The Effect of Short-Term Kinesiology Taping on Neuromuscular Controls in Hallux Valgus During Gait: A Study of Muscle and Kinematic Synergy

To investigate the biomechanical mechanisms underlying the pathogenesis and explore the effects of kinesiology taping (KT) on neuromuscular control in HV patients. The study population consisted of 16 young controls (YC group) and 15 patients with hallux valgus (HV group). All subjects underwent a natural velocity gait assessment. Additionally, 11 patients from the HV group received KT intervention over a period of one month, consisting of 15 sessions administered every other day. After the one-month intervention, these patients underwent a gait assessment and were included in the HV-KT group. The electromyography (EMG) and joint motion were evaluated using non-negative matrix factorization (NNMF) to compare the difference in muscle and kinematic synergy among the three groups. The center of plantar pressure (COP) and ground reaction force (GRF) were measured by the force platform. The number of synergies did not differ within the three groups, but the structure of muscle synergies and kinematic synergies differed in the HV group. The KT intervention (HV-KT group) altered the structure of synergies. The correlation between kinematic synergies and muscular synergies was lower in the HV group than in the YC group, whereas the correlation between the two increased after the KT intervention in the HV group. During gait, the HV group tended to activate more muscles around foot joints to maintain body stability. The visual analogue scale (VAS) scores, hallux valgus angle (HVA), and COP were significantly decreased after the intervention ( ${P}\lt 0.05$ ). HV patients exhibited altered kinematic and muscular synergies structures as well as muscle activation. Also, it weakened the balance and athletic ability of HV patients. KT intervention improved neuromuscular control to provide a better gait performance.

The Effect of Short-Term Kinesiology Taping on Neuromuscular Controls in Hallux Valgus During Gait: A Study of Muscle and Kinematic Synergy assessment.Additionally, 11 patients from the HV group received KT intervention over a period of one month, consisting of 15 sessions administered every other day.After the one-month intervention, these patients underwent a gait assessment and were included in the HV-KT group.The electromyography (EMG) and joint motion were evaluated using non-negative matrix factorization (NNMF) to compare the difference in muscle and kinematic synergy among the three groups.The center of plantar pressure (COP) and ground reaction force (GRF) were measured by the force platform.The number of synergies did not differ within the three groups, but the structure of muscle synergies and kinematic synergies differed in the HV group.The KT intervention (HV-KT group) altered the structure of synergies.The correlation between kinematic synergies and muscular synergies was lower in the HV group than in the YC group, whereas the correlation between the two increased after the KT intervention in the HV group.During gait, the HV group tended to activate more muscles around foot joints to maintain body stability.The visual analogue scale (VAS) scores, hallux valgus angle (HVA), and COP were significantly decreased after the intervention (P < 0.05).HV patients exhibited altered kinematic and muscular synergies structures as well as muscle activation.Also, it weakened the balance and athletic ability of HV patients.KT intervention improved neuromuscular control to provide a better gait performance.Index Terms-Hallux valgus, muscle synergy, kinematic synergy, gait, kinesiology taping.

