The Impact of Draw Weight on Archers’ Posture and Injury Risk Through Motion Capture Analysis

Abstract

Archery has increasingly captivated attention in its use for rehabilitation and physical education due to its adaptability for various abilities. However, this repetitive sport carries some injury risk in the shoulder, elbow, and back during the draw and release phases. While research often explores factors affecting shooting performance, limited studies have examined the interplay between gender-specific biomechanics and bow-related variables on lumbar stress and shooting mechanics. This study addresses this gap by leveraging the Xsens MVN Awinda motion capture system and JACK Siemens ergonomic software to analyze full-body movements of archers with different experience levels, bow types, and target placements. Thirteen subjects participated in this investigation, each equipped with standard gear. We analyzed their posture throughout the shooting sequence and the forces acting on their lower back. This innovative approach streamlines data collection and eliminates the need for extensive prototyping. Our findings highlight natural biomechanical adaptations between males and females when using bows of varying draw weights. Males generally exhibited greater consistency and stability, while females showed increased variability, particularly with heavier bows. This research establishes a foundation for ergonomic and reproducible archery techniques, enabling individualized training and performance optimization strategies.

1. Introduction

Target archery demands a unique blend of physical and mental skills. It is a precision sport requiring an upright, static stance with strong proprioception. Slight variations in posture, environment, concentration, and fine motor control can significantly impact performance [1,2,3,4]. Archers must consistently repeat a practiced sequence with precise timing and focus, from planning to execution, to achieve consistent accuracy. While valued for its recreational and rehabilitative benefits, archery carries injury risks. During the drawing phase, archers pull the bowstring to full draw while maintaining a stable and controlled posture for precise aiming. This movement requires significant strength from the shoulders, arms, and back muscles. Improper technique or using a bow with an excessive draw weight can result in muscle strain, especially in the rotator cuff. A study of 396 surveys, involving 37% of archers practicing for more than 10 years, 23% for 5 to 10 years, and the remainder for less than 5 years, revealed that over half (57.3%) of archers experienced injuries, with shoulders (28.2%) and neck/back (19.9%) being the most common body segments. These injuries even force over half (50.3%) of those affected to stop practicing [5]. Physical therapists categorize archery as a medium-risk activity for shoulders, elbows, and wrists due to its repetitive nature of drawing and releasing the bowstring [6,7]. Shoulder injuries, such as impingement syndrome and rotator cuff tears, commonly arise from the significant forces placed on the joint during the draw and release phases, particularly when improper form or excessive draw weight is involved [8]. Improving upper body and core strength, particularly in the forearms and shoulder girdle, directly translates to better archery performance [1,4,9]. Research has also emphasized the prevalence of back-related injuries in archery. Lower back pain is often linked to hyperextension and rotational stress during aiming and bow stabilization, which can result in muscle imbalances or strain. One study noted that archers frequently exhibited excessive lower back arch [10], leading to improper muscle engagement and impacting shot technique. Additionally, another report underscored the critical role of back tension in achieving optimal performance, particularly among elite archers [11].

Currently, many studies have investigated specific variables that directly impact or present tools to enhance shooting performance in archers. These reports include neuroimaging studies examining the neural correlates that differentiate archers from non-archers during specific tasks [12,13,14], improvements through neurofeedback training [15], the unequal performance decline caused by climate change that induced extreme heat increases [16], locating the yips [17], psychological stress and performance anxiety [17,18], landscape characteristics in archery hunting and success [19], and conducting performance predictions after identifying indicators, often using machine learning [18,20,21,22].

Proper technique, using the right equipment, and managing the workload are all essential for preventing injuries and improving performance in archery [23]. Some of the earliest relevant research involved muscular analysis by measuring the biopotentials or electrical output during archery shooting. Electromyographic (EMG) studies have investigated the activation patterns of the forearm and shoulder girdle muscles [1,4] with a focus on muscle tremors, postural control, and behavioral performance. Another study used electroencephalography (EEG) to study motor learning in archery training, emphasizing motor execution and attention as crucial components of shot preparation [2]. A force plate was also used to collect and analyze ground reaction forces, revealing that reduced body sway, indicative of higher postural control, could lead to increased shooting performance [3]. Additionally, one report found significant improvement in shooting performance through standardized observational assessments after applying elastic taping to the lower part of the trapezius to activate the muscle [24].

In one of the latest studies [25], archery’s direct impact on humeral morphology was examined using EMG, along with kinematic data collected through an 11-camera motion capture system (Qualisys Track Manager) and processed using C-Motion’s Visual 3D Software. This study is one of the few that implements motion capture and digital human modeling (DHM) in archery research. DHM enables the identification of an ergonomic shooting technique that is easily reproducible and can be used systematically. However, this study [25] did not directly measure muscle force or mechanical loading.

Archery involves various bow types, each with different draw weights. Recurve bows, commonly used in Olympic archery and training, range from 15 to 50 lbs. Compound and crossbows, often used for hunting, typically range from 40 to 200 lbs. Longbows and bare bows, popular for recreational shooting, vary from 15 to 100 lbs. Success in archery depends on maintaining a stable, upright posture, coordinating upper and lower body movements, and ensuring consistent timing and accuracy [26]. However, the repetitive nature of shooting, coupled with the physical demands of drawing bows with varying draw weights, places significant stress on the musculoskeletal system. The shoulders, elbows, and lumbar spine are particularly vulnerable, as they endure forces and postural adaptations that can lead to strain or injury [5,6,10].

Gender differences in muscle strength, joint mobility, and movement strategies play a significant role in shaping biomechanical patterns in sports. For example, males typically possess greater muscle strength due to higher muscle mass, which enhances their force production capabilities [27]. In contrast, females often demonstrate superior joint mobility and flexibility, owing to anatomical differences and hormonal influences, which can increase ligament laxity [28]. These physiological distinctions affect movement strategies, with males generally relying on strength-based approaches, while females tend to emphasize joint mobility and endurance to achieve comparable outcomes. Moreover, gender differences in postural control and stabilization are apparent, with females often relying more on hip and trunk adjustments during dynamic movements [29]. These gender-specific patterns highlight the complex interaction between strength, technique, and body mechanics, all of which are essential for optimal performance.

Bow draw weight and target distance significantly affect archery biomechanics. Higher draw weights require increased physical effort, activating the upper body muscles, especially the shoulders, back, and arms, to stabilize the bow and execute the shot [7]. This heightened demand can alter joint angles, such as increased shoulder abduction and trunk extension, as archers adjust their posture to accommodate the added force. Target distance also plays a crucial role in biomechanics, as shooting at greater distances necessitates more precise control and stability to counteract the effects of gravity and wind on the arrow’s trajectory [30]. These adjustments often involve subtle modifications in trunk rotation and elbow alignment to maintain accuracy.

