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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Hum. Neurosci.</journal-id>
<journal-title>Frontiers in Human Neuroscience</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Hum. Neurosci.</abbrev-journal-title>
<issn pub-type="epub">1662-5161</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fnhum.2025.1629003</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Human Neuroscience</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Dual 500-&#x03BC;s wide pulse neuromuscular electrical stimulation enhancing sensorimotor cortical excitability</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" corresp="yes">
<name><surname>Zhao</surname> <given-names>Yun</given-names></name>
<xref ref-type="corresp" rid="c001"><sup>&#x002A;</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/3067825/overview"/>
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</contrib>
<contrib contrib-type="author">
<name><surname>Yan</surname> <given-names>Yanying</given-names></name>
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</contrib>
<contrib contrib-type="author">
<name><surname>Zhang</surname> <given-names>Xiaoling</given-names></name>
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</contrib>
<contrib contrib-type="author">
<name><surname>Xie</surname> <given-names>Guanghui</given-names></name>
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</contrib>
<contrib contrib-type="author">
<name><surname>Yang</surname> <given-names>Renqaing</given-names></name>
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</contrib>
<contrib contrib-type="author">
<name><surname>Zou</surname> <given-names>Shuaidong</given-names></name>
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</contrib>
<contrib contrib-type="author">
<name><surname>Gao</surname> <given-names>Fengmei</given-names></name>
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</contrib>
<contrib contrib-type="author">
<name><surname>Sun</surname> <given-names>Wencheng</given-names></name>
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</contrib-group>
<aff><institution>School of Smart Health, Chongqing Polytechnic University of Electronic Technology</institution>, <addr-line>Chongqing</addr-line>, <country>China</country></aff>
<author-notes>
<fn fn-type="edited-by" id="fn0001">
<p>Edited by: William M. Land, University of Texas at San Antonio, United States</p>
</fn>
<fn fn-type="edited-by" id="fn0002">
<p>Reviewed by: Markey Cierra Olson, Barrow Neurological Institute (BNI), United States</p>
<p>Pawan Sharma, Kessler Foundation, United States</p>
</fn>
<corresp id="c001">&#x002A;Correspondence: Yun Zhao, <email>zhaoyun@cqcet.edu.cn</email></corresp>
</author-notes>
<pub-date pub-type="epub">
<day>28</day>
<month>07</month>
<year>2025</year>
</pub-date>
<pub-date pub-type="collection">
<year>2025</year>
</pub-date>
<volume>19</volume>
<elocation-id>1629003</elocation-id>
<history>
<date date-type="received">
<day>15</day>
<month>05</month>
<year>2025</year>
</date>
<date date-type="accepted">
<day>15</day>
<month>07</month>
<year>2025</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x00A9; 2025 Zhao, Yan, Zhang, Xie, Yang, Zou, Gao and Sun.</copyright-statement>
<copyright-year>2025</copyright-year>
<copyright-holder>Zhao, Yan, Zhang, Xie, Yang, Zou, Gao and Sun</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<sec id="sec1">
<title>Background</title>
<p>Neuromuscular electrical stimulation (NMES) is an effective tool to improve motor activation of patients with motor dysfunction. However, to enhance the cortical activities induced by NMES, the corresponding strategies should be carefully designed with optimal stimulation parameters. The aim of the present study is to investigate whether the pulse assignment with wide-pulse-based Variable Frequency Trains improves sensorimotor cortical excitability.</p>
</sec>
<sec id="sec2">
<title>Methods</title>
<p>A block-designed experiment was conducted with NMES delivering current to right biceps brachii muscle in nine healthy right-handed adults to evoke repetitive elbow flexion under similar kinetic parameters (<italic>p</italic>&#x202F;&#x003E;&#x202F;0.05). A new NMES pattern with the combination of wide-pulse and Variable Frequency Trains (wDFT, variable-frequency trains with 2-let frequency train) was set to compare with other NMES patterns, i.e., variable-frequency trains with narrow-pulse (nVFT, 8-let frequency train), constant-frequency trains with narrow-pulse (nCFT, one pulse), and CFT with wide-pulse (wCFT, one pulse). The excitability levels of sensorimotor regions were investigated based on beta event-related desynchronization (ERD) analysis.</p>
</sec>
<sec id="sec3">
<title>Results</title>
<p>Although evoking similar elbow flexion movements, variable-frequency trains (VFT) could induce stronger cortical activities than constant-frequency trains (CFT). Moreover, the sensorimotor cortex responded significantly more preferably to the dual 500&#x202F;&#x03BC;s wide pulse VFT (wDFT) stimulation pattern (<italic>p</italic>&#x202F;&#x003C;&#x202F;0.05). In general, VFT induced higher amplitudes and descending slopes of beta ERD than CFT did during evoking elbow flexion movements, among which wDFT induced the highest beta ERD intensity and its descending slope (<italic>p</italic>&#x202F;&#x003C;&#x202F;0.05). In addition, the current efficiency of VFT to modulate sensorimotor cortical activities was higher than that of CFT pattern.</p>
</sec>
<sec id="sec4">
<title>Conclusion</title>
<p>The VFT pattern, especially dual 500&#x202F;&#x03BC;s wide pulse VFT, could enhance sensorimotor cortical excitability, and the central neural activities improvements may attribute to the fact that more afferent fibers are effectively activated. Therefore, our findings indicated the high potential of utilizing DFT with wide pulses to optimize NMES applications in motor rehabilitation.</p>
</sec>
</abstract>
<kwd-group>
<kwd>neuromuscular electrical stimulation</kwd>
<kwd>variable-frequency trains</kwd>
<kwd>cortical excitability</kwd>
<kwd>afferent fibers</kwd>
<kwd>EEG</kwd>
</kwd-group>
<counts>
<fig-count count="8"/>
<table-count count="1"/>
<equation-count count="4"/>
<ref-count count="42"/>
<page-count count="11"/>
<word-count count="7771"/>
</counts>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Motor Neuroscience</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec sec-type="intro" id="sec5">
<label>1</label>
<title>Introduction</title>
