Comparable in vivo joint kinematics between self-reported stable and unstable knees after TKA can be explained by muscular adaptation strategies

Abstract

In this supplementary dataset, we made available: a) the raw EMG data, already concatenated for all trials in level walking, downhill walking, and stair descent separately; b) the code for the EMG data processing; c) Source data files of anterior-posterior(A-P) translations on the medial and lateral condyles during all activities; d) Source data files of tibiofemoral rotation angles during all activities, and e) the core codes to evaluate the kinematic data. The raw EMG data files are in RData format named “RAW_EMG_stable.RData” for the stable group and “RAW_EMG_unstable.RData” for the unstable group. These RData files are R lists consisting of elements of S3 class “EMG”, each of which is a human locomotion trial containing cycle segmentation timings (cycles) and raw electromyographic (emg) data frames from 8 muscles of the tested leg. The “cycles” data frames are structured as data frames containing two columns that correspond to touchdown (first column) and lift-off (second column), and “emg” data frames are also structured as data frames with one row for each recorded data point and 9 columns. The first column contains the incremental time in seconds. The remaining 8 columns contain the raw EMG data, named with the following muscle abbreviations: RF = rectus femoris, VM = vastus medialis, VL = vastus lateralis, TA = tibialis anterior, HM = hamstring medialis, HL = hamstring lateralis, GM = gastrocnemius medialis, GL = gastrocnemius lateralis. Trials are named like “ID05_gt_f_R_01”, where the characters “ID05” indicate the participant number, the character “gt_f” indicates locomotion type(gt_f=level walking, rd_f=downhill walking, sd_f=stair descent), the characters “L” indicate the side of the tested leg (L=left, R=right), and the numbers “01” indicate the trial number. All the code used for pre-processing EMG data and extracting muscle synergies is available in R format. Explanatory comments are profusely present throughout the script “MuscleSynergy_analyzing_codes”. The latest version of this code can be found at https://github.com/alesantuz/musclesyneRgies. The kinematic data files are in mat format named "kinematics_translations_gt.mat" and "kinematics_rotations_gt.mat" for level walking, "kinematics_translations_rd.mat" and "kinematics_rotations_rd.mat" for downhill walking, and "kinematics_translations_sd.mat" and "kinematics_rotations_sd.mat" for stair descent. Kinematic parameters, including tibiofemoral A-P translations, flexion/extension, ab/adduction, and internal/external rotation angles during all gait activities, were interpolated to 101 data points over a full gait cycle. Condylar A-P translations as well as knee rotation angles were presented relative to the corresponding medial condyle position at the initial heel strike of the gait cycle. In each mat file with A-P translation data, 6 structures are listed, which contain the subject-specific mean A-P translations on the medial (mean_med_stable, mean_med_unstable) and lateral condyle (mean_lat_stable, mean_lat_unstable), as well as the mean toe-off events (mean_toeoff_stable, mean_toeoff_unstable) in both stable and unstable groups. In each mat file with tibiofemoral rotation data, 6 structures are listed, which contain the subject-specific mean tibiofemoral flexion/extension (mean_flex_stable, mean_flex_unstable), ab/adduction (mean_ab_stable, mean_ab_unstable), and internal/external rotation angles (mean_rot_stable, mean_rot_unstable). --> Postoperative knee instability is one of the major reasons accounting for unsatisfactory outcomes, as well as a major failure mechanism leading to total knee arthroplasty (TKA) revision. Nevertheless, subjective knee instability is not well defined clinically, plausibly because the relationships between instability and implant kinematics during functional activities of daily living remain unclear. Although muscles play a critical role in supporting the dynamic stability of the knee joint, the influence of joint instability on muscle synergy patterns is poorly understood. therefore, the aim of this study is to understand the impact of self-reported joint instability on tibiofemoral kinematics and muscle synergy patterns after TKA during functional gait activities of daily living. Tibiofemoral kinematics and muscle synergy patterns were examined during level walking, downhill walking, and stair descent in eight self-reported unstable knees after TKA and compared against ten stable TKA knees. Our results reveal that average