However, few focus on kinematic methodologies as the primary mode of data collection or conduct a comprehensive full-body analysis of the biomechanics involved in each phase of executing archery shots. No study has yet provided data by computer-simulating the shooting process or by running motion data through ergonomic software for optimization. Additionally, many previous studies with a kinetic orientation relied on observational data, had to compensate for clicker reaction time, or only examined a single variable. The motions involved in an archery shot constitute a multi-component process that requires detailed analysis to fully evaluate all contributing factors [24]. Additionally, limited research has explored how gender-specific biomechanics and bow-related variables interact to impact lumbar stress and overall shooting mechanics. Understanding these factors is essential for optimizing performance and preventing overuse injuries in archery.

Thus, to effectively analyze each phase of the shooting process, we employ real-time, full-body motion capture of archery participants using different bows and target placements. This is achieved with the Xsens MVN Awinda motion tracking system [31] and the JACK Siemens ergonomics tools [32]. The portable Xsens setup simplifies data collection, requiring only suit arrangement on the participant, calibration, and capture without restrictions related to the recording area or light conditions [33]. The software package provides relevant and accurate results that can be rapidly used as instantaneous visual biofeedback for training, allowing for corrections in posture and movement, or identifying unintended habits [34].

The Xsens motion tracking system has been extensively used to increase ergonomics, thereby reducing injuries and improving performance in tools, workplaces, and sports [35,36,37,38]. One of its unique features is its easy integration with JACK ergonomics software (v9.0), which is considered one of the most popular tools in advanced visualization [39,40]. This integration significantly reduces time by eliminating the need for extensive prototyping or large-scale human-subject data collection, which include diverse databases covering visible, biophysical, physiological, and intelligent virtual human models [36,37].

This study aims to examine the biomechanical patterns related to lumbar stress, gender differences, and bow/distance factors in archery. Using advanced motion tracking systems and ergonomic analysis tools, we aim to provide a comprehensive understanding of how these variables influence archery performance. The insights gained will serve as a foundation for creating personalized training programs and optimizing technique.

2. Methods

2.1. Participants and System Setup

Thirteen student volunteers (seven males and six females; see Table 1) with varying levels of archery experience were recruited. They were divided into three skill levels: 4 experts, 4 intermediates, and 5 novices. The majority of participants were recruited through the university archery club, which generously provided the shooting range and all necessary equipment for the study. The sample size was determined to be 13 based on an a priori power calculation, using input parameters set for a t-test with one tail, an effect size of 0.6, an error rate of 0.05, and a power of 0.8. Out of the 13 participants, only 1 was left-handed. Therefore, this participant’s right shoulder and elbow were grouped with the left shoulder and elbow, consistent with the other 12 participants. Additionally, for the trunk’s internal and external rotations, this participant’s data were summarized inversely, as with the other participants.

Live motion tracking of the archers’ movements was captured using the Xsens MVN Awinda system [31]. This system combines accelerometers, gyroscopes, and magnetometers within a single inertial sensor. It employs 17 wireless inertial sensors placed on each participant, covering key body areas including the head, shoulders, forearms, hands, torso, upper legs, lower legs, and feet. The wireless communication range extends up to 20 m, and the default sampling rate is set to 60 Hz. This technology enables the precise measurement of even slight movements, allowing for differentiation between individual shooting techniques in archery, a crucial aspect for injury prevention research [34].

An orientation session ensured accurate digital human models (DHMs) for each participant. During this session, we measured key body segments, including upper body (shoulder width, arm lengths, and hand length) and lower body (hip width, leg lengths, and foot/heel height). These measurements, along with 17 strategically placed inertial sensors following the MVN Awinda hardware guidelines, were used to generate an initial DHM (DHM_Xsens) in the MVN Analyze software (v2019) before motion capture.

To leverage the strengths of both the MVN Awinda and JACK Siemens software [32], a second DHM (DHM_JACK) was created in JACK. This approach utilized JACK’s unique features by constraining the skeletal structure of DHM_Xsens within DHM_JACK. A designated network streamer port ensured accurate kinematic data transfer from Xsens to JACK, enabling comprehensive injury risk analysis.

2.2. Operational Tasks

Archers were equipped with standard gear: an arm guard, a split finger tab, and three different bare recurve bows (shown in Figure 1). The bows had varying draw weights (20 lbs, 25 lbs, and 32 lbs), but all maintained the industry standard 28-inch draw length. The bows themselves weighed 9 Newtons (N), 11 N, and 25 N, respectively.

Each participant completed a series of shooting trials, where they shot five arrows at specific target height, distances, and bow draw weights. They shot at two distances: 10 yards (close target—C) and 15 yards (far target—F). The target center was positioned 140 cm from the floor. In total, each participant shot 30 unique arrows: 5 arrows with each of the three bows at both close and far distances. This variation in shooting conditions allows for a more comprehensive analysis of archery form and biomechanics. A GoPro camera (HERO8) filmed each combination listed below for later analysis.

Task#1: Shot five arrows with a 20-lb bow at 10 yards (close distance).

Task#2: Shot five arrows with a 20-lb bow at 15 yards (far distance).

Task#3: Shot five arrows with a 25-lb bow at 10 yards (close distance).

Task#4: Shot five arrows with a 25-lb bow at 15 yards (far distance).

Task#5: Shot five arrows with a 32-lb bow at 10 yards (close distance).

Task#6: Shot five arrows with a 32-lb bow at 15 yards (far distance).

This study focused on target archery using recurve bows, adhering to USA Archery guidelines. All participants, regardless of prior archery experience, were guided through the shooting sequence and encouraged to perform to their best ability. Before each shooting session and when switching bows, participants were given ample time to warm up until they felt comfortable proceeding. A certified archery coach ensured range safety and provided instruction on safe and methodical shooting techniques beforehand. To maintain consistency, guidance was limited to a few fundamental steps: stance, arrow knocking, draw, anchor point, aiming, and release. The coach instructed participants to use the 3-under finger shooting technique (where the index, middle, and ring fingers grip the string below the nock) and to anchor the bow hand at the corner of the mouth.

The experiment began with participants shooting five arrows at the close target (10 yards) using the lightest draw weight bow (20 lbs). This constituted one combination. Participants then repeated the combination at the far target (15 yards) before moving on to the 25-lb bow and repeating the entire close-far target sequence. Finally, they followed the same process with the heaviest bow (32 lbs). This structured approach allowed participants to gradually adapt to increasing draw weight and target distance.

2.3. Data Analysis

Thirty trials were analyzed for each participant. We examined both the spinal forces calculated by JACK Siemens’ Force Solver software and the joint angles captured during each shot to assess potential injury risks. The specific posture of interest was captured at the moment the archer releases the bowstring, propelling the arrow forward, as shown in Figure 2. Archers must maintain a steady and controlled posture while holding the bow at full draw. This phase requires pulling the bowstring to its full extension, placing significant demands on the shoulder, arm, and back muscles. Prolonged or improper posture during this phase can result in fatigue or overuse injuries. Thus, this point represents the peak force application on the bow by both hands, and consequently, the greatest reaction forces experienced by the archer’s body. Ideally, at this critical moment, the archer achieves skeletal alignment by shifting the holding load from the arms to the back muscles and skeletal frame. This is accomplished through a slight external rotation of the draw arm’s shoulder and a squeeze of the shoulder blades.

