2011","journal-title":"J. Hand Surg. Eur. Vol."},{"key":"ref_73","doi-asserted-by":"crossref","unstructured":"Camargo-Vargas, D., Callejas-Cuervo, M., and Mazzoleni, S. (2021). Brain\u2013Computer Interfaces Systems for Upper and Lower Limb Rehabilitation: A Systematic Review. Sensors, 21.","DOI":"10.3390\/s21134312"},{"key":"ref_74","doi-asserted-by":"crossref","unstructured":"Ar\u0131, E., and Ta\u00e7g\u0131n, E. (2024). NF-EEG: A Generalized CNN Model for Multi-Class EEG Motor Imagery Classification without Signal Preprocessing for Brain\u2013Computer Interfaces. Biomed. Signal Process. Control, 92.","DOI":"10.1016\/j.bspc.2024.106081"},{"key":"ref_75","doi-asserted-by":"crossref","unstructured":"Choi, S.H., Yoon, H., Baek, H.J., and Long, X. (2025). Biomedical Signal Processing and Health Monitoring Based on Sensors. Sensors, 25.","DOI":"10.3390\/s25030641"},{"key":"ref_76","doi-asserted-by":"crossref","unstructured":"Liu, Z., Shore, J., Wang, M., Yuan, F., Buss, A., and Zhao, X. (2021). A systematic review on hybrid EEG\/fNIRS in brain-computer interface. Biomed. Signal Process. Control, 68.","DOI":"10.1016\/j.bspc.2021.102595"},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"e16194","DOI":"10.2196\/16194","article-title":"An Integrated Brain\u2013Machine Interface Platform with Thousands of Channels","volume":"21","author":"Musk","year":"2019","journal-title":"J. Med. Internet Res."},{"key":"ref_78","doi-asserted-by":"crossref","unstructured":"Merletti, R., and Farina, D. (2016). Surface Electromyography: Physiology, Engineering and Applications, John Wiley & Sons, Inc.","DOI":"10.1002\/9781119082934"},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1109\/TMRB.2020.3046847","article-title":"Single EMG Sensor-Driven Robotic Glove Control for Reliable Augmentation of Power Grasping","volume":"3","author":"Cheon","year":"2021","journal-title":"IEEE Trans. Med. Robot. Bionics"},{"key":"ref_80","unstructured":"Favieiro, G.W. (2009). Controle de uma Pr\u00f3tese Experimental do Segmento M\u00e3o-Bra\u00e7o por Sinais Mioel\u00e9tricos e Redes Neurais Artificiais. [Master\u2019s Thesis, Universidade Federal do Rio Grande do Sul]."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1109\/JBHI.2024.3484994","article-title":"Continuous Prediction of Wrist Joint Kinematics Using Surface Electromyography from the Perspective of Muscle Anatomy and Muscle Synergy Feature Extraction","volume":"1","author":"Wei","year":"2025","journal-title":"IEEE J. Biomed. Health Inform."},{"key":"ref_82","doi-asserted-by":"crossref","unstructured":"Foroutannia, A., Akbarzadeh, M., and Akbarzadeh, A. (2022). A deep learning strategy for EMG-based joint position prediction in hip exoskeleton assistive robots. Biomed. Signal Process. Control, 75.","DOI":"10.1016\/j.bspc.2022.103557"},{"key":"ref_83","doi-asserted-by":"crossref","unstructured":"Jaramillo-Y\u00e1nez, A., Benalc\u00e1zar, M.E., and Mena-Maldonado, E. (2020). Real-Time Hand Gesture Recognition Using Surface Electromyography and Machine Learning: A Systematic Literature Review. Sensors, 20.","DOI":"10.3390\/s20092467"},{"key":"ref_84","doi-asserted-by":"crossref","unstructured":"Castro, A., Pinheiro, W.C., and Rigolin, G. (2021). A Hybrid 3D-Printed Hand Prosthesis Prototype based on sEMG with Embedded Computer Vision. Front. Neurorobot., 15.","DOI":"10.3389\/fnbot.2021.751282"},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"031002","DOI":"10.1088\/1741-2552\/abc902","article-title":"A Survey on Deep Learning-based Non-Invasive Brain Signals: Recent Advances and New Frontiers","volume":"18","author":"Zhang","year":"2019","journal-title":"J. Neural Eng."},{"key":"ref_86","unstructured":"Choi, B.J. (2025). Removing Neural Signal Artifacts with Autoencoder-Targeted Adversarial Transformers (AT-AT). arXiv."},{"key":"ref_87","doi-asserted-by":"crossref","unstructured":"Chen, J., Bi, S., Zhang, G., and Cao, G. (2020). High-Density Surface EMG-Based Gesture Recognition Using a 3D Convolutional Neural Network. Sensors, 20.","DOI":"10.3390\/s20041201"}],"container-title":["Machines"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2075-1702\/13\/9\/804\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,9]],"date-time":"2025-10-09T18:38:44Z","timestamp":1760035124000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2075-1702\/13\/9\/804"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,3]]},"references-count":87,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2025,9]]}},"alternative-id":["machines13090804"],"URL":"https:\/\/doi.org\/10.3390\/machines13090804","relation":{},"ISSN":["2075-1702"],"issn-type":[{"value":"2075-1702","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,9,3]]}}}