Role of kicking action in front crawl: the inter-relationships between swimming velocity, hand propulsive force and trunk inclination.

This study aimed to investigate the essential role of the kicking action in front crawl. To achieve this objective, we examined the relationships of the hand propulsive force and trunk inclination with swimming velocity over a wide range of velocities from 0.75 m·s-1 to maximum effort, including the experimental conditions of arm stroke without a pull buoy. Seven male swimmers performed a 25 m front crawl at various speeds under three swimming conditions: arm stroke with a pull buoy, arm stroke without a pull buoy (AWOB) and arm stroke with a six-beat kick (SWIM). Swimming velocity, hand propulsive force and trunk inclination were calculated using an underwater motion-capture system and pressure sensors. Most notably, AWOB consistently exhibited greater values than SWIM for hand propulsive force across the range of observed velocities (p < 0.05) and for trunk inclination below the severe velocity (p < 0.05), and these differences increased with decreasing velocity. These results indicate that 1) the kicking action in front crawl has a positive effect on reducing the pressure drag acting on the trunk, thereby allowing swimmers to achieve a given velocity with less hand propulsive force, and 2) this phenomenon is significant in low-velocity ranges.

Pattern Matching for Real-Time Extraction of Fast and Slow Spectral Components From sEMG Signals.

Previous studies have demonstrated the potential of surface electromyography (sEMG) spectral decomposition in evaluating muscle performance, motor learning, and early diagnosis of muscle conditions. However, decomposition techniques require large data sets and are computationally demanding, making their implementation in real-life scenarios challenging. Based on the hypothesis that spectral components will present low inter-subject variability, the present paper proposes the foundational principles for developing a real-time system for their extraction by utilizing a pre-defined library of components derived from an extensive data set to match new measurements. The model library was tailored to fulfill specific requirements for real-time system application and the challenges encountered during implementation are discussed in the paper. For system validation, four distinct data sets comprising isotonic and isometric muscle activations were utilized. The extracted during validation showed low inter-subject variability, suggesting that a wide range of physiological variations can be described with them. The adoption of the proposed system for muscle analysis could provide a deeper understanding of the underlying mechanisms governing different motor conditions and neuromuscular disorders, as it allows for the measurement of these components in various daily-life scenarios.

Mediation of the mediolateral ground reaction force profile to maintain straight running among unilateral transfemoral amputees.

The mediolateral ground reaction force (M-L GRF) profile that realizes a symmetrical mediolateral ground reaction impulse (M-L GRI) between both limbs is essential for maintaining a straight movement path. We aimed to examine the M-L GRF production across different running speeds in unilateral transfemoral amputees (TFA) to identify strategies for maintaining straight running. The average medial and lateral GRF, contact time (tc), M-L GRI, step width, and center of pressure angle (COPANG) were analyzed. Nine TFAs performed running trials at 100% speed on an instrumented treadmill. Trials were set at 30-80% speed with an increment of 10%. Seven steps from the unaffected and affected limbs were analyzed. Overall, the unaffected limbs exhibited a higher average medial GRF than the affected limbs. The M-L GRI were similar between both limbs at all speeds, implying that the participants were able to maintain a straight running path. The affected limb exhibited a longer tc and a lower M-L GRF profile than the unaffected limb. The results showed that unilateral TFAs adopted limb-specific strategies to maintain a straight running path, and that these limb-specific strategies were consistent across different running speeds.

Determination of subset models for predicting vertical centre of mass position during front crawl in male swimmers.

We attempted to find a subset model that would allow robust prediction of a swimmer's vertical body position during front crawl with fewer markers, which can reduce extra drag and time-consuming measurements. Thirteen male swimmers performed a 15-metre front crawl either with three different lung-volume levels or various speeds, or both, without taking a breath with 36 reflective markers. The vertical positions of the centre of mass (CoM) and four representative landmarks in the trunk segment over a stroke cycle were calculated using an underwater motion-capture system. We obtained 212 stroke cycles across trials and analysed the vertical position derived from 15 patterns as candidates for the subset models. Unconstrained optimisation minimises the root-mean-square error between the vertical CoM position and each subset model. The performance evaluated from the intra-class correlation coefficient (ICC) and weight parameters of each subset model were detected from the mean values across five-fold cross-validation. The subset model with four markers attached to the trunk segment showed good reliability (ICC: 0.776 ± 0.019). This result indicates that the subset model with few markers can robustly predict a male swimmer's vertical CoM position during front crawl under a wide range of speeds from 0.66 to 1.66 m · s-1.