While hand positions (the draw hand pulls the string, the bow hand grips and stabilizes) are crucial for proper form, analyzing the forces acting on the spine during archery requires more sophisticated techniques. In this study, we employed a digital force gauge (SF-500) to measure hand forces exerted on the bow. However, to understand the impact on the spine, we utilized the JACK Siemens Ergonomics tool, which provides valuable data for biomechanical analysis.

During each shot, participants experience a horizontal compressive force in both hands, along with a vertical downward force from gravity on the bow hand. The contact points for these forces, as identified by the JACK Siemens’ Force Solver software, are the finger knuckles on the draw hand and the palm center of the bow hand. The magnitude of these forces, particularly the two reaction forces experienced by the bow hand and their resulting combined force, is one factor considered when evaluating potential lower back strain. The weight of each bow and the pulling force exerted by the archer were measured using the digital force gauge. Additionally, the direction of forces exerted by the fingers and palm is crucial for injury assessment. These directions are determined by three vectors: x (lateral–medial), y (superior–inferior), and z (anterior–posterior), as illustrated in Figure 3. Ideally, in the bow hand, these forces should be slightly superimposed and aligned parallel to the longitudinal axis of the arrow shaft.

The x and z vector values range from 0 to 1.0. These values are estimated by aligning the horizontal resultant vector in JACK software with the expected arrow trajectory, which also coincides with the horizontal compressive force acting on the bow hand. The y vector value on the bow hand is determined using Equation (1) below. Using JACK software, we predicted the compressive force acting on the fourth and fifth lumbar vertebrae (L4/L5) for each participant at the moment of peak force.

(1)${\displaystyle \frac{\mathrm{b}\mathrm{o}\mathrm{w} \mathrm{w}\mathrm{e}\mathrm{i}\mathrm{g}\mathrm{h}\mathrm{t} \left(\mathrm{N}\right)}{\mathrm{h}\mathrm{o}\mathrm{r}\mathrm{i}\mathrm{z}\mathrm{o}\mathrm{n}\mathrm{t}\mathrm{a}\mathrm{l}\mathrm{l}\mathrm{y} \mathrm{r}\mathrm{e}\mathrm{s}\mathrm{u}\mathrm{l}\mathrm{t}\mathrm{a}\mathrm{n}\mathrm{t} \mathrm{r}\mathrm{e}\mathrm{a}\mathrm{c}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n} \mathrm{f}\mathrm{o}\mathrm{r}\mathrm{c}\mathrm{e} \left(\mathrm{N}\right)}}={\displaystyle \frac{\mathrm{y} \mathrm{v}\mathrm{e}\mathrm{c}\mathrm{t}\mathrm{o}\mathrm{r} \mathrm{v}\mathrm{a}\mathrm{l}\mathrm{u}\mathrm{e}}{\mathrm{x}\mathrm{z} \mathrm{r}\mathrm{e}\mathrm{s}\mathrm{u}\mathrm{l}\mathrm{t}\mathrm{a}\mathrm{n}\mathrm{t} \mathrm{v}\mathrm{e}\mathrm{c}\mathrm{t}\mathrm{o}\mathrm{r} \mathrm{v}\mathrm{a}\mathrm{l}\mathrm{u}\mathrm{e}}}$

where the “bow weight” refers to the weight of each bow as measured; the “horizontally resultant reaction force” is the combined force acting in the x and z directions, as measured by the software; the “y vector value” is the calculated force acting in the vertical direction on the bow hand; the “xz resultant vector value” combines the x and z vector values to represent the overall force direction in the horizontal plane.

This study focused on several key joint angles relevant to archery form and injury risk: shoulders (abduction/adduction, internal/external rotation, and flexion/extension), elbows (flexion/extension), and trunk (flexion/extension and axial rotation). Analyzing these angles throughout the shooting motion allows us to assess consistency between shots and understand how different factors might influence injury potential.

2.4. Statistical Analysis

Statistical analysis was conducted using MATLAB (2023a) (MathWorks Inc., Monterey, CA, USA). A t-test was performed and we set a significance level of 0.05 to identify statistically meaningful differences in spinal forces, joint angles, and shooting form across various factors. These factors included bow draw weight, shooting distance, and participant genders. Additionally, we employed the Pearson product moment correlation coefficient (using r values) to investigate the relationships between spinal forces and body measurements (anthropometric variables). This analysis helps us understand how body characteristics might influence the forces acting on the spine during archery, ultimately contributing to a more comprehensive injury risk assessment.

3. Results

Previous studies [39,41] have emphasized the sensitivity of trunk flexion to compressive forces on the back. Additionally, variations in bow weights and elbow and shoulder angles contribute to gender differences in postures. The recommended safety threshold for compressive force is 3400 N [42]. Accordingly, Table 2 presents an analysis of spinal forces and joint angles conducted in this study. The anterior–posterior (AP) and lateral shear forces were also analyzed in this study. The average AP shear force ranged from 36 N to 64 N, while the average lateral shear force ranged from 18 N to 55 N across all participants and bows. Given that the recommended safety threshold for shear force is 700 N [43], both the AP and lateral shear forces observed in this study were negligible and well within safe limits.

In Figure 4, the bars depict the range of values (minimum to maximum) for both males and females within each of the six combinations. Additionally, the average value and standard deviation are included to provide a more comprehensive picture of the data distribution.

The statistical analysis revealed some interesting gender differences. Right shoulder flexion/extension showed a significant difference when using the 32-lb bow at both close and far distances (32C: p = 0.05; 32F: p = 0.02). Left shoulder abduction/adduction also showed significant differences when drawing the 25-lb bow at close and far distances (25C: p = 0.03; 25F: p = 0.04). Furthermore, significant differences were found in trunk flexion/extension (32C: p = 0.01; 32F: p = 0.003) and rotation (32C: p = 0.04; 32F: p = 0.008) when using the 32-lb bow. The range of these significant differences was between 9° and 15°.

Interestingly, when an analysis was conducted to compare the differences in the previously mentioned joint angles between the three bows, significant differences in left elbow flexion/extension were only observed for females. These differences occurred when shooting at 10 yards (20C vs 32C: p = 0.04; 25C vs. 32C: p = 0.04) and 15 yards (20F vs 32F: p = 0.19; 25F vs. 32F: p = 0.02). While no significant differences were found in left shoulder flexion/extension or rotation, these angles differed by more than 20° when females used the 32-lb bow compared to the other two bows. Due to differences in postural control and movement strategies, the results highlight the biomechanical adaptations when using bows with varying draw weights. Notably, significant differences were observed in the joints of the trunk, elbows, and shoulders, with p-values less than 0.05. Consequently, for the Pearson correlation analysis, this study examined the relationships between the trunk and other factors, including compressive force, elbows, and shoulders.

According to Table 3, correlations between trunk flexion/extension and two other factors, compressive force and left elbow flexion/extension, became stronger as draw weight increased from 20 lbs to 32 lbs for all participants. Interestingly, the relationship between trunk flexion/extension and right shoulder flexion/extension remained consistent across different draw weights.

