Characterization of the Relative Change in Objective and Subjective Metrics by Baselining Patients Who Have Wearable Technology Before Total Knee Arthroplasty.

BACKGROUND: Wearable sensors and associated supporting technologies (ie, patient applications) can provide both objective (joint position, step counts, etc.) and subjective data (ie, pain scores and patient-reported outcome measures) to track a patient's episode of care. Establishing a subjective and objective baseline of a patient's experience may arguably be beneficial for multiple reasons, including setting recovery expectations for the patient and demonstrating the effectiveness or success of the intervention. METHODS: In this pilot study, we characterized a subset of patients (n = 82 from 7 surgeons) using a wearable sensor system at least 6 days before total knee arthroplasty and provided postsurgical data up to 50 days postintervention. The 5-day average before surgery for total step counts (activity), achieved flexion and extension on a progress test (functional limit) and visual analog scale daily pain score were calculated. The difference from baseline was then calculated for each patient for each day postsurgery and reported as averages. RESULTS: On average, a patient will experience a relative deficit of 4,000 steps immediately following surgery that will return to near-baseline levels 50 days postintervention. A 30° deficit in flexion and a 10° deficit in extension will return at a similar rate as steps. Relative pain scores will worsen with an increase of approximately 3 points immediately following surgery. However, pain will decrease by 2 points relative to baseline between 40 and 50 days. CONCLUSIONS: The results of this pilot study demonstrate a method to baseline a patient's presurgical subjective and objective data and to provide a reference for postsurgical recovery expectations. Applications for these data include benchmarking for evaluating intervention success as well as setting patient expectations.

Normative Values for Daily Functional Recovery Patterns Following Total Knee Arthroplasty.

BACKGROUND: Wearable devices provide the ability for clinical teams to continuously monitor patients' rehabilitation progress with objective data. Understanding expected recovery patterns following total knee arthroplasty (TKA) enables prompt identification of patients failing to meet these milestones. The aim of this study was to establish normative values for daily functional recovery in the first 6 weeks after TKA using a wearable device. METHODS: This prospective study included patients who underwent TKA between 2020 and 2023, treated by 11 surgeons from 8 institutions. Eligible participants were aged 18 or older, had a primary unilateral TKA, and owned a smartphone. Knee range of motion, total daily steps, cadence, and device usage were measured continuously over 6 weeks. Statistical analysis included analysis of variance using post hoc Tukey honest significant difference tests. RESULTS: The cohort of 566 participants had a mean age of 65 and 69 for men and women, respectively (range, 50 to 80). Women comprised 61% (n = 345) of study participants. There were 82% of women and 90% of men who had a body mass index > 30. The average daily wear time of the device was 12 hours (±4) for a total of 45 days (±27). Recovery was nonlinear, with the greatest gains in the first 3 weeks postsurgery for all metrics. Men demonstrated greater total daily step counts and cadence when compared to women. Obese patients demonstrated poorer performance when compared to lower body mass index patients. CONCLUSIONS: To our knowledge, this study presents the first normative data for tracking daily functional recovery in TKA patients using wearable sensors. Standardizing the TKA recovery timeline allows surgeons to isolate factors affecting patients' healing processes, accurately counsel them preoperatively, and intervene more promptly postoperatively when rehabilitation is not within standard recovery parameters.

The effects of height and distance on the force production and acceleration in martial arts strikes.

Almost all cultures have roots in some sort of self defence system and yet there is relatively little research in this area, outside of a sports related environment. This project investigated different applications of strikes from Kung Fu practitioners that have not been addressed before in the literature. Punch and palm strikes were directly compared from different heights and distances, with the use of a load cell, accelerometers, and high speed video. The data indicated that the arm accelerations of both strikes were similar, although the force and resulting acceleration of the target were significantly greater for the palm strikes. Additionally, the relative height at which the strike was delivered was also investigated. The overall conclusion is that the palm strike is a more effective strike for transferring force to an object. It can also be concluded that an attack to the chest would be ideal for maximizing impact force and moving an opponent off balance. Key PointsIt has been determined that the palm strike is more effective than the punch for developing force and for transferring momentum, most likely the result of a reduced number of rigid links and joints.A strike at head level is less effective than a strike at chest level for developing force and transferring momentum.Distance plays an effect on the overall force and momentum changes, and most likely is dependent on the velocity of the limb and alignment of the bones prior to impact.The teaching of self defence for novices and law enforcement would benefit from including the palm strike as a high priority technique.