Projected frontal area and its components during front crawl depend on lung volume.

We examined the influence of lung volume on the vertical body position, trunk inclination, and projected frontal area (PFA) during swimming and the inter-relationships among these factors. Twelve highly trained male swimmers performed a 15 m front crawl with sustained maximal inspiration (INSP), maximal expiration (EXP), and intermediate (MID) at a target velocity of 1.20 m·s-1 . Using our developed digital human model, which allows inverse kinematics calculations by fitting individual body shapes measured with a three-dimensional photonic image scanner to individually measured underwater motion capture data, vertical center of mass (CoM) position, trunk inclination, and PFA were calculated for each complete stroke cycle. In particular, the PFA was calculated by automatic processing of a series of parallel frontal images obtained from a reconstructed digital human model. The vertical CoM position was higher with a larger lung-volume level (p < 0.01). The trunk inclination was smaller in INSP and MID than in EXP (p < 0.01). PFA was smaller with a larger lung-volume level (p < 0.01). Additionally, there was a significant interaction of vertical CoM position and trunk inclination with PFA (p = 0.006). There was a negative association between PFA and vertical CoM position, and a positive association between PFA and trunk inclination less than the moderate vertical CoM position (each p < 0.05). These results obtained using our methodology indicate that PFA decreases with increasing lung volume due to an increase in vertical CoM position, and additionally due to a decrease in trunk inclination at low-to-moderate lung-volume levels.

Vertical body position during front crawl increases linearly with swimming velocity and the rate of its increase depends on individual swimmers.

Vertical body position during swimming is assumed to closely affect drag. It is consequently associated with swimming velocity; however, the association between swimming velocity and vertical body position has not yet been sufficiently established. Here, we aimed to clarify how vertical body position increases with front crawl velocity and whether there are inter-individual differences in velocity effect. Eleven college-level male swimmers performed a 15 m front crawl with sustained forced maximal inspiration at various swimming velocities. The body's centre of mass (CoM) was estimated from individual digital human models with inertial parameters using inverse kinematics. The horizontal CoM velocity and vertical CoM position from the water surface were averaged for one stroke cycle as respective indexes of swimming velocity and vertical body position. Linear mixed-effects model analysis revealed that there is a positive trend between swimming velocity and vertical CoM position during front crawl across the participants. These results indicate that swimming velocity is associated with vertical body position during front crawl. Additionally, the linear mixed-effects model with random intercepts and slopes was a better fit than that with only random intercepts, indicating that there are inter-individual differences in the rate of increase in vertical body position against swimming velocity.

Muscle Activity Estimation at Drop Vertical Jump Landing Using Passive Muscle Mechanical Model.

Among the various elements that facilitate the movement of the lower limbs, the anterior cruciate ligament (ACL) is prone to injury. An adequate joint control of the lower limb can prevent ACL injury. Balancing activities between the agonist and the antagonist muscles is vital for joint control. However, prior studies on muscle activities were limited since they could not determine passive muscle activities. In this study, we develop a muscle model considering the passive properties to analyze the movement mechanism of the ACL under heavy loads, such as those produced during jump landing. We estimated the muscle activities occurring during a drop vertical jump (DVJ) by applying to the proposed method the physiological constraint that muscle activities are constant during a short time around landing. In addition, the knee joint torque and muscle forces were calculated from the estimated muscle activities, which were thereafter compared with those obtained using the conventional method. The results revealed that this passive muscle model appropriately represented the knee joint torque at DVJ landing by decreasing the passive muscle strain and increasing the isometric maximum muscle force. Moreover, the estimated muscle activities were larger than those obtained using the conventional method, which may be caused by the co-contraction between agonist and antagonist muscles that cannot be represented by the conventional method. This muscle co-contraction estimation algorithm would estimate the muscle load under heavy loads, and applying this knowledge to training would help to prevent ACL injuries.

DATSURYOKU Sensor-A Capacitive-Sensor-Based Belt for Predicting Muscle Tension: Preliminary Results.