Additionally, the correlation between trunk rotation and three other joint angles also strengthened with the 32-lb draw weight as shown in Table 4. These joints were right shoulder flexion/extension, left shoulder flexion/extension, and left elbow flexion/extension.

4. Discussion

This study successfully analyzed the archery posture and back forces when using three different bows to shoot at targets at two different distances. The main joint angle differences were observed in the shoulder, elbow, and trunk. Due to the biomechanical differences between men and women and the different draw weights of the bows, we gained a better understanding of the influence of gender and draw weight on shooting mechanics.

For right shoulder flexion/extension, a smaller angle indicates that the right arm is closer to the body, while a larger angle indicates that it is farther away. Males tend to maintain more consistent angles across different bow weights, indicating greater adaptability in their posture regardless of draw weight. In contrast, females exhibit a distinct pattern where shoulder angles decrease with lighter bows (20 lbs), increase with intermediate weights (25 lbs), and decrease again with the heaviest bow (32 lbs). This can be understood by considering that the 20-lb bow is easier to draw, so the flexion/extension angle is smaller. When drawing the 25-lb bow, it requires more effort, so the angle increases. When using the 32-lb bow, it is the most strenuous, so maximum effort is required to draw it, and the angle decreases again [44]. This pattern suggests a gradual adaptation to the increasing physical demands of drawing heavier bows. Females may face difficulty generating enough force to draw the heavier bows, especially the 32-lb draw weight, leading to changes in their right arm posture.

When examining left shoulder abduction/adduction, an interesting observation is that the most significant gender difference occurs with the 25-lb bow. Females display smaller angles, indicating a lowered left arm posture, likely due to the increased effort required to aim at distant targets when using bows ranging from 20 lbs to 25 lbs. In contrast, males show a greater left arm angle, suggesting enhanced use of counteracting forces to stabilize the bow. Males maintain a horizontal left arm posture even with the 32-lb bow, demonstrating their ability to make compensatory adjustments through body flexion, extension, and rotation. However, twisting and bending were reported as the most common risk factors for back injuries [45].

While no significant differences were observed in left shoulder extension/flexion and left shoulder rotation between genders or across different bow weights, it is noteworthy that females exhibited substantial variations in both angles. Particularly when drawing the 32-lb bow, the larger flexion/extension and rotation angles indicate insufficient muscle strength in females, which can lead to inaccurate performance. Proper archery technique involves maintaining an upright posture and avoiding twisting while aiming [46].

Previous studies have identified key risk factors for shoulder MSDs, including highly repetitive tasks, shoulder postures, and applied forces. Maintaining shoulder flexion or abduction below 90° is generally considered safe, as angles exceeding 90° may lead to pain or disorders. Research [47,48] has shown that severe arm elevations (>90°) for 10% or more of a work cycle can predict chronic or recurrent shoulder issues. Likewise, internal and external shoulder rotations beyond 70° can strain the rotator cuff and cause joint instability [49]. Some studies [50,51] suggest a connection between hand and shoulder muscle activity, with high static handgrip forces, especially in elevated arm positions, imposing additional load on shoulder muscles. This load is more likely to affect stabilizing muscles like the rotator cuff than larger muscles such as the deltoid and trapezius. As a result, movements that combine abduction and external rotation, especially during the draw phase with a high handgrip force, should be kept within moderate ranges to avoid impingement or overuse injuries.

For the analysis of trunk flexion/extension and rotation, positive values indicate flexion and body rotation to the right, while negative values indicate extension and body rotation to the left. Trunk movements also highlight gender-specific adaptations. Females demonstrate approximately 10 degrees more trunk extension and rotation when using heavier bows, particularly the 32-lb bow. This pattern reflects their reliance on trunk adjustments to compensate for left arm drooping and elbow extension, which may result from insufficient muscle strength [52]. Males, on the other hand, exhibit smaller variations in trunk movements, maintaining a more upright posture across all draw weights and distances. During the draw phase, the trunk should maintain a neutral posture with minimal flexion and extension [53]. A slight trunk rotation is recommended to align the hips and shoulders, ensuring an even distribution of load. Lateral flexion should be avoided to reduce the risk of imbalanced stress on the lumbar spine [54].

Interestingly, the left elbow angle reveals contrasting strategies between genders. Males tend to maintain a more neutral posture, while females often rely on the elbow joint’s supporting force to assist the left arm in bearing the bow’s pulling force [55], which may cause pain because of the locked elbow on draw [56]. For optimal elbow mechanics, the drawing arm should maintain a flexion angle between 90° and 120° to avoid hyperflexion, which can strain the biceps and joint capsule [57,58]. The bow arm should maintain a slight flexion of 5° to 10° when holding the bowstring to prevent joint locking, as hyperextension increases the risk of ligament strain and joint instability [59].

In this posture, the average angles of several joints involved in drawing the bow remain within the physiological range, including right shoulder flexion and rotation, as well as left shoulder angles. However, the average right shoulder abduction exceeded 90°, and the average right elbow flexion was approximately 155°. Notably, during the draw phase with a 32-lb bow, the left elbow exhibited hyperextension (negative angle), which increases the risk of ligament injury. As for trunk flexion, extension, and rotation, the angles increased while drawing the 32-lb bow. Given that the draw weight of some bows can reach up to 100 lbs, these joint angles may exceed recommended limits, potentially leading to injury.

For the analysis of R values, the relationship between compressive force and trunk flexion/extension exhibits an increasing trend as the bow was changed from 20 lbs to 32 lbs. This indicates that as the body leans back, the compressive force on the back decreases. This explains why males experience greater compressive force compared to females. This difference is attributed to their relatively smaller trunk extension. Previous studies [39,41] have highlighted the sensitivity of trunk flexion to compressive force on the back. However, in this study, the trunk is predominantly in an extended state. Consequently, the variations in compressive force are minimal. Nevertheless, this analysis can still be employed to explain the gender-based differences in back force distribution [60].

When using the 32-lb bow, R values reveal relationships between trunk flexion/extension and both right shoulder flexion/extension and left elbow angle. This influence is particularly strong in females. A smaller right arm angle (indicating the arm closer to the body) and a negative elbow angle (extension) are both associated with the body leaning back further. Similarly, trunk rotation is linked to right and left shoulder flexion/extension and left elbow angle. Smaller right shoulder flexion/extension values and larger left shoulder flexion/extension values are linked to greater body rotation to the right, with the opposite being true for larger right and smaller left shoulder values. A straighter left elbow facilitates body rotation to the right, while a more bent elbow promotes rotation to the left during aiming. These postural adjustments are ultimately determined by the body’s natural coordination mechanisms [61,62].

To prevent injury in archery, it is important to maintain a neutral position with the shoulders and elbows, avoiding excessive extension or flexion [46]. This alignment helps keep the spine straight and prevents strain. Additionally, it is important to ensure the bow is properly sized and adjusted for each individual [63]. An ill-fitting bow can force archers into awkward postures, leading to discomfort and potential injury. Moreover, one should complement archery practice with exercises that specifically target and strengthen the muscles used in the sport. This will enhance endurance and ultimately reduce the risk of injury [4,64].

