Knee Joint Contact Forces during High-Risk Dynamic Tasks: 90° Change of Direction and Deceleration Movements

Cassiolas, Giorgio; Paolo, Stefano Di; Marchiori, Gregorio; Grassi, Alberto; Villa, F.; Bragonzoni, Laura; Visani, Andrea; Giavaresi, Gianluca; Fini, Milena; Zaffagnini, Stefano; Lopomo, N.

doi:10.3390/bioengineering10020179

Cited by 5 publications

(4 citation statements)

References 59 publications

(87 reference statements)

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“…in the start position) to 4 kN at the maximal squat depth. These values correspond to the range of 0.58 to 4.6 body weights (BW) and, generally are close to data, reported in the literature for squatting [10] and high-risk dynamic tasks [38], and are reasonably higher, than forces, reported for walking/running [15]. The force maximums generally coincided with the sensor readouts, and hence, with plantar pressure maximums.…”

Section: Correlation Between Knee Joint Force and Sock Sensor Datasupporting

confidence: 87%

Estimation of the knee joint load using plantar pressure data measured by smart socks: A feasibility study

Daugulis,

Kataševs,

Okss

2023

THC

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BACKGROUND: Unsupervised sports activities could cause traumas, about 70% of them are those of the low extremities. To avoid traumas, the athlete should be aware of dangerous forces acting within low extremity joints. Research in gait analysis indicated that plantar pressure alteration rate correlates with the gait pace. Thus, the changes in plantar pressure should correlate with the accelerations of extremities, and with the forces, acting in the joints. Smart socks provide a budget solution for the measurement of plantar pressure. OBJECTIVE: To estimate the correlation between the plantar pressure, measured using smart socks, and forces, acting in the joints of the lower extremities. METHODS: The research is case study based. The volunteer performed a set of squats. The arbitrary plantar pressure-related data were obtained using originally developed smart socks with embedded knitted pressure sensors. Simultaneously, the lower extremity motion data were recorded using two inertial measurement units, attached to the tight and the ankle, from which the forces acted in the knee joint were estimated. The simplest possible model of knee joint mechanics was used to estimate force. RESULTS: The estimates of the plantar pressure and knee joint forces demonstrate a strong correlation (r= 0.75, P< 0.001). The established linear regression equation enables the calculation of the knee joint force with an uncertainty of 22% using the plantar pressure estimate. The accuracy of the classification of the joint force as excessive, i.e., being more than 90% of the maximal force, was 82%. CONCLUSION: The results demonstrate the feasibility of the smart socks for the estimation of the forces in the knee joints. Smart socks therefore could be used to develop excessive joint force alert devices, that could replace less convenient inertial sensors.

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Section: Correlation Between Knee Joint Force and Sock Sensor Datasupporting

confidence: 87%

Estimation of the knee joint load using plantar pressure data measured by smart socks: A feasibility study

Daugulis,

Kataševs,

Okss

2023

THC

View full text Add to dashboard Cite

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“…The range of joint contact forces of the hip, knee, and ankle joints predicted by the current study is comparable to previous studies. 12,16,17,22,[35][36][37] Prior simulation studies reported hip joint forces during slow to fast runs to be 7.5-10.0 BW 16 with speed range (0.8 to 3.6 m/sec), compared to our predicted 8.2-11.6 BW. Knee joint forces were reported around 7.8-12.0 BW at 4.36 m/sec 12,22 , while our prediction was 9.7-10.5 BW.…”

Section: Discussioncontrasting

confidence: 53%

Lower limb joint Loading during high-impact activities: implication for bone health

