An Investigation Into the Measurement of Injury Severity in Running-Related Injury Research: A Scoping Review.

Understanding injury severity is essential to inform injury prevention practice. The aims of this scoping review were to investigate how running-related injury (RRI) severity is measured, compare how it differs across studies, and examine whether it influences study outcomes (i.e., injury rates and risk factor identification). This scoping review was prospectively registered with Open Science Framework. A systematic electronic search was conducted using PubMed, Scopus, SPORTDiscuss, MEDLINE, and Web of Science databases. Included studies were published in English between January 1980 and December 2023, investigated RRIs in adult running populations, and included a measure of injury severity. Results were extracted and collated. Sixty-six studies were included. Two predominant primary criteria are used to define injury severity: the extent of the effect on running and/or the extent of the physical description. When secondary definition criteria are considered, 13 variations of injury severity measurement are used. Two approaches are used to grade injury severity: a categorization approach or a continuous numerical scale. Overall, the measurement of RRI severity is relatively inconsistent across studies. Less than half of studies report incidence rates per level of injury severity, while none report specific risk factors across levels, making it difficult to determine if the approach to measuring injury severity influences these study outcomes. This lack of information is possibly contributing to inconsistent rates of RRIs reported, and the lack of clarity on risk factors.

Definitions and surveillance methods of running-related injuries: A scoping review.

Inconsistent and restricted definitions of injury have contributed to limitations in determining injury rates and identifying risk factors for running-related injuries (RRIs). The aim of this scoping review was to investigate the definitions and surveillance methods of RRIs. A systematic electronic search was performed using PubMed, Scopus, SPORTDiscuss, MEDLINE, and Web of Science databases. Included studies were published in English between January 1980 and June 2023 which investigated RRIs in adult running populations, providing a definition for a general RRI. Results were extracted and collated. 204 articles were included. Three primary criteria were used to define RRIs: physical description, effect on training and medical intervention, while three secondary criteria are also associated with definitions: cause/onset of injury, location, and social consequences. Further descriptors and sub-descriptors form these criteria. The use of Boolean operators resulted in nine variations in definitions. Inconsistency is evident among definitions of RRIs. Injury definitions seem to be important for two main reasons: firstly, determining accurate injury rates, and secondly, in research examining risk factors. For the latter, definitions seem to be very limited, only capturing severe injuries and failing to recognise the full development process of RRIs, precluding the identification of conclusive risk factors. A potential two-approach solution is the initial use of a broad definition acting as a gatekeeper for identifying any potential injury, and follow-up with an extensive surveillance tool to capture the specific consequences of the varying severity of RRIs.

S-WD-EEMD: A hybrid framework for imbalanced sEMG signal analysis in diagnosis of human knee abnormality.

The diagnosis of human knee abnormalities using the surface electromyography (sEMG) signal obtained from lower limb muscles with machine learning is a major problem due to the noisy nature of the sEMG signal and the imbalance in data corresponding to healthy and knee abnormal subjects. To address this challenge, a combination of wavelet decomposition (WD) with ensemble empirical mode decomposition (EEMD) and the Synthetic Minority Oversampling Technique (S-WD-EEMD) is proposed. In this study, a hybrid WD-EEMD is considered for the minimization of noises produced in the sEMG signal during the collection, while the Synthetic Minority Oversampling Technique (SMOTE) is considered to balance the data by increasing the minority class samples during the training of machine learning techniques. The findings indicate that the hybrid WD-EEMD with SMOTE oversampling technique enhances the efficacy of the examined classifiers when employed on the imbalanced sEMG data. The F-Score of the Extra Tree Classifier, when utilizing WD-EEMD signal processing with SMOTE oversampling, is 98.4%, whereas, without the SMOTE oversampling technique, it is 95.1%.

Sensorimotor Dysfunction Following Anterior Cruciate Ligament Reconstruction- an Afferent Perspective: A Scoping Review.

Background: Sensorimotor dysfunction is thought to occur following anterior cruciate ligament (ACL) injury which may have implications on future reinjury risk. Dysfunction has been demonstrated within the efferent component of the sensorimotor system. However, no reviews have examined the two main components of the afferent system: the visual and somatosensory systems. Hypothesis/Purpose: This study aimed to report differences in function (central processing and local processing) within the (1) somatosensory and (2) visual systems between individuals following anterior cruciate ligament reconstruction (ACLR) and healthy controls (between-subject). The study also aimed to report differences in function within the two systems between the two limbs of an individual following ACLR (within-subject). Study Design: Scoping review. Methods: A search was conducted in PubMed, SPORTDiscus, CINAHL, Medline and Embase up until September 2021. Level I-IV studies assessing somatosensory and visual systems were included if they compared ACLR limbs to the uninjured contralateral limb (within-subject) or a healthy control limb (between-group). The function of somatosensory and visual systems was assessed across both central processing (processing of information in the central cortex) and local processing (all other assessments outside of central processing of information). Results: Seventy studies were identified (52 somatosensory, 18 visual). Studies examining somatosensory central processing demonstrated significant differences; 66% of studies exhibited within-subject differences and 100% of the studies exhibited between-group differences. Studies examining local somatosensory processing had mixed findings; 40% of the 'joint position sense (JPS)' and 'threshold to detect motion (TTDM)' studies showed significant within-subject differences (JPS=0.8°-3.8° and TTDPM=0.2°-1.4°) and 42% demonstrated significant between-group differences (JPS=0.4°-5° and TTDPM=0.3°-2.8°). Eighty-three percent of visual central processing studies demonstrated significant dysfunction between-groups with no studies assessing within-subject differences. Fifty percent of the studies examining local visual processing demonstrated a significant between-group difference. Conclusion: Significant differences in central processing exist within somatosensory and visual systems following ACLR. There is mixed evidence regarding local somatosensory and visual processing. Increased compensation by the visual system and local visual processing dysfunction may occur in conjunction with somatosensory dysfunction.