<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>0188-9532</journal-id>
<journal-title><![CDATA[Revista mexicana de ingeniería biomédica]]></journal-title>
<abbrev-journal-title><![CDATA[Rev. mex. ing. bioméd]]></abbrev-journal-title>
<issn>0188-9532</issn>
<publisher>
<publisher-name><![CDATA[Sociedad Mexicana de Ingeniería Biomédica]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0188-95322025000100202</article-id>
<article-id pub-id-type="doi">10.17488/rmib.46.1.1472</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[Emerging technologies as a support for proprioceptive rehabilitation: A scoping review]]></article-title>
<article-title xml:lang="es"><![CDATA[Tecnologías emergentes como apoyo en la rehabilitación propioceptiva: una revisión del alcance]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Trujillo Colón]]></surname>
<given-names><![CDATA[Uziel]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Hernández Hernández]]></surname>
<given-names><![CDATA[José Luis]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Cruz Gámez]]></surname>
<given-names><![CDATA[Eduardo De La]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Maldonado Astudillo]]></surname>
<given-names><![CDATA[Rayma Ireri]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Salazar]]></surname>
<given-names><![CDATA[Ricardo]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad Autónoma de Guerrero  ]]></institution>
<addr-line><![CDATA[ Guerrero]]></addr-line>
<country>Mexico</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Tecnológico Nacional de México Instituto Tecnológico de Acapulco ]]></institution>
<addr-line><![CDATA[ Guerrero]]></addr-line>
<country>Mexico</country>
</aff>
<aff id="Af3">
<institution><![CDATA[,Universidad Autónoma de Guerrero  ]]></institution>
<addr-line><![CDATA[ Guerrero]]></addr-line>
<country>Mexico</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>04</month>
<year>2025</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>04</month>
<year>2025</year>
</pub-date>
<volume>46</volume>
<numero>1</numero>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S0188-95322025000100202&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S0188-95322025000100202&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S0188-95322025000100202&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract Proprioceptive training encompasses interventions aimed at enhancing proprioceptive function to improve motor function performance. Three types of interventions are considered: Movement Training (MT); Somatosensory Stimulation Training (SST), and Force Reproduction Training (FRT). This study analyzes the potential of emerging technologies, such as exoskeletons, mechanical devices, Artificial Intelligence (AI), Virtual Reality (VR), the Internet of Things (IoT), and sensors, highlighting their application in proprioceptive therapies, with particular emphasison MT, SST, and FRT. A total of 107 articles published in scientific journals were reviewed, of which 30 complied with inclusion criteria: 1) Implementation of proprioceptive intervention therapy; 2) use of technology; 3) publication after 2019, and 4) written in the English language. Of the studies analyzed, 43% employed AI, indicating its increasing adoption, while IoT was the least utilized technology, with only 3 %. It is concluded that emerging technologies plays a crucial role in proprioceptive rehabilitation by enabling the analysis of data before and after surgical procedures, real-time pattern assessment, and the classification of sensory signals. Moreover, it offers alternatives to traditional measurement methods.