<p>Motor dysfunction after stroke is generally associated with a reduction of central nervous system (CNS) circuit excitability and a decreased cortical representation area corresponding to the affected limbs (<xref ref-type="bibr" rid="ref40">Yu et al., 2024</xref>). Successful rehabilitation with partial/entire functional recovery may enhance brain activities that control spontaneous movements (<xref ref-type="bibr" rid="ref14">Joy and Carmichael, 2021</xref>). Recently, neuromuscular electrical stimulation (NMES) has been considered as one sufficient intervention to induce high-level cortical excitability or rapid reorganization in sensorimotor cortices for patients with physical impairments (<xref ref-type="bibr" rid="ref5">Carson and Buick, 2021</xref>; <xref ref-type="bibr" rid="ref42">Zhang et al., 2023</xref>). <xref ref-type="bibr" rid="ref27">Powell et al. (1999)</xref> have reported that NMES could increase recovery of wrist extension over standard care in hemiplegic patients, and it has been also demonstrated to induce neuroplasticity by increasing the baseline level of spinal excitability such that low levels of input result in voluntary motor function in the patients with spinal cord injury (<xref ref-type="bibr" rid="ref16">Karamian et al., 2022</xref>). Brain imaging studies showed that the NMES-evoked movements induced reliable cortical excitability enhancement and plastic changes in specific neural regions (<xref ref-type="bibr" rid="ref35">Tenberg et al., 2023</xref>; <xref ref-type="bibr" rid="ref12">Insausti-Delgado et al., 2021</xref>). Further research on chronic stroke patients confirmed that changes in sensorimotor area are accompanied with effective hand recovery (<xref ref-type="bibr" rid="ref19">Kimberley et al., 2004</xref>). It is clear that the NMES-induced activity change and adaptive reorganization in brain play an important role in human behavioral restorations following rehabilitation treatments. Researchers have attempted to improve the rehabilitation-mediated functional brain changes through optimizing the NMES patterns (<xref ref-type="bibr" rid="ref43">Zhao et al., 2018</xref>; <xref ref-type="bibr" rid="ref25">Obayashi and Saito, 2022</xref>; <xref ref-type="bibr" rid="ref30">Ryoki et al., 2017</xref>). Parameters of the NMES patterns, such as stimulation intensity, frequency or pulse width were optimized to enhance the sensorimotor cortical excitability and subsequently impact the efficiency of rehabilitation (<xref ref-type="bibr" rid="ref22">Makii et al., 2015</xref>; <xref ref-type="bibr" rid="ref39">Wegrzyk et al., 2017</xref>; <xref ref-type="bibr" rid="ref13">Jiang et al., 2019</xref>).</p>
<p>Usually, neuromuscular electrical stimulations directly activate motor axons beneath the electrodes to induce isometric contractions (i.e., efferent/peripheral pathway) (<xref ref-type="bibr" rid="ref3">Bergquist et al., 2011</xref>). Also, the electric pulse can generate contractions through reflexive recruitments of motoneurons by depolarizing the sensory fibers and ascending afferent volleys that contribute to cortical activity regulation (i.e., afferent/central pathway) (<xref ref-type="bibr" rid="ref28">Qu et al., 2020</xref>). Therefore, the neuroplasticity changes in the central nervous system driven by NMES may be substantially related to increasing sensory axons recruitments. The sensory fibers and motor axons were reported to have different electrical excitabilities depending upon their intrinsic properties including strength-duration time constant and rheobase (<xref ref-type="bibr" rid="ref36">Veale et al., 1973</xref>; <xref ref-type="bibr" rid="ref18">Kiernan et al., 2004</xref>). Accordingly, the pulse duration was considered as a major factor affecting the priority of sensory or motor axon recruitments in NMES (<xref ref-type="bibr" rid="ref39">Wegrzyk et al., 2017</xref>). Some recent studies have reported the effect of stimulation intensity and stimulation frequency on brain activation patterns (<xref ref-type="bibr" rid="ref12">Insausti-Delgado et al., 2021</xref>; <xref ref-type="bibr" rid="ref2">Backes et al., 2000</xref>; <xref ref-type="bibr" rid="ref15">Kampe et al., 2000</xref>), but few studies have investigated whether stimulation pulse width affects cortical activities. The brain imaging study has just reported that the modulation of wide pulses resulted in differently activated brain regions, that is, NMES with wide pulses (100&#x202F;Hz-1&#x202F;ms) resulted in lower deactivation in the secondary somatosensory cortex and precuneus, while the conventional pattern (25&#x202F;Hz&#x2013;0.05&#x202F;ms) induced larger hyperactivated in the bilateral thalami and caudate nuclei during stimulating the triceps surae of healthy subjects (<xref ref-type="bibr" rid="ref39">Wegrzyk et al., 2017</xref>). Herein, the present study wanted to determine whether the optimized NMES pattern with wide pulses could better enhance cortical activities.</p>
<p>Traditional NMES pattern is constant-frequency trains (CFT) which generally composes of successive narrow stimulus pulses (&#x003C; 400&#x202F;&#x03BC;s) and is applied at repetitive frequency of 15-40&#x202F;Hz (<xref ref-type="bibr" rid="ref7">Collins, 2007</xref>). This conventional CFT stimulations can artificially elicit muscle contractions to recruit motor units (MUs) resulting from motor neurons depolarization primarily through efferent/peripheral mechanism (<xref ref-type="bibr" rid="ref39">Wegrzyk et al., 2017</xref>) and less sensory fiber activation through afferent/central pathway. The low priority of sensory axons recruitments in CFT stimulation is attributed to the differential sensitivity and antidromic collisions between sensory and motor fibers (<xref ref-type="bibr" rid="ref36">Veale et al., 1973</xref>; <xref ref-type="bibr" rid="ref18">Kiernan et al., 2004</xref>). Recently, wide duration pulses (pulse width of 0.5&#x2013;1&#x202F;ms) have been reported a tendency of preferably stimulating more sensory rather than motor axons, causing the resultant afferent inputs ascending through spine pathway to enhance cortical activities in the central nervous system circuit (<xref ref-type="bibr" rid="ref3">Bergquist et al., 2011</xref>). <xref ref-type="bibr" rid="ref26">Panizza et al. (1992)</xref> demonstrated that wider stimulus duration (0.5&#x2013;1&#x202F;ms) facilitated eliciting Hoffmann reflexes (H-reflexes) in healthy volunteers which reflected information of the sensory fiber excitation (<xref ref-type="bibr" rid="ref29">Rongsawad and Ratanapinunchai, 2018</xref>). <xref ref-type="bibr" rid="ref20">Lagerquist and Collins (2010)</xref> also observed that NMES with wide pulses applied to 15 healthy subjects evoked more afferent volley.</p>
<p>Compared to conventional CFT, Variable Frequency Trains (VFT) is an alternative stimulus pattern that can evoke muscle contractions in a more physiological manner (<xref ref-type="bibr" rid="ref8">Deley et al., 2014</xref>; <xref ref-type="bibr" rid="ref17">Karu et al., 1995</xref>; <xref ref-type="bibr" rid="ref10">Doll et al., 2018</xref>; <xref ref-type="bibr" rid="ref4">Carole et al., 2016</xref>). Each of those electrical pulses in VFT could only induce subthreshold depolarizations of axons, and different numbers of subthreshold depolarizations could be temporally summed to activate different axons with different activation thresholds, leading to recruiting MUs in asynchronous pattern (<xref ref-type="bibr" rid="ref4">Carole et al., 2016</xref>). MUs recruitment in asynchronous pattern mainly resulted from directly activating motor axons (efferent pathway) and indirectly recruiting motoneurons in the spinal cord by activating sensory axons (afferent pathway) (<xref ref-type="bibr" rid="ref3">Bergquist et al., 2011</xref>). Carole employed a special stimulation protocol of VFT that consisted of N high-frequency stimuli (called N-lets) with long inter-period intervals (<xref ref-type="bibr" rid="ref4">Carole et al., 2016</xref>), and doublet-frequency train (DFT, <italic>N</italic>&#x202F;=&#x202F;2) was acknowledged as the most successful train in force improvement (<xref ref-type="bibr" rid="ref17">Karu et al., 1995</xref>). While VFT has been reported more profit to evoking muscle contraction compared to CFT, studies have not investigated the effect of VFT, especially DFT with wide pulses, on cortical activities. Herein, we hypothesized that the pulse assignment with wide-pulse-based VFT neuromuscular stimulation would better enhance sensorimotor cortical activities due to the activation of more sensory fibers during evoking elbow flexion movements of right upper limb. The purposes of the present study were to evaluate the effect of pulse assignment of NMES patterns on the neural activations in sensorimotor areas and investigate whether dual wide-pulses in doublets have an advantage in the sensorimotor cortical excitability improvement during evoking functional elbow flexion movements. We evaluated sensorimotor cortical excitability through quantifying the Beta ERD from EEG data from Electrode C3 located in left sensorimotor cortex with the corresponding ERD properties (amplitude and descending slope).</p>
