Documentation:FIB book/Kinetics of Arm Injuries in Snowboarding Falls

Introduction

Skiing and snowboarding are incredibly popular sports across the globe, especially in British Columbia, where there is a continuing growth in participation each season. While this boosts tourism and recreational revenue, it also increases the potential for injuries. These injuries can include fractures, dislocations, and ligament tears, with arm injuries being the most common. Whistler Blackcomb recorded 1.35 million people in the winter months of 2024 alone. With record numbers of people taking to the slopes, it is expected that the number of injuries will also increase. Understanding the biomechanical factors behind these injuries is essential for several reasons, such as enabling the development and refinement of protective gear such as wrist guards, which are tailored to prevent or reduce the severity of fractures. It can also guide training and education programs that teach safer fall techniques improving overall participant safety. Biomechanical data can also be used to improve on the rehabilitation protocols for those recovering from forearm or wrist fractures. As skiing and snowboarding continue to grow in popularity, investigating the root cause of arm injuries is important to ensure the safety of those involved in winter sports.

Definitions and Key Concepts

An arm injury refers to any damage, impairment, or dysfunction affecting the bones, joints, muscles, tendons, ligaments, or nerves within the upper extremity (from the shoulder to fingertips). These injuries may arise from acute trauma, such as falls or collisions, or from repetitive stress and overuse. These injuries include bony fractures, dislocations, soft tissue damage, and nerve damage.

Figure 1: Illustration of Wrist Injury from FOOSH Injury Mechanism

Fall onto outstretched hand (FOOSH) refers to the reflexive act of extending one’s arms to brace a fall (Figure 1), transmitting high compressive axial forces through the wrist and forearm. The FOOSH mechanism is a critical factor in understanding forearm fractures and is often used as the foundation for biomechanical studies that simulate various fall scenarios. When a sudden impact exceeds the threshold for bone fracture, which is in the range of 2.0 to 2.5 kN for the distal radius, various types of fractures can occur. Common fracture examples include Colles’ (distal radius injury from hyperextension), Smith’s (distal radius injury from hyperflexion), and scaphoid (involving one of the carpal bones). This review will focus on acute fractures of the wrist bones and adjacent forearm bones.

In clinical and research settings, standardized scoring systems are essential for objectively evaluating and comparing the severity of injuries across different patients and studies. Two widely used systems are the Abbreviated Injury Scale (AIS) and the Injury Severity Score (ISS). This AIS assigns a numerical value range from 1 to 6 to individual injuries based on their anatomical location and severity, with 1 being minor and 6 representing un-survivable injuries. The ISS builds on the AIS by combining the three most severe injuries (from different body regions) into a single score, which provides an overall assessment of trauma severity. This scoring is crucial for triaging patients, guiding treatment decisions, conducting epidemiological studies, and evaluating outcomes in trauma research and clinical trials. These tools help standardize communication among healthcare providers and enable data-driven improvements.

Anatomy of the Wrist and Forearm

The wrist consists of 8 carpal bones, which are divided into 2 rows: proximal and distal (Figure 2). Among the most common fall-related injuries is the scaphoid fracture, accounting for roughly 70% of all osseous injuries to the carpal bones. This typically occurs when the wrist experiences compressive loads while in a hyperextended position, most commonly seen in falls where an individual braces with their hands.

Figure 2: Labelled Carpal Bones

The forearm consists of two bones: the radius and the ulna. The radius (located on the thumb side) is more commonly injured as people brace with their arms during falls. Colloquially, the term “wrist fracture” actually involves an injury to the distal radius (forearm), rather than the carpal bones. As previously mentioned, a fracture is more likely to occur when the arm is fully outstretched at the moment of impact. Fractures are more common near the distal end (Figure 3), as this region typically contacts the impact surface first.

Figure 3: Bone Structure of Arm

Background

The most common types of injuries sustained during skiing are fractures, contusions, and sprains to the arm, which make up 22% of downhill ski injuries, followed by sprains to the knee/lower leg which account for 17.8%. Interestingly, snowboarding arm injuries account for 43.1% of total injuries, where only 9.3% are sprains to the knee/lower leg.