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen El entrenamiento propioceptivo representa cualquier intervención de la función propioceptiva que ayude a mejorar el desempeño de la función motora. Se consideran tres tipos de intervenciones: Entrenamiento de Movimiento (EM); Entrenamiento de Estimulación Somatosensorial (EES) y Entrenamiento de Reproducción de Fuerza (ERF). Este estudio analiza el alcance de las tecnologías emergentes, como los exoesqueletos, dispositivos mecánicos, Inteligencia Artificial (IA), Realidad Virtual (VR), el Internet de las Cosas (IdC) y sensores, destacando su aplicación en las terapias propioceptivas, con énfasis en el EM, EES, y ERF. Se revisaron 107 artículos publicados en revistas científicas, de los cuales 30 cumplieron los criterios de inclusión: 1) Implementación de terapia de intervención propioceptiva; 2) uso de tecnología; 3) publicación posterior al año 2019, y 4) redacción en inglés. De los estudios analizados, el 43 % empleó IA, mostrando su creciente adopción, mientras que el IdC fue la tecnología menos utilizada, con un 3 %. Se concluye que las tecnologías emergentes son fundamentales en la rehabilitación propioceptiva, al permitir el análisis de información antes y después de procedimientos quirúrgicos, la evaluación de patronesentiemporeal, y la clasificación de señales sensoriales. Además, ofrecen alternativas efectivas frente a métodos tradiciones de medición.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[convolutional neural networks]]></kwd>
<kwd lng="en"><![CDATA[exoskeletons]]></kwd>
<kwd lng="en"><![CDATA[mechanical devices]]></kwd>
<kwd lng="en"><![CDATA[therapies]]></kwd>
<kwd lng="es"><![CDATA[dispositivos mecánicos]]></kwd>
<kwd lng="es"><![CDATA[exoesqueletos]]></kwd>
<kwd lng="es"><![CDATA[redes neuronales convolucionales]]></kwd>
<kwd lng="es"><![CDATA[terapias]]></kwd>
</kwd-group>
</article-meta>
</front><back>
<ref-list>
<ref id="B1">
<label>[1]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Bruyneel]]></surname>
<given-names><![CDATA[A.-V.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Evaluación de la propiocepción: pruebas de estatestesia y cinestesia]]></article-title>
<source><![CDATA[EMC-Kinesiter.-Med. Fis.]]></source>
<year>2016</year>
<volume>37</volume>
<numero>4</numero>
<issue>4</issue>
<page-range>1-11</page-range></nlm-citation>
</ref>
<ref id="B2">
<label>[2]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Tulimieri]]></surname>
<given-names><![CDATA[D. T.]]></given-names>
</name>
<name>
<surname><![CDATA[Semrau]]></surname>
<given-names><![CDATA[J. A.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Aging increases proprioceptive error for a broad range of movement speedand distance estimates in the upper limb]]></article-title>
<source><![CDATA[Front. Hum. Neurosci.]]></source>
<year>2023</year>
<volume>17</volume>
</nlm-citation>
</ref>
<ref id="B3">
<label>[3]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Alfonso Mora]]></surname>
<given-names><![CDATA[M. L.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Métodos de evaluación de la propiocepción en deportistas. Revisión de la Literatura]]></article-title>
<source><![CDATA[Rev. Digi. Act. Fís. Deport.]]></source>
<year>2018</year>
<volume>4</volume>
<numero>1</numero>
<issue>1</issue>
<page-range>69-82</page-range></nlm-citation>
</ref>
<ref id="B4">
<label>[4]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Khrulev]]></surname>
<given-names><![CDATA[A. E.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Modern Rehabilitation Technologies of Patients with Motor Disorders at an Early Rehabilitation of Stroke (Review)]]></article-title>
<source><![CDATA[Sovrem Tekhnologii Med.]]></source>
<year></year>
<volume>14</volume>
<numero>6</numero>
<issue>6</issue>
<page-range>64-78</page-range></nlm-citation>
</ref>
<ref id="B5">
<label>[5]</label><nlm-citation citation-type="confpro">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Cherpin]]></surname>
<given-names><![CDATA[A.]]></given-names>
</name>
</person-group>
<source><![CDATA[Apreliminary study on therelationship between proprioceptive deficits and motor functions in chronic stroke patients]]></source>
<year>2019</year>
<conf-name><![CDATA[ IEEE 16th International Conference on Rehabilitation Robotics (ICORR)]]></conf-name>
<conf-date>2019</conf-date>
<conf-loc>Toronto, Canada </conf-loc>
<page-range>465-70</page-range></nlm-citation>
</ref>
<ref id="B6">
<label>[6]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Suglia]]></surname>
<given-names><![CDATA[V.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[ASerious Game for the Assessment of Visuomotor Adaptation Capabilities during Locomotion Tasks Employing an Embodied Avatar in Virtual Reality]]></article-title>