</sec>
<sec sec-type="methods" id="sec6">
<label>2</label>
<title>Methods</title>
<sec id="sec7">
<label>2.1</label>
<title>Subjects</title>
<p>Nine healthy right-handed subjects (three females and six males, 24&#x202F;&#x00B1;&#x202F;2&#x202F;years old) were recruited. All subjects were confirmed with no history of former cardiovascular disease, neurological disorders or orthopedic problems in arms. Subjects were also free of upper limb resistance training in the past 6&#x202F;months and no NMES treatment experience before. This study was reviewed and approved by the Ethics Committee of Chongqing Polytechnic University of Electronic Technology (approval code: 001/2024), and written informed consent was obtained from every participant, in accordance with the Declaration of Helsinki.</p>
</sec>
<sec id="sec8">
<label>2.2</label>
<title>Experimental protocol</title>
<p>The diagram of the experimental setup was illustrated in <xref ref-type="fig" rid="fig1">Figure 1a</xref>. The stimulation electrodes were placed on right biceps brachii muscle of all subjects to evoke the specific elbow flexion movements, and the stimulation current was delivered using Programmable Stimulator (Master-9, AMPI, Jerusalem, Israel) and isolated cables (ISO-Flex, AMPI, Jerusalem, Israel). An inertial measurement unit (IMU) (MPU6050, Vit motion, China) was placed on dorsal forearm of subjects to collect the kinematic data of elbow flexion movements. During the experiment, a multichannel wireless Electroencephalographic (EEG) acquisition system (STARSTIM-8, Neuroelectrics, Inc., Spain) was used to record EEG signals.</p>
<fig position="float" id="fig1">
<label>Figure 1</label>
<caption>
<p>Experimental setup for sensorimotor cortex excitability assessment during NMES: <bold>(a)</bold> the experimental framework, <bold>(b)</bold> the designed NMES patterns for delivery, <bold>(c)</bold> the experimental paradigm of each trial.</p>
</caption>
<graphic xlink:href="fnhum-19-1629003-g001.tif">
<alt-text content-type="machine-generated">Diagram of an experimental setup showing: (a) a person with EEG sensors and NMES electrodes on the arm, and an IMU near the elbow. (b) Graphs of stimulation patterns named wCFT, wDFT, nCFT, and nVFT, with time intervals marked, showing different pulse widths. (c) A timeline divided into preparation, elbow flexion movements, and rest phases, spanning zero to thirteen seconds.</alt-text>
</graphic>
</fig>
<p>The stimulation protocol was consisted of four stimulation patterns (<xref ref-type="fig" rid="fig1">Figure 1b</xref>), i.e., VFT with narrow-pulse (nVFT, Variable Frequency Trains with 8-let frequency train), DFT with wide-pulse (wDFT, Variable Frequency Trains with 2-let frequency train), CFT with narrow-pulse (nCFT, one pulse), and CFT with wide-pulse (wCFT, one pulse). During the 3-s elbow flexion, electric pulse trains were delivered with a repetitive frequency of 50&#x202F;Hz (burst frequency of pulse trains) with the pulse width of narrow pulse of 250&#x202F;&#x03BC;s and the pulse width of wide pulse of 500&#x202F;&#x03BC;s. The detail of stimulation parameters was illustrated in <xref ref-type="table" rid="tab1">Table.1</xref>.</p>
<table-wrap position="float" id="tab1">
<label>Table 1</label>
<caption>
<p>The parameters of four types stimulation patterns.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th>Patterns</th>
<th align="left" valign="top">Pulse width</th>
<th align="left" valign="top">Burst frequency of pulse trains</th>
<th align="left" valign="top">Pulses per train</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top">nVFT</td>
<td align="center" valign="top">250&#x202F;&#x03BC;s</td>
<td align="center" valign="top">50&#x202F;Hz</td>
<td align="center" valign="top">8</td>
</tr>
<tr>
<td align="left" valign="top">wDFT</td>
<td align="center" valign="top">500&#x202F;&#x03BC;s</td>
<td align="center" valign="top">50&#x202F;Hz</td>
<td align="center" valign="top">2</td>
</tr>
<tr>
<td align="left" valign="top">nCFT</td>
<td align="center" valign="top">250&#x202F;&#x03BC;s</td>
<td align="center" valign="top">50&#x202F;Hz</td>
<td align="center" valign="top">1</td>
</tr>
<tr>
<td align="left" valign="top">wCFT</td>
<td align="center" valign="top">500&#x202F;&#x03BC;s</td>
<td align="center" valign="top">50&#x202F;Hz</td>
<td align="center" valign="top">1</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>In each trial (13&#x202F;s), subjects were required to keep their arm sagging naturally in a peaceful and relaxed state at the first 2&#x202F;s for preparation; then a 3-s elbow flexion task (described in section 2.3) was performed and natural elbow extension followed to the initial position within an 8-s rest interval before next trial (<xref ref-type="fig" rid="fig1">Figure 1c</xref>). In addition, a 10-min rest interval was set between two elbow flexion tasks to avoid muscle fatigue. Experiments were carried out in a quiet room with room temperature kept at 26&#x202F;&#x00B1;&#x202F;1&#x00B0;C.</p>
</sec>
<sec id="sec9">
<label>2.3</label>
<title>Experimental tasks</title>
<p>Subjects paid two visits to the laboratory on 2 separate days with 1&#x202F;day interval. The main purpose of the 1st visit was to determine the stimulating parameters, such as the maximum angle of elbow flexion. To determine the stimulation electrode position, the skin of all subjects was firstly prepared using an alcohol pad. Then we placed round hydrogel electrodes (3&#x202F;cm in diameter) on the top of the right biceps brachii (BIC) muscle. Once determined the stimulation point, we marked and fixed the position by medical adhesive tape. Subjects were blind to these parameters during whole tasks.</p>
<p>The tasks were performed during the second visit. There were four tasks performed according to the order of nVFT-evoked elbow flexion movements, wDFT-evoked elbow flexion movements, nCFT-evoked elbow flexion movements, and wCFT-evoked elbow flexion movements. Each task was performed for 15 trials by every subject. Before the experiment, the surface skin on right biceps brachii muscle of all subjects was cleaned with medical alcohol so that the stimulation electrodes could have good contact with skin. Moreover, the stimulating electrodes were fixed with medical adhesive tape to avoid the displacement of the stimulation point. According to experiment instructions, the stimulator was turned on to evoke right biceps brachii muscle contraction to reach a specific angle position (50&#x00B0;) for a 3&#x202F;s elbow flexion movement. Then the stimulator was turned off, and subjects put down their arm naturally back to initial position for a rest before next trial. To ensure all tasks to be performed in a certain movement pattern, a long handle protractor was used in all NMES-evoked tasks. During the experiment, subjects were required to close their eyes so as to have no visual access to the ongoing elbow flexion movement in order to avoid observation interferences.</p>