The mechanical parameters associated with forward and backwards falling on a snowboard were studied. From research, this study seems to be one of the only ones that truly investigates the biomechanics linked to the high percentage of arm injuries.

Studies conducted on the mechanical parameters associated with forward and backward falls found that wrist injuries account for 20% of total snowboarding accidents and that 35.9% of total snowboarding accidents impact the hand, wrist, or lower arm, with 14.1% in radius/ulna and humerus injury. Across research there is a gap in understanding the most common location and mode of ski and snowboard injuries. For example, one study uses an ISS score to evaluate injury, whereas another uses AIS.

Most research papers are focused on the epidemiology of skiing injuries, while there are only a few biomechanical studies on the factors affecting injuries. Many studies are available for general falls that are unrelated to skiing, this review utilizes a cross analysis of the epidemiological work related to ski injuries combined with the empirical data from general fall cases. This could be done by assuming that the falls skiing take place from rest.

The insights gained can contribute to the design of protective equipment, such as wrist guards or specialized braces and add clarification to controversies regarding wrist guards. Some biomechanists suggest wearing wrist guards can change the way people fall leading to awkward landings and translating forces to other parts of the body, ultimately leading to injury. Furthermore, these findings provide a foundation for recommending specific bracing techniques or fall-training protocols to help athletes minimize the risk of injury. By integrating these biomechanical principles into safety equipment and training, we can enhance skier protection and promote safer participation in the sport.

Injury Biomechanics

By simulating various fall scenarios, the internal forces and moments acting on the wrist joint can be quantified. Forward and backward falls involving the FOOSH mechanism are commonly studied due to their high potential for upper extremity injury. During these falls, the body braces to protect vital areas like the head, but this shifts the impact forces to the smaller structures of the wrist and forearm, rather than dispersing the force across the larger body mass. The resulting concentrated forces transmitted through the wrist and hands lead to significantly higher stress on these structures, increasing the risk of injuries.

In real-world conditions, the compressibility of snow allows for deformation upon impact, increasing the time over which force is applied, thereby reducing the impact force and energy experienced by the arm. On the other hand, rigid impacts, such as when the wrist hits a solid surface like compacted snow or ice, transmit the load immediately through the joint, greatly increasing the risk of injury. This difference highlights the need for specific biomechanical testing setups tailored to snowboarding injuries, with testing environments that can simulate realistic snowboarding conditions, and account for variations in snow type, fall angle, and wrist positioning. Understanding the dynamics of these falls is crucial in accurately assessing the forces involved and their potential to cause injury.

Study Methods

Both cadaveric and live human testing are commonly used to assess internal loading of the wrist during impact. Cadaveric testing is more commonly employed to investigate fracture thresholds and injury mechanisms, while human testing is typically conducted to verify natural (hand, arm, wrist) positions during various types of falls and to validate loading conditions in non-destructive tests.

Among fall-related injury scenarios, two common worst-case patterns have been widely identified in the literature: forwards and backwards falls with outstretched arms. Although backwards falls are generally recognized for posing a greater injury risk, they have been studied less extensively. In contrast, forward falls have been the subject of more frequent studies, both within snow-sport research and in the broader context of fall-related upper extremity injuries. Given the greater availability of data, this review will focus specifically on forward fall scenarios.

Figure 4: Fall Scenarios

Human Testing

A study examined the kinetics of the upper extremities during different fall conditions. 18 participants were positioned in a seated or kneeling stance, with hands in front hovering in the air. They were then asked to drop and land on in-ground force plates. Drop heights were varied, and the resultant wrist angles, velocities, and forces during impact were recorded.

Another study measured the hand impact forces in a single type of forward fall. 16 participants knelt forwards, with their outstretched arms a set distance from the ground before falling forwards. These trials were repeated at different drop heights. The data collected were used to establish parameters for a mathematical prediction model. This model was then employed to estimate impact forces from varying fall heights.