<source><![CDATA[Sensors]]></source>
<year>2023</year>
<volume>23</volume>
<numero>11</numero>
<issue>11</issue>
</nlm-citation>
</ref>
<ref id="B7">
<label>[7]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Avanzino]]></surname>
<given-names><![CDATA[L.]]></given-names>
</name>
<name>
<surname><![CDATA[Fiorio]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Proprioceptive dysfunction in focal dystonia: From experimental evidence to rehabilitation strategies]]></article-title>
<source><![CDATA[Front. Hum. Neurosci.]]></source>
<year>2014</year>
<volume>8</volume>
</nlm-citation>
</ref>
<ref id="B8">
<label>[8]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Shibasaki]]></surname>
<given-names><![CDATA[H.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Anew form of congenital proprioceptive sensory neuropathy associated with arthrogryposis multiplex]]></article-title>
<source><![CDATA[J. Neurol.]]></source>
<year>2004</year>
<volume>251</volume>
<numero>11</numero>
<issue>11</issue>
<page-range>1340-4</page-range></nlm-citation>
</ref>
<ref id="B9">
<label>[9]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Aman]]></surname>
<given-names><![CDATA[J. E.]]></given-names>
</name>
<name>
<surname><![CDATA[Elangovan]]></surname>
<given-names><![CDATA[N.]]></given-names>
</name>
<name>
<surname><![CDATA[Yeh]]></surname>
<given-names><![CDATA[I. L.]]></given-names>
</name>
<name>
<surname><![CDATA[Konczak]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[The effectiveness of proprioceptive training for improving motor function: A systematic review]]></article-title>
<source><![CDATA[Front. Hum. Neurosci.]]></source>
<year>2015</year>
<volume>8</volume>
</nlm-citation>
</ref>
<ref id="B10">
<label>[10]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Vladimirovich Zakharov]]></surname>
<given-names><![CDATA[A.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Proprioception in Immersive Virtual Reality]]></article-title>
<source><![CDATA[Proprioception]]></source>
<year>2021</year>
<page-range>668</page-range></nlm-citation>
</ref>
<ref id="B11">
<label>[11]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Sidarta]]></surname>
<given-names><![CDATA[A.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Current clinical practice in managing somatosensory impairments and the use of technology in stroke rehabilitation]]></article-title>
<source><![CDATA[PLoS One]]></source>
<year>2022</year>
<volume>17</volume>
<numero>8</numero>
<issue>8</issue>
</nlm-citation>
</ref>
<ref id="B12">
<label>[12]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Valdes]]></surname>
<given-names><![CDATA[K.]]></given-names>
</name>
<name>
<surname><![CDATA[Manalang]]></surname>
<given-names><![CDATA[K. C.]]></given-names>
</name>
<name>
<surname><![CDATA[Leach]]></surname>
<given-names><![CDATA[C.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Proprioception: An evidence-based review]]></article-title>
<source><![CDATA[J. Hand Ther.]]></source>
<year>2023</year>
</nlm-citation>
</ref>
<ref id="B13">
<label>[13]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Mennella]]></surname>
<given-names><![CDATA[C.]]></given-names>
</name>
<name>
<surname><![CDATA[Maniscalco]]></surname>
<given-names><![CDATA[U.]]></given-names>
</name>
<name>
<surname><![CDATA[Pietro]]></surname>
<given-names><![CDATA[G. De]]></given-names>
</name>
<name>
<surname><![CDATA[Esposito]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Adeep learning system to monitor and assess rehabilitation exercises in home-based remote and unsupervised conditions]]></article-title>
<source><![CDATA[Comput. Biol. Med.]]></source>
<year>2023</year>
<volume>166</volume>
</nlm-citation>
</ref>
<ref id="B14">
<label>[14]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Aleixo]]></surname>
<given-names><![CDATA[P.]]></given-names>
</name>
<name>
<surname><![CDATA[Atalaia]]></surname>
<given-names><![CDATA[T.]]></given-names>
</name>
<name>
<surname><![CDATA[Patto]]></surname>
<given-names><![CDATA[J. V.]]></given-names>
</name>
<name>