5. Conclusions

Our analysis of posture and spinal forces using the Xsens motion capture system and JACK Siemens ergonomic software revealed notable differences in joint angles and trunk movements. These variations highlight the natural biomechanical adaptations of males and females to increasing bow draw weights, reflecting differences in muscle strength, coordination, and mechanical strategies. Understanding these patterns can inform the development of training programs customized to individual biomechanics, thereby optimizing archery performance.

Author Contributions

Conceptualization, X.J. and D.P.; Methodology, X.J. and D.P.; Software, X.J., Z.A.T. and X.G.; Validation, X.G.; Formal analysis, X.J. and X.G.; Investigation, X.J.; Resources, X.J. and D.P.; Writing—original draft, X.J. and Z.A.T.; Writing—review & editing, X.G. and D.P. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

This study was conducted in accordance with the Declaration of Helsinki, and approved by the Gannon Institutional Review Board (protocol code: GUIRB-2023-3-7063, and date of approval: April 2023) for studies involving humans.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

Footnotes

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Figures and Tables

Figure 1. (a) Three bows with different draw weights 20 lbs (right), 25 lbs (middle) and 32 lbs (left). (b) Targets at different distances.

Figure 2. The participant’s pose (a) The Xsens DHM; (b) The JACK DHM.

Figure 3. The calculating spinal forces on (a) Force Solver; and the arrow direction on the (b) draw hand; and on the (c) bow hand.

Figure 4. The range of values for the following parameters within each combination: (a) compressive spinal force; (b) right shoulder flexion/extension; (c) right shoulder abduction/adduction; (d) right shoulder rotation; (e) left shoulder flexion/extension; (f) left shoulder abduction/adduction; (g) left shoulder rotation; (h) right elbow flexion/extension; (i) left elbow flexion/extension; (j) trunk flexion/extension; (k) trunk rotation. The bold lines represent the mean values, while the range of each bar indicates the minimum and maximum values.

Figure 4. The range of values for the following parameters within each combination: (a) compressive spinal force; (b) right shoulder flexion/extension; (c) right shoulder abduction/adduction; (d) right shoulder rotation; (e) left shoulder flexion/extension; (f) left shoulder abduction/adduction; (g) left shoulder rotation; (h) right elbow flexion/extension; (i) left elbow flexion/extension; (j) trunk flexion/extension; (k) trunk rotation. The bold lines represent the mean values, while the range of each bar indicates the minimum and maximum values.

Table 1

The body weight and body height for females and males are presented in the format of Mean ± Standard Deviation.

Subjects	Number	Body Mass (kg)	Body Height (cm)
Females	6	66.2 ± 17.2	162.5 ± 7.5
Males	7	75.4 ± 20.4	174.7 ± 9.6

Table 2

An analysis of spinal forces and corresponding joint angles was conducted to identify potentially injurious postures. “Comp” indicates the compressive force on the lower back. “L_Shoulder” and “R_Shoulder” represent the left and right shoulder joint angles, respectively. “L_Elbow” and “R_Elbow” denote the left and right elbow joint angles. “AVE_M” and “AVE_F” denote the average values for males and females. For the degrees of freedom in movement, “F/E” represents flexion/extension, “Abd/Add” represents abduction/adduction, and “Rot” represents rotation. Additionally, “20C”, “20F”, “25C”, “25F”, “32C” and “32F” refer to bows with 20-lb, 25-lb and 32-lb draw weights used at close and far distances, respectively.

		Comp (N)	R_Shoulder (°)			L_Shoulder (°)			R_Elbow (°)	L_Elbow (°)	Trunk (°)
			F/E	Add/Abd	Rot	F/E	Add/Abd	Rot	F/E	F/E	F/E	Rot
20C	AVE_F	511.0 ± 97.9	33.8 ± 11.3	117.1 ± 11.1	-40.6 ± 18.7	18.0 ± 8.7	74.8 ± 4.1	−35.3 ± 19.7	156.9 ± 6.2	1.0 ± 5.8	−9.0 ± 10.5	4.4 ± 9.1
	AVE_M	581.0 ± 177.8	46.7 ± 11.6	105.6 ± 22.9	−46.6 ± 18.3	9.2 ± 15.5	79.9 ± 8.3	−43.5 ± 15.9	156.7 ± 9.5	−0.1 ± 7.3	−2.4 ± 2.3	0.0 ± 4.4
20F	AVE_F	469.3 ± 110.8	35.1 ± 10.1	114.9 ± 12.4	−40.7 ± 21.6	15.7 ± 8.4	76.7 ± 6.6	−38.4 ± 17.4	157.2 ± 5.7	2.1 ± 11.9	−7.6 ± 9.2	−1.9 ± 9.9
	AVE_M	588.0 ± 191.7	45.5 ± 11.3	107.6 ± 25.0	−47.8 ± 20.7	9.9 ± 15.7	81.5 ± 8.0	−44.6 ± 11.1	156.9 ± 7.7	−2.3 ± 8.6	−4.9 ± 4.8	0.3 ± 5.4
25C	AVE_F	554.9 ± 115.1	40.1 ± 14.9	114.0 ± 12.7	−40.9 ± 20.1	17.5 ± 11.8	75.8 ± 3.6	−37.6 ± 23.7	158.0 ± 5.7	2.1 ± 7.0	−9.8 ± 8.3	0.7 ± 8.9
	AVE_M	618.1 ± 266.5	47.2 ± 12.2	104.9 ± 21.4	−45.5 ± 20.1	9.3 ± 11.0	84.4 ± 7.8	−44.8 ± 16.2	157.4 ± 7.6	−1.2 ± 5.5	−3.4 ± 3.4	−1.7 ± 8.1
25F	AVE_F	501.1 ± 72.1	39.4 ± 15.8	113.4 ± 9.8	−39.4 ± 19.4	11.2 ± 13.6	74.3 ± 5.0	−28.8 ± 29.2	156.5 ± 6.3	3.8 ± 4.5	−7.7 ± 6.6	−0.5 ± 10.8
	AVE_M	606.1 ± 311.1	45.0 ± 13.1	100.9 ± 30.9	−42.5 ± 23.3	10.2 ± 11.2	83.4 ± 8.5	−42.3 ± 17.1	157.1 ± 7.9	−0.9 ± 6.2	−2.4 ± 3.5	−5.0 ± 8.1
32C	AVE_F	488.4 ± 43.0	32.0 ± 7.1	107.1 ± 1.6	−24.4 ± 14.0	28.9 ± 12.1	76.4 ± 13.1	−58.4 ± 32.1	159.5 ± 4.4	−9.2 ± 6.2	−17.7 ± 4.5	7.5 ± 8.6
	AVE_M	772.8 ± 261.3	46.4 ± 11.2	110.6 ± 20.8	−49.3 ± 22.8	15.2 ± 12.9	81.9 ± 6.9	−47.0 ± 15.3	157.5 ± 7.4	−4.3 ± 7.6	−7.5 ± 4.6	−6.1 ± 7.8
32F	AVE_F	513.3 ± 47.6	28.0 ± 7.1	109.2 ± 4.4	−25.2 ± 14.8	29.0 ± 15.6	79.6 ± 13.6	−60.2 ± 30.0	157.9 ± 5.2	−9.5 ± 9.0	−17.9 ± 3.8	14.3 ± 11.9
	AVE_M	718.4 ± 294.7	43.4 ± 8.2	108.1 ± 19.8	−47.3 ± 17.4	12.6 ± 13.2	81.6 ± 7.6	−47.7 ± 15.1	156.9 ± 9.6	−3.5 ± 5.6	−6.4 ± 3.9	−1.0 ± 2.4

Table 3

The correlations between trunk flexion/extension and other factors.