A third study investigated the biomechanics of real-world arm injuries during snowboarding falls. The study employed a two-part methodology: a surrogate arm drop test, followed by a field test involving real snowboarders. First, a surrogate arm model fitted with an instrumented glove, performed drop tests to verify sensor accuracy. Once successfully calibrated, real snowboarders were provided with these gloves to wear on their snowboarding trips to collect field data.

Table 1: Comparison of Impact Parameters Between Trials

Fall Type	Fall height (cm)	Peak Force (N)	Study
Forward	80.7 67.1 (measured from shoulder to ground)	759 ± 455 700 ± 371	Human
Forward	1 3 5 (measured from palm to ground)	400* 750* 1020*	Human
Forward	5 50 100	800* 2000* 3000*	Model
Forward (Drop Test)	48 33 13	1802 ± 119 1389 ± 52 860 ± 17	Surrogate Arm
(Unspecified)	N/A	266 ± 232	Human Field Tests

*Data is estimated from graphs and values may not be exact

Strengths and Limitations

One notable methodological strength observed across many of the reviewed studies was the strict control of participants' initial positioning. Variables such as arm and wrist flexion angles, as well as drop height, were held constant across each trial. This minimized extraneous variability, ensuring impact responses were attributable to mechanics of the fall, rather than differences in initial conditions. As a result, intra-subject force curves and peak force values showed low variability, improving data reliability.

In contrast, a limitation is the lack of standardization in testing methodology between different studies. While each study maintains control over their own initial conditions, these specific setups differ across studies. These variables significantly influence force distribution, and the types of injuries sustained that are reported in epidemiological data. While allowing participants to fall in a more natural, self-selected posture may improve ecological validity, it limits the comparability of results across studies.

Another source of variability is the definition of drop height. Among the studies reviewed, different reference points were used to define the distance between the arm and impact surface. Most commonly this distance is measured from the palm, or the shoulder but sometimes it was unspecified. Even among studies that appear to use the same reference point, the actual drop heights selected were different. This further complicates cross-study comparisons.

Another limitation lies in the test environment. Most tests are conducted in a controlled laboratory setting, where subjects are positioned in a predetermined, static stance. While this allows for control between trials, it fails to replicate the dynamic nature of real snowboarding falls. Additionally, tests also involve impacts onto specialized equipment that does not mimic the properties of snow. As observed in field tests [11], despite involving real snowboarding falls, reported peak impact forces were much lower compared to lab tests. This highlights a key research gap, where studies need to better replicate real-world conditions, to improve the validity of findings.

Epidemiological research provides longitudinal data on injury trends that show how factors such as age, gender, and equipment use impact forearm fractures; however, some studies rely on retrospective data, which may not fully account for recent skiing equipment and biomedical advances. Another limitation is the current lack of studies that focus on skiing and snowboarding injuries. This means that the cross-analysis conducted might not provide enough information on injury biomechanics and prevention.

A controversial aspect in the field is the effectiveness of wrist guards in preventing injuries. A study suggests that wrist guards reduce the risk of distal radius fractures, but some studies say they may redistribute force upward, leading to forearm fractures. Another study found that chronic repetitive stress in the wrist is not often accounted for in general sports injury studies.

Future Work

It is clear that not enough work has been conducted on this area of research. While there is some merit in consulting the epidemiological research for awareness and mitigation, there is not enough biomechanical data to understand how the injury might have occurred.

It is interesting to see the lack of biomechanical research in this area when compared to the popularity of skiing and snowboarding. One such factor could be the lack of models for snow deformation in a laboratory setting and a computer simulation, as snow can exhibit many different characteristics and never has the same properties. If a consistent snow model could be created, FEA could be a very powerful tool. This also relies on the need for empirical data to create boundary conditions and loading scenarios.

Our suggestion for future work of this field is to conduct enough cadaver studies to create reliable data to compare computer models to. With a base data set, computer models could help simulate these arm injuries with the goal of creating a safer environment. This could be done by reducing environmental factors or creating wearable safety devices.