<surname><![CDATA[Abrantes]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[The Effect of a Proprioceptive Exercises Programme on Disease Activity and Gait Biomechanical Parameters of Post-Menopausal Women with Rheumatoid Arthritis]]></article-title>
<source><![CDATA[Rheumatoid Arthritis]]></source>
<year>2022</year>
</nlm-citation>
</ref>
<ref id="B15">
<label>[15]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Liao]]></surname>
<given-names><![CDATA[Y.]]></given-names>
</name>
<name>
<surname><![CDATA[Vakanski]]></surname>
<given-names><![CDATA[A.]]></given-names>
</name>
<name>
<surname><![CDATA[Xian]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[ADeep Learning Framework for Assessing Physical Rehabilitation Exercises]]></article-title>
<source><![CDATA[IEEE Trans. Neural Syst. Rehabil. Eng.]]></source>
<year>2020</year>
<volume>28</volume>
<numero>2</numero>
<issue>2</issue>
<page-range>468-77</page-range></nlm-citation>
</ref>
<ref id="B16">
<label>[16]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Hossain]]></surname>
<given-names><![CDATA[D.]]></given-names>
</name>
<name>
<surname><![CDATA[Scott]]></surname>
<given-names><![CDATA[S. H.]]></given-names>
</name>
<name>
<surname><![CDATA[Cluff]]></surname>
<given-names><![CDATA[T.]]></given-names>
</name>
<name>
<surname><![CDATA[Dukelow]]></surname>
<given-names><![CDATA[S. P.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[The use of machine learning and deep learning techniques to assess proprioceptive impairments of the upper limb after stroke]]></article-title>
<source><![CDATA[J. Neuroeng. Rehabil.]]></source>
<year>2023</year>
<volume>20</volume>
<numero>1</numero>
<issue>1</issue>
</nlm-citation>
</ref>
<ref id="B17">
<label>[17]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Liu]]></surname>
<given-names><![CDATA[X. H.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Impaired Lower Limb Proprioception in Spinocerebellar Ataxia Type 3 and Its Affected Factors]]></article-title>
<source><![CDATA[Front. Neurol.]]></source>
<year>2022</year>
<volume>13</volume>
</nlm-citation>
</ref>
<ref id="B18">
<label>[18]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Vargas]]></surname>
<given-names><![CDATA[L.]]></given-names>
</name>
<name>
<surname><![CDATA[Huang]]></surname>
<given-names><![CDATA[H. H.]]></given-names>
</name>
<name>
<surname><![CDATA[Zhu]]></surname>
<given-names><![CDATA[Y.]]></given-names>
</name>
<name>
<surname><![CDATA[Hu]]></surname>
<given-names><![CDATA[X.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Static and dynamic proprioceptive recognition through vibrotactile stimulation]]></article-title>
<source><![CDATA[J. Neural. Eng.]]></source>
<year>2021</year>
<volume>18</volume>
<numero>4</numero>
<issue>4</issue>
<page-range>art. no. 046093</page-range></nlm-citation>
</ref>
<ref id="B19">
<label>[19]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Cyma-Wejchenig]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
<name>
<surname><![CDATA[Tarnas]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Marciniak]]></surname>
<given-names><![CDATA[K.]]></given-names>
</name>
<name>
<surname><![CDATA[Stemplewski]]></surname>
<given-names><![CDATA[R.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[The influence of proprioceptive training with the use of virtual reality on postural stabil ity of workers working at height]]></article-title>
<source><![CDATA[Sensors]]></source>
<year>2020</year>
<volume>20</volume>
<numero>13</numero>
<issue>13</issue>
</nlm-citation>
</ref>
<ref id="B20">
<label>[20]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Bogaar]]></surname>
<given-names><![CDATA[M. Van Den]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Validity of deep learning based motion capture using DeepLabCut to assess proprioception]]></article-title>
<source><![CDATA[Gait Posture]]></source>
<year>2023</year>
<volume>106</volume>
<numero>1</numero>
<issue>1</issue>
</nlm-citation>
</ref>
<ref id="B21">
<label>[21]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Saiki]]></surname>
<given-names><![CDATA[Y.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Reliabitily and validity of pose estimation algorithm for measurement of knee range of motion after total knee arthroplasty]]></article-title>
<source><![CDATA[Bone Joint Res.]]></source>
