What are the perceptions and concerns of people living with diabetes and National Health Service staff around the potential implementation of AI-assisted screening for diabetic eye disease? Development and validation of a survey for use in a secondary care screening setting.

INTRODUCTION: The English National Health Service (NHS) Diabetic Eye Screening Programme (DESP) performs around 2.3 million eye screening appointments annually, generating approximately 13 million retinal images that are graded by humans for the presence or severity of diabetic retinopathy. Previous research has shown that automated retinal image analysis systems, including artificial intelligence (AI), can identify images with no disease from those with diabetic retinopathy as safely and effectively as human graders, and could significantly reduce the workload for human graders. Some algorithms can also determine the level of severity of the retinopathy with similar performance to humans. There is a need to examine perceptions and concerns surrounding AI-assisted eye-screening among people living with diabetes and NHS staff, if AI was to be introduced into the DESP, to identify factors that may influence acceptance of this technology. METHODS AND ANALYSIS: People living with diabetes and staff from the North East London (NEL) NHS DESP were invited to participate in two respective focus groups to codesign two online surveys exploring their perceptions and concerns around the potential introduction of AI-assisted screening.Focus group participants were representative of the local population in terms of ages and ethnicity. Participants' feedback was taken into consideration to update surveys which were circulated for further feedback. Surveys will be piloted at the NEL DESP and followed by semistructured interviews to assess accessibility, usability and to validate the surveys.Validated surveys will be distributed by other NHS DESP sites, and also via patient groups on social media, relevant charities and the British Association of Retinal Screeners. Post-survey evaluative interviews will be undertaken among those who consent to participate in further research. ETHICS AND DISSEMINATION: Ethical approval has been obtained by the NHS Research Ethics Committee (IRAS ID: 316631). Survey results will be shared and discussed with focus groups to facilitate preparation of findings for publication and to inform codesign of outreach activities to address concerns and perceptions identified.

Ethnic disparities in progression rates for sight-threatening diabetic retinopathy in diabetic eye screening: a population-based retrospective cohort study.

INTRODUCTION: The English Diabetic Eye Screening Programme (DESP) offers people living with diabetes (PLD) annual eye screening. We examined incidence and determinants of sight-threatening diabetic retinopathy (STDR) in a sociodemographically diverse multi-ethnic population. RESEARCH DESIGN AND METHODS: North East London DESP cohort data (January 2012 to December 2021) with 137 591 PLD with no retinopathy, or non-STDR at baseline in one/both eyes, were used to calculate STDR incidence rates by sociodemographic factors, diabetes type, and duration. HR from Cox models examined associations with STDR. RESULTS: There were 16 388 incident STDR cases over a median of 5.4 years (IQR 2.8-8.2; STDR rate 2.214, 95% CI 2.214 to 2.215 per 100 person-years). People with no retinopathy at baseline had a lower risk of sight-threatening diabetic retinopathy (STDR) compared with those with non-STDR in one eye (HR 3.03, 95% CI 2.91 to 3.15, p<0.001) and both eyes (HR 7.88, 95% CI 7.59 to 8.18, p<0.001). Black and South Asian individuals had higher STDR hazards than white individuals (HR 1.57, 95% CI 1.50 to 1.64 and HR 1.36, 95% CI 1.31 to 1.42, respectively). Additionally, every 5-year increase in age at inclusion was associated with an 8% reduction in STDR hazards (p<0.001). CONCLUSIONS: Ethnic disparities exist in a health system limited by capacity rather than patient economic circumstances. Diabetic retinopathy at first screen is a strong determinant of STDR development. By using basic demographic characteristics, screening programmes or clinical practices can stratify risk for sight-threatening diabetic retinopathy development.

Two-year recall for people with no diabetic retinopathy: a multi-ethnic population-based retrospective cohort study using real-world data to quantify the effect.

