The Use of Wearable Sensors for Preventing, Assessing, and Informing Recovery from Sport-Related Musculoskeletal Injuries: A Systematic Scoping Review

Abstract

Wearable technologies are often indicated as tools that can enable the in-field collection of quantitative biomechanical data, unobtrusively, for extended periods of time, and with few spatial limitations. Despite many claims about their potential for impact in the area of injury prevention and management, there seems to be little attention to grounding this potential in biomechanical research linking quantities from wearables to musculoskeletal injuries, and to assessing the readiness of these biomechanical approaches for being implemented in real practice. We performed a systematic scoping review to characterise and critically analyse the state of the art of research using wearable technologies to study musculoskeletal injuries in sport from a biomechanical perspective. A total of 4952 articles were retrieved from the Web of Science, Scopus, and PubMed databases; 165 were included. Multiple study features-such as research design, scope, experimental settings, and applied context-were summarised and assessed. We also proposed an injury-research readiness classification tool to gauge the maturity of biomechanical approaches using wearables. Five main conclusions emerged from this review, which we used as a springboard to propose guidelines and good practices for future research and dissemination in the field.

Keywords: accelerometer; athlete; biomechanics; exercise; force transducers; inertial sensors; injury mechanisms; movement analysis; prevention; rehabilitation.

Figure 1

The injury-research readiness level classification model, where different classes of research maturity (IrRL1-3, in columns) are mapped against the following feature domains (rows): knowledge of causal relationship, experimental settings, testing technology, and normative guidelines.

Figure 2

The PRISMA-ScR flowchart, showing the search and selection process.

Figure 3

Time distribution of the original studies selected for this scoping review (black), and reviews (white), ordered by publication year. The graph also reports the number of original articles published, normalised (%) to the overall number of manuscripts published in the same year in the broader area of sport injury biomechanics, where this quantity was retrieved using the following MeSH term search in PubMed: ((sport[MeSH Terms]) AND (injury[MeSH Terms])) AND (biomechanics[MeSH Terms])).

Figure 4

The distribution of studies at different time settings in relation to injury, reported from different perspectives: (a) experimental setting; (b) strength of evidence; (c) injury type; (d) level of sport participation. Multiple counts are allowed for injury type and level of sports, since some articles analysed multiple types of injuries and/or tested athletes at different levels of sport.

Figure 5

(a,b) Breakdown of studies (absolute number) by injury location (i.e., ankle and foot, knee, lower limb, head and spine, upper limb), tissue affected (i.e., soft or skeletal), and injury type (acute or overuse). Articles in which the body region was not specified, or considering any injury location, along with articles including both acute and overuse injuries, are not reported in the figure (34 studies in total). (c) Body map showing injury location and the associated sports disciplines for which there is prevalence of published research in the areas considered by this review.

Figure 6

(a) Boxplot of healthy and post-injury athletes divided by gender. (b) Left: number of athletes analysed in groups of the sample size reported in abscissa; right: their cumulative value. (c) Number of athletes, divided by gender, tested in the sports analysed in the 21 studies comprising half of the overall sample of this review (F = females, M = males, NS = gender not specified).

Figure 7

Breakdown of published articles by sport and motor task. Multiple counts are allowed for articles performing comparative studies across sports.

Figure 8

The most used body positions (head, trunk, arm, pelvis, and tibia) and the associated methods of sensor attachment (pocket in a vest/belt/tape, double-side tape directly on the skin, tape above the sensor, elastic strap, and rigid frame). The numbers represent how many studies implemented that type of sensor attachment for each specific location.

Figure 9

Distribution of studies at different IrRL levels is reported from different perspectives: (a) strength of evidence; (b) scope; (c) relevance of wearable-based parameters.

Figure 10

Distribution of studies at different injury-related readiness levels (IrRLs) for different time settings (columns) and injury types (rows).