<year>2023</year>
<volume>12</volume>
<numero>5</numero>
<issue>5</issue>
<page-range>313-20</page-range></nlm-citation>
</ref>
<ref id="B22">
<label>[22]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Wang]]></surname>
<given-names><![CDATA[Y.]]></given-names>
</name>
<name>
<surname><![CDATA[Pei]]></surname>
<given-names><![CDATA[Z.]]></given-names>
</name>
<name>
<surname><![CDATA[Wang]]></surname>
<given-names><![CDATA[C.]]></given-names>
</name>
<name>
<surname><![CDATA[Tang]]></surname>
<given-names><![CDATA[Z.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Depth-aware pose estimation using deep learning for exoskeleton gait analysis]]></article-title>
<source><![CDATA[Sci Rep]]></source>
<year>2023</year>
<volume>13</volume>
<numero>1</numero>
<issue>1</issue>
</nlm-citation>
</ref>
<ref id="B23">
<label>[23]</label><nlm-citation citation-type="confpro">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Su]]></surname>
<given-names><![CDATA[W.]]></given-names>
</name>
<name>
<surname><![CDATA[Liu]]></surname>
<given-names><![CDATA[Y.]]></given-names>
</name>
<name>
<surname><![CDATA[Li]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
<name>
<surname><![CDATA[Cai]]></surname>
<given-names><![CDATA[Z.]]></given-names>
</name>
</person-group>
<source><![CDATA[Proprioception-Driven Wearer Pose Estimation for Egocentric Video]]></source>
<year>2022</year>
<conf-name><![CDATA[ 26thInternational Conference on Pattern Recognition (ICPR)]]></conf-name>
<conf-date>2022</conf-date>
<conf-loc>Montreal, Canada </conf-loc>
<page-range>3728-35</page-range></nlm-citation>
</ref>
<ref id="B24">
<label>[24]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Guler]]></surname>
<given-names><![CDATA[Y.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Shoulder Proprioception Following Reverse Total Shoulder Arthroplasty for Unreconstructable Upper Third Fractures of the Humerus: 2-Year Outcomes 2022]]></article-title>
<source><![CDATA[Indian J. Orthop.]]></source>
<year>2022</year>
<volume>56</volume>
<numero>12</numero>
<issue>12</issue>
<page-range>2245-52</page-range></nlm-citation>
</ref>
<ref id="B25">
<label>[25]</label><nlm-citation citation-type="">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Melício]]></surname>
<given-names><![CDATA[Dos Santos]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[DeepRehab: Real Time Pose Estimation on the Edge for Knee Injury Rehabilitation]]></article-title>
<source><![CDATA[Artificial Neural Networks and Machine Learning-ICANN 2021]]></source>
<year>2021</year>
<publisher-loc><![CDATA[Bratislava, Slovakia ]]></publisher-loc>
</nlm-citation>
</ref>
<ref id="B26">
<label>[26]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Mo]]></surname>
<given-names><![CDATA[F.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Asimulation-based framework with a proprioceptive musculoskeletal model for evaluating the rehabilitation exoskeleton system]]></article-title>
<source><![CDATA[Comput. Methods Programs Biomed.]]></source>
<year>2021</year>
<volume>208</volume>
</nlm-citation>
</ref>
<ref id="B27">
<label>[27]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Boswell]]></surname>
<given-names><![CDATA[M. A.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Aneural network to predict the knee adduction moment in patients with osteoarthritis using anatomical landmarks obtainable from 2D video analysis]]></article-title>
<source><![CDATA[Osteoarthritis Cartilage]]></source>
<year>2021</year>
<volume>29</volume>
<numero>3</numero>
<issue>3</issue>
<page-range>346-56</page-range></nlm-citation>
</ref>
<ref id="B28">
<label>[28]</label><nlm-citation citation-type="confpro">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Lapresa]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
</person-group>
<source><![CDATA[ASmart Solution for Proprioceptive Rehabilitation through M-IMU Sensors]]></source>
<year>2020</year>
<conf-name><![CDATA[ IEEE International Workshop on Metrology for Industry 4.0 &amp; IoT]]></conf-name>
<conf-date>2020</conf-date>
<conf-loc>Roma, Italy </conf-loc>
<page-range>591-5</page-range></nlm-citation>
</ref>
<ref id="B29">
