000130139 001__ 130139
000130139 005__ 20241125101150.0
000130139 0247_ $$2doi$$a10.1109/TNSRE.2023.3315146
000130139 0248_ $$2sideral$$a136504
000130139 037__ $$aART-2023-136504
000130139 041__ $$aeng
000130139 100__ $$aLubel, Emma
000130139 245__ $$aNon-linearity in motor unit velocity twitch dynamics: implications for ultrafast ultrasound source separation
000130139 260__ $$c2023
000130139 5060_ $$aAccess copy available to the general public$$fUnrestricted
000130139 5203_ $$aUltrasound (US) muscle image series can be used for peripheral human-machine interfacing based on global features, or even on the decomposition of US images into the contributions of individual motor units (MUs). With respect to state-of-the-art surface electromyography (sEMG), US provides higher spatial resolution and deeper penetration depth. However, the accuracy of current methods for direct US decomposition, even at low forces, is relatively poor. These methods are based on linear mathematical models of the contributions of MUs to US images. Here, we test the hypothesis of linearity by comparing the average velocity twitch profiles of MUs when varying the number of other concomitantly active units. We observe that the velocity twitch profile has a decreasing peak-to-peak amplitude when tracking the same target motor unit at progressively increasing contraction force levels, thus with an increasing number of concomitantly active units. This observation indicates non-linear factors in the generation model. Furthermore, we directly studied the impact of one MU on a neighboring MU, finding that the effect of one source on the other is not symmetrical and may be related to unit size. We conclude that a linear approximation is partly limiting the decomposition methods to decompose full velocity twitch trains from velocity images, highlighting the need for more advanced models and methods for US decomposition than those currently employed.
000130139 536__ $$9info:eu-repo/grantAgreement/EC/H2020/899822/EU/Ultrasound peripheral interface and in-vitro model of human somatosensory system and muscles for motor decoding and restoration of somatic sensations in amputees/SOMA$$9This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 899822-SOMA$$9info:eu-repo/grantAgreement/ES/MICINN/RYC2021-031905-I
000130139 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000130139 590__ $$a4.8$$b2023
000130139 592__ $$a1.315$$b2023
000130139 591__ $$aREHABILITATION$$b5 / 170 = 0.029$$c2023$$dQ1$$eT1
000130139 593__ $$aBiomedical Engineering$$c2023$$dQ1
000130139 591__ $$aENGINEERING, BIOMEDICAL$$b32 / 123 = 0.26$$c2023$$dQ2$$eT1
000130139 593__ $$aComputer Science Applications$$c2023$$dQ1
000130139 593__ $$aRehabilitation$$c2023$$dQ1
000130139 593__ $$aMedicine (miscellaneous)$$c2023$$dQ1
000130139 593__ $$aNeuroscience (miscellaneous)$$c2023$$dQ1
000130139 593__ $$aInternal Medicine$$c2023$$dQ1
000130139 594__ $$a8.6$$b2023
000130139 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000130139 700__ $$aSgambato, Bruno Grandi
000130139 700__ $$aRohlén, Robin
000130139 700__ $$0(orcid)0000-0001-8439-151X$$aIbánez, Jaime$$uUniversidad de Zaragoza
000130139 700__ $$aBarsakcioglu, Deren Y.
000130139 700__ $$aTang, Meng-Xing
000130139 700__ $$aFarina, Dario
000130139 7102_ $$15008$$2800$$aUniversidad de Zaragoza$$bDpto. Ingeniería Electrón.Com.$$cÁrea Teoría Señal y Comunicac.
000130139 773__ $$g31 (2023), 3699-3710$$pIEEE trans. neural syst. rehabil. eng.$$tIEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING$$x1534-4320
000130139 8564_ $$s14847574$$uhttps://zaguan.unizar.es/record/130139/files/texto_completo.pdf$$yVersión publicada
000130139 8564_ $$s3492503$$uhttps://zaguan.unizar.es/record/130139/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000130139 909CO $$ooai:zaguan.unizar.es:130139$$particulos$$pdriver
000130139 951__ $$a2024-11-22-12:06:42
000130139 980__ $$aARTICLE