	Compressive			R_SH_EF			L_Elbow
	20 lbs	25 lbs	32 lbs	20 lbs	25 lbs	32 lbs	20 lbs	25 lbs	32 lbs
Trunk_E/F	0.35	0.39	0.53	0.42	0.37	0.48	0.18	0.24	0.37

Table 4

The correlations between trunk rotation and other factors.

	R_SH_EF			L_SH_EF			L_Elbow
	20 lbs	25 lbs	32 lbs	20 lbs	25 lbs	32 lbs	20 lbs	25 lbs	32 lbs
Trunk_Rot	0.29	0.52	0.76	0.22	0.34	0.50	0.17	0.33	0.44

References

1. Shinohara, H.; Hosomi, R.; Sakamoto, R.; Urushihata, T.; Yamamoto, S.; Higa, C.; Oyama, S. Effect of exercise devised to reduce arm tremor in the sighting phase of archery. PLoS ONE; 2023; 18, e0285223. [DOI: https://dx.doi.org/10.1371/journal.pone.0285223] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/37126499]

2. Rampp, S.; Spindler, K.; Hartwigsen, G.; Scheller, C.; Simmermacher, S.; Scheer, M.; Strauss, C.; Prell, J. Archery under the (electroencephalography-) hood: Theta-lateralization as a marker for motor learning. Neuroscience; 2022; 499, pp. 23-39. [DOI: https://dx.doi.org/10.1016/j.neuroscience.2022.07.019] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/35870564]

3. Simsek, D.; Cerrah, A.; Ertan, H.; Soylu, A. A comparison of the ground reaction forces of archers with different levels of expertise during the arrow shooting. Sci. Sports; 2019; 34, pp. 137-145. [DOI: https://dx.doi.org/10.1016/j.scispo.2018.08.008]

4. Kim, R.N.; Lee, J.-H.; Hong, S.H.; Jeon, J.H.; Jeong, W.K. The characteristics of shoulder muscles in archery athletes. Clin. Shoulder Elb.; 2018; 21, 145. [DOI: https://dx.doi.org/10.5397/cise.2018.21.3.145] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/33330168]

5. Alberola-Zorrilla, P.; Castaño-Ortiz, C.; Sánchez-Zuriaga, D. Where do archers hurt? Epidemiology of injuries during archery practice. Physiother. Theory Pract.; 2024; 40, pp. 1343-1350. [DOI: https://dx.doi.org/10.1080/09593985.2022.2136507]

6. Chen, S.-K.; Cheng, Y.-M.; Huang, P.-J.; Chou, P.-H.; Lin, Y.-C.; Hong, Y.-J. Investigation of management models in elite athlete injuries. Kaohsiung J. Med. Sci.; 2005; 21, pp. 220-227. [DOI: https://dx.doi.org/10.1016/S1607-551X(09)70191-3] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/15960068]

7. Mann, D.; Littke, N. Shoulder injuries in archery. Can. J. Sport Sci.; 1989; 14, pp. 85-92.

8. Cools, A.M.; Witvrouw, E.E.; Declercq, G.A.; Danneels, L.A.; Cambier, D.C. Scapular muscle recruitment patterns: Trapezius muscle latency with and without impingement symptoms. Am. J. Sports Med.; 2003; 31, pp. 542-549. [DOI: https://dx.doi.org/10.1177/03635465030310041101] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/12860542]

9. Bostancı, Ö.; Kabadayı, M.; Mayda, M.H.; Yılmaz, A.K.; Yılmaz, C. The differential impact of several types of sports on pulmonary functions and respiratory muscle strength in boys aged 8–12. Isokinet. Exerc. Sci.; 2019; 27, pp. 307-312. [DOI: https://dx.doi.org/10.3233/IES-192105]

10. Niestroj, C.K.; Schöffl, V.; Küpper, T. Acute and overuse injuries in elite archers. J. Sports Med. Phys. Fit.; 2017; 58, pp. 1063-1070. [DOI: https://dx.doi.org/10.23736/S0022-4707.17.07828-8] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/28944650]

11. Yi, J.-H.; Hah, C.-K.; Ryu, J.-S.; Kim, K.-C. Evaluation on motion features of the world’s second archer during back-tension in archery. Korean J. Sport Biomech.; 2007; 17, pp. 197-207.

12. Chang, Y.; Lee, J.J.; Seo, J.H.; Song, H.J.; Kim, Y.T.; Lee, H.J.; Kim, H.J.; Lee, J.; Kim, W.; Woo, M. Neural correlates of motor imagery for elite archers. NMR Biomed.; 2011; 24, pp. 366-372. [DOI: https://dx.doi.org/10.1002/nbm.1600]

13. Kim, J.; Lee, H.M.; Kim, W.J.; Park, H.J.; Kim, S.W.; Moon, D.H.; Woo, M.; Tennant, L.K. Neural correlates of pre-performance routines in expert and novice archers. Neurosci. Lett.; 2008; 445, pp. 236-241. [DOI: https://dx.doi.org/10.1016/j.neulet.2008.09.018] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/18805460]

14. Kim, Y.-T.; Seo, J.-H.; Song, H.-J.; Yoo, D.-S.; Lee, H.J.; Lee, J.; Lee, G.; Kwon, E.; Kim, J.G.; Chang, Y. Neural correlates related to action observation in expert archers. Behav. Brain Res.; 2011; 223, pp. 342-347. [DOI: https://dx.doi.org/10.1016/j.bbr.2011.04.053] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/21575660]

15. Paul, M.; Ganesan, S.; Sandhu, J.; Simon, J. Effect of sensory motor rhythm neurofeedback on psycho-physiological, electro-encephalographic measures and performance of archery players. Ibnosina J. Med. Biomed. Sci.; 2012; 4, pp. 32-39. [DOI: https://dx.doi.org/10.4103/1947-489X.210753]

16. Qiu, Y.; Zhao, J. Adaptation and the distributional effects of heat: Evidence from professional archery competitions. South. Econ. J.; 2022; 88, pp. 1149-1177. [DOI: https://dx.doi.org/10.1002/soej.12553]

17. Rooke, E. Target panic: Disrupted ecologies of skill in archery. Area; 2023; 55, pp. 348-355. [DOI: https://dx.doi.org/10.1111/area.12859]

