Materials and Methods
This reliability study with a repeated-measures design was conducted at the biomechanics lab of the university campus of San Jorge University, Spain, in accordance with the Helsinki Declaration and approved by the regional ethics committee “Comité de Ética de la Investigación de la Comunidad Autónoma de Aragón” (C.P.-C.I. PI18/385). All participants provided written informed consent before entering the study. The present study has been reported following the Guidelines for Reporting Reliability and Agreement Studies (GRRAS) ( Kottner et al., 2011 ). The methodology and procedures used in the present study were adapted from previous studies on multimodal sensorimotor assessment of the lower extremities ( Doménech-García et al., 2023 ; Bellosta-López et al., 2023 ; Bellosta-López et al., 2024 ).

Participants were recruited from the local community through advertisements at the university campus and on social media. The inclusion criteria were: (i) age 18 to 50 years and (ii) absence of pain and functional limitations due to past or current injuries or pathologies in the upper extremities. Exclusion criteria were: (i) a history of pain at any part of the body in the previous 3 months; (ii) presence of chronic pain ( e.g ., chronic low back pain, fibromyalgia, migraine); (iii) a history of serious injury to the upper extremities ( e.g ., fracture, surgery); (iv) chronic use of medication; and (v) diagnosis of serious diseases. The rationale for recruiting healthy participants was to ensure consistency in participant status across the first and second assessments for test-retest reliability. Participants were instructed to avoid engaging in any physical activity or exercise that was unaccustomed or of high intensity throughout the study period.

A total of 30 participants were needed to reach a power of 90% with an alfa error of 0.05, expecting a ‘good’ to ‘excellent’ intraclass correlation coefficient (ICC) values between 0.70 and 0.90 for a single measurement two-way mixed model ( Walter, Eliasziw & Donner, 1998 ).

Participants attended two test sessions separated by a 7-day interval. The assessments took place at the same time of day to ensure consistent testing conditions ( Bellosta-López et al., 2023 ). Following a standardized protocol, the same assessor, who was trained in the assessment protocol, conducted all the test sessions. An external supervisor provided oversight to ensure methodological quality and consistency. All sessions were conducted in a controlled environment, in a quiet room with consistent ambient light, and temperature and humidity controlled. After verifying the inclusion criteria and obtaining informed consent, socio-demographic data and anthropometric characteristics were collected. Anthropometric measurements were performed according to the International Society for Advancement of Kinanthropometry ( International Society for Advancement of Kinanthropometry I, 2001 ) and included forearm and wrist circumferences, forearm length, humerus bi-epicondylar and wrist bi-styloid diameters, and forearm skinfold. During the anthropometric assessment, reference points (detailed later in each assessment procedure) were identified by palpation of anatomical landmarks. These points were marked on the skin with semi-permanent ink to facilitate the repeatability of the measurements. The standardized protocol included the following tests, administered in the specified order to minimize the influence of preceding tests on the performance of the subsequent ones: myotonometry, the Nine-Hole Peg Test, algometry, inclinometry, and dynamometry. Each test session lasted approximately 25 min, and the assessor was blinded to findings obtained in previous sessions. The side order ( i.e ., dominant, non-dominant) was randomized for each participant before the first session and maintained across all assessments.

The position of the participants was controlled during the execution of all tests ( Figure 1 ). In Testing Position 1, the participant was seated at the edge of the table with knees bent at 90°, lower back supported by the backrest, shoulders in slight flexion, elbows bent at 90°, palms of the hand supported, and fingers relaxed. The distance between the trunk and the edge of the table was a closed fist, equivalent to approximately 10 cm ( Figure 1A ). Testing Position 2 consisted of rotating 90° from ‘Testing Position 1’ so that the proximal two-thirds of the forearm remained resting on the table, with the distal third and wrist remaining free in the air ( Figure 1B ).

