Context: A novel virtual game system Knee Biofeedback Rehabilitation Interface for game-based home therapy (KneeBright) was developed for strength training using integrated electromyography biofeedback of the quadriceps muscle to control the game. The study aimed to compare the KneeBright and electromyography biofeedback interface among patients with knee osteoarthritis. Design: Controlled before and after design. Methods: Nineteen patients with knee osteoarthritis took part in this laboratory-based study. Exercise sessions took place on 2 separate days. During session 1, participants used a conventional electromyography biofeedback system while performing 3 sets of lower body exercises with emphasis on maximal muscle activation, endurance, and precision. During session 2, participants used the KneeBright game to match the exercise sets in the first session. For both sessions, knee extension torque during the isometric muscle activation exercises and time to voluntary additional exercise were recorded. Patient engagement was assessed using the technology acceptance model and System Usability Score questionnaires. Results: The peak knee extension torque produced during the control exercise session and the KneeBright exercise session were positively correlated. Knee extension torque generated during KneeBright game exercise sessions was increased by an average of 25% compared to the control sessions (2.14 vs 1.77 N·m/kg, P = .02). The mean technology acceptance model score for the KneeBright system was 3.4/5 and the mean System Usability Score was 79, both indicating positive patient engagement. Conclusions: Patients using the KneeBright game produced greater knee torque than patients using the conventional system, had positive levels of engagement, and exercised longer with the KneeBright game.

Introduction: The objective of this study was to compare Zip and Clozex with a typical closure using a running 3-0 Prolene suture. Methods: A prospective, randomized, controlled trial was conducted in patients aged 18 years and older undergoing elective orthopaedic surgical procedures between 2019 and 2021. Patients were randomized to undergo skin closure using a running 3-0 Prolene suture, Zip, or Clozex. The length and location of incision, time to close, surgeon satisfaction, and complications were recorded. The Stony Brook Scar Evaluation Scale (SBSES) was used to assess cosmesis at 2 weeks and 3 months postoperatively. Patient satisfaction and adverse events were also recorded. Results: Thirty-two patients were included in the analysis. Suture closure time was longer than Zip (266 vs 123 seconds; P = 0.02) and Clozex (266 vs 91 seconds; P = 0.005). SBSES scores were greater for Clozex at 2 weeks compared with suture (4.09 vs 2.8; P = 0.005). At 3 months, Clozex maintained greater scores compared with suture (3.82 vs 2.85; P = 0.023) and Zip (3.82 vs 3.0; P = 0.046).No differences were observed in patient satisfaction at any time points. Discussion: Although patient satisfaction was similar across groups, wound closure times, SBSES scores, and total cost favor Clozex compared with Prolene suture or Zip. ClinicalTrials.gov Registration Number: NCT05251064

Context: Anterior cruciate ligament reconstruction (ACLR) patients commonly adopt poor movement patterns that potentially place them at an increased risk for reinjury if untreated. Limb loading characteristics during functional tasks can highlight movement compensations. Objective: To examine loading symmetry during a bilateral bodyweight squatting task between sexes, compare loading metrics between limbs and sexes, and describe the relationship between loading metrics and patient-reported outcomes (PROs) after ACLR. Design: Cross-sectional study. Setting: Laboratory. Patients or Other Participants: One hundred forty-two patients (71 male, 71 female, age = 24.4 ± 11.10 years) with a primary, unilateral, uncomplicated ACLR completed a squatting assessment and PRO measures at approximately 5.2 months post-ACLR. Main Outcome Measure(s): Normalized limb loading peak force (N/kg) and unilateral cumulative load (%) were collected bilaterally during the squatting task. Limb symmetry index (%) was calculated for normalized peak force. First, we compared limb loading symmetry (%) between sexes using an independent-samples t test. Second, we assessed differences in limb loading metrics between limbs and sexes via an analysis of covariance. Third, we used Spearman ρ correlations to determine the relationship between limb loading metrics and PROs. Results: The majority of individuals (91 of 142, 64.1%) offloaded their ACLR limb (ACLR = 6.6 ± 1.56 N/kg, contralateral = 7.3 ± 1.61 N/kg, P < .001). Females significantly offloaded their ACLR limb (ACLR = 6.3 ± 1.38 N/kg, contralateral = 7.2 ± 1.62 N/kg, P < .001) whereas males did not significantly offload their ACLR limb (ACLR = 6.98 ± 1.65 N/kg, contralateral = 7.4 ± 1.60 N/kg, P = .07). Weak relationships were observed (Ρ value range: −.23 to .19) across limb loading metrics and PROs. Conclusions: Individuals approximately 5 months after ACLR, on average, offloaded their ACLR limb compared with the contralateral limb. Patients’ tendency to offload their weight during a squat was influenced by sex. Relationships between limb loading metrics and PROs indicate patients who load their limbs disproportionately have a lower perception of their capability to complete activities of daily living and lower subjective knee function.

Background/Objectives: Outcomes following Anterior Cruciate Ligament (ACL) reconstruction vary widely among patients, yet existing classification techniques often lack transparency and clinical interpretability. To address this gap, we developed a multi-modal framework that integrates gait dynamics with patient-specific characteristics to enhance personalized assessment of ACL reconstruction outcomes. Methods: Participants, both post-ACL reconstruction and healthy controls, were equipped with inertial measurement unit (IMU) sensors on bilateral wrists, ankles, and the sacrum during standardized locomotion tasks. Using the Phase Slope Index (PSI), we quantified causal relationships between sensor pairs, hypothesizing that (1) PSI-derived metrics capture discriminative biomechanical interactions; (2) task-specific differences in segment coordination patterns influence model performance; and (3) recovery duration modulates classifier confidence and the structure of high-dimensional data distributions. Classification models were trained using PSI features, and permutation-based sensor importance analyses were conducted to interpret task-specific biomechanical contributions. Results: PSI-based classifiers achieved 96.37% accuracy in distinguishing ACL reconstruction outcomes, validating the first hypothesis. Permutation importance revealed that jogging tasks produced more focused importance distributions across fewer sensor pairs while improving accuracy, confirming task-specific coordination effects (hypothesis two). Visualization via t-SNE demonstrated that longer recovery durations corresponded to reduced model confidence but more coherent feature clusters, supporting the third hypothesis. Conclusions: By integrating causal gait metrics and patient recovery profiles, this approach enables interpretable and high-performing ACL outcome prediction. Quantitative evaluation measures—including model confidence and t-SNE cluster coherence—offer clinicians objective tools for personalized rehabilitation monitoring and data-driven return-to-sport decisions.