18. Lu, Y.; Zhong, S. Contactless Real-Time Heart Rate Predicts the Performance of Elite Athletes: Evidence from Tokyo 2020 Olympic Archery Competition. Psychol. Sci.; 2023; 34, pp. 384-393. [DOI: https://dx.doi.org/10.1177/09567976221143127] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/36608215]

19. Rowland, M.M.; Nielson, R.M.; Wisdom, M.J.; Johnson, B.K.; Findholt, S.; Clark, D.; Didonato, G.T.; Hafer, J.M.; Naylor, B.J. Influence of landscape characteristics on hunter space use and success. J. Wildl. Manag.; 2021; 85, pp. 1394-1409. [DOI: https://dx.doi.org/10.1002/jwmg.22107]

20. Taha, Z.; Musa, R.M.; Majeed, A.P.A.; Alim, M.M.; Abdullah, M.R. The identification of high potential archers based on fitness and motor ability variables: A Support Vector Machine approach. Hum. Mov. Sci.; 2018; 57, pp. 184-193. [DOI: https://dx.doi.org/10.1016/j.humov.2017.12.008] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/29248809]

21. Muazu Musa, R.; PP Abdul Majeed, A.; Taha, Z.; Chang, S.W.; Ab. Nasir, A.F.; Abdullah, M.R. A machine learning approach of predicting high potential archers by means of physical fitness indicators. PLoS ONE; 2019; 14, e0209638. [DOI: https://dx.doi.org/10.1371/journal.pone.0209638] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/30605456]

22. Musa, R.M.; Majeed, A.A.; Taha, Z.; Abdullah, M.; Maliki, A.H.M.; Kosni, N.A. The application of Artificial Neural Network and k-Nearest Neighbour classification models in the scouting of high-performance archers from a selected fitness and motor skill performance parameters. Sci. Sports; 2019; 34, pp. 241-249. [DOI: https://dx.doi.org/10.1016/j.scispo.2019.02.006]

23. Palsbo, S. Epidemiology of recreational archery injuries: Implications for archery ranges and injury prevention. J. Sports Med. Phys. Fit.; 2012; 52, pp. 293-299.

24. Kisa, E.P.; Kaya, B.K. Does taping have an immediate effect on shooting the target?. Percept. Mot. Ski.; 2023; 130, pp. 1609-1623. [DOI: https://dx.doi.org/10.1177/00315125231174080] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/37130195]

25. Dorshorst, T.; Weir, G.; Hamill, J.; Holt, B. Archery’s signature: An electromyographic analysis of the upper limb. Evol. Hum. Sci.; 2022; 4, 25. [DOI: https://dx.doi.org/10.1017/ehs.2022.20]

26. Na, J.Y.; Ryu, D.; Ko, J.H. Anticipatory postural adjustments during an archery performance. Eur. J. Sport Sci.; 2024; 24, pp. 458-465. [DOI: https://dx.doi.org/10.1002/ejsc.12099]

27. Kenney, W.L.; Wilmore, J.H.; Costill, D.L. Physiology of Sport and Exercise; Human Kinetics: Champaign, IL, USA, 2022.

28. Wojtys, E.M.; Huston, L.J.; Boynton, M.D.; Spindler, K.P.; Lindenfeld, T.N. The effect of the menstrual cycle on anterior cruciate ligament injuries in women as determined by hormone levels. Am. J. Sports Med.; 2002; 30, pp. 182-188. [DOI: https://dx.doi.org/10.1177/03635465020300020601] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/11912085]

29. Gribble, P.A.; Hertel, J.; Plisky, P. Using the Star Excursion Balance Test to assess dynamic postural-control deficits and outcomes in lower extremity injury: A literature and systematic review. J. Athl. Train.; 2012; 47, pp. 339-357. [DOI: https://dx.doi.org/10.4085/1062-6050-47.3.08] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/22892416]

30. Ertan, H.; Kentel, B.; Tümer, S.; Korkusuz, F. Activation patterns in forearm muscles during archery shooting. Hum. Mov. Sci.; 2003; 22, pp. 37-45. [DOI: https://dx.doi.org/10.1016/S0167-9457(02)00176-8]

31. Movella. MVN Awinda. Available online: https://www.movella.com/products/motion-capture/xsens-mvn-awinda (accessed on 5 January 2025).

32. Siemens. Human Centered Design and Simulation. Available online: https://plm.sw.siemens.com/en-US/tecnomatix/human-centered-design-simulation/ (accessed on 22 January 2024).

33. Cheung, R.T.; An, W.W.; Au, I.P.; Zhang, J.H.; Chan, Z.Y.; MacPhail, A.J. Control of impact loading during distracted running before and after gait retraining in runners. J. Sports Sci.; 2018; 36, pp. 1497-1501. [DOI: https://dx.doi.org/10.1080/02640414.2017.1398886] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/29099654]

34. Dinu, D.; Fayolas, M.; Jacquet, M.; Leguy, E.; Slavinski, J.; Houel, N. Accuracy of postural human-motion tracking using miniature inertial sensors. Procedia Eng.; 2016; 147, pp. 655-658. [DOI: https://dx.doi.org/10.1016/j.proeng.2016.06.266]

35. Jadhav, G.S.; Arunachalam, M.; Salve, U.R. Ergonomics design and evaluation of the stitching workstation for the hand-crafted Kolhapuri footwear using a digital human modeling approach. J. Ind. Prod. Eng.; 2019; 36, pp. 563-575. [DOI: https://dx.doi.org/10.1080/21681015.2019.1702593]

36. Ahmed, S.; Irshad, L.; Gawand, M.S.; Demirel, H.O. Integrating human factors early in the design process using digital human modelling and surrogate modelling. J. Eng. Des.; 2021; 32, pp. 165-186. [DOI: https://dx.doi.org/10.1080/09544828.2020.1869704]

37. Yu, X.; Shi, Y.; Yu, H.; Liu, T.; An, J.; Zhang, L.; Su, Y.; Xu, K. Digital human modeling and its applications: Review and future prospects. J. X-Ray Sci. Technol.; 2015; 23, pp. 385-400. [DOI: https://dx.doi.org/10.3233/XST-150489] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/26410472]

38. Vyavahare, R.T.; Kallurkar, S.P. Ergonomic evaluation of electric hedge trimmer using digital human modeling. Agric. Eng. Int. CIGR J.; 2015; 17, pp. 100-108.

