The purpose of the study was to compare the tibiofemoral contact forces of participants with chronic ankle instability versus controls during landings using a computer-simulated musculoskeletal model. A total of 21 female participants with chronic ankle instability and 21 pair-matched controls performed a drop landing task on a tilted force plate. A 7-camera motion capture system and 2 force plates were used to test participants’ lower-extremity biomechanics. A musculoskeletal model was used to calculate the tibiofemoral contact forces (femur on tibia). No significant between-group differences were observed for the peak tibiofemoral contact forces (P = .25–.48) during the landing phase based on paired t tests. The group differences ranged from 0.05 to 0.58 body weight (BW). Most participants demonstrated a posterior force (peak, ∼1.1 BW) for most duration of the landing phase and a medial force (peak, ∼0.9 BW) and large compressive force (peak, ∼10 BW) in the landing phase. The authors conclude that chronic ankle instability may not be related to the increased tibiofemoral contact forces or knee injury mechanisms during landings on the tilted surface.
Yumeng Li, He Wang, and Kathy J. Simpson
Yumeng Li, Shuqi Zhang, and Christina Odeh
The purposes of the study were (1) to compare postural sway between participants with Parkinson’s disease (PD) and healthy controls and (2) to develop and validate an automated classification of PD postural control patterns using a machine learning approach. A total of 9 participants in the early stage of PD and 12 healthy controls were recruited. Participants were instructed to stand on a force plate and maintain stillness for 2 minutes with eyes open and eyes closed. The center of pressure data were collected at 50 Hz. Linear displacements, standard deviations, total distances, sway areas, and multiscale entropy of center of pressure were calculated and compared using mixed-model analysis of variance. Five supervised machine learning algorithms (ie, logistic regression, K-nearest neighbors, Naïve Bayes, decision trees, and random forest) were used to classify PD postural control patterns. Participants with PD exhibited greater center of pressure sway and variability compared with controls. The K-nearest neighbor method exhibited the best prediction performance with an accuracy rate of up to 0.86. In conclusion, participants with PD exhibited impaired postural stability and their postural sway features could be identified by machine learning algorithms.
Yumeng Li, Melissa A. Mache, and Teri A. Todd
The purpose of this study was to compare the complexity of postural control between children with autism spectrum disorder (ASD) and typical developing children during altered visual and somatosensory conditions using the multiscale entropy. Eleven children with ASD and 11 typical developing children were tested during quiet standing under 4 conditions: (1) eyes open and standing on a stable surface, (2) eyes open and standing on a compliant surface, (3) eyes closed and standing on a stable surface, and (4) eyes closed and standing on a compliant surface. The center of pressure data were collected, and multiscale entropy and sway area of center of pressure were calculated. The ASD group exhibited lower complexity in mediolateral sway compared with typical developing children with a large effect size (partial η 2 = .21). However, based on the different postural control modes, the anteroposterior sway complexity did not demonstrate a similar decrease for children with ASD. The altered visual or somatosensory conditions alone did not significantly affect the postural sway complexity. The authors concluded that the complexity of postural control for children with ASD was partially compromised. Reduced mediolateral sway complexity could potentially increase the risks of fall.
Yumeng Li, Rumit S. Kakar, Marika A. Walker, Li Guan, and Kathy J. Simpson
The upper trunk–pelvic coordination patterns used in running are not well understood. The purposes of this study are to (1) test the running speed effect on the upper trunk–pelvis axial rotation coordination and (2) present a step-by-step guide of the relative Fourier phase algorithm, as well as some further issues to consider. A total of 20 healthy young adults were tested under 3 treadmill running speeds using a 3-dimensional motion capture system. The upper trunk and pelvic segmental angles in axial rotation were calculated, and the coordination was quantified using the relative Fourier phase method. Results of multilevel modeling indicated that running speed did not significantly contribute to the changes in coordination in a linear pattern. A qualitative template analysis suggested that participants displayed different change patterns of coordination as running speed increased. Participants did not significantly change the upper trunk and pelvis coordination mode in a linear pattern at higher running speeds, possibly because they employed different motion strategies to achieve higher running speeds and thus displayed large interparticipant variations. For most of our runners, running at a speed deviated from the preferred speed could alter the upper trunk–pelvis coordination. Future studies are still needed to better understand the influence of altered coordination on running performance and injuries.
