{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,23]],"date-time":"2026-08-23T16:37:32Z","timestamp":1787503052916,"version":"build-2736575974"},"reference-count":207,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2025,6,22]],"date-time":"2025-06-22T00:00:00Z","timestamp":1750550400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Committee of Science of the Ministry of Science and Higher Education of the Republic of Kazakhstan","award":["BR24992820"],"award-info":[{"award-number":["BR24992820"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Hands are central to nearly every aspect of daily life, so losing an upper limb due to amputation can severely affect a person\u2019s independence. Robotic prostheses offer a promising solution by mimicking many of the functions of a natural arm, leading to an increasing need for advanced prosthetic designs. However, developing an effective robotic hand prosthesis is far from straightforward. It involves several critical steps, including creating accurate models, choosing materials that balance biocompatibility with durability, integrating electronic and sensory components, and perfecting control systems before final production. A key factor in ensuring smooth, natural movements lies in the method of control. One popular approach is to use electromyography (EMG), which relies on electrical signals from the user\u2019s remaining muscle activity to direct the prosthesis. By decoding these signals, we can predict the intended hand and arm motions and translate them into real-time actions. Recent strides in machine learning have made EMG-based control more adaptable, offering users a more intuitive experience. Alongside this, researchers are exploring tactile sensors for enhanced feedback, materials resilient in harsh conditions, and mechanical designs that better replicate the intricacies of a biological limb. This review brings together these advancements, focusing on emerging trends and future directions in robotic upper-limb prosthesis development.<\/jats:p>","DOI":"10.3390\/s25133892","type":"journal-article","created":{"date-parts":[[2025,6,23]],"date-time":"2025-06-23T04:50:05Z","timestamp":1750654205000},"page":"3892","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Emerging Frontiers in Robotic Upper-Limb Prostheses: Mechanisms, Materials, Tactile Sensors and Machine Learning-Based EMG Control: A Comprehensive Review"],"prefix":"10.3390","volume":"25","author":[{"given":"Beibit","family":"Abdikenov","sequence":"first","affiliation":[{"name":"Science and Innovation Center \u201cArtificial Intelligence\u201d, Astana IT University, Astana 010000, Kazakhstan"},{"name":"ReLive Research, Astana 010000, Kazakhstan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Darkhan","family":"Zholtayev","sequence":"additional","affiliation":[{"name":"Science and Innovation Center \u201cArtificial Intelligence\u201d, Astana IT University, Astana 010000, Kazakhstan"},{"name":"ReLive Research, Astana 010000, Kazakhstan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kanat","family":"Suleimenov","sequence":"additional","affiliation":[{"name":"ReLive Research, Astana 010000, Kazakhstan"},{"name":"Department of Information Technology and Entrepreneurship, Narva College, University of Tartu, 20307 Narva, Estonia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0662-7130","authenticated-orcid":false,"given":"Nazgul","family":"Assan","sequence":"additional","affiliation":[{"name":"ReLive Research, Astana 010000, Kazakhstan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kassymbek","family":"Ozhikenov","sequence":"additional","affiliation":[{"name":"Institute of Automation and Information Technologies, Satbayev University, Almaty 050000, Kazakhstan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aiman","family":"Ozhikenova","sequence":"additional","affiliation":[{"name":"Institute of Automation and Information Technologies, Satbayev University, Almaty 050000, Kazakhstan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nurbek","family":"Nadirov","sequence":"additional","affiliation":[{"name":"ReLive Research, Astana 010000, Kazakhstan"},{"name":"Department of Orthopedics, Mother and Child Health Center, Corporate Fund University Medical Center, Astana 010000, Kazakhstan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3700-6214","authenticated-orcid":false,"given":"Akim","family":"Kapsalyamov","sequence":"additional","affiliation":[{"name":"Faculty of Engineering and Mathematics, Hochschule Bielefeld, 33619 Bielefeld, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,6,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"422","DOI":"10.1016\/j.apmr.2007.11.005","article-title":"Estimating the prevalence of limb loss in the United States: 2005 to 2050","volume":"89","author":"MacKenzie","year":"2008","journal-title":"Arch. 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