Estimated Brain Tissue Response Following Impacts Associated With and Without Diagnosed Concussion.

Kinematic measurements of head impacts are sensitive to sports concussion, but not highly specific. One potential reason is these measures reflect input conditions only and may have varying degrees of correlation to regional brain tissue deformation. In this study, previously reported head impact data recorded in the field from high school and collegiate football players were analyzed using two finite element head models (FEHM). Forty-five impacts associated with immediately diagnosed concussion were simulated along with 532 control impacts without identified concussion obtained from the same players. For each simulation, intracranial response measures (max principal strain, strain rate, von Mises stress, and pressure) were obtained for the whole brain and within four regions of interest (ROI; cerebrum, cerebellum, brain stem, corpus callosum). All response measures were sensitive to diagnosed concussion; however, large inter-athlete variability was observed and sensitivity strength depended on measure, ROI, and FEHM. Interestingly, peak linear acceleration was more sensitive to diagnosed concussion than all intracranial response measures except pressure. These findings suggest FEHM may provide unique and potentially important information on brain injury mechanisms, but estimations of concussion risk based on individual intracranial response measures evaluated in this study did not improve upon those derived from input kinematics alone.

Group-wise evaluation and comparison of white matter fiber strain and maximum principal strain in sports-related concussion.

Sports-related concussion is a major public health problem in the United States and yet its biomechanical mechanisms remain unclear. In vitro studies demonstrate axonal elongation as a potential injury mechanism; however, current response-based injury predictors (e.g., maximum principal strain, ε(ep)) typically do not incorporate axonal orientations. We investigated the significance of white matter (WM) fiber orientation in strain estimation and compared fiber strain (ε(n)) with ε(ep) for 11 athletes with a clinical diagnosis of concussion. Geometrically accurate subject-specific head models with high mesh quality were created based on the Dartmouth Head Injury Model (DHIM), which was successfully validated (performance categorized as "good" to "excellent"). For WM regions estimated to be exposed to high strains using a range of injury thresholds (0.09-0.28), substantial differences existed between ε(n) and ε(ep) in both distribution (Dice coefficient of 0.13-0.33) and extent (∼ 5-10-fold differences), especially at higher threshold levels and higher rotational acceleration magnitudes. For example, an average of 3.2% vs. 29.8% of WM was predicted above an optimal threshold of 0.18 established from an in vivo animal study using ε(n) and ε(ep), respectively, with an average Dice coefficient of 0.14. The distribution of WM regions with high ε(n) was consistent with typical heterogeneous patterns of WM disruptions in diffuse axonal injury, and the group-wise extent at the optimal threshold matched well with the percentage of WM voxels experiencing significant longitudinal changes of fractional anisotropy and mean diffusivity (3.2% and 3.44%, respectively) found from a separate independent study. These results suggest the significance of incorporating WM microstructural anisotropy in future brain injury studies.

Effect of head impacts on diffusivity measures in a cohort of collegiate contact sport athletes.

OBJECTIVE: To determine whether exposure to repetitive head impacts over a single season affects white matter diffusion measures in collegiate contact sport athletes. METHODS: A prospective cohort study at a Division I NCAA athletic program of 80 nonconcussed varsity football and ice hockey players who wore instrumented helmets that recorded the acceleration-time history of the head following impact, and 79 non-contact sport athletes. Assessment occurred preseason and shortly after the season with diffusion tensor imaging and neurocognitive measures. RESULTS: There was a significant (p = 0.011) athlete-group difference for mean diffusivity (MD) in the corpus callosum. Postseason fractional anisotropy (FA) differed (p = 0.001) in the amygdala (0.238 vs 0.233). Measures of head impact exposure correlated with white matter diffusivity measures in several brain regions, including the corpus callosum, amygdala, cerebellar white matter, hippocampus, and thalamus. The magnitude of change in corpus callosum MD postseason was associated with poorer performance on a measure of verbal learning and memory. CONCLUSION: This study suggests a relationship between head impact exposure, white matter diffusion measures, and cognition over the course of a single season, even in the absence of diagnosed concussion, in a cohort of college athletes. Further work is needed to assess whether such effects are short term or persistent.

Parametric comparisons of intracranial mechanical responses from three validated finite element models of the human head.