39. Ji, X.; Hettiarachchige, R.O.; Littman, A.L.; Lavery, N.L.; Piovesan, D. Prevent workers from injuries in the Brewing Company via using digital human modelling technology. Appl. Sci.; 2023; 13, 3593. [DOI: https://dx.doi.org/10.3390/app13063593]

40. Ji, X.; Hettiarachchige, R.O.; Littman, A.L.; Piovesan, D. Using digital human modelling to evaluate the risk of musculoskeletal injury for workers in the healthcare industry. Sensors; 2023; 23, 2781. [DOI: https://dx.doi.org/10.3390/s23052781] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/36904986]

41. Ji, X.; Littman, A.; Hettiarachchige, R.O.; Piovesan, D. The effect of key anthropometric and biomechanics variables affecting the lower back forces of healthcare workers. Sensors; 2023; 23, 658. [DOI: https://dx.doi.org/10.3390/s23020658] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/36679454]

42. Waters, T.R.; Putz-Anderson, V.; Garg, A.; Fine, L.J. Revised NIOSH equation for the design and evaluation of manual lifting tasks. Ergonomics; 1993; 36, pp. 749-776. [DOI: https://dx.doi.org/10.1080/00140139308967940]

43. Gallagher, S.; Marras, W.S. Tolerance of the lumbar spine to shear: A review and recommended exposure limits. Clin. Biomech.; 2012; 27, pp. 973-978. [DOI: https://dx.doi.org/10.1016/j.clinbiomech.2012.08.009]

44. Legend. The Most Common Archery Injuries and How You Can Avoid Them. Available online: https://legendarchery.com/blogs/archery-bowhunting-blog/the-most-common-archery-injuries-and-how-you-can-avoid-them?srsltid=AfmBOooD7RvnLOpR7WA-JPALoEmMJeFO3Jeo6x65UwGtuwQQXjfXMHbo (accessed on 5 May 2024).

45. UNC. Environment, Health and Safety. Lifting and Material Handling. Available online: https://ehs.unc.edu/topics/ergonomics/lifting-and-material-handling/ (accessed on 12 July 2024).

46. Prine, B.R.; Pazik, M.N.; Prine, A.; Haley, H.; Bruner, M.L.; Vincent, H.K. Characteristics and reported injuries of recreational and competitive archers. J. Sports Med. Phys. Fit.; 2023; 63, pp. 1202-1207. [DOI: https://dx.doi.org/10.23736/S0022-4707.23.15257-1] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/37695565]

47. Punnett, L.; Fine, L.J.; Keyserling, W.M.; Herrin, G.D.; Chaffin, D.B. Shoulder disorders and postural stress in automobile assembly work. Scand. J. Work. Environ. Health; 2000; 26, pp. 283-291. [DOI: https://dx.doi.org/10.5271/sjweh.544] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/10994793]

48. Svendsen, S.W.; Bonde, J.P.; Mathiassen, S.E.; Stengaard-Pedersen, K.; Frich, L. Work related shoulder disorders: Quantitative exposure-response relations with reference to arm posture. Occup. Environ. Med.; 2004; 61, pp. 844-853. [DOI: https://dx.doi.org/10.1136/oem.2003.010637] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/15377771]

49. Ellenbecker, T.S.; Cools, A. Rehabilitation of shoulder impingement syndrome and rotator cuff injuries: An evidence-based review. Br. J. Sports Med.; 2010; 44, pp. 319-327. [DOI: https://dx.doi.org/10.1136/bjsm.2009.058875] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/20371557]

50. Chiang, H.-C.; Ko, Y.-C.; Chen, S.-S.; Yu, H.-S.; Wu, T.-N.; Chang, P.-Y. Prevalence of shoulder and upper-limb disorders among workers in the fish-processing industry. Scand. J. Work. Environ. Health; 1993; 19, pp. 126-131. [DOI: https://dx.doi.org/10.5271/sjweh.1496] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/8316780]

51. Sporrong, H.; Palmerud, G.; Herberts, P. Hand grip increases shoulder muscle activity: An EMG analysis with static handcontractions in 9 subjects. Acta Orthop. Scand.; 1996; 67, pp. 485-490. [DOI: https://dx.doi.org/10.3109/17453679608996674] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/8948256]

52. Patel, P.; Parmar, L. Comparison between genders for trunk mobility in normal adults: A cross sectional study. Int. J. Health Sci.; 2022; 6, pp. 1564-1573. [DOI: https://dx.doi.org/10.53730/ijhs.v6nS4.6284]

53. Archery Stance and Posture. Online Archery Academy. Available online: https://www.onlinearcheryacademy.com/archery-stance-and-posture (accessed on 3 November 2024).

54. The Best Method Biomechanically Efficient Shooting Technique. USA Archery. Available online: https://www.mfaa-archery.org/Tech-Support/Archery_Form_Handbook.pdf (accessed on 3 November 2024).

55. Bowsite. Bowsite’s ER. Available online: https://www.bowsite.com/bowsite/features/bowdoc/elbow/ (accessed on 12 July 2024).

56. ArcheryTalk. Elbow Locked on Draw?. Available online: https://www.archerytalk.com/threads/elbow-locked-on-draw.1582923/ (accessed on 12 July 2024).

57. Islam, S.U.; Glover, A.; MacFarlane, R.J.; Mehta, N.; Waseem, M. The anatomy and biomechanics of the elbow. Open Orthop. J.; 2020; 14, pp. 95-100. [DOI: https://dx.doi.org/10.2174/1874325002014010095]

58. Felix, H. Elbow Anatomy & Biomechanics. Available online: https://www.orthobullets.com/shoulder-and-elbow/3078/elbow-anatomy-and-biomechanics (accessed on 5 January 2025).

59. Chapleau, J.; Canet, F.; Petit, Y.; Laflamme, G.-Y.; Rouleau, D.M. Validity of goniometric elbow measurements: Comparative study with a radiographic method. Clin. Orthop. Relat. Res.; 2011; 469, pp. 3134-3140. [DOI: https://dx.doi.org/10.1007/s11999-011-1986-8]

60. Ji, X.; Hernandez, J.; Schweitzer, E.; Wang, W.; Piovesan, D. The assessment of injury risk in the healthcare sector via integrating motion tracking techniques with digital human modelling ergonomic tools. Int. J. Hum. Factors Model. Simul.; 2023; 8, pp. 1-20. [DOI: https://dx.doi.org/10.1504/IJHFMS.2023.130120]

61. Simsek, D.; Cerrah, A.O.; Ertan, H.; Soylu, R.A. Muscular coordination of movements associated with arrow release in archery. South Afr. J. Res. Sport Phys. Educ. Recreat.; 2018; 40, pp. 141-155.

62. Taha, Z.; Haque, M.; Musa, R.M.; Abdullah, M.R.; Maliki, A.B.H.M.; Mat-Rashid, S.M.; Kosni, N.A.; Adnan, A. Analysis of biological and mechanical related performance parameters of Malaysian senior youth archers. Adv. Hum. Biol.; 2017; 7, pp. 137-141.

63. WA. Equipment Compound. World Archery. Available online: https://www.worldarchery.sport/sport/equipment/compound# (accessed on 25 October 2024).

64. Deodato, M.; Saponaro, S.; Šimunič, B.; Martini, M.; Murena, L.; Buoite Stella, A. Trunk muscles’ characteristics in adolescent gymnasts with low back pain: A pilot study on the effects of a physiotherapy intervention including a postural reeducation program. J. Man. Manip. Ther.; 2023; 32, pp. 310-324. [DOI: https://dx.doi.org/10.1080/10669817.2023.2252202]