</sec>
<sec id="sec10">
<label>2.4</label>
<title>Data recordings</title>
<p>EEG data were record with 8Ag/AgCl scalp electrodes (7 electrodes FC1, C3, CP1, FC2, C4, CP2, and Cz were installed in international 10/20 system, and the other one was placed below the right eye for recording the ocular artifact). The dual reference EARCLIP was placed on the right ear of subjects. The sampling rate was 500&#x202F;Hz and band-pass filtering range was set from 2 to 40&#x202F;Hz. Kinematic data were sampled at 100&#x202F;Hz.</p>
</sec>
<sec id="sec11">
<label>2.5</label>
<title>Data processing</title>
<p>All experimental data were processed in MATLAB2012b (MathWorks, Natick, MA) environment. EEG signals were firstly band-pass filtered with the frequency band of 2-40&#x202F;Hz by the Butterworth filter in EEGLAB. Then, independent component analysis (ICA) algorithm in FastICA was adopted to remove the ocular artifact from EEG data (<xref ref-type="bibr" rid="ref9">Delorme and Makeig, 2004</xref>). EEG signals were re-referenced to Electrode Cz. Before further analysis, EEG data were segmented in trials according to <xref ref-type="fig" rid="fig1">Figure 1c</xref>.</p>
<p>As Electrode C3 corresponds to primary sensorimotor cortex projecting to right upper limb, EEG data of Electrode C3 were analyzed trial by trial for all tasks. Based on the literatures (<xref ref-type="bibr" rid="ref24">M&#x00FC;ller et al., 2003</xref>; <xref ref-type="bibr" rid="ref37">Wang et al., 2023</xref>), we analyzed the ERD of EEG in Beta rhythm (14&#x2013;30&#x202F;Hz) to evaluate the cortical excitability during NMES-evoked elbow flexion movements. Event-Related Spectral Perturbation (ERSP) was utilized to inspect the spectral power changes of EEG signals in time-frequency domain for ERD evaluation. The ERSP maps for Electrode C3 of all tasks were computed using Short-time Fourier transform (STFT) with a Hanning-tapered window applied in EEGLAB (<xref ref-type="bibr" rid="ref9">Delorme and Makeig, 2004</xref>). Baseline-normalized ERSP values (dB) was calculated from 0&#x202F;s to 13&#x202F;s based upon the 2&#x202F;s baseline of pre-onset period, as shown in <xref ref-type="fig" rid="fig2">Figure 2</xref>. The final ERSP values were averaged among all 15 trials in time-by-frequency plane for each task.</p>
<fig position="float" id="fig2">
<label>Figure 2</label>
<caption>
<p>Averaged time-frequency maps at electrode position C3 during VFT-evoked elbow flexion movement, and CFT-evoked elbow flexion movement for all trials of one subject. Blue denotes ERD. The first vertical line denotes movement onset, the second one denotes task offset.</p>
</caption>
<graphic xlink:href="fnhum-19-1629003-g002.tif">
<alt-text content-type="machine-generated">Four spectrograms show frequency over time for different evoked movements: nVFT, nCFT, wDFT, and wCFT. Frequency ranges from zero to thirty Hertz, and time spans zero to ten seconds. Each spectrogram uses a color scale from blue, indicating lower decibels, to red, indicating higher decibels.</alt-text>
</graphic>
</fig>
<p>To investigate the amplitude of sensorimotor cortical oscillation during tasks, ERD value was extracted as follows in <xref ref-type="disp-formula" rid="EQ1">Equation 1</xref>:</p>
<disp-formula id="EQ1">
<label>(1)</label>
<mml:math id="M1">
<mml:mi mathvariant="italic">ER</mml:mi>
<mml:msub>
<mml:mi>D</mml:mi>
<mml:mtext mathvariant="italic">value</mml:mtext>
</mml:msub>
<mml:mo>=</mml:mo>
<mml:munder>
<mml:mo>min</mml:mo>
<mml:mrow>
<mml:mn>14</mml:mn>
<mml:mo>&#x2264;</mml:mo>
<mml:mi>K</mml:mi>
<mml:mo>&#x226A;</mml:mo>
<mml:mn>30</mml:mn>
</mml:mrow>
</mml:munder>
<mml:mo stretchy="true">(</mml:mo>
<mml:mfrac>
<mml:mn>1</mml:mn>
<mml:mi>N</mml:mi>
</mml:mfrac>
<mml:munderover>
<mml:mo movablelimits="false">&#x2211;</mml:mo>
<mml:mrow>
<mml:mi>f</mml:mi>
<mml:mo>=</mml:mo>
<mml:mi>K</mml:mi>
</mml:mrow>
<mml:mrow>
<mml:mi>K</mml:mi>
<mml:mo>+</mml:mo>
<mml:mn>2</mml:mn>
</mml:mrow>
</mml:munderover>
<mml:munderover>
<mml:mo movablelimits="false">&#x2211;</mml:mo>
<mml:mrow>
<mml:mi>t</mml:mi>
<mml:mo>=</mml:mo>
<mml:mn>2</mml:mn>
</mml:mrow>
<mml:mn>5</mml:mn>
</mml:munderover>
<mml:mtext mathvariant="italic">ERSP</mml:mtext>
<mml:mo stretchy="true">(</mml:mo>
<mml:mi>f</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi>t</mml:mi>
<mml:mo stretchy="true">)</mml:mo>
<mml:mo stretchy="true">)</mml:mo>
<mml:mspace width="0.25em"/>
</mml:math>
</disp-formula>
<p>Where <italic>N</italic> is the number of time-frequency bins in a 2&#x202F;Hz wide frequency band. Averaged ERSP values were extracted from 2 to 5&#x202F;s after trial onset in the special time-frequency band by sliding a 2&#x202F;Hz wide window from 14&#x202F;Hz to 30&#x202F;Hz, the minimum of which was selected as the ERD value. Since ERD is a negative value, the absolute ERD value <inline-formula>
<mml:math id="M2">
<mml:mo>&#x2223;</mml:mo>
<mml:mi mathvariant="italic">ER</mml:mi>
<mml:msub>
<mml:mi>D</mml:mi>
<mml:mi mathvariant="italic">abs</mml:mi>
</mml:msub>
<mml:mo>=</mml:mo>
<mml:mi mathvariant="italic">ER</mml:mi>
<mml:msub>
<mml:mi>D</mml:mi>
<mml:mtext mathvariant="italic">value</mml:mtext>
</mml:msub>
<mml:mo>&#x2223;</mml:mo>
</mml:math>
</inline-formula> was calculated for statistical analysis.</p>
<p>Beta ERD changes in corresponding frequency bin, named as <italic>ERSP<sub>T</sub></italic> (as shown in <xref ref-type="fig" rid="fig3">Figure 3</xref>), were used to investigate temporal characteristics of the sensorimotor cortical excitability. The descending slope <italic>ERD<sub>Slope</sub></italic> of <italic>ERSP<sub>T</sub></italic> against time was calculated from the movement onset to the achievement of <italic>ERSP<sub>T</sub></italic> plateau as in <xref ref-type="disp-formula" rid="E1">Equation 2</xref>:</p>
<disp-formula id="E1">
<label>(2)</label>
<mml:math id="M3">
<mml:mi mathvariant="italic">ER</mml:mi>
<mml:msub>
<mml:mi>D</mml:mi>
<mml:mtext mathvariant="italic">Slope</mml:mtext>
</mml:msub>
<mml:mo>=</mml:mo>
<mml:mo>&#x2223;</mml:mo>
<mml:mi mathvariant="italic">ER</mml:mi>
<mml:msub>
<mml:mi>D</mml:mi>
<mml:mrow>
<mml:mi>T</mml:mi>
<mml:mn>1</mml:mn>
</mml:mrow>
</mml:msub>
<mml:mo>&#x2212;</mml:mo>
<mml:mi mathvariant="italic">ER</mml:mi>
<mml:msub>
<mml:mi>D</mml:mi>
<mml:mrow>
<mml:mi>T</mml:mi>
<mml:mn>0</mml:mn>
</mml:mrow>
</mml:msub>
<mml:mo>&#x2223;</mml:mo>
<mml:mo>/</mml:mo>
<mml:mi>T</mml:mi>
<mml:mn>1</mml:mn>
</mml:math>
</disp-formula>
<fig position="float" id="fig3">
<label>Figure 3</label>
<caption>
<p>The temporal changes of ERSP values in corresponding frequency bin during the whole trial at contralateral sensorimotor cortex (C3): T1 is the moment when ERD value falls on a plateau segment.</p>
</caption>
<graphic xlink:href="fnhum-19-1629003-g003.tif">