I. INTRODUCTION
H ALLUX valgus (HV) is a common foot deformity.
Studies have reported that the prevalence of HV is 23% among adults aged 18-65 years [1], [2].Further research on HV revealed that HV deformity not only involves complex three-dimensional deformities, including hallux valgus and first metatarsal inversion in the horizontal plane, but also hallux valgus and first metatarsal rotation forward, sesamoid bone subluxation, forefoot transverse arch collapse, and foot muscle dysfunction.These changes result from anatomical and biomechanical alterations in the foot [2], [3].It is generally agreed that the imbalance between the adductor hallux and retractor hallux is the core factor in the pathogenesis of HV [4].Moreover, studies using surface electromyography (sEMG) and skeletal muscle ultrasound have confirmed that the adductor hallux muscles in HV feet not only exhibit altered anatomical alignment shifting from the medial to metatarsal but also demonstrate varying degrees of electrophysiological and morphological changes compared to that of normal feet [5], [6].HV can cause reduced walking speed and affect activities of daily living [7], [8].In addition, HV deformities cause altered gait patterns and biomechanical characteristics in hip, knee, and ankle joints in patients with HV experiencing increased hip internal rotation and knee abduction moments compared to healthy individuals [9], [10], [11], [12].However, the specific effects of HV on foot and lower extremity muscles and movements remain unclear.Patients with HV may have altered neuromuscular control to compensate for altered biomechanics resulting from the disease.
Studies have established treatments for HV: conservative treatments-kinesiology taping (KT), orthotics, exercise training, and electrotherapy-and surgical treatments [1], [7], [13].The mechanism of action of KT may involve mechanical and neuromuscular stimulus effects.For mechanical effects, KT provides elastic support by imposing movement restrictions on the joint while maintaining sufficient mobility.In addition, KT exerts retraction forces on the underlying tissue after application and has been shown to widen the subcutaneous tissue gap [14], enhancing stability in the target area [15].From a neuromuscular perspective, the tensile stimulation of the tape may enhance sensory inputs and improve proprioception [16], augment motor neuron excitability, and thereby facilitate neuromuscular regulation at a motor level [17].Simultaneously, increased sensory inputs may inhibit pain signal conduction and mitigate pain sensation [18].It has been shown that muscle strength enhancement was not demonstrated after treatment with KT [14], but after short-term KT intervention, the hallux valgus angle (HVA) reduced in HV in the hallux resting posture [21].Furthermore, KT application may potentially influence muscle contraction, either promoting or inhibiting it [17], [19], and is widely used in clinical practice [20].Nevertheless, it remains uncertain whether KT can significantly alter neuromuscular control in patients with HV.
Musculoskeletal disorders often present with abnormalities in neuromuscular control [21], [22].HV, as a common musculoskeletal disorder, may also present with abnormalities in muscle neuromodulation, which in turn may manifest as gait abnormalities.Bipedal gait represents one of the most fundamental sensorimotor tasks that humans perform daily [23].Walking is a complex task that requires coordinated movements of multiple muscles and joints [24].To overcome the complexity of controlling a large number of degrees of freedom (DoF), it is hypothesized that muscles or joints are activated in groups with a fixed spatial structure (i.e., motor modules or synergies) [25].According to this hypothesis, the central nervous system (CNS) generates a variety of physical activities by flexibly invoking a limited number of modules over time [26], [27], [28].Muscle synergy analysis has been employed to elucidate alterations in the neuromuscular system and can be used to analyze synergy and coherence among signals to reveal motor control strategies of the CNS as well as assess motor function and rehabilitation effects [29], [30].Muscle synergy structure provides insights into the relationship between musculoskeletal dynamics [31] and other biomechanical properties of the limb [32].Muscle synergy provides a new approach to studying motor control mechanisms during movement [33] and may be beneficial for studying musculoskeletal disorders that affect limb biomechanics [21].When diseases impact the nervous and musculoskeletal systems, muscle coordination may also be impaired, which can cause movement disorders that affect patients' daily activities and the quality of life [34].Kinematic synergy can estimate motor control problems by accessing the joint DoFs [35], [36].Kinematic synergy is important for stability while performing coordinated lower extremity movements during walking [37].However, patterns of muscle and kinematic synergy in patients with HV are unknown.Meanwhile, we hypothesized that KT may indeed modulate muscle and kinematic synergy to some extent in HV patients.
The aims of this study were twofold: first, to clarify whether patients with HV demonstrate alterations in muscle and kinematic synergy and investigate the biomechanical mechanisms underlying the pathogenesis, and second, to explore the effects of KT on neuromuscular control in patients with HV.

A. Ethical Statement
The experimental design was approved by our Institutional Review Board before the study started.Written informed consent was obtained from all study participants.

B. Experimental Subjects
The study included 16 young controls (YC), 15 young patients with HV, and 11 individuals who underwent KT intervention for HV (HV-KT).Participant demographics are shown in TABLE I. Four subjects from the HV group discontinued KT treatment for personal reasons.The inclusion criteria were as follows: HVA > 15 • [2], age 20-45 years, right leg dominance (all subjects completed the Waterloo Footedness questionnaire [38]), no history of lower extremity surgery or neuromuscular disorders causing gait abnormalities (e.g., prolapsed lumbar disk and chronic ankle instability), no conservative foot treatment for HV within the last three months, and bilateral HV.

C. Data Collection
All subjects participating in this study underwent measurement of the HV angle (HVA) using a protractor (SINWA, Japan).HVA is the angle between the first metatarsal and the first phalanx.The HV group also completed a Visual Analog Pain scale (VAS) [39].Subsequently, all subjects walked at their self-selected natural speed along a walkway consisting of three embedded force plates (sampled at 1000 Hz; 9260AA6, Kistler, Switzerland).To ensure the reliability of the data and better adaptability of the subjects, participants practiced the walking task 3-5 times in the gait analysis room before the formal test.During practice, participants were instructed to walk at a natural pace while maintaining a forward gaze and natural arm swing.Adjustments were made to ensure their feet stepped on the center of the force measuring platform.Formal  experiments immediately commenced after acclimatization practice, with 3 formal tests.The data require valid sEMG activation and motion trajectories, and both feet stepping over the center of the force platform.Motion trajectories are fully captured and electrode sheets were not shedding during the gait cycle is required for valid data.The center of pressure (COP) and ground reaction force (GRF) were measured using force plates.The COP trajectory, spanning from the heel to the plantar aspect of the forefoot, was assessed, and commonly used calculated indices included total COP displacement (COP-D), average COP displacement in the medial-lateral direction (COP-X), and average COP displacement in the anterior-posterior direction (COP-Y).GRF, the force exerted by the ground on the foot, was also measured.Key indicators comprised the first (GRF-F) during the loading response (LR) phase and the second peak of GRF (GRF-S) during the terminal stance (Tst) phase [40].
A camera-based motion capture system was used to determine the spatial location of the body segments and calculate each joint angle (Fig. 1e) during gait.Markers were affixed in accord with the CAST lower limb model [41] and the IOR foot model [41], [42], [43], enabling the motion capture system to track the subject's trajectory by recognizing the marker location.The joints included the pelvis, hip, knee, and ankle, and was defined the foot pitch as an additional joint.The HV group underwent KT intervention for a period of one month consisting of 15 sessions, administered every other day (Fig. 2).The tests mentioned above were conducted before the beginning of the intervention and 1 month after the intervention had ended when subjects were no longer using KT.We used the kinesiology therapeutic tape (KT Health, LLC, American Fork, UT 84003, USA), and all subjects received interventions from the same therapist.The sEMG data was synchronized with the acquisition of kinematic and kinetic measures.Data collected by Qualisys Track Manager was imported into Visual 3D software for gait time-phase segmentation.

D. Data Preprocessing
For data processing, we used Matlab software (version 9.0, R2016b, Mathworks Inc., Natick, MA).To extract the envelope of the surface EMG signal, we sequentially applied a high-pass filter (50 Hz), de-meaning, full-wave rectification, and low-pass filtering (5 Hz) [44] to the original surface EMG signal [45].The zero-lag fourth-order Butterworth filters were employed for this purpose [46].The surface EMG signals during the walking cycles were temporally normalized to account for differences in individual gait patterns.The gait cycle was defined as a process in which the ipsilateral heel touches the ground twice in succession.A gait cycle was divided into seven temporal phases: LR (Loading response), Mst (Mid-stance), Tst (Terminal stance), Psw (Pre-swing), Isw (Initial swing), Msw (Mid-swing), and Tsw (Terminal swing [47]).
For intra-subject comparisons, the data were processed over each gait cycle to fit normalized data.In addition, muscle activity from EMG data was normalized to the peak values across all trials.Kinematic and kinetic data were low-pass filtered (10 Hz) using a zero-lag fourth-order Butterworth filter.The kinematic data were normalized similarly to the sEMG.In particular, as the kinematic synergy was extracted from the joint angles using non-negative matrix factorization (NNMF) [33], it was assumed that each DoF was composed of two positive DoFs.Therefore, the kinematic DoFs were decomposed using half-wave rectification, and each joint angle was normalized to its maximum value to ensure that its weights were equal.This yielded a matrix consisting of 26 DoFs.

E. Muscle Synergies Extraction and Kinematic Synergies Extraction
In this study, we defined a muscle module or kinematic module as the component of each muscle or kinematic synergy.Both muscle synergy and kinematic synergy were extracted using NNMF [29].The EMG and joint angle data matrices (M) consist of m × n dimensions (where m is the number of muscles or DoFs and n is the number of time points in the gait cycle).NNMF can be expressed as follows: where M is a linear combination of the spatial component W (m × r matrix, where r is the number of modules) and the temporal component C (r × n matrix).R represents the set of real numbers, and E is the residual error matrix.The number of muscle and kinematic modules was determined using the variance accounted for (VAF).The number of modules is determined when VAF ≥ 95% [48].VAF describes the variation of M, which is described by the following:

F. Muscle Module and Kinematic Motor Module Similarity
To measure the consistency of synergy across subjects, we employed the Pearson correlation coefficient (r).
where n is the number of muscles or DoFs, i represents which muscle or joint DoFs between 1 and n, x and y represent the weights the two synergistic spatial structures to be measured of each muscle or DoFs.
Based on the principle of NNMF, the modules of each subject must be independent of each other (i.e., A and B must be independent).Concurrently, the corresponding modules within the group must be highly similar [21].When r > 0.7, it is considered that there is a similarity between the two synergies [49].
To establish the reliability data of each subject over three times, the threshold of r > 0.7 is used to validate the motion trajectories and sEMG activation.
Furthermore, to determine the number of activated muscles or kinematic DoFs within each module, active muscles in a module were defined as those with a median value of > 0.3 in the spatial pattern [50].Effective kinematic DoFs within a module were defined as those with a median value of > 0.25 in the spatial pattern [51].To determine at which period during gait the muscle synergy module is activated, we followed the methodology outlined by Yang et al [52].When the activation coefficient H(t) exceeds the average activation coefficient H(t), it indicates activation of the muscle module at that specific point.The average H(t) calculation is expressed as:

G. Correlation Between Muscle Synergy and Kinematic Synergy
The cross-correlation measures the level of similarity between two random signals x(t) and y(t) across time.The formula for this is provided below: Authorized licensed use limited to the terms of the applicable license agreement with IEEE.Restrictions apply.where R(s) represents the degree of correlation between the signals x(t) and y(t).Cross-correlation can depict the directional relationship between two signals, such as the lead-follow relationship, where the lead signal initiates a response and the following signal replicates it.In this study, we used crosscorrelation to assess the relationship between muscle and kinematic synergy.

H. Statistics
Evaluation indicators in this study include the peak Met-Hal flexion angle, COP, GRF, VAF, the weight of synergies, and the number of muscle and kinematic motor modules.Two independent samples t-tests were employed to evaluate the differences between YC and HV groups.A repeated measures ANOVA was to evaluate the differences between YC and HV-KT groups.Statistical parameter mapping (SPM) was utilized to compare the temporal pattern between YC and HV groups, as well as HV and HV-KT groups.Statistical significance was indicated as P < 0.05.

A. Number of Muscle and Kinematic Modules
There were no significant differences in the number of muscle (Fig. 3a) and kinematic modules (Fig. 3b) between the YC and HV groups, HV and HV-KT groups.The muscle (Fig. and kinematic (Fig. 4b) modules of the YC, HV, and HV-KT groups were 4 when the mean value of VAF was > 95%.

B. Profiles for Each Muscle and Motion Module
Fig. 5 and Fig. 6 show the temporal and spatial components of muscle and kinematic modules in each group, respectively.
1) Muscle Modules: In module A of the YC group (YC-A), BF, EO, ES, GLM, SED, VL, VM, and RF played major roles during LR, Msw, and Tsw (Fig. 5), They were responsible for stabilizing the trunk and knee joints while extending the knee joint, thereby propelling the body forward.In module B of the YC group (YC-B), EDL, FHL, GL, FL, SOL, and GM played major roles in the post-period of Mst and throughout Tst.In this period, these muscles are activated to achieve plantarflexion of the ankle by activating the calf muscles to weight-bear and balance the body.In module C of the YC group (YC-C), AH, ES, FHL, and FL played major roles in LR, Tst, and Psw.These muscles expanded the weight-bearing surface of the toes, reducing contact pressures and assisting in foot pronation during Tst, with some contribution to limb swing.Module D of the YC group (YC-D) mainly featured EDL, EO, FL, and TA, which played major roles in LR, Isw, and Tsw.They significantly influenced ankle joint movement and contributed to ankle joint stability.
The spatial components of the HV and HV-KT groups closely resembled those of the YC group, but notable differences were observed in their muscle modules.
Compared with the YC group, the temporal components in the HV group did not change (Fig. 7a).Additionally, VL, VM, and RF were additionally activated in module D, but in module A less GLM activation and module B less EDL activation in the HV group compared with that in the YC group.
When comparing the temporal components between the HV group and the HV-KT group, statistical significance was observed in module D during the Msw stage ((Fig.7b, P < 0.001), indicating greater activation in the HV-KT group.However, module D did not significantly influence this stage (Fig. 5).
2) Motion Modules: In the YC group, module a (YC-a) contained the following effective DoFs: A/EVR, H/FLX, H/ADD, P/LO, CM/FLE, MH/FLE, and SC/EXT.YC-a primarily operated during LR and the initial phase of Mst, as well as Tsw (Fig. 6

C. Similarity Comparison of Spatial Components of Each Module Group
1) Similarity of Muscle Modules: Each value in Fig. 5 represents the mean similarity among individual modules within the group.The observed similarities were high, with values ranging from 0.72 to 0.89 for YC, 0.73 to 0.88 for HV, and 0.75 to 0.86 for HV-KT.Pearson similarity coefficients were used to assess the similarity of muscle modules within and between groups (TABLE II).The low similarity observed among the four muscle modules within each group indicated a high level of independence between A, B, C, and D modules (TABLE II; right).Conversely, the high similarity observed for each muscle module between groups indicated high similarity between YC, HV, and HV-KT (TABLE II; left).
2) Similarity of Motion Modules: Each value in Fig. 6 represents the average similarity among individual modules within the group.The same approach was used to assess the similarity between kinematic modules within and between groups (TABLE III).The comparison of similarities between corresponding modules across groups showed a high degree of similarity, with values ranging from 0.88 to 0.89 for YC, 0.88 to 0.91 for HV, and 0.86 to 0.92 for HV-KT.Moreover, examining the similarities between the four kinematic synergies within each group revealed that modules a, b, c, and d within each group were independent of each other  III; right), with r > 0.7 indicating high degree of similarity.high similarity observed for each kinematic module between groups further high similarity YC, HV, and HV-KT (TABLE III; left).