BACKGROUND/AIMS: The English Diabetic Eye Screening Programme (DESP) offers people living with diabetes (PLD) annual screening. Less frequent screening has been advocated among PLD without diabetic retinopathy (DR), but evidence for each ethnic group is limited. We examined the potential effect of biennial versus annual screening on the detection of sight-threatening diabetic retinopathy (STDR) and proliferative diabetic retinopathy (PDR) among PLD without DR from a large urban multi-ethnic English DESP. METHODS: PLD in North-East London DESP (January 2012 to December 2021) with no DR on two prior consecutive screening visits with up to 8 years of follow-up were examined. Annual STDR and PDR incidence rates, overall and by ethnicity, were quantified. Delays in identification of STDR and PDR events had 2-year screening intervals been used were determined. FINDINGS: Among 82 782 PLD (37% white, 36% South Asian, and 16% black people), there were 1788 incident STDR cases over mean (SD) 4.3 (2.4) years (STDR rate 0.51, 95% CI 0.47 to 0.55 per 100-person-years). STDR incidence rates per 100-person-years by ethnicity were 0.55 (95% CI 0.48 to 0.62) for South Asian, 0.34 (95% CI 0.29 to 0.40) for white, and 0.77 (95% CI 0.65 to 0.90) for black people. Biennial screening would have delayed diagnosis by 1 year for 56.3% (1007/1788) with STDR and 43.6% (45/103) with PDR. Standardised cumulative rates of delayed STDR per 100 000 persons for each ethnic group were 1904 (95% CI 1683 to 2154) for black people, 1276 (95% CI 1153 to 1412) for South Asian people, and 844 (95% CI 745 to 955) for white people. INTERPRETATION: Biennial screening would have delayed detection of some STDR and PDR by 1 year, especially among those of black ethnic origin, leading to healthcare inequalities.

Wales Anaerobic Test: Reliability and Fitness Profiles of International Rugby Union Players.

ABSTRACT: Beard, A, Ashby, J, Chambers, R, Millet, GP, and Brocherie, F. Wales Anaerobic Test (WAT): Reliability and fitness profiles of international rugby union players. J Strength Cond Res 36(9): 2589-2596, 2022-To provide strength and conditioning coaches a practical and evidence-based test for repeated-sprint ability (RSA) in rugby union players, this study assessed the relative and absolute test-retest reliability of the Wales Anaerobic Test (WAT) and its position-specific association with other fitness performance indices. Thirty-four players (forwards: n = 19; backs: n = 15) of the Welsh rugby union male senior national team performed the WAT (10 × 50-m distance, 25-30 seconds of passive recovery) twice within 4 days. Time for each repetition was recorded, with the best (WAT Best ) and total time (WAT TT ) retained for analysis. Relative (intraclass correlation coefficient [ICC]) and absolute ( SEM ) reliability of the WAT indices were quantified. Furthermore, association (Pearson's product-moment correlations and stepwise backward elimination procedure) with other fitness performance indices (10- and 40-m sprinting times, 30-15 intermittent fitness test [30-15 IFT ] and the Yo-Yo intermittent recovery test level 2 [YYIR2]) was investigated. Pooled values revealed "moderate" to "high" ICCs for WAT Best (ICC = 0.89, p = 0.626) and WAT TT (ICC = 0.95, p = 0.342). Good test sensitivity was reported for forwards and backs' WAT TT ( p > 0.101). Both WAT Best and WAT TT correlated with 10-m and 40-m sprinting times ( r > 0.69, p < 0.001) as well as with 30-15 IFT ( r < -0.77, p < 0.001) and YYIR2 ( r < -0.68, p < 0.001) for pooled values. The WAT proved to be a reliable and sensitive test to assess the rugby union specific RSA-related fitness of international players.

Effect of ethnicity and other sociodemographic factors on attendance at diabetic eye screening: a 12-month retrospective cohort study.

OBJECTIVES: To examine the association of sociodemographic characteristics with attendance at diabetic eye screening in a large ethnically diverse urban population. DESIGN: Retrospective cohort study. SETTING: Screening visits in the North East London Diabetic Eye Screening Programme (NELDESP). PARTICIPANTS: 84 449 people with diabetes aged 12 years or older registered in the NELDESP and scheduled for screening between 1 April 2017 and 31 March 2018. MAIN OUTCOME MEASURE: Attendance at diabetic eye screening appointments. RESULTS: The mean age of people with diabetes was 60 years (SD 14.2 years), 53.4% were men, 41% South Asian, 29% White British and 17% Black; 83.4% attended screening. Black people with diabetes had similar levels of attendance compared with White British people. However, South Asian, Chinese and 'Any other Asian' background ethnicities showed greater odds of attendance compared with White British. When compared with their respective reference group, high levels of deprivation, younger age, longer duration of diabetes and worse visual acuity, were all associated with non-attendance. There was a higher likelihood of attendance per quintile improvement in deprivation (OR, 1.06; 95% CI, 1.03 to 1.08), with increasing age (OR per decade, 1.17; 95% CI, 1.15 to 1.19), with better visual acuity (OR per Bailey-Lovie chart line 1.12; 95% CI, 1.11 to 1.14) and with longer time of NELDESP registration (OR per year, 1.02; 95% CI, 1.01 to 1.03). CONCLUSION: Ethnic differences in diabetic eye screening uptake, though small, are evident. Despite preconceptions, a higher likelihood of screening attendance was observed among Asian ethnic groups when compared with the White ethnic group. Poorer socioeconomic profile was associated with higher likelihood of non-attendance for screening. Further work is needed to understand how to target individuals at risk of non-attendance and reduce inequalities.