condylar A-P translations, rotations, as well as their ranges of motion, were comparable between stable and unstable groups. However, the unstable group exhibited more heterogeneous muscle synergy patterns and prolonged activation of knee flexors compared to the stable group. In addition, subjects who reported instability events during measurement showed distinct, subject-specific tibiofemoral kinematic patterns in the early/mid-swing phase of gait. These findings suggest that accurate movement analysis is sensitive for detecting acute instability events but might be less robust in identifying general joint instability. Conversely, muscle synergy patterns seem to be able to identify muscular adaptation associated with underlying chronic knee instability. In this supplementary dataset, we made available: a) clinical assessment data file; b) the raw EMG data, already concatenated for all trials in level walking, downhill walking, and stair descent separately; c) the code for the EMG data processing; d) Source data files of anterior-posterior(A-P) translations on the medial and lateral condyles during all activities; e) Source data files of tibiofemoral rotation angles during all activities, and f) the core codes to evaluate the kinematic data. The clinical assessment date file is an excel table that contains: • Group: the participant's group (stable and unstable) • Posterior tibial slope of knee in [°] • Passive range of Motion (Left/Right) in [°] for each patient • Oxford Knee scores (OKS) for each patient • UCLA scores for each patient • EQ-5D VAS scores for each patient • Core Outcome Measure Index-knee (COMI-knee) scores for each patient The raw EMG data files are in RData format named “RAW_EMG_stable.RData” for the stable group and “RAW_EMG_unstable.RData” for the unstable group. These RData files are R lists consisting of elements of S3 class “EMG”, each of which is a human locomotion trial containing cycle segmentation timings (cycles) and raw electromyographic (emg) data frames from 8 muscles of the tested leg. The “cycles” data frames are structured as data frames containing two columns that correspond to touchdown (first column) and lift-off (second column), and “emg” data frames are also structured as data frames with one row for each recorded data point and 9 columns. The first column contains the incremental time in seconds. The remaining 8 columns contain the raw EMG data, named with the following muscle abbreviations: RF = rectus femoris, VM = vastus medialis, VL = vastus lateralis, TA = tibialis anterior, HM = hamstring medialis, HL = hamstring lateralis, GM = gastrocnemius medialis, GL = gastrocnemius lateralis. Trials are named like “ID05_gt_f_R_01”, where the characters “ID05” indicate the participant number, the character “gt_f” indicates locomotion type(gt_f=level walking, rd_f=downhill walking, sd_f=stair descent), the characters “L” indicate the side of the tested leg (L=left, R=right), and the numbers “01” indicate the trial number. All the code used for pre-processing EMG data and extracting muscle synergies is available in R format. Explanatory comments are profusely present throughout the script “MuscleSynergy_analyzing_codes”. The latest version of this code can be found at https://github.com/alesantuz/musclesyneRgies. The kinematic data files are in mat format named "kinematics_translations_gt.mat" and "kinematics_rotations_gt.mat" for level walking, "kinematics_translations_rd.mat" and "kinematics_rotations_rd.mat" for downhill walking, and "kinematics_translations_sd.mat" and "kinematics_rotations_sd.mat" for stair descent. Kinematic parameters, including tibiofemoral A-P translations, flexion/extension, ab/adduction, and internal/external rotation angles during all gait activities, were interpolated to 101 data points over a full gait cycle. Condylar A-P translations as well as knee rotation angles were presented relative to the corresponding medial condyle position at the initial heel strike of the gait cycle. In each mat file with A-P translation data, 6 structures are listed, which contain the subject-specific mean A-P translations on the medial (mean_med_stable, mean_med_unstable) and lateral condyle (mean_lat_stable, mean_lat_unstable), as well as the mean toe-off events (mean_toeoff_stable, mean_toeoff_unstable) in both stable and unstable groups. In each mat file with tibiofemoral rotation data, 6 structures are listed, which contain the subject-specific mean tibiofemoral flexion/extension (mean_flex_stable, mean_flex_unstable), ab/adduction (mean_ab_stable, mean_ab_unstable), and internal/external rotation angles (mean_rot_stable, mean_rot_unstable).