A number of human head finite element (FE) models have been developed from different research groups over the years to study the mechanisms of traumatic brain injury. These models can vary substantially in model features and parameters, making it important to evaluate whether simulation results from one model are readily comparable with another, and whether response-based injury thresholds established from a specific model can be generalized when a different model is employed. The purpose of this study is to parametrically compare regional brain mechanical responses from three validated head FE models to test the hypothesis that regional brain responses are dependent on the specific head model employed as well as the region of interest (ROI). The Dartmouth Scaled and Normalized Model (DSNM), the Simulated Injury Monitor (SIMon), and the Wayne State University Head Injury Model (WSUHIM) were selected for comparisons. For model input, 144 unique kinematic conditions were created to represent the range of head impacts sustained by male collegiate hockey players during play. These impacts encompass the 50th, 95th, and 99th percentile peak linear and rotational accelerations at 16 impact locations around the head. Five mechanical variables (strain, strain rate, strain × strain rate, stress, and pressure) in seven ROIs reported from the FE models were compared using Generalized Estimating Equation statistical models. Highly significant differences existed among FE models for nearly all output variables and ROIs. The WSUHIM produced substantially higher peak values for almost all output variables regardless of the ROI compared to the DSNM and SIMon models (p < 0.05). DSNM also produced significantly different stress and pressure compared with SIMon for all ROIs (p < 0.05), but such differences were not consistent across ROIs for other variables. Regardless of FE model, most output variables were highly correlated with linear and rotational peak accelerations. The significant disparities in regional brain responses across head models regardless of the output variables strongly suggest that model-predicted brain responses from one study should not be extended to other studies in which a different model is utilized. Consequently, response-based injury tolerance thresholds from a specific model should not be generalized to other studies either in which a different model is used. However, the similar relationships between regional responses and the linear/rotational peak accelerations suggest that each FE model can be used independently to assess regional brain responses to impact simulations in order to perform statistical correlations with medical images and/or well-selected experiments with documented injury findings.

Martial arts striking hand peak acceleration, accuracy and consistency.

The goal of this paper was to investigate the possible trade-off between peak hand acceleration and accuracy and consistency of hand strikes performed by martial artists of different training experiences. Ten male martial artists with training experience ranging from one to nine years volunteered to participate in the experiment. Each participant performed 12 maximum effort goal-directed strikes. Hand acceleration during the strikes was obtained using a tri-axial accelerometer block. A pressure sensor matrix was used to determine the accuracy and consistency of the strikes. Accuracy was estimated by the radial distance between the centroid of each subject's 12 strikes and the target, whereas consistency was estimated by the square root of the 12 strikes mean squared distance from their centroid. We found that training experience was significantly correlated to hand peak acceleration prior to impact (r(2)=0.456, p =0.032) and accuracy (r(2)=0. 621, p=0.012). These correlations suggest that more experienced participants exhibited higher hand peak accelerations and at the same time were more accurate. Training experience, however, was not correlated to consistency (r(2)=0.085, p=0.413). Overall, our results suggest that martial arts training may lead practitioners to achieve higher striking hand accelerations with better accuracy and no change in striking consistency.

The effect of hand dominance on martial arts strikes.

The main goal of this study was to compare dominant and non-dominant martial arts palm strikes under different circumstances that usually happen during martial arts and combative sports applications. Seven highly experienced (10±5 years) right hand dominant Kung Fu practitioners performed strikes with both hands, stances with left or right lead legs, and with the possibility or not of stepping towards the target (moving stance). Peak force was greater for the dominant hand strikes (1593.76±703.45 N vs. 1042.28±374.16 N; p<.001), whereas no difference was found in accuracy between the hands (p=.141). Additionally, peak force was greater for the strikes with moving stance (1448.75±686.01 N vs. 1201.80±547.98 N; p=.002) and left lead leg stance (1378.06±705.48 N vs. 1269.96±547.08 N). Furthermore, the difference in peak force between strikes with moving and stationary stances was statistically significant only for the strikes performed with a left lead leg stance (p=.007). Hand speed was higher for the dominant hand strikes (5.82±1.08 m/s vs. 5.24±0.78 m/s; p=.001) and for the strikes with moving stance (5.79±1.01 m/s vs. 5.29±0.90 m/s; p<.001). The difference in hand speed between right and left hand strikes was only significant for strikes with moving stance. In summary, our results suggest that the stronger palm strike for a right-handed practitioner is a right hand strike on a left lead leg stance moving towards the target.