How is the risk of being diagnosed with referable diabetic retinopathy affected by failure to attend diabetes eye screening appointments?

BACKGROUND/AIMS: This study examines the anecdotal impression that in diabetes eye screening there is a relationship between number of consecutive missed screening appointments and the incidence of referable retinopathy at the next screening appointment that is attended. METHODS: A retrospective observational audit was conducted of data from 62,067 people who were due for annual diabetes eye screening in the North East London Diabetes Eye Screening Programme between January 2010 and January 2017, and who had missed at least one screening appointment within that time. RESULTS: Missing 5 consecutive screening appointments increased the incidence of referable retinopathy from a programme average of 4% up to 15%. The incidence of referable retinopathy in people missing 10 or more consecutive appointments was ~20%. There was an association between younger age, male gender, type I disease, and being of African ethnicity with increasing number of missed appointments. CONCLUSIONS: There was a strong association between the number of missed appointments and the proportion of patients showing referable retinopathy at the next visit. Approaches to reduce the number of missed appointments may help to reduce the incidence of referable retinopathy. These may be targeted at those showing the greatest non-attendance behaviour in the current study.

Diagnostic accuracy of diabetic retinopathy grading by an artificial intelligence-enabled algorithm compared with a human standard for wide-field true-colour confocal scanning and standard digital retinal images.

BACKGROUND: Photographic diabetic retinopathy screening requires labour-intensive grading of retinal images by humans. Automated retinal image analysis software (ARIAS) could provide an alternative to human grading. We compare the performance of an ARIAS using true-colour, wide-field confocal scanning images and standard fundus images in the English National Diabetic Eye Screening Programme (NDESP) against human grading. METHODS: Cross-sectional study with consecutive recruitment of patients attending annual diabetic eye screening. Imaging with mydriasis was performed (two-field protocol) with the EIDON platform (CenterVue, Padua, Italy) and standard NDESP cameras. Human grading was carried out according to NDESP protocol. Images were processed by EyeArt V.2.1.0 (Eyenuk Inc, Woodland Hills, California). The reference standard for analysis was the human grade of standard NDESP images. RESULTS: We included 1257 patients. Sensitivity estimates for retinopathy grades were: EIDON images; 92.27% (95% CI: 88.43% to 94.69%) for any retinopathy, 99% (95% CI: 95.35% to 100%) for vision-threatening retinopathy and 100% (95% CI: 61% to 100%) for proliferative retinopathy. For NDESP images: 92.26% (95% CI: 88.37% to 94.69%) for any retinopathy, 100% (95% CI: 99.53% to 100%) for vision-threatening retinopathy and 100% (95% CI: 61% to 100%) for proliferative retinopathy. One case of vision-threatening retinopathy (R1M1) was missed by the EyeArt when analysing the EIDON images, but identified by the human graders. The EyeArt identified all cases of vision-threatening retinopathy in the standard images. CONCLUSION: EyeArt identified diabetic retinopathy in EIDON images with similar sensitivity to standard images in a large-scale screening programme, exceeding the sensitivity threshold recommended for a screening test. Further work to optimise the identification of 'no retinopathy' and to understand the differential lesion detection in the two imaging systems would enhance the use of these two innovative technologies in a diabetic retinopathy screening setting.

Prospective evaluation of an artificial intelligence-enabled algorithm for automated diabetic retinopathy screening of 30 000 patients.