<label>[29]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Wang]]></surname>
<given-names><![CDATA[R.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Real-time Soft Body 3D Proprioception via Deep Vision-based Sensing]]></article-title>
<source><![CDATA[IEEE Robot Autom. Lett.]]></source>
<year>2020</year>
<volume>5</volume>
<numero>2</numero>
<issue>2</issue>
<page-range>3382-9</page-range></nlm-citation>
</ref>
<ref id="B30">
<label>[30]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Rahlf]]></surname>
<given-names><![CDATA[A. L.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Validity and Reliability of an Inertial Sensor-Based Knee Proprioception Test in Younger vs. Older Adults]]></article-title>
<source><![CDATA[Front. Sports Act. Living.]]></source>
<year>2019</year>
<volume>1</volume>
</nlm-citation>
</ref>
<ref id="B31">
<label>[31]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Kuling]]></surname>
<given-names><![CDATA[I. A.]]></given-names>
</name>
<name>
<surname><![CDATA[Brouwer]]></surname>
<given-names><![CDATA[A. J. de]]></given-names>
</name>
<name>
<surname><![CDATA[Smeets]]></surname>
<given-names><![CDATA[J. B. J.]]></given-names>
</name>
<name>
<surname><![CDATA[Flanagan]]></surname>
<given-names><![CDATA[J. R.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Correcting for natural visuo-proprioceptive matching errors based on reward as opposed to error feedback does not lead to higher retention]]></article-title>
<source><![CDATA[Exp. Brain Res.]]></source>
<year>2019</year>
<volume>237</volume>
<numero>3</numero>
<issue>3</issue>
<page-range>735-41</page-range></nlm-citation>
</ref>
<ref id="B32">
<label>[32]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Sandbrink]]></surname>
<given-names><![CDATA[K. J.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Contrasting action and posture coding with hierarchical deep neural network models of proprioception]]></article-title>
<source><![CDATA[Elife]]></source>
<year>2023</year>
<volume>12</volume>
</nlm-citation>
</ref>
<ref id="B33">
<label>[33]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Winter]]></surname>
<given-names><![CDATA[L.]]></given-names>
</name>
<name>
<surname><![CDATA[Huang]]></surname>
<given-names><![CDATA[Q.]]></given-names>
</name>
<name>
<surname><![CDATA[Sertic]]></surname>
<given-names><![CDATA[J. V. L.]]></given-names>
</name>
<name>
<surname><![CDATA[Konczak]]></surname>
<given-names><![CDATA[J.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[The Effectiveness of Proprioceptive Training for Improving Motor Performance and Motor Dysfunction: A Systematic Review]]></article-title>
<source><![CDATA[Front. Rehabil. Sci.]]></source>
<year>2022</year>
<volume>3</volume>
</nlm-citation>
</ref>
<ref id="B34">
<label>[34]</label><nlm-citation citation-type="book">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Mehta]]></surname>
<given-names><![CDATA[P.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Paresthesias and dysesthesias]]></article-title>
<source><![CDATA[Imaging Acute Neurologic Disease: A Symptom-Based Approach]]></source>
<year>2014</year>
<page-range>332-46</page-range><publisher-name><![CDATA[Cambridge University Press]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B35">
<label>[35]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Buist]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Novel Wearable Device for Mindful Sensorimotor Training: Integrating Motor Decoding and Somatosensory Stimulation for Neurorehabilitation]]></article-title>
<source><![CDATA[IEEE Trans. Neural Syst. Rehabil. Eng.]]></source>
<year>2024</year>
<volume>32</volume>
<page-range>1515-23</page-range></nlm-citation>
</ref>
<ref id="B36">
<label>[36]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Marin Vargas]]></surname>
<given-names><![CDATA[A.]]></given-names>
</name>
<name>
<surname><![CDATA[Bisi]]></surname>
<given-names><![CDATA[A.]]></given-names>
</name>
<name>
<surname><![CDATA[Chiappa]]></surname>
<given-names><![CDATA[A. S.]]></given-names>
</name>
<name>
<surname><![CDATA[Versteeg]]></surname>
<given-names><![CDATA[C.]]></given-names>
</name>
<name>
<surname><![CDATA[Miller]]></surname>
