Reliability and Minimal Detectable Change Values for Predictions of Knee Forces during Gait and Stair Ascent Derived from the FreeBody Musculoskeletal Model of the Lower Limb

FreeBody is a musculoskeletal model of the lower limb used to calculate predictions of muscle and joint contact forces. The validation of FreeBody has been described in a number of publications however its reliability has yet to be established. The purpose of this study was therefore to establish the test-retest reliability of FreeBody in a population of healthy adults in order to add support to previous and future research using FreeBody that demonstrates differences between cohorts after an intervention. We hypothesized that test-retest estimations of knee contact forces from FreeBody would demonstrate a high intra-class correlation. Kinematic and kinetic data from nine older participants (4 men: mean age = 63±11 years; 5 women: mean age = 49±4 years) performing level walking and stair ascent was collected on consecutive days and then analysed using FreeBody. There was a good level of intra-session agreement between the waveforms for the individual trials of each activity during testing session 1 (R = 0.79-0.97). Similarly, overall there was a good inter-session agreement within subjects (R = 0.69-0.97) although some subjects showed better agreement than others. There was a high level of agreement between the group mean waveforms of the two sessions for all variables (R = 0.882-0.997). The intra-class correlation coefficients (ICC) were very high for peak tibiofemoral joint contact forces (TFJ) and hamstring forces during gait, for peak patellofemoral joint contact forces and quadriceps forces during stair ascent and for peak lateral TFJ and the proportion of TFJ accounted for by the medial compartment during both tasks (ICC = 0.86-0.96). Minimal detectable change (MDC) of the peak knee forces during gait ranged between 0.43 and 1.53 × body weight (18-170% of the mean peak values). The smallest MDCs were found for medial TFJ share (4.1 % and 5.8% for walking and stair ascent respectively, or 4.8% and 6.7% of the mean peak values). In conclusion, the results of this study support the use of FreeBody to investigate the effect of interventions on muscle and joint contact forces at the cohort level, but care should be taken if using FreeBody at the subject level

The Influence of Head Impact Threshold for Reporting Data in Contact and Collision Sports: Systematic Review and Original Data Analysis

- Background - Head impacts and resulting head accelerations cause concussive injuries. There is no standard for reporting head impact data in sports to enable comparison between studies. - Objective - The aim was to outline methods for reporting head impact acceleration data in sport and the effect of the acceleration thresholds on the number of impacts reported. - Methods - A systematic review of accelerometer systems utilised to report head impact data in sport was conducted. The effect of using different thresholds on a set of impact data from 38 amateur senior rugby players in New Zealand over a competition season was calculated. - Results - Of the 52 studies identified, 42 % reported impacts using a >10-g threshold, where g is the acceleration of gravity. Studies reported descriptive statistics as mean ± standard deviation, median, 25th to 75th interquartile range, and 95th percentile. Application of the varied impact thresholds to the New Zealand data set resulted in 20,687 impacts of >10 g, 11,459 (45 % less) impacts of >15 g, and 4024 (81 % less) impacts of >30 g. Discussion Linear and angular raw data were most frequently reported. Metrics combining raw data may be more useful; however, validity of the metrics has not been adequately addressed for sport. Differing data collection methods and descriptive statistics for reporting head impacts in sports limit inter-study comparisons. Consensus on data analysis methods for sports impact assessment is needed, including thresholds. Based on the available data, the 10-g threshold is the most commonly reported impact threshold and should be reported as the median with 25th and 75th interquartile ranges as the data are non-normally distributed. Validation studies are required to determine the best threshold and metrics for impact acceleration data collection in sport. Conclusion Until in-field validation studies are completed, it is recommended that head impact data should be reported as median and interquartile ranges using the 10-g impact threshold