BACKGROUND/AIMS: Human grading of digital images from diabetic retinopathy (DR) screening programmes represents a significant challenge, due to the increasing prevalence of diabetes. We evaluate the performance of an automated artificial intelligence (AI) algorithm to triage retinal images from the English Diabetic Eye Screening Programme (DESP) into test-positive/technical failure versus test-negative, using human grading following a standard national protocol as the reference standard. METHODS: Retinal images from 30 405 consecutive screening episodes from three English DESPs were manually graded following a standard national protocol and by an automated process with machine learning enabled software, EyeArt v2.1. Screening performance (sensitivity, specificity) and diagnostic accuracy (95% CIs) were determined using human grades as the reference standard. RESULTS: Sensitivity (95% CIs) of EyeArt was 95.7% (94.8% to 96.5%) for referable retinopathy (human graded ungradable, referable maculopathy, moderate-to-severe non-proliferative or proliferative). This comprises sensitivities of 98.3% (97.3% to 98.9%) for mild-to-moderate non-proliferative retinopathy with referable maculopathy, 100% (98.7%,100%) for moderate-to-severe non-proliferative retinopathy and 100% (97.9%,100%) for proliferative disease. EyeArt agreed with the human grade of no retinopathy (specificity) in 68% (67% to 69%), with a specificity of 54.0% (53.4% to 54.5%) when combined with non-referable retinopathy. CONCLUSION: The algorithm demonstrated safe levels of sensitivity for high-risk retinopathy in a real-world screening service, with specificity that could halve the workload for human graders. AI machine learning and deep learning algorithms such as this can provide clinically equivalent, rapid detection of retinopathy, particularly in settings where a trained workforce is unavailable or where large-scale and rapid results are needed.

Comparison of true-colour wide-field confocal scanner imaging with standard fundus photography for diabetic retinopathy screening.

BACKGROUND: Screening of diabetic retinopathy (DR) reduces blindness by early identification of retinopathy. This study compares DR grades derived from a two-field imaging protocol from two imaging platforms, one providing a single 60-degree horizontal field of view (FOV) and the other, a standard 45-degree FOV. METHODS: Cross-sectional study which included 1257 diabetic patients aged ≥18 years attending their DR screening visit in the English National Diabetic Eye Screening Programme (NDESP). Patients with maculopathy (M1), preproliferative (R2) or proliferative DR (R3) were referred to an ophthalmologist. Patients with ungradable images (U) are examined in a slit-lamp biomicroscopy clinic. Image acquisition under mydriasis of two images per eye was carried out with the EIDON and with standard fundus cameras. Evaluation was performed by masked graders. RESULTS: Agreement after consensus with kappa statistic was 0.89 (quadratic weights (95% CI 0.87 to 0.92)) for NDESP severity grade, 0.88 (quadratic weights (95% CI 0.82 to 0.94)) for referable disease and 0.92 (linear weights (95% CI 0.88 to 0.95)) for maculopathy. The EIDON detected clinically relevant DR features outside the 45-degree fields in two patients (0.16%): one with intraretinal microvascular abnormalities (IRMAs) and one with neovascularisation. In eight patients (0.64%), the EIDON allowed DR feature visualisation inside the 45-degree fields that were not identified in the NDESP images: three patients (0.24%) with IRMA and five patients (0.40%) with maculopathy. The rates of ungradable encounters were 12 (0.95%) and 13 (1.03%) with the EIDON and NDESP images, respectively. CONCLUSION: The EIDON identifies a small number of additional patients with referable disease which are not detected with standard imaging. This is due to the EIDON finding disease outside the standard FOV and greater clarity finding disease within the standard FOV.

Assessing the whole-match and worst-case scenario locomotor demands of international women's rugby union match-play.

OBJECTIVES: To profile the distances covered during international women's rugby union match-play and assess the duration-specific worst-case scenario locomotor demands over 60-s to 600-s epochs, whilst comparing the values determined by fixed epoch (FIXED) versus rolling average (ROLL) methods of worst-case scenario estimation and assessing positional influences. DESIGN: Descriptive, observational. METHODS: Twenty-nine international women's rugby union players wore 10Hz microelectromechanical systems during eight international matches (110 observations). Total, and per-half, distances were recorded, whilst relative total and high-speed (>4.4ms-1) distances were averaged using FIXED and ROLL methods over 60-600-s. Linear mixed models compared distances covered between match halves, assessed FIXED versus ROLL, and examined the influence of playing position. RESULTS: Players covered ∼5.8kmmatch-1, with reduced distances in the second- versus first-half (p<0.001). For worst-case scenario total (∼8-25%) and high-speed (∼10-26%) distance, FIXED underestimated ROLL. In ROLL, worst-case scenario relative total and high-speed distances reduced from ∼144-161mmin-1 and ∼30-69mmin-1 over 60-s, to ∼8089mmin-1 and ∼516mmin-1 in the 600-s epoch, respectively. Forwards performed less high-speed running over all epochs and covered less total distance during epochs of 60-s, 180-s, 420-s and 480-s, compared with backs. Front row players typically returned the lowest locomotor demands. CONCLUSIONS: This is the first study reporting the positional and worst-case scenario demands of international women's rugby union, and indicates an underestimation in FIXED versus ROLL over 60-s to 600-s epochs. Knowledge of the most demanding periods of women's rugby union match-play facilitates training specificity by enabling sessions to be tailored to such demands.