Excessive muscle tension is implicitly caused by inactivity or tension in daily activities, and it results in increased joint stiffness and vibration, and thus, poor performance, failure, and injury in sports. Therefore, the routine measurement of muscle tension is important. However, a co-contraction observed in excessive muscle tension cannot be easily detected because it does not appear in motion owing to the counteracting muscle tension, and it cannot be measured by conventional motion capture systems. Therefore, we focused on the physiological characteristics of muscle, that is, the increase in muscle belly cross-sectional area during activity and softening during relaxation. Furthermore, we measured muscle tension, especially co-contraction and relaxation, using a DATSURYOKU sensor, which measures the circumference of the applied part. The experiments showed high interclass correlation between muscle activities and circumference across maximal voluntary co-contractions of the thigh muscles and squats. Moreover, the circumference sensor can measure passive muscle deformation that does not appear in muscle activities. Therefore, the DATSURYOKU sensor showed the potential to routinely measure muscle tension and relaxation, thus avoiding the risk of failure and injury owing to excessive muscle tension and can contribute to the realization of preemptive medicine by measuring daily changes.

Lower lung-volume level induces lower vertical center of mass position and alters swimming kinematics during front-crawl swimming.

We examined the impact of lung-volume levels on the vertical center of mass (CoM) position and kinematics during submaximal front-crawl swimming at constant velocity. Thirteen well-trained male swimmers (21.2 ± 2.0 years) swam the front-crawl for 15 m at a target velocity of 1.20 m s-1 while holding one of three lung-volume levels: maximal inspiration (MAX), maximal expiration (MIN), and intermediate between these (MID). The three-dimensional positions of 25 reflective markers attached to each participant's body were recorded using an underwater motion capture system and then used to estimate the body's CoM. The swimming velocity and the vertical CoM position relative to the water's surface were calculated and averaged for one stroke cycle. Stroke rate, stroke length, kick rate, kick amplitude, kick velocity, and trunk inclination were also calculated for one stroke cycle. Swimming velocity was statistically comparable among the three different lung-volume levels (ICC [2,3] = 0.875). The vertical CoM position was significantly decreased with the lower lung-volume level (MAX: -0.152 ± 0.009 m, MID: -0.163 ± 0.009 m, MIN: -0.199 ± 0.007 m, P < 0.001). Stroke rate, kick rate, kick amplitude, kick velocity, and trunk inclination were significantly higher in MIN than in MAX and MID, whereas the stroke length was significantly lower (all P < 0.05). These results indicate that a lower lung-volume level during submaximal front-crawl swimming induces a lower vertical CoM position that is accompanied by a modulation of the swimming kinematics to overcome the increased drag arising from a larger projected frontal area.

Factors associated with a risk of prosthetic knee buckling during walking in unilateral transfemoral amputees.

BACKGROUND: Walking and mobility are essential for a satisfactory quality of life. However, individuals with transfemoral amputations have difficulties in preventing falls due to prosthetic knee buckling, defined as the sudden loss of postural support during weight-bearing activities. The risk of prosthetic knee buckling can be evaluated by determining the prosthetic knee angular impulse (PKAI) during the early stance phase. However, little is known about the factors associated with PKAI in individuals with unilateral transfemoral amputations. RESEARCH QUESTION: What are the demographic factors that can be associated with the risk of prosthetic knee buckling, quantified by PKAI, during walking in individuals with unilateral transfemoral amputations? METHODS: Thirteen individuals with unilateral transfemoral amputations were instructed to perform level walking at a comfortable, self-selected speed on a straight, 10-m walkway. PKAI was calculated as the time integral of the prosthetic knee external flexion-extension moment during the initial 40 % of the prosthetic gait cycle. We used Pearson's correlation coefficients to examine the relationship of PKAI with the following variables: the subject's body height, body mass, and age; the time since amputation; and the current prosthesis use history. Furthermore, an independentt-test was used to compare PKAI according to the sex (male vs. female) and etiology (trauma vs. nontrauma). RESULTS: PKAI exhibited a significant negative linear relationship with the subject's body height and body mass. However, it showed no significant correlation with age, the time since amputation, and the current prosthesis use history. It was also significantly greater in women than in men and was not significantly influenced by the etiology. SIGNIFICANCE: Awareness about demographic factors associated with PKAI during walking can contribute to fall assessments in gait rehabilitation programs for individuals with unilateral transfemoral amputations.

Bicycle exercise training improves ambulation in patients with peripheral artery disease.