Mechanical properties of the muscle were assessed with a hand-held digital myotonometer (MyotonPRO, Müomeetria AS, Estonia), a non-invasive and painless tool that provides objective measurements of the mechanical properties of the muscle via the impulses it exerts on the tissue ( Leonard et al., 2003 ). The study focused on (i) oscillation frequency (Hz), as an indicator of muscle tone characterizing the resting tension level of the tissue; (ii) dynamic stiffness (N/m), reflecting the tissue resistance to the force deforming the muscle (mechanical impulse); and (iii) logarithmic decrement (arbitrary unit), characterizing the ability of the muscle to return to its initial position after an external force perturbation and corresponding to the elasticity of the tissue ( Aird, Samuel & Stokes, 2012 ). Tests were performed with participants positioned in Testing Position 1. Measurements were performed bilaterally on the extensor carpi radialis brevis muscle at its most prominent point following the procedure described by Riek, Carson & Wright (2000) . This point was approximately located in the first third of the line connecting the lateral epicondyle with the styloid of the radius. The measurements were taken after requesting a counter-resistance wrist extension to visualize the muscle mass and different partitions, considering the anatomical sequence of the common extensor of the fingers, extensor carpi radialis brevis, extensor carpi radialis longus, and brachioradialis ( Riek, Carson & Wright, 2000 ). The assessor ensured there was no tension on the skin, and the probe was perpendicular to the tissue surface for each measurement. One measurement set of ten consecutive impulses (scan mode) was conducted at each of the marked points with a time interval of 1 s between each impulse. The average value of each series was accepted if the coefficient of variation of the measurement set was less than 3%.

Manual dexterity was assessed using the Nine-Hole Peg test. This test was performed using a plastic commercially available version (Smith & Nephew, Watford, United Kingdom) with nine holes on one side and a hole with nine pegs on the other side. The objective was to insert the pegs into the holes using the hand as quickly as possible ( Oxford Grice et al., 2003 ). Participants performed the test in Testing Position 1, keeping the palm of the opposite hand on the table. The position of the box was standardized for each participant, being placed 20 cm from the edge of the table and aligned with the center of the body ( i.e ., perpendicular to the sternum). After a familiarization trial for each side, three trials were performed for each side. The test completion time was obtained with a stopwatch, and the average value of the three attempts was extracted for reliability analysis. If any of the pegs jumped out of the hole or fell to the ground during the course of the test, that attempt was discarded and a new one was performed.

A digital handheld pressure algometer (Somedic, Hörby, Sweden) mounted with a 1 cm 2 probe and connected by a cable to a pushbutton was used to assess pressure pain thresholds. A pre-established familiarization protocol was followed at each session ( Bellosta-López et al., 2023 ). The assessor explained to the participants that ‘Pressure pain threshold is the pressure reached when you first feel that the pressure becomes painful’. Pressure pain thresholds were assessed bilaterally over two muscles with participants in the Testing Position 1: (i) extensor carpi radialis brevis muscle, at the same point as for myotonometry and (ii) deltoideus muscle, as a control point in the upper extremity at the midline between the acromion and the deltoid tuberosity of the humerus. The pressure was gradually increased at the stimulation site with a ramp of 30 kPa/s. Two measurements of pressure pain thresholds were recorded for each site with a 30-s interval before assessing the same site again. The average value for each site was extracted for reliability analysis.

A handheld digital inclinometer (microFET 3 ® , Hogan Health Industries, Salt Lake City, UT, USA) was used to assess the active range of motion of the wrist ( Kolber & Hanney, 2012 ). Participants were asked to actively perform maximal flexion and extension movements from Testing Position 2, stabilizing their forearm with the opposite hand to avoid compensatory movements. The angle between the vertical and the wrist was recorded by placing the inclinometer on the third metacarpal. The inclinometer was calibrated on a horizontal surface before the assessment of each side. Participants had to hold the maximum range of motion for 3 s without shaking for the measurement to be considered valid. During wrist flexion movements, special care was taken to ensure that no finger flexion occurred. Three consecutive trials were performed interspersed by an interval of 10 s. The average angle value, expressed in degrees, was extracted for further analysis.