Comparison of Game Movement Positional Profiles Between Professional Club and Senior International Rugby Union Players.

The purpose of this study was to compare the game movement demands between professional club and senior international rugby union players. Data were obtained from 188 players from 4 professional club teams (Rabo Direct Pro12) and the affiliated international team during the 2014-15 season. Players were tracked by global positioning system (GPS) sampled at 10 Hz and were categorized into 6 different positional groups (front row forwards, FRF; second row forwards, SRF; back row forwards, BRF; half backs, HB; centres, C; outside backs, OB) and separated into playing standard (club vs. international level). Data on distance, distance per minute, high speed running, maximum velocity, sprint distance and efforts as well as repeated high-intensity locomotion efforts (RHILE) were collected. Significant effects (P<0 .05) between club and international were found for RHILE in all 6 positional groupings with a higher number of RHILE in international vs. club games. Significantly (P<0.05) greater total distance and meterage were also shown in international compared to club for OB position. The RHILE differences between club and international games whatever the positions appear of practical relevance for coaches and performance staff to concentrate on training protocols to enhance this quality as well as evaluation methods.

Automatic detection of one-on-one tackles and ruck events using microtechnology in rugby union.

OBJECTIVES: To automate the detection of ruck and tackle events in rugby union using a specifically-designed algorithm based on microsensor data. DESIGN: Cross-sectional study. METHODS: Elite rugby union players wore microtechnology devices (Catapult, S5) during match-play. Ruck (n=125) and tackle (n=125) event data was synchronised with video footage compiled from international rugby union match-play ruck and tackle events. A specifically-designed algorithm to detect ruck and tackle events was developed using a random forest classification model. This algorithm was then validated using 8 additional international match-play datasets and video footage, with each ruck and tackle manually coded and verified if the event was correctly identified by the algorithm. RESULTS: The classification algorithm's results indicated that all rucks and tackles were correctly identified during match-play when 79.4±9.2% and 81.0±9.3% of the random forest decision trees agreed with the video-based determination of these events. Sub-group analyses of backs and forwards yielded similar optimal confidence percentages of 79.7% and 79.1% respectively for rucks. Sub-analysis revealed backs (85.3±7.2%) produced a higher algorithm cut-off for tackles than forwards (77.7±12.2%). CONCLUSIONS: The specifically-designed algorithm was able to detect rucks and tackles for all positions involved. For optimal results, it is recommended that practitioners use the recommended cut-off (80%) to limit false positives for match-play and training. Although this algorithm provides an improved insight into the number and type of collisions in which rugby players engage, this algorithm does not provide impact forces of these events.

Validity of a Microsensor-Based Algorithm for Detecting Scrum Events in Rugby Union.

PURPOSE: Commercially available microtechnology devices containing accelerometers, gyroscopes, magnetometers, and global positioning technology have been widely used to quantify the demands of rugby union. This study investigated whether data derived from wearable microsensors can be used to develop an algorithm that automatically detects scrum events in rugby union training and match play. METHODS: Data were collected from 30 elite rugby players wearing a Catapult OptimEye S5 (Catapult Sports, Melbourne, Australia) microtechnology device during a series of competitive matches (n = 46) and training sessions (n = 51). A total of 97 files were required to "train" an algorithm to automatically detect scrum events using random forest machine learning. A further 310 files from training (n = 167) and match-play (n = 143) sessions were used to validate the algorithm's performance. RESULTS: Across all positions (front row, second row, and back row), the algorithm demonstrated good sensitivity (91%) and specificity (91%) for training and match-play events when the confidence level of the random forest was set to 50%. Generally, the algorithm had better accuracy for match-play events (93.6%) than for training events (87.6%). CONCLUSIONS: The scrum algorithm was able to accurately detect scrum events for front-row, second-row, and back-row positions. However, for optimal results, practitioners are advised to use the recommended confidence level for each position to limit false positives. Scrum algorithm detection was better with scrums involving ≥5 players and is therefore unlikely to be suitable for scrums involving 3 players (eg, rugby sevens). Additional contact- and collision-detection algorithms are required to fully quantify rugby union demands.