<alt-text content-type="machine-generated">Line graph showing ERSP in decibels over time in seconds, with four colored lines representing different methods: red (nVFT), blue (wDFT), black (nCFT), and green (wCFT). Significant points include "Onset" at around 2 seconds and "T1" at around 4 seconds. Vertical and horizontal lines mark key values.</alt-text>
</graphic>
</fig>
<p>Where T1 is the moment when ERD value falls to a plateau phase, and T0 is the moment of the movement onset, <italic>ERD</italic><sub><italic>T</italic>1</sub> and <italic>ERD</italic><sub><italic>T</italic>0</sub> are ERD values in the time at T1 and T0, respectively.</p>
<p>To further evaluate the stimulation efficiency under different electric pulse assignments, we calculated the neural activations (ERD) of per stimulation input (current and phase charge) as:</p>
<disp-formula id="EQ2">
<label>(3)</label>
<mml:math id="M4">
<mml:msub>
<mml:mi>ERD</mml:mi>
<mml:mtext>current</mml:mtext>
</mml:msub>
<mml:mo>=</mml:mo>
<mml:mfrac>
<mml:mi>ERD</mml:mi>
<mml:mi mathvariant="normal">I</mml:mi>
</mml:mfrac>
</mml:math>
</disp-formula>
<disp-formula id="EQ3">
<label>(4)</label>
<mml:math id="M5">
<mml:msub>
<mml:mi>ERD</mml:mi>
<mml:mtext>charge</mml:mtext>
</mml:msub>
<mml:mo>=</mml:mo>
<mml:mfrac>
<mml:mi>ERD</mml:mi>
<mml:mi mathvariant="normal">Q</mml:mi>
</mml:mfrac>
<mml:mspace width="0.25em"/>
</mml:math>
</disp-formula>
<p>Where ERD is the beta ERD value obtained in <xref ref-type="disp-formula" rid="EQ1">Equation 1</xref>, and I is the stimulation intensity (current in mA) in <xref ref-type="disp-formula" rid="EQ2">Equation 3</xref>. <italic>Q</italic> is the phase charge (in &#x03BC;C) in <xref ref-type="disp-formula" rid="EQ3">Equation 4</xref>, the current-time integral of the pulses each burst (<xref ref-type="bibr" rid="ref10">Doll et al., 2018</xref>).</p>
<p>Kinematic data were also segmented in trials according to <xref ref-type="fig" rid="fig1">Figure 1c</xref>. Angular curves of elbow flexion movements across all 15 trials were averaged task by task. Angular range and its corresponding movement duration were extracted to evaluate the movement performance in different tasks.</p>
</sec>
<sec id="sec12">
<label>2.6</label>
<title>Statistical analysis</title>
<p>Kinematic parameters (angular range and duration with elbow flexion respectively) and EEG activities (<italic>ERD<sub>abs</sub></italic> and <italic>ERD<sub>Slope</sub></italic>) of all elbow flexion movements were analyzed with one-way repeated measures ANOVA. The elbow flexion movement was set as an independent factor. In addition, current intensity (<inline-formula>
<mml:math id="M6">
<mml:msub>
<mml:mi>I</mml:mi>
<mml:mtext mathvariant="italic">value</mml:mtext>
</mml:msub>
</mml:math>
</inline-formula>) and current efficiency (<inline-formula>
<mml:math id="M7">
<mml:msub>
<mml:mi>ERD</mml:mi>
<mml:mtext>current</mml:mtext>
</mml:msub>
</mml:math>
</inline-formula>) were also analyzed by one-way repeated measures ANOVA with NMES patterns as an independent factor and the current intensity or current efficiency as a within-subject factor. The Least Significant Difference (LSD) correction was used to make the <italic>post-hoc</italic> pairwise comparisons. Furthermore, phase charge (<italic>Q</italic>) and its efficiency (<inline-formula>
<mml:math id="M8">
<mml:msub>
<mml:mi>ERD</mml:mi>
<mml:mtext>charge</mml:mtext>
</mml:msub>
</mml:math>
</inline-formula>) were compared between nVFT and wDFT by a paired <italic>t</italic>-test. Statistical analyses were performed using SPSS 22 (SPSS Inc., Chicago, Illinois), and the significance level was set at <italic>p</italic>&#x202F;&#x003C;&#x202F;0.05 for all procedures.</p>
</sec>
</sec>
<sec sec-type="results" id="sec13">
<label>3</label>
<title>Results</title>
<sec id="sec14">
<label>3.1</label>
<title>Elbow flexion movements evoked by all NMES patterns</title>
<p><xref ref-type="fig" rid="fig4">Figures 4a</xref>,<xref ref-type="fig" rid="fig4">b</xref> showed angular curves and the statistical results of angular ranges for all NMES-evoked movements, respectively. As the elbow flexion movements were performed, all angular curves began to increase at 2&#x202F;s and reached their peak at 5&#x202F;s, followed by the kinematic curves for the arm back to the initial position which were not analyzed in this study. The statistical results of angular ranges showed no significant difference (<italic>p</italic>&#x202F;&#x003E;&#x202F;0.05) among different NMES-evoked tasks (nVFT: 49.87&#x202F;&#x00B1;&#x202F;8.75&#x00B0;, wDFT: 48.30&#x202F;&#x00B1;&#x202F;11.67&#x00B0;, nCFT: 51.35&#x202F;&#x00B1;&#x202F;9.64&#x00B0;, wCFT: 51.02&#x202F;&#x00B1;&#x202F;7.92&#x00B0;). Meanwhile, the durations from initial movement onset to the moment of the peak angle of all evoked movements were statistically calculated (<xref ref-type="fig" rid="fig4">Figure 4c</xref>), and the results showed also insignificantly different duration (<italic>p</italic>&#x202F;&#x003E;&#x202F;0.05) among all the elbow flexion tasks (nVFT: 2.68&#x202F;&#x00B1;&#x202F;0.20s, wDFT: 2.60&#x202F;&#x00B1;&#x202F;0.27&#x202F;s, nCFT: 2.72&#x202F;&#x00B1;&#x202F;0.11&#x202F;s, wCFT: 2.85&#x202F;&#x00B1;&#x202F;0.17&#x202F;s respectively). Combining the above results with the parameters set for this study that the stimulation duration of each trial was 3&#x202F;s and the initial movement and the ending positions of elbow flexion were fixed for all tasks, it could be concluded that all NMES patterns evoked similar elbow flexion movements.</p>
<fig position="float" id="fig4">
<label>Figure 4</label>
<caption>
<p>Kinematic measurements of all elbow flexion tasks: <bold>(a)</bold> angle curves, <bold>(b)</bold> the statistical results of angular ranges, <bold>(c)</bold> the statistical results of the durations of all NMES-evoked elbow flexion movements.</p>
</caption>
<graphic xlink:href="fnhum-19-1629003-g004.tif">
<alt-text content-type="machine-generated">Chart (a) shows elbow flexion angle over time for four conditions: nVFT, wDFT, nCFT, and wCFT, with a peak at around 80 degrees. Bar chart (b) displays average angles for each condition, ranging from 40 to 60 degrees. Bar chart (c) depicts time duration for each condition, all around 2.5 to 3 seconds, with slight variations.</alt-text>
</graphic>
</fig>
</sec>
<sec id="sec15">
<label>3.2</label>
<title>VFT vs. CFT on cortical activities</title>
<p>The time-frequency information of EEG data at electrode C3 was analyzed for all elbow flexion tasks, and the ERD patterns in beta rhythm were extracted after movement onset (<xref ref-type="fig" rid="fig2">Figure 2</xref>). Although all the tasks showed the movements with similar kinematic performance, the induced sensorimotor cortical activities were significantly affected by stimulation patterns [<italic>F</italic><sub>(3, 34)</sub> =&#x202F;7.781, <italic>p</italic> &#x003C;&#x202F;0.005]. As shown in <xref ref-type="fig" rid="fig5">Figure 5</xref>, stronger cortical excitability was induced via VFT rather than CFT. The beta ERD values (3.31&#x202F;&#x00B1;&#x202F;1.3&#x202F;dB) during wDFT-evoked elbow flexion tasks were significantly higher than those (2.27&#x202F;&#x00B1;&#x202F;1.10&#x202F;dB) during wCFT-evoked elbow flexion tasks (<italic>p</italic>&#x202F;&#x003C;&#x202F;0.05). nVFT-evoked elbow flexion movement also induced higher beta ERD values (2.55&#x202F;+&#x202F;0.83&#x202F;dB) than nCFT-evoked tasks (2.26&#x202F;&#x00B1;&#x202F;1.11&#x202F;dB) did, although the difference (<italic>p</italic>&#x202F;&#x003E;&#x202F;0.05) was insignificant. It can be observed that wDFT-evoked elbow flexion induced highest ERD intensity among all NMES-evoked tasks (<italic>p</italic>&#x202F;&#x003C;&#x202F;0.05). In contrast, beta ERD value did not significantly respond to pulse duration fluctuations in CFT, as no significant difference was observed between wCFT and conventional nCFT according to the beta <italic>ERD<sub>abs</sub></italic> metric (<italic>p</italic>&#x202F;&#x003E;&#x202F;0.05).</p>