A handheld digital dynamometer (microFET 3 ® , Hogan Health Industries, Salt Lake City, UT, USA) mounted with an arc-shaped piece adapted to the metacarpophalangeal region was used to assess the maximal isometric strength of the extensor muscles of the wrist ( Schrama et al., 2014 ). Participants were placed in Testing Position 1 with the forearm resting over a wedge with a 30-degree tilt ( Doménech-García et al., 2020 ). The wrist was positioned at its edge to allow a slight wrist flexion-extension range before starting to exert force. The forearm was fixed to the table with a strap at the upper third of the forearm. A second strap was adjusted in such a way that, when the dynamometer was placed, the angle of the wrist and the edge allowed a mechanical advantage during the isometric contraction of 5–10 degrees of extension ( Schrama et al., 2014 ). A mobile application (Tabata Timer: Interval Timer, Oleksandr Serhiienko, Ukraine) was used to establish an audible and visual preparation countdown of 3 s and a worktime of 5 s to ensure that the muscle contraction had a similar length over repetitions. Participants were also asked to keep the opposite arm relaxed to avoid compensatory movements. Before data collection, a submaximal familiarization trial was performed for each side. Finally, participants performed three repetitions on each side, with an interval of 90 s between assessments of the same side. Visual inspection of the force-time curve was performed to prevent values from distorting the results. The average maximal isometric force value was extracted for further analysis.

Asymmetries were calculated by subtracting the non-dominant value to the dominant value and dividing by the maximum value of one of these two values ( i.e ., (dominant − non-dominant)/(Max. dominant, non-dominant)). This method to calculate asymmetries is considered one of the most appropriate due to its ability to express the magnitude and direction of asymmetry, thereby overcoming the limitations associated with selecting a reference limb ( Parkinson et al., 2021 ).

The Shapiro-Wilk test was used to determine the normal distribution of the sample, and data were presented in terms of mean and standard deviation.

Mixed-model repeated measures analysis of the variance (RM-ANOVA) for the raw values with day (assessment 1 and assessment 2) as within factor and side (dominant, non-dominant) as between factor were performed to explore the absence of systematic bias ( i.e ., fixed and proportional bias ( Ludbrook, 2010 )), as well as consistently explore significant between-side differences within tests. Besides, for the asymmetries, paired Student T-tests were performed to explore the presence or absence of systematic bias. When significant, data were presented as mean difference (MD) and 95% confidence intervals (95% CI).

Reliability was evaluated for single measurement absolute agreement based on a two-way mixed model by computing intraclass correlation coefficients (ICC 3,1 ). The ICCs were calculated both for the raw values in the non-dominant and the dominant side, as well as for asymmetries. An ICC above 0.90 was considered as ‘excellent’, 0.75–0.90 as ‘good’, 0.50–0.75 as ‘moderate’, and less than 0.50 as ‘poor’ reliability ( Koo & Li, 2016 ). The standard error of measurement (SEM) was calculated using the following formula: SEM = SD pooled × √(1-ICC). The SEM represented the expected random variation in scores within a subject when no real change has happened ( Furlan & Sterr, 2018 ). The minimum detectable change (MDC) at 95% (MDC 95 ) and 90% (MDC 90 ) was calculated using the formulas: MDC 95 = 1.96 × SEM × √2; MDC 90 = SEM × √2 × 1.64. The MDC is considered the minimal change needed for being a real change in a sample rather than a random measurement error ( Furlan & Sterr, 2018 ). MDC was also calculated at the 90% level due to is considered adequate for measuring a change in ordinary clinical practice ( Donoghue & Stokes, 2009 ).

Pearson’s correlation was used to assess the interrelationship between the raw values in the non-dominant and the dominant side, as well as for asymmetries in each test procedure. Correlations were considered as ‘strong’ (ρ ≥ 0.70), ‘moderate’ (0.40 > ρ < 0.69), ‘weak’ (0.10 > ρ < 0.39), and ‘negligible’ (ρ < 0.10) ( Schober, Boer & Schwarte, 2018 ).

Statistical analysis was performed using SPSS v.28 (IBM, Chicago, IL, USA), and a significance level of P < 0.05 was accepted. However, due to the multiple comparisons ( i.e ., nine comparisons per variable), the significant level for the correlation analysis was corrected to P < 0.006 ( i.e ., 0.05 divided by 9).