OBJECTIVE: Exercise training has multiple beneficial effects in patients with arteriosclerotic diseases; however, the exact underlying mechanisms of the effects are not completely understood. This study aimed to evaluate the effectiveness of a supervised exercise program in improving gait parameters, including the variability and walking performance of lower limb movements, in patients with peripheral artery disease (PAD) and intermittent claudication (IC). METHODS: Sixteen patients with a history of PAD and IC were recruited for this study, and they completed a 3-month supervised bicycle exercise program. The ankle-brachial index and responses to quality of life (QOL) questionnaires were evaluated. Near-infrared spectroscopy was also performed to determine the hemoglobin oxygen saturation in the calf. Patients' kinematics and dynamics, including joint range of motion and muscle tension, were evaluated using an optical motion capture system. Computed tomography images of each muscle were assessed by manual outlining. Data were collected before and after the supervised bicycle exercise program, and differences were analyzed. RESULTS: Significant differences were not found in step length, ankle-brachial index, and hemoglobin oxygen saturation before and after the supervised bicycle exercise program; however, IC distance (P = .034), maximum walking distance (P = .006), and all QOL questionnaire scores (P < .001) showed significant improvement. Hip range of motion (P = .035), maximum hip joint torque (right, P = .031; left, P = .044), maximum tension of the gluteus maximus muscle (right, P = .044; left, P = .042), and maximum hip joint work (right, P = .048; left, P = .043) also significantly decreased bilaterally. Computed tomography images showed a significant increase in the cross-sectional area of the abdominal, trunk, and thigh muscles but not in that of the lower leg muscles after the supervised exercise program intervention. CONCLUSIONS: In this study, bicycle exercise training improved the QOL and walking distance and decreased hip movement. The results showed that bicycling might be as useful as walking in patients with PAD.

Robustness analysis of decoding SSVEPs in humans with head movements using a moving visual flicker.

OBJECTIVE: The emergence of mobile electroencephalogram (EEG) platforms have expanded the use cases of brain-computer interfaces (BCIs) from laboratory-oriented experiments to our daily life. In challenging situations where humans' natural behaviors such as head movements are unrestrained, various artifacts could deteriorate the performance of BCI applications. This paper explored the effect of muscular artifacts generated by participants' head movements on the signal characteristics and classification performance of steady-state visual evoked potentials (SSVEPs). APPROACH: A moving visual flicker was employed to induce not only SSVEPs but also horizontal and vertical head movements at controlled speeds, leading to acquiring EEG signals with intensity-manipulated muscular artifacts. To properly induce neck muscular activities, a laser light was attached to participants' heads to give visual feedback; the laser light indicates the direction of the head independently from eye movements. The visual stimulus was also modulated by four distinct frequencies (10, 11, 12, and 13 Hz). The amplitude and signal-to-noise ratio (SNR) were estimated to quantify the effects of head movements on the signal characteristics of the elicited SSVEPs. The frequency identification accuracy was also estimated by using well-established decoding algorithms including calibration-free and fully-calibrated approaches. MAIN RESULTS: The amplitude and SNR of SSVEPs tended to deteriorate when the participants moved their heads, and this tendency was significantly stronger in the vertical head movements than in the horizontal movements. The frequency identification accuracy also deteriorated in proportion to the speed of head movements. Importantly, the accuracy was significantly higher than its chance-level regardless of the level of artifact contamination and algorithms. SIGNIFICANCE: The results suggested the feasibility of decoding SSVEPs in humans freely moving their head directions, facilitating the real-world applications of mobile BCIs.

Joint moments during sprinting in unilateral transfemoral amputees wearing running-specific prostheses.

Knowledge of joint moments will provide greater insight into the manner in which lower-extremity amputees wearing running-specific prostheses regain running capacity and compensate for replacement of an active leg with a passive prosthetic implement. Thus, the purpose of this study was to investigate three-dimensional joint moments during sprinting for unilateral transfemoral amputees wearing running-specific prostheses. Ten sprinters with unilateral transfemoral amputation performed maximal sprinting at the 22 m mark while wearing running-specific prostheses. Joint moments were calculated through an inverse dynamics approach. All peak flexion and extension moments in the prosthetic leg were found to be lower than those of the intact leg, except for the peak plantar flexion moment. In the frontal plane, the peak adduction and abduction moments in the prosthetic leg were generally lower than those of the intact leg. The peak internal rotation moments differed significantly between the legs, but the peak external rotation moments did not. The results of the present study suggest that asymmetric joint moment adaptations occur for unilateral transfemoral amputees to compensate for replacement of the biological leg with a passive prosthetic knee joint and running-specific prosthesis.

Semi-simulation Experiments for Quantifying the Performance of SSVEP-based BCI after Reducing Artifacts from Trapezius Muscles.

Muscular artifacts often contaminate electroencephalograