Gait deviations of patients with ruptured anterior cruciate ligament: a cross-sectional gait analysis study on male patients

Park, Jay Hoon; Choi, Mihye; Lee, Joon‐Hee; Han, Hyuk-Soo; Lee, Myung Chul; Ro, Du Hyun

doi:10.1186/s43019-021-00128-w

Cited by 7 publications

(4 citation statements)

References 27 publications

(72 reference statements)

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“…We tested our hypothesis (H2) that the association of CS profiles with muscle fiber lengths and CCSAs would remain consistently strong over a range of walking conditions and participant characteristics using both shank and thigh sleeve data from participants spanning 19 to 76 years of age (Figure 2). Each unimpaired participant performed a baseline walking gait, as well as a mock impaired-walking gait, where they were directed to keep their nondominant knee straight during the entire walking trial, in a similar fashion to a commonly occurring post-surgical stiff-knee gait [34,35] . When the data were analyzed for individual subjects and the results sectioned into groups by body segment, walking gait, and participant age, the CS profiles remained strongly correlated with the CCSAs (all group median adjusted r 2 's ≥ 0.88; all correlation p-values < 0.0001).…”

Section: Fundamental Insight: What Is Capacitive Sensing Measuring?mentioning

confidence: 99%

“…In addition to monitoring changes due to therapeutic gait modifications, CS may also enable monitoring of post-surgical recovery. For example, stiff-knee gait, occurring after knee surgery, can increase the risk of either degenerative diseases [34] or revision surgeries [35] . We found that binary classifiers aimed at distinguishing stiff-knee gait from normal gait were more accurate when using CS or EMG data (F1 = 0.94 for both) than when using IMU data (F1 = 0.81) in both unimpaired individuals and a patient recovering from total knee arthroplasty (TKA) surgery (grouped with the stiff-knee gait trials for this analysis) (Figure 3b).…”

Section: Capacitive Sensing In Clinical Applicationsmentioning

confidence: 99%

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Capacitive Sensing for Natural Environment Biomechanics Monitoring

Pearl,

Rokhmanova,

Dankovich

et al. 2024

Preprint

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Inexpensive wearable sensors could transform how we monitor patient movement outside of the laboratory and help personalize the treatment of mobility impairments[1]. To meet these expectations, wearable sensors must be benchmarked against clinical standards, provide reliable data over extended periods of time, be robust to placement errors by non-experts, and offer tangible translational potential. Inertial sensing is one of the only wearable technologies that have been comprehensively characterized and benchmarked against gold-standard biomechanical measurements, but it remains sensitive to both drift and placement error[2–4] and does not capture muscle activity, which is relevant to both mobility impairments and the development of assistive wearables. Here we investigate capacitive sensing[5] as a muscle-activity monitoring technology, finding for the first time that it can accurately track changes in muscle bulging and fiber length with the fidelity of laboratory tools, in natural environments, over long durations, on multiple body parts, and across people of varying compositions. We also demonstrate translational potential in two clinical applications and show that capacitive sensing complements inertial sensing better than electromyography in multimodal wearable-sensing systems, achieving state-of-the-art accuracy for wearable motion tracking. Our results indicate that capacitive sensing wearables could be used synergistically with other emerging wearable technologies to provide real-time feedback and make rehabilitation monitoring outside of laboratory environments more feasible[6]. We expect this foundational study of capacitive sensing for natural environment biomechanics monitoring—combining wearable sensor design, human experiments, biomechanical modeling, multimodal data fusion, magnetic resonance imaging, and clinical research—to be applicable to a wide range of mobility-related pathologies and emerging human-in-the-loop assistive devices[7–9].

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Section: Fundamental Insight: What Is Capacitive Sensing Measuring?mentioning

confidence: 99%

Section: Capacitive Sensing In Clinical Applicationsmentioning

confidence: 99%

Capacitive Sensing for Natural Environment Biomechanics Monitoring

Pearl,

Rokhmanova,

Dankovich

et al. 2024

Preprint

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“…On the shank, we demonstrated that CS can successfully monitor adherence to therapeutic gait retraining. On the thigh, it may be valuable to measure quadriceps avoidance after surgery or muscle co-contractions that increase joint loads and the risk of degenerative diseases [32] . To confirm that CS can be adapted to other parts of the leg, we fabricated a preliminary CS sleeve for the thigh and tested whether the resulting CS profile for a single subject performing baseline walking correlated with the change in crosssectional area of the muscles on the thigh (Figure 5).…”

Section: Mainmentioning

confidence: 99%

Capacitive Sensing for Natural Environment Rehabilitation Monitoring

Halilaj

Pearl

Rokhmanova

et al. 2022

Preprint

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Inexpensive wearable sensors are expected to transform both research and clinical practice by monitoring patient movement outside of the laboratory and helping personalize the treatment of mobility impairments [1]. To meet these expectations, wearable sensors need to be benchmarked against clinical standards, be robust to placement errors by non-experts, and provide reliable data over long periods of time. Inertial sensing remains the only wearable technology that has been comprehensively characterized and benchmarked against gold-standard biomechanical measurements, but it is sensitive to both drift and placement error [2] and does not provide estimations of muscle activity, which are relevant to numerous mobility impairments. Here we characterize capacitive touch sensing [3] as a gait rehabilitation monitoring technology for the first time, finding that it captures clinically relevant biomechanical measures with the fidelity of laboratory tools. We also show that a circumferential lower-limb capacitive sensing sleeve is more effective than electromyography and musculoskeletal simulations at detecting therapeutically relevant gait modifications used to prevent osteoarthritis progression. Finally, we show that our capacitive sensing approach is robust to placement errors and measurement drift over a 6-hour trial, both of which are insignificant to tracking adherence to therapeutic gait prescriptions. Our results indicate that capacitive sensing wearables could make rehabilitation monitoring outside laboratory environments more feasible and could be used synergistically with other emerging wearable technologies to provide real-time feedback to patients during daily life [4]. We expect this foundational study of capacitive sensing for rehabilitation monitoring to be translatable to other parts of the body and applicable to a wide range of mobility-related pathologies and emerging human-in-the-loop wearable health technologies [5–7].

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“…Anterior cruciate ligament (ACL) injury may result in functional instability, and ACL reconstruction (ACLR) is recommended for patients with such instability. 1 2) After ACL injury, the main goal of reconstruction is to restore performance to pre-injury levels, and many surgeons regard return to sports as an indicator of successful surgery. 3 4 5 6) However, many patients who have undergone ACLR do not recover to pre-injury levels due to decreased knee function.…”

mentioning

confidence: 99%

Does a Lower Limb Balance Test after Anterior Cruciate Ligament Reconstruction Have a Significant Correlation with Postoperative Clinical Score, Stability, and Functional Performance Test?

et al. 2023

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Background Lower limb balance ability is reduced after anterior cruciate ligament reconstruction (ACLR). However, the recovery of balance based on functional test scores after ACLR is not known because the correlation between balance and clinical scores remains unclear. We aimed to analyze the correlation between lower limb balance assessed by functional test and clinical knee test scores after ACLR. Methods We evaluated lower limb balance using the anterior-posterior stability index (APSI) of the Biodex Balance System (BBS). Patients underwent clinical tests to evaluate the knee, including the Tegner activity score, International Knee Documentation Committee (IKDC) subjective score, Lysholm score, and KT-2000 arthrometer measurement, hamstring per quadriceps muscle strength ratio at 60°/sec (HQ ratio), and functional performance tests (single-leg hop and single-leg vertical jump tests) 1 year after ACLR. We used a paired t -test to compare continuous preoperative and postoperative variables and Pearson’s correlation coefficient to determine the relationship between BBS-APSI and clinical scores. Results Forty-eight patients (35 men and 13 women; mean age, 28.9 ± 8.3 years) were included. The follow-up period and BBS-APSI were 12.4 ± 2.0 months and 0.9 ± 0.4, respectively. Tegner activity score, IKDC subjective score, Lysholm score, and KT-2000 arthrometer measurement improved significantly postoperatively ( p < 0.001). BBS-APSI was correlated with the Tegner activity score ( r = –0.335, p = 0.020), IKDC subjective score ( r = –0.301, p = 0.037), Lysholm score ( r = –0.323, p = 0.025), single-leg hop test results ( r = –0.300, p = 0.038), and single-leg vertical jump test results ( r = –0.336, p = 0.019). There was no correlation between KT-2000 arthrometer measurement and HQ ratio. Conclusions BBS-APSI was correlated with functional performance test scores after ACLR, rendering the BBS-APSI as a useful assessment tool to evaluate postoperative functional recovery. Continuously improving balance after ACLR could be useful for functional recovery after surgery.

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Gait deviations of patients with ruptured anterior cruciate ligament: a cross-sectional gait analysis study on male patients

Cited by 7 publications

References 27 publications

Capacitive Sensing for Natural Environment Biomechanics Monitoring

Capacitive Sensing for Natural Environment Biomechanics Monitoring

Capacitive Sensing for Natural Environment Rehabilitation Monitoring

Does a Lower Limb Balance Test after Anterior Cruciate Ligament Reconstruction Have a Significant Correlation with Postoperative Clinical Score, Stability, and Functional Performance Test?

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