Repeated-Sprint Training in Hypoxia in International Rugby Union Players.

Purpose: To investigate the effects of repeated-sprint training in hypoxia vs in normoxia on world-level male rugby union players' repeated-sprint ability (RSA) during an international competition period. Methods: A total of 19 players belonging to an international rugby union senior male national team performed 4 sessions of cycling repeated sprints (consisting of 3 × eight 10-s sprints with 20 s passive recovery) either in normobaric hypoxia (RSH, 3000 m; n = 10) or in normoxia (RSN, 300 m; n = 9) over a 2-wk period. Before and after the training intervention, RSA was evaluated using a cycling repeated-sprint test (6 × 10-s maximal sprint and 20-s passive recovery) performed in normoxia. Results: Significant interaction effects (all P < .05, ηp2>.37 ) between condition and time were found for RSA-related parameters. Compared with Pre, maximal power significantly improved at Post in RSH (12.84 [0.83] vs 13.63 [1.03] W·kg-1, P < .01, ηp2=.15 ) but not in RSN (13.17 [0.89] vs 13.00 [1.01] W·kg-1, P = .45, ηp2=.01 ). Mean power was also significantly enhanced from Pre to Post in RSH (11.15 [0.58] vs 11.86 [0.63] W·kg-1, P < .001, ηp2=.26 ), whereas it remained unchanged in RSN (11.54 [0.61] vs 11.75 [0.65] W·kg-1, P = .23, ηp2=.03 ). Conclusion: As few as 4 dedicated specific RSH sessions were beneficial to enhance repeated power production in world-level rugby union players. Although the improvement from RSA to game behavior remains unclear, this finding appears to be of practical relevance as only a short preparation window is available prior to international rugby union games.

The Use of Wearable Microsensors to Quantify Sport-Specific Movements.

BACKGROUND: Microtechnology has allowed sport scientists to understand the locomotor demands of various sports. While wearable global positioning technology has been used to quantify the locomotor demands of sporting activities, microsensors (i.e. accelerometers, gyroscopes and magnetometers) embedded within the units also have the capability to detect sport-specific movements. OBJECTIVE: The objective of this study was to determine the extent to which microsensors (also referred to as inertial measurement units and microelectromechanical sensors) have been utilised in quantifying sport-specific movements. METHODS: A systematic review of the use of microsensors and associated terms to evaluate sport-specific movements was conducted; permutations of the terms used included alternate names of the various technologies used, their applications and different applied environments. Studies for this review were published between 2008 and 2014 and were identified through a systematic search of six electronic databases: Academic Search Complete, CINAHL, PsycINFO, PubMed, SPORTDiscus, and Web of Science. Articles were required to have used athlete-mounted sensors to detect sport-specific movements (e.g. rugby union tackle) rather than sensors mounted to equipment and monitoring generic movement patterns. RESULTS: A total of 2395 studies were initially retrieved from the six databases and 737 results were removed as they were duplicates, review articles or conference abstracts. After screening titles and abstracts of the remaining papers, the full text of 47 papers was reviewed, resulting in the inclusion of 28 articles that met the set criteria around the application of microsensors for detecting sport-specific movements. Eight articles addressed the use of microsensors within individual sports, team sports provided seven results, water sports provided eight articles, and five articles addressed the use of microsensors in snow sports. All articles provided evidence of the ability of microsensors to detect sport-specific movements. Results demonstrated varying purposes for the use of microsensors, encompassing the detection of movement and movement frequency, the identification of movement errors and the assessment of forces during collisions. CONCLUSION: This systematic review has highlighted the use of microsensors to detect sport-specific movements across a wide range of individual and team sports. The ability of microsensors to capture sport-specific movements emphasises the capability of this technology to provide further detail on athlete demands and performance. However, there was mixed evidence on the ability of microsensors to quantify some movements (e.g. tackling within rugby union, rugby league and Australian rules football). Given these contrasting results, further research is required to validate the ability of wearable microsensors containing accelerometers, gyroscopes and magnetometers to detect tackles in collision sports, as well as other contact events such as the ruck, maul and scrum in rugby union.