Altai,

Hayford,

Phillips

et al. 2024

Preprint

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Osteoporosis, a significant concern among the elderly, results in low-trauma fractures affecting millions globally. Despite the inclusion of physical activities in strategies to mitigate osteoporosis-related fractures, the optimal exercises for bone health remain uncertain. Determining exercises that enhance bone mass requires an understanding of loading on lower limb joints. This study investigates hip, knee, and ankle joint loading during walking, running, jumping, and hopping exercises, assessing impacts at various intensities (maximal, medium, and minimum efforts). A total of 37 healthy, active participants were recruited, with a mean (SD) age of 40.3 (13.1) years, height of 1.7 (0.08) m, and mass of 68.4 (11.7) kg. Motion capture data were collected for each participant while performing six different exercises: a self-selected level of walking, running, counter-movement jump, squat jump, unilateral hopping, and bilateral hopping. A lower body musculoskeletal model was developed for each participant in OpenSim. The static optimization method was used to calculate muscle forces and hip joint contact forces. The study reveals that running and hopping induce increased joint contact forces compared to walking, with increments of 83% and 21%, respectively, at the hip; 134% and 94%, respectively, at the knee; and 94% and 77%, respectively, at the ankle. Jump exercises exhibit less hip and ankle loading compared to walking, with reductions of 36% and 19%, respectively. Joint loading varies across exercises and intensities, running faster increases forces on all joints, especially the hip. Sprinting raises hip forces but lowers forces on the knee and ankle. Higher jumps intensify forces on the hip, knee, and ankle, whereas hopping faster reduces forces on all joints. The study emphasizes the site-specific impact of exercises on lower limb joint loadings, highlighting the potential of running and hopping for bone formation compared to jumping alone. These findings offer insights for optimizing exercise routines to improve bone health, with potential implications for risk prevention, rehabilitation, and prosthetic development.

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“…50,51 Single studies evaluated the effects of sex, 52 speed, 53 lab versus field, 54 limb differences, 55 cutting on a softball base compared to a flat surface, 56 and the joint contact forces of the medial versus the lateral tibiofemoral joint (table 2). 57 The median number of participants was 24 .…”

Section: Cuttingmentioning

confidence: 99%

Scoping Review of One-Dimension Statistical Parametric Mapping in Lower Limb Biomechanical Analysis

Yona,

Kamel,

Cohen-Eick

et al. 2023

Preprint

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BackgroundBiomechanics is crucial in enhancing sports performance and preventing injury. Traditionally, discrete point analysis is used to analyze important kinetic and kinematic data points, reducing continuous data to a single point. One-dimensional Statistical Parametric Mapping (spm1d) offers a more comprehensive approach by assessing entire movement curves instead of isolated peak values. Nevertheless, spm1d is still underutilized in various sports and sports-related injuries.PurposeTo summarize the existing literature on the application of spm1d in sports biomechanics, including the kinetics and kinematics of the hip, knee, and ankle joints, as well as to identify gaps in the literature that may require further research.MethodsA scoping review was conducted, searching PubMed, Embase, Web of Science, and ProQuest databases. English peer-reviewed studies using SPM to assess lower limb kinetics or kinematics in different sports or sports-related injuries were included. In contrast, reviews, meta-analyses, conference abstracts, grey literature, and studies focusing on non-kinetic or kinematic outcomes were excluded.ResultsThe review yielded 129 papers, with an increased number of studies published in the last three years. Of these studies, 81 examined healthy individuals (63%), and 48 focused on injured populations (37%). Running (n=28), cutting (n=21), and jumping/landing (n=14) were the most common activities. The most prevalent sport-related injuries examined were anterior cruciate ligament rupture (n=21), chronic ankle instability (n=16), and hip-related pain (n=9). Research gaps include the underrepresentation of common sports and movements, small sample size, lack of studies in non-laboratory settings and varied active age groups, and absence of evaluations on the effects of protective sports gear other than shoes.ConclusionThe application of spm1d in sports biomechanics demonstrates diverse uses in sports performance, injury reduction, and rehabilitation. While spm1d shows promise in improving our understanding of sports biomechanics, there are still significant gaps in the literature that present future research opportunities.

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Knee Joint Contact Forces during High-Risk Dynamic Tasks: 90° Change of Direction and Deceleration Movements

Cited by 5 publications

References 59 publications

Estimation of the knee joint load using plantar pressure data measured by smart socks: A feasibility study

Estimation of the knee joint load using plantar pressure data measured by smart socks: A feasibility study

Lower limb joint Loading during high-impact activities: implication for bone health

Scoping Review of One-Dimension Statistical Parametric Mapping in Lower Limb Biomechanical Analysis

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