D. Cross-Correlations of Muscle and Kinematic Synergies in Each Module
Fig. 8 shows a strong correlation in activation coefficients between muscle and kinematic synergy throughout the gait cycle.Within the YC group, all four modules (Syn.1-4,where exp.Syn.1 comprises module A of muscle synergy and module a of motion synergy) showed a high correlation (0.77-0.98).In the HV group, the correlation was high in most modules (0.79-0.98,Syn.1-3), except for Syn.4 (r = 0.67).In the HV-KT group, all four modules (Syn.1-4)showed high similarity (0.77-0.97).The correlation for Syn.4 significantly increased in the HV-KT group following KT intervention.These findings suggest that KT treatments may lead to an increased correlation between HV muscle and kinematic synergy.

E. Clinical Evaluation of KT Treatment
The clinical evaluation parameters included HVA, VAS scores, Met-Hal flexion angle, and COP for the HV and HV-KT groups (each group consisting of 11 participants), and Met-Hal flexion angle, COP measures between the YC (with 16 participants) and HV (with 11 participants).
KT had a positive effect on the clinical evaluation of the subjects.HVA (P < 0.001) and VAS scores (P < 0.005) decreased significantly compared with the values recorded before KT (Fig. 9a and b).Furthermore, the peak Met-Hal flexion angles in the HV group were significantly larger than the YC group ((Fig.9c, P < 0.05), without a significant difference between in HV and HV-KT groups (Fig. 9c).TABLE IV demonstrated the comparison of COP and GRF metrics between the YC and HV groups or HV and HV-KT groups.COP-Y and COP-D in the HV group were significantly larger than those in the YC group (P = 0.001) and the HV-KT group (P < 0.001).

IV. DISCUSSION
The objectives of this study were (1) to elucidate the muscle and kinematic synergy characteristics of HV through a detailed analysis of the muscle and kinematic synergy components and (2) to investigate whether KT intervention could effectively improve the synergy characteristics in the Authorized licensed use limited to the terms of the applicable license agreement with IEEE.Restrictions apply.for two independent sample between YC and HV groups.(b) the solid line represents the F-value of the statistical parameter mapping (SPM {F}) for a repeated measures ANOVA between HV and HV-KT groups.The gray-shaded area is the supra-threshold cluster where the t-curve exceeds the critical threshold (red dashed line, α = 0.05).The P-value indicates the probability that the same supra-threshold cluster would be observed by chance in the equally smooth random field process.The supra-threshold cluster with P < 0.05 means a significant difference between the groups.
HV group.HV represents one of the most common foot problems and can be a mild asymptomatic change or a severe foot deformity.These deformities can cause pain and severely affect daily functioning, such as altered gait patterns and increased knee and hip torque [6], [53].In this study, the muscle and kinematic synergy structure was altered in the HV and HV-KT group, and KT treatment not only reduced HVA but VAS also reduced the harm of the disease in terms of neuromuscular modulation.
The concept of kinematic synergies offers an approach to quantify the covariation of joint motions and muscle activations [54].While principal component analysis (PCA) has been commonly used for extracting kinematic synergies due to its simplicity [55], [56].NNMF has been reported to outperform PCA in analyzing neuromuscular actions since it provides more clinically interpretable results.This is because negative weights in PCA lack physiological interpretation for muscle and kinematic activation [28], [54], [57].Also, we used NNMF to process the muscle and kinematic data, facilitating a more comprehensive comparison of the cross-correlation of muscle and kinematic synergies across module groups.
Studies have shown that lower limb biomechanics, such as increased knee abduction moments, are altered in patients with HV [9], [10], [11], [12].This requires more muscle activation to move the body forward and stabilize various joints.A comparison of the muscle synergy structure showed that the absence of the GLM in module A and the EDL in module B were the characteristic patterns of muscle activity in the HV group, which may indicate that weakened lower limb strength in the HV group causes increased anterior-posterior and left-right swaying of the body's center of gravity during walking, causing poor lower limb stability [58].This suggests that the disease affects muscle synergistic contraction for lower limb stability.However, the KT intervention did not have an effect on the number of muscle modules but it did affect the structure of muscle synergy, suggesting that HV and KT treatments may change the neuromuscular control of patients by altering muscle components.
The number of kinematic synergy modules did not significantly differ between the groups (YC and HV group, HV and HV-KT group), suggesting that muscle compensations adjusted movement patterns.Furthermore, there was no significant change in movement patterns in HV, suggesting that changes in muscle modulation patterns in HV preceded changes in movement patterns.A comparison of kinematic synergy structures revealed that the HV groups preferred to have more foot joint DoFs (SC/FLE) during the swing phase.This preference may be due to increased compensatory activity in the foot, indicating that patients with HV experience decreased body balance due to the onset of HV disease [59], causing the body to require more foot joint mobilization to maintain balance.
Many studies have shown that KT has a positive effect on the musculoskeletal system, particularly in alleviating painful symptoms caused by musculoskeletal injuries [60], [61].In our study, the structure of muscle synergy has altered.In the HV-KT group, the VL, VM, and RF did not exhibit additional activation in module D compared with that in the HV group, while BF, ES, GLM, and SED were activated additionally.This observation suggests that the CNS adaptively adjusts these four muscles to assist in knee extension and provide stability to Authorized licensed use limited to the terms of the applicable license agreement with IEEE.Restrictions apply.the knee through co-activation.Alternatively, KT treatment may induce compensation of these four muscles, a possibility that requires further investigation over an extended treatment period.However, the HV and HV-KT groups lacked EDL activation during the Mst and Tst phases, indicating that KT did not enhance ankle joint stability in the support phase of HV.Previous research has shown that KT improves muscle mobilization rates and motor unit recruitment by increasing mechanoreceptor sensitivity [62].In this study, localized KT intervention in the HV group enhanced muscle activation and enabled the CNS to efficiently execute movements, thus improving resistance to perturbation in patients with HV.The peak Met-Hal flexion angle (Fig. 9c) of the HV group differed from that in the YC group, whether with or without KT intervention, suggesting that KT only improves the muscle activation coefficient during gait, effectively completing the target movements.The larger peak Met-Hal flexion angle in the HV and HV-KT groups implies that KT did not improve foot joint stability in patients with HV [21].
Muscle and kinematic synergy are strongly correlated [28], which was confirmed by our results, but Syn.4 in the HV group displayed a weaker relationship.This discrepancy may be due to the onset of the disease, during which the body initiates an adaptive process in the CNS to reduce pain, causing altered activation of the muscles of the lower extremities of the HV group and adaptations in joint movements.KT treatment strengthened the correlation between synergies, which may be attributed to the reduction in pain and correction of hallux position facilitated by KT.These effects caused a decrease in HVA (P < 0.01) and changed muscle components, thus improving the correlation between muscle and kinematic components of Syn.4.This observation suggests that the treatment is effective, which may be the biomechanical mechanism underlying KT treatment.
The results of our study showed a significant decrease in HVA after 1 month of KT intervention (P < 0.01), which is consistent with the findings of ŻŁOBI ŃSKI T [63].Simultaneously, the reduction in VAS scores (P < 0.05) indicated that KT effectively alleviated local pain sensations.These improvements may result from temporary correction of the hallux position, causing reduced pathological stretching of the medial ligaments and joint capsule [1], [2].Consequently, pain in this area of the foot was reduced.Furthermore, the smaller COP-D and COP-Y values in the HV-KT group than those in the HV group (P < 0.001) suggest that KT improves gait stability in patients with HV.

V. LIMITATION
This study had some limitations.First, walking speed was not controlled to provide a comfortable experimental condition and minimize behavioral changes due to cognitive factors.Second, because of the limitations of surface EMG, the deep muscles could not be detected, causing the inability to detect the activation of the small deep muscles that control the foot joints.Third, the gender ratio was not strictly controlled in this study, and there may be gender differences in anatomical structure and muscle strength [64].Finally, the study did not differentiate between different severity levels of HV.

VI. CONCLUSION
There were no significant differences in the number of muscle and kinematic modules between the groups (YC and HV groups, HV and HV-KT groups).However, the HV group required more supplementary activation of the lower limb muscles.KT intervention reduced the need for such supplementation, suggesting that the HV and HV-KT groups exhibit alterations in muscle components.Based on the validation of clinical indicators, muscle synergy can be considered as an additional tool for HV diagnosis.The results of this study may contribute to a better understanding of the kinematic and muscle control mechanisms in HV and provide a theoretical basis for the rehabilitation of KT intervention in patients with HV.

Fig. 1 .
Fig. 1.Application of the motion markers and EMG electrodes: (a) back view, (b) front view, (c) left side, and (d) right side view while walking.(e) Gait linkage model.

Fig. 2 .
Fig. 2. Application of KT.Foot before (a) application: dorsal view, (b) foot after application of the first Y-tape: dorsal and (c) medial views, (d) foot after application of the second I-tape: dorsal view, (e) foot after bipedal application.

Fig. 3 .
Fig. 3.The number of muscle modules (a) and kinematic modules (b) between YC and HV groups, HV and HV-KT groups.

Fig. 4 .
Fig. 4. (a) The number of muscle modules selected accounted for >95% of VAF, as depicted by the plot from all patients.(b) The number of kinematic motor modules selected accounted for >95% of VAF, as depicted by the plot from all patients.
). Module b of the YC group (YC-b) involved the following effective DoFs: A/DF, A/EVR, H/EXT, H/ADD, P/RO, and SC/FLE.YC-b primarily functioned during the post-period of Mst and throughout Tst.Module c of the YC group (YC-c) contained the following effective DoFs: A/PF, A/INV, K/FLX, P/RO, and SC/EXT.YC-c mainly played a

Fig. 5 .
Fig. 5. Muscle modules.The component was processed into four modules with temporal and spatial components for each group.Each solid line and bar represent the mean value for all patients in each group.The grayscale and error bars represent the standard deviation.Each value represents the Pearson similarity of each module.A, B, C, and D represent the muscle modules of each group.The horizontal line on the curve represents H(t).Red, blue, and green colors represent the YC group, HV group, and HV-KT group respectively.Comparison of muscle module weights across groups, * * * indicates P < 0.005, * * indicates P < 0.01, and * indicates P < 0.05.

Fig. 6 .
Fig. 6.Motion modules.The component was processed into four modules with temporal and spatial components for each group.Each solid line and bar represent the mean value for all patients in each group.The grayscale and error bars represent the standard deviation.Each value represents the Pearson similarity of each module.a, b, c, and d represent the kinematic modules of each group.The horizontal line on the curve represents H(t).Red, blue, and green colors represent the YC group, HV group, and HV-KT group respectively.Comparison of motion module weights across groups, * * * indicates P < 0.005, * * indicates P < 0.01, and * indicates P < 0.05.

Fig. 7 .
Fig. 7. Comparison of the muscle temporal components: (a) the solid line represents the t-value of the statistical parameter mapping (SPM {t})for two independent sample between YC and HV groups.(b) the solid line represents the F-value of the statistical parameter mapping (SPM {F}) for a repeated measures ANOVA between HV and HV-KT groups.The gray-shaded area is the supra-threshold cluster where the t-curve exceeds the critical threshold (red dashed line, α = 0.05).The P-value indicates the probability that the same supra-threshold cluster would be observed by chance in the equally smooth random field process.The supra-threshold cluster with P < 0.05 means a significant difference between the groups.

TABLE II COMPARISON
OF SIMILARITY OF FOUR MUSCLE SYNERGIES BETWEEN AND WITHIN GROUPS TABLE III COMPARISON OF OF FOUR KINEMATIC SYNERGIES BETWEEN AND WITHIN GROUPS (TABLE

TABLE IV COMPARISON
OF THE CENTER OF PLANTAR PRESSURE AND GROUND REACTION FORCE BETWEEN THE GROUPS