<fig position="float" id="fig5">
<label>Figure 5</label>
<caption>
<p>The averaged absolute beta ERD values at contralateral sensorimotor cortex (C3) among all elbow flexion tasks. Stars indicate significance: &#x2217;indicates <italic>p</italic> &#x003C;&#x202F;0.05, and NS indicates no significance.</p>
</caption>
<graphic xlink:href="fnhum-19-1629003-g005.tif">
<alt-text content-type="machine-generated">Bar graph showing ERD in decibels for four groups: nCFT, wCFT, nVFT, and wDFT. Error bars indicate variability. Statistical significance is marked by asterisks, showing differences between groups, with NS indicating no significant difference between nCFT and wCFT.</alt-text>
</graphic>
</fig>
<p>To further investigate the cortical activity modulation effects of different stimulation patterns, the descending slope <italic>ERD<sub>slope</sub></italic> of beta ERD values at contralateral sensorimotor cortex (C3) was calculated (<xref ref-type="fig" rid="fig6">Figure 6</xref>), and it was significantly affected by stimulation patterns [<italic>F</italic><sub>(3, 34)</sub> =&#x202F;3.462, <italic>p</italic> &#x003C;&#x202F;0.05]. The <italic>ERD<sub>slope</sub></italic> responding to wDFT (3.39&#x202F;&#x00B1;&#x202F;0.99&#x202F;dB/s) was significantly greater (<italic>p</italic>&#x202F;&#x003C;&#x202F;0.05) than that responding to both wCFT (2.34&#x202F;&#x00B1;&#x202F;0.63&#x202F;dB/s) and nCFT (1.88&#x202F;&#x00B1;&#x202F;0.36&#x202F;dB/s) patterns, indicating that beta ERD in sensorimotor area could reach the value in the time of T1 faster during wDFT-evoked elbow flexion. Moreover, the <italic>ERD<sub>slope</sub></italic> induced by nVFT (2.75&#x202F;&#x00B1;&#x202F;1.1&#x202F;dB/s) was also higher than that of both conventional nCFT and wCFT though the difference was not significant (<italic>p</italic>&#x202F;&#x003E;&#x202F;0.05).</p>
<fig position="float" id="fig6">
<label>Figure 6</label>
<caption>
<p>The averaged descending slope of beta ERD values at contralateral sensorimotor cortex (C3) among all elbow flexion tasks. Stars indicate significance: &#x2217;indicates <italic>p</italic> &#x003C;&#x202F;0.05, and NS indicates no significance.</p>
</caption>
<graphic xlink:href="fnhum-19-1629003-g006.tif">
<alt-text content-type="machine-generated">Bar graph displaying the descending slope of ERD in decibels per second for four groups: nCFT, wCFT, nVFT, and wDFT. Values range from 0 to 4.5. Bars for nVFT and wDFT are higher, with statistical significance indicated by asterisks. The nCFT and wCFT groups show no significant difference, marked by "NS." Error bars are included.</alt-text>
</graphic>
</fig>
</sec>
<sec id="sec16">
<label>3.3</label>
<title>wDFT vs. nVFT on phase charge efficiency</title>
<p>Although evoking similar elbow flexion movements, four NMES patterns delivered different current intensities [<italic>F</italic><sub>(3, 24)</sub> =&#x202F;3.874, <italic>p</italic> &#x003C;&#x202F;0.05]. As shown in <xref ref-type="fig" rid="fig7">Figure 7a</xref>, with the same pulse duration, current intensity of VFT was significantly lower than CFT. wDFT (5.35&#x202F;&#x00B1;&#x202F;1.04&#x202F;mA) required significant lower current intensity (<italic>p</italic>&#x202F;&#x003C;&#x202F;0.05) than wCFT (5.93&#x202F;&#x00B1;&#x202F;1.07) did. nVFT (6.5&#x202F;&#x00B1;&#x202F;1.09&#x202F;mA) required significant lower current intensity (<italic>p</italic> &#x003C;&#x202F;0.05) than nCFT (7.29&#x202F;&#x00B1;&#x202F;0.86&#x202F;mA) did. Furthermore, we explored whether there were differences in the current efficiency when NMES patterns induced sensorimotor cortical excitability. The current efficiency of all stimulation patterns was calculated according to <xref ref-type="disp-formula" rid="EQ2">Equation 3</xref>. It can be seen from <xref ref-type="fig" rid="fig7">Figure 7b</xref> that the current efficiency of wDFT (0.64&#x202F;&#x00B1;&#x202F;0.26&#x202F;dB/s) was significantly higher (<italic>p</italic>&#x202F;&#x003C;&#x202F;0.05) than that of both nCFT (0.31&#x202F;&#x00B1;&#x202F;0.13&#x202F;dB/s) and wCFT (0.39&#x202F;&#x00B1;&#x202F;0.18&#x202F;s). The current efficiency of wDFT was same as to that of nVFT (0.41&#x202F;&#x00B1;&#x202F;0.15&#x202F;dB/s). The current efficiency of nVFT was also higher than that of the two CFT patterns, although there was no significant difference (<italic>p</italic>&#x202F;&#x003E;&#x202F;0.05). Therefore, the current efficiency of VFT to modulate sensorimotor cortical activities was better than that of CFT pattern.</p>
<fig position="float" id="fig7">
<label>Figure 7</label>
<caption>
<p>Current intensity <bold>(a)</bold> and its efficiency <bold>(b)</bold> among all four NMES patterns. Stars indicate significance: <sup>&#x2217;</sup>indicates <italic>p</italic>&#x202F;&#x003C;&#x202F;0.05.</p>
</caption>
<graphic xlink:href="fnhum-19-1629003-g007.tif">
<alt-text content-type="machine-generated">Two bar graphs compare different conditions. Graph (a) shows current intensity in milliamperes across four conditions: nCFT, wCFT, nVFT, and wDFT. Significant differences are indicated. Graph (b) shows current efficiency in dB per mA across the same conditions, also highlighting significant differences.</alt-text>
</graphic>
</fig>
<p>Due to different stimulation intensities, pulse widths and durations of each train, the phase charge was used to synthetically characterize the pulse delivery pattern of VFT, and then the phase charge efficiencies (beta ERD amplitudes induced by unit phase charge) to activate cortical excitability were compared between two VFT patterns (nVFT vs. wDFT). It could be observed in <xref ref-type="fig" rid="fig8">Figure 8</xref> that with similar evoked elbow movements, wDFT required significantly less phase charges than nVFT (<italic>p</italic>&#x202F;&#x003C;&#x202F;0.05). As mentioned above, the beta ERD amplitudes induced by wDFT was significantly higher than that of nVFT (<italic>p</italic>&#x202F;&#x003C;&#x202F;0.05). Therefore, the phase charge efficiency of the beta ERD intensity induced by wDFT-evoked elbow flexion movements was significantly higher than that by nVFT-evoked movements (<italic>p</italic>&#x202F;&#x003C;&#x202F;0.05), as shown in <xref ref-type="fig" rid="fig8">Figure 8b</xref>. Those results indicated that the wide-pulse VFT had better stimulation efficiency of modulating sensorimotor cortical activities.</p>
<fig position="float" id="fig8">
<label>Figure 8</label>
<caption>
<p>The phase charge <bold>(a)</bold> and its efficiency <bold>(b)</bold> between wDFT and nVFT. Stars indicate significance: <sup>&#x2217;</sup>indicates <italic>p</italic>&#x202F;&#x003C;&#x202F;0.05.</p>
</caption>
<graphic xlink:href="fnhum-19-1629003-g008.tif">
<alt-text content-type="machine-generated">Bar graph (a) compares phase charge between nVFT and wDFT. nVFT is around 14 microcoulombs (uC), higher than wDFT at around 6 uC. Bar graph (b) shows charge efficiency, with nVFT at approximately 0.2 decibels microcoulombs inverse (dB&#x00B7;uC^-1), lower than wDFT at around 0.7 dB&#x00B7;uC^-1. Both graphs include error bars and indicate significant differences with an asterisk.</alt-text>