<given-names><![CDATA[L. E.]]></given-names>
</name>
<name>
<surname><![CDATA[Mathis]]></surname>
<given-names><![CDATA[A.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Task-driven neural network models predict neural dynamics of proprioception]]></article-title>
<source><![CDATA[Cell]]></source>
<year>2024</year>
<volume>187</volume>
<numero>7</numero>
<issue>7</issue>
<page-range>1745-61</page-range></nlm-citation>
</ref>
<ref id="B37">
<label>[37]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Yeh]]></surname>
<given-names><![CDATA[L.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Effects of a robot&#8208;aided somatosensory training on proprioception and motor function in stroke survivors]]></article-title>
<source><![CDATA[J. Neuroeng. Rehabil.]]></source>
<year>2021</year>
<volume>18</volume>
<numero>1</numero>
<issue>1</issue>
</nlm-citation>
</ref>
<ref id="B38">
<label>[38]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Valle]]></surname>
<given-names><![CDATA[G.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[APsychometric Platform to Collect Somatosensory Sensations for Neuroprosthetic Use]]></article-title>
<source><![CDATA[Front. Med. Technol.]]></source>
<year>2021</year>
<volume>3</volume>
</nlm-citation>
</ref>
<ref id="B39">
<label>[39]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Lim]]></surname>
<given-names><![CDATA[C.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Multi-sensorimotor training improves proprioception and balance in subacute stroke patients: A randomized controlled pilot trial]]></article-title>
<source><![CDATA[Front. Neurol.]]></source>
<year>2019</year>
<volume>10</volume>
</nlm-citation>
</ref>
<ref id="B40">
<label>[40]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Dover]]></surname>
<given-names><![CDATA[G.]]></given-names>
</name>
<name>
<surname><![CDATA[Powers]]></surname>
<given-names><![CDATA[M. E.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Reliability of Joint Position Sense and Force-Reproduction Measures During Internal and External Rotation of the Shoulder]]></article-title>
<source><![CDATA[J. Athl. Train.]]></source>
<year>2003</year>
<volume>38</volume>
<numero>4</numero>
<issue>4</issue>
<page-range>304-10</page-range></nlm-citation>
</ref>
<ref id="B41">
<label>[41]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Coskun]]></surname>
<given-names><![CDATA[G.]]></given-names>
</name>
<name>
<surname><![CDATA[Talu]]></surname>
<given-names><![CDATA[B.]]></given-names>
</name>
<name>
<surname><![CDATA[Cools]]></surname>
<given-names><![CDATA[A.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Proprioceptive force-reproduction of the rotator cuff in healthy subjects before and after muscle fatigue]]></article-title>
<source><![CDATA[Isokinet. Exerc. Sci.]]></source>
<year>2018</year>
<volume>26</volume>
<numero>3</numero>
<issue>3</issue>
<page-range>175-81</page-range></nlm-citation>
</ref>
<ref id="B42">
<label>[42]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Zhang]]></surname>
<given-names><![CDATA[H.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[AFramework of a Lower Limb Musculoskeletal Model with Implemented Natural Proprioceptive Feedback and Its Progressive Evaluation]]></article-title>
<source><![CDATA[IEEE Trans. Neural Syst. Rehabil. Eng.]]></source>
<year>2020</year>
<volume>28</volume>
<numero>8</numero>
<issue>8</issue>
<page-range>1866-75</page-range></nlm-citation>
</ref>
<ref id="B43">
<label>[43]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Xu]]></surname>
<given-names><![CDATA[C.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Anadvanced bionic knee joint mechanism with neural network controller]]></article-title>
<source><![CDATA[Front. Neurorobot]]></source>
<year>2023</year>
<volume>17</volume>
</nlm-citation>
</ref>
<ref id="B44">
<label>[44]</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Li]]></surname>
<given-names><![CDATA[L.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Effect of pinch types on pinch force sense in healthy adults]]></article-title>
<source><![CDATA[Front. Hum. Neurosci.]]></source>
<year>2022</year>
<volume>16</volume>
</nlm-citation>
</ref>
</ref-list>
</back>
</article>