Jupil Ko, Erik Wikstrom, Yumeng Li, Michelle Weber, and Cathleen N. Brown
Context: The modified Star Excursion Balance Test (mSEBT) and Y-Balance Test (YBT) are common dynamic postural stability assessments for individuals with chronic ankle instability (CAI). However, the reach distance measurement technique and movement strategy used during the mSEBT and YBT differ. To date, no studies have compared task performance differences on these tests in CAI patients. Objective: To determine whether individuals with CAI perform the mSEBT and YBT differently. Design: Cross-sectional. Setting: Biomechanics laboratory. Participants: Of 97 consented participants, 86 (43 females, 43 males; age 21.5 [3.3] y, height 169.8 [10.3] cm, mass 69.5 [13.4] kg), who reported ≤25 on the Cumberland Ankle Instability Tool, ≥11 on the Identification of Functional Ankle Instability, and had a history of a moderate to severe ankle sprain(s) participated. Interventions: Participants were instructed to perform the mSEBT and YBT in a predetermined counterbalanced order. Three anterior, posteromedial, and posterolateral trials of each test were completed on the involved limb after 4 practice trials. Test direction order was randomized for each participant. Main Outcome Measures: Normalized (expressed in percentage) reach distance in each direction. Paired sample t tests were performed to compare each of the 3 directions between the mSEBT and YBT. Results: Significantly shorter reach distances in the anterior (58.9% [5.8%] vs 61.4% [5.4%], P = .001) and the posteromedial (98.8% [8.6%] vs 100.8% [8.1%], P = .003) directions were noted on the mSEBT relative to the YBT. No differences in the posterolateral directions were observed. Conclusions: Within those with CAI, mSEBT and YBT normalized reach distances differ in the anterior and posteriomedial directions. As a result, clinicians and researchers should not directly compare the results of these tests.
Yumeng Li, Jupil Ko, Marika A. Walker, Cathleen N. Brown, and Kathy J. Simpson
The purpose of the present study was to examine the effect of chronic ankle instability (CAI) on lower-extremity joint coordination and stiffness during landing. A total of 21 female participants with CAI and 21 pair-matched healthy controls participated in the study. Lower-extremity joint kinematics were collected using a 7-camera motion capture system, and ground reaction forces were collected using 2 force plates during drop landings. Coupling angles were computed based on the vector coding method to assess joint coordination. Coupling angles were compared between the CAI and control groups using circular Watson–Williams tests. Joint stiffness was compared between the groups using independent t tests. Participants with CAI exhibited strategies involving altered joint coordination including a knee flexion dominant pattern during 30% and 70% of their landing phase and a more in-phase motion pattern between the knee and hip joints during 30% and 40% and 90% and 100% of the landing phase. In addition, increased ankle inversion and knee flexion stiffness were observed in the CAI group. These altered joint coordination and stiffness could be considered as a protective strategy utilized to effectively absorb energy, stabilize the body and ankle, and prevent excessive ankle inversion. However, this strategy could result in greater mechanical demands on the knee joint.
Rumit S. Kakar, Seth Higgins, Joshua M. Tome, Natalie Knight, Zachary Finer, Zachary Doig, and Yumeng Li
The purpose of this study was to investigate normative and age-related differences in trunk and pelvis kinematics and intersegmental coordination during sagittal plane flexion–extension. Trunk and pelvis kinematics were recorded while 76 participants performed a maximal range of motion task in the sagittal plane. Cross-correlation was calculated to determine the phase lag between adjacent segment motion, and coupling angles were calculated using vector coding and classified into one of 4 coordination patterns: in-phase, antiphase, superior, and inferior phase. A 2-way mixed-model multivariate analysis of variance was used to compare lumbar spine and pelvis angular kinematics, phase lags, and cross-correlation coefficients between groups. Young participants exhibited greater trunk range of motion compared with middle-aged participants. The lumbar spine and pelvis were predominantly rotating with minimum phase lag during flexion and extension movement for both age groups, and differences in coordination between the groups were seen during hyperextension and return to upright position. In conclusion, middle-aged adults displayed lower range of motion but maintained similar movement patterns to young adults, which could be attributed to protective mechanisms. Healthy lumbar and pelvis movement patterns are important to understand and need to be quantified as a baseline, which can be used to develop rehabilitation protocols for individuals with spinal ailments.
Yumeng Li, Rumit S. Kakar, Marika A. Walker, Yang-Chieh Fu, Timothy S. Oswald, Cathleen N. Brown, and Kathy J. Simpson
The purpose of the study was to determine if the intratrunk coordination of axial rotation exhibited by individuals with spinal fusion for adolescent idiopathic scoliosis (SF-AIS) during running varies from healthy individuals and how the coordination differs among adjacent trunk-segment pairs. Axial rotations of trunk segments (upper, middle, lower trunk) and pelvis were collected for 11 SF-AIS participants and 11 matched controls during running. Cross-correlation determined the phase lag between the adjacent segment motions. The coupling angle was generated using the vector coding method and classified into 1 of the 4 major, modified coordination patterns: in-phase, anti-phase, superior, and inferior phase. Two-way, mixed-model ANCOVA was employed to test phase lag, cross-correlation r, and time spent in each major coordination pattern. A significantly lower phase lag for SF-AIS was observed compared with controls. Qualitatively, there was a tendency that SF-AIS participants spent less time in anti-phase for middle-lower trunk and lower trunk-pelvis coordinations compared to controls. Phase lag and anti-phase time was significantly increased from cephalic to caudal segment pairs, regardless of group. In conclusion, SF-AIS participants and controls displayed similar patterns of intra-trunk coordination; however, the spinal fusion hindered decoupling of intra-trunk motions particularly between the lower trunk-pelvic motion.