</graphic>
</fig>
</sec>
</sec>
<sec sec-type="discussion" id="sec17">
<label>4</label>
<title>Discussion</title>
<p>The present study investigated the impact of dual wide-pulses in doublets on sensorimotor cortical excitability improvement by combining the wide pulse with Variable Frequency Trains. Beta ERD of EEG signals from Electrode C3 located in left sensorimotor cortex was utilized to evaluate the activation level in cortex region during elbow flexion tasks (<xref ref-type="bibr" rid="ref37">Wang et al., 2023</xref>; <xref ref-type="bibr" rid="ref34">Tacchino et al., 2016</xref>; <xref ref-type="bibr" rid="ref38">Wang et al., 2024</xref>). VFT stimulation could induce stronger sensorimotor cortical excitability than CFT stimulation, especially, the DFT with the dual 500&#x202F;&#x03BC;s wide pulse trains was found the most effective pattern for brain activity improvements, which supports our hypothesis.</p>
<p>As mentioned above, to evoke similar elbow flexion movements, wide-pulse stimulation for both CFT and VFT utilized lower current intensity than narrow-pulse stimulation suggesting that compared to NMES with narrow pulses, NMES with wide pulses had more advantages in activating muscle contraction. Wide-pulse pattern not only directly activated motor axons but also favored to depolarize the sensory fibers, resulting in recruiting motor units to evoke muscle contraction by the combination of the peripheral efferent with afferent pathways (<xref ref-type="bibr" rid="ref3">Bergquist et al., 2011</xref>). The activated sensory fibers can generate the afferent volley ascending to the central nervous system (CNS) which contributes to the cortical excitability regulation, and the enhancement of cortical excitability is the key to the improvement of motor rehabilitation (<xref ref-type="bibr" rid="ref25">Obayashi and Saito, 2022</xref>).</p>
<p>The present study focused on investigating sensorimotor cortical excitability induced by different NMES patterns through quantifying the beta ERD amplitudes of EEG signals at Electrode C3. Beta ERD amplitude has been reported to be strongly related to the level of sensorimotor cortical activation. The higher beta ERD amplitude is, the greater the cortical excitability is <xref ref-type="bibr" rid="ref34">Tacchino et al. (2016)</xref>. The results showed that compared to CFT patterns, VFT patterns favor the activation of sensorimotor cortical activities (i.e., significantly higher beta ERD amplitudes), which may be attributed to the way that VFT evokes muscle contraction. VFT was more prone to recruiting motor units in asynchronous pattern (i.e., more natural recruitment method) (<xref ref-type="bibr" rid="ref4">Carole et al., 2016</xref>), and asynchronous motor units were generally recruited from the direct activation of motor axons (peripheral pathway) and the depolarization of sensory axons (central pathway) that activates motoneurons in the spinal cord (<xref ref-type="bibr" rid="ref3">Bergquist et al., 2011</xref>). Together with those results in the present study, although CFT and VFT evoked similar elbow flexion movements, the stimulation current applied to right arm biceps of subjects in VFT pattern not only activated the motor axons, but also depolarized sensory fibers. This was also confirmed in the study of the MUs recruitment method during NMES-evoked muscle contraction (<xref ref-type="bibr" rid="ref7">Collins, 2007</xref>). The sensory information generated by the activation of afferent fibers by electrical stimulation is transmitted to the central nervous system via the ascending afferent pathway. Siobhan&#x2019;s research also demonstrated that afferent inputs generated by electrical stimulation through activating sensory axons could enhance cortical activity, driving transient or even long-term plastic changes to promote motor rehabilitation (<xref ref-type="bibr" rid="ref31">Schabrun et al., 2012</xref>). Therefore, it may be speculated that VFT can induce larger beta ERD amplitudes due to the activation of more sensory axons.</p>
<p>Moreover, another important finding in this study was that the descending slope of beta ERD induced by VFT-evoked elbow flexion movements was significantly higher than that induced by CFT-evoked movements. This may be due to the fact that VFT activated more sensory axons and sensory volley ascending to the CNS for regulating cortical activities, thus developing the beta desynchronization more quickly. Previous study showed that electrical stimulation-evoked sensory inputs could regulate cortical activity networks (<xref ref-type="bibr" rid="ref5">Carson and Buick, 2021</xref>). This was also verified in the monkey experiment that sensory afferents could encode cortical oscillations (<xref ref-type="bibr" rid="ref1">Alonso et al., 2023</xref>). Therefore, the stimulation pattern of VFT in the present study was more inclined to depolarize sensory fibers so as to efficiently modulate cortical activities. The key to the improvement of motor function in motor rehabilitation lies in the enhancement of cortical excitability (<xref ref-type="bibr" rid="ref14">Joy and Carmichael, 2021</xref>), and thus it is worthwhile to explore the potential of VFT in motor rehabilitation.</p>
<p>The results in the present study also showed that the pulse width of VFT could affect the sensorimotor cortical activities. We observed that wDFT induced higher amplitudes and the descending slope of beta ERD than nVFT did. By further comparison of the phase charges of the two VFT stimulation patterns, we found that to evoke similar elbow flexion motions, wDFT required significantly less phase charges than nVFT did. However, the beta ERD amplitude induced by the unit phase charge of wDFT was higher than that of nVFT, indicating that wDFT had higher phase charge efficiency to induce sensorimotor cortical excitability. In other words, the pulse assignment of VFT might regulate the level of cortical activities. Thus, the dual wide pulse train (wDFT) was more advantageous. The activation of axons is not only related to the accumulated charges applied to the membrane (<xref ref-type="bibr" rid="ref32">Schwarz and Volkmer, 1965</xref>), but also affected by the physiological capacitance and input impedance of the membrane cells (<xref ref-type="bibr" rid="ref21">Li and Bak, 1976</xref>). Due to the properties, such as large diameter, smaller input impedance and greater strength-duration constant, sensory fibers required less charges to be activated by the stimulation pulses with long sustained phase. Therefore, with longer pulse width (500&#x202F;&#x03BC;s), wDFT in the present study required less phase charges, suggesting that more sensory axons could be activated by unit phase charge of wide-pulse VFT to better regulate cortical activities. Those results supported our hypothesis that VFT could induce stronger sensorimotor cortical excitability than CFT did. Further potential benefits on the modulation of cortical activities may be obtained by combining the wide-pulse with doublet VFT patterns.</p>
<p>The value of NMES in motor recovery has been widely reported. The activation of sensory fibers has become a new method to improve its clinical efficiency in rehabilitation due to the activation and regulation of central nervous activities by evoked sensory volley through afferent pathway (<xref ref-type="bibr" rid="ref25">Obayashi and Saito, 2022</xref>). Wide-pulse stimulation has been shown to be more conducive to activating sensory fibers which have a larger intensity-time constant and lower base intensity than motor axons (<xref ref-type="bibr" rid="ref36">Veale et al., 1973</xref>; <xref ref-type="bibr" rid="ref18">Kiernan et al., 2004</xref>), but traditional CFT induced rapid muscle fatigue (<xref ref-type="bibr" rid="ref11">Doucet et al., 2012</xref>). In contrast, VFT has been reported to induce fatigue-resistant muscle contraction and increase muscle contraction torque (<xref ref-type="bibr" rid="ref20">Lagerquist and Collins, 2010</xref>; <xref ref-type="bibr" rid="ref17">Karu et al., 1995</xref>). Some studies have suggested that this feature was due to the non-linear summation in induced muscle strength (<xref ref-type="bibr" rid="ref17">Karu et al., 1995</xref>) and an intrinsic catch like property of muscle fibers itself (<xref ref-type="bibr" rid="ref33">Stuart et al., 1991</xref>). Others have shown that motor units were recruited asynchronously during VFT-evoked muscle contraction (<xref ref-type="bibr" rid="ref4">Carole et al., 2016</xref>). However, few studies have investigated whether VFT was more likely to activate sensory fibers when evoking muscle contraction. Therefore, the present study designed a new stimulation pattern combining wide pulse with VFT to investigate whether it may induce stronger cortical activities when evoking upper limb movements, thereby indirectly evaluate its activation of sensory axons. The results confirmed that wide-pulse VFT could not only induce stronger central nervous activities, but also establish the activation pattern more efficiently. In addition, although similar elbow flexion movements could be evoked by different stimulation patterns, both wide pulses and VFT enhanced sensorimotor cortical excitability by activating sensory fibers which is necessary for promoting motor rehabilitation. Therefore, those results in the present study further suggested that rehabilitation training should not be limited to joint movements, but also enhance sensory inputs ascending to sensorimotor areas.</p>
<p>Based on previous studies of VFT-evoked muscle contraction pattern and wide-pulse NMES for the activation of sensory fibers, the present study combined the two stimulation patterns to investigate whether VFT, especially the wide-pulse DFT, had more advantages of central cortical modulation over traditional CFT from the perspective of cortical activity regulation. The results showed that compared to simply increasing the pulse width in several previous studies, the comprehensive optimization of NMES patterns through the combination of wide pulse and VFT pattern was more conducive to enhancing cortical excitability. Therefore, the proposed NMES pattern may provide a new idea to optimize NMES parameters for the improvement of motor rehabilitation efficiency. However, the present study also has some limitations. The first one is the fixed order of four stimulation patterns applied in all subjects. This may cause a confounding impact from the stimulation order, such as muscle fatigue. Although every subject was provided a 10-min rest between any two NMES patterns to reduce muscle fatigue, it could be better to avoid this confounding factor using a randomized order of the four NMES patterns in different subjects. Early research in human brain electrophysiology has already investigated the cortical response to various kinematic parameters, and concluded that sensorimotor oscillation activities were different with different movements (<xref ref-type="bibr" rid="ref41">Yuan et al., 2010</xref>; <xref ref-type="bibr" rid="ref6">Cassim et al., 2000</xref>). Hence, further evaluations according to different kinematic characteristics should be designed in future for a more comprehensive understanding in the cortical modulation induced via dual wide pulse trains. Moreover, the participants involved in our study were all healthy subjects. Considering the reduction of movement-related beta ERD at the contralateral sensorimotor cortex in stroke patients (<xref ref-type="bibr" rid="ref37">Wang et al., 2023</xref>), it is also necessary to extend the present findings more specific to pathological populations with motor function disorders in further studies.</p>
</sec>
<sec sec-type="conclusions" id="sec18">
<label>5</label>
<title>Conclusion</title>
<p>This study investigated the effects of NMES with wide-pulsed DFT on sensorimotor cortical excitability. Our findings established that the induced cortical excitability could be improved by optimized pulse width and VFT pattern, whereby the dual 500&#x202F;&#x03BC;s wide pulse train (wDFT) maximized the benefits. The profound reason may attribute to the facilitation of afferent fibers activation enhancement which consequently increased the ascending volleys. Therefore, our results implied the potential of wide-pulse DFT in assisting cortical excitability modulation through modifying the related afferent inputs, which suggested a promising usage in the improvement of rehabilitation efficiency for patients with motor dysfunction.</p>
</sec>
</body>
<back>
<sec sec-type="data-availability" id="sec19">
<title>Data availability statement</title>
<p>The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.</p>
</sec>
<sec sec-type="ethics-statement" id="sec20">
<title>Ethics statement</title>
<p>The studies involving humans were approved by the Ethics Committee of Chongqing Polytechnic University of Electronic Technology. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.</p>
</sec>
<sec sec-type="author-contributions" id="sec21">
<title>Author contributions</title>
<p>YZ: Data curation, Funding acquisition, Supervision, Writing &#x2013; original draft, Writing &#x2013; review &#x0026; editing. YY: Visualization, Writing &#x2013; review &#x0026; editing. XZ: Data curation, Visualization, Writing &#x2013; review &#x0026; editing. GX: Formal analysis, Visualization, Writing &#x2013; review &#x0026; editing. RY: Data curation, Formal analysis, Funding acquisition, Visualization, Writing &#x2013; review &#x0026; editing. SZ: Data curation, Investigation, Writing &#x2013; review &#x0026; editing. FG: Data curation, Visualization, Writing &#x2013; review &#x0026; editing. WS: Data curation, Visualization, Writing &#x2013; review &#x0026; editing.</p>
</sec>
<sec sec-type="funding-information" id="sec22">
<title>Funding</title>
<p>The author(s) declare that financial support was received for the research and/or publication of this article. The Scientific and Technological Research Program of the Chongqing Education Commission (KJZD-K202303103, KJZD-K202203104, and KJQN202403120).</p>
</sec>
<ack>
<p>We would like to thank all participants in the experiments for their valuable time.</p>
</ack>
<sec sec-type="COI-statement" id="sec23">
<title>Conflict of interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec sec-type="ai-statement" id="sec24">
<title>Generative AI statement</title>
<p>The authors declare that no Gen AI was used in the creation of this manuscript.</p>
</sec>
<sec sec-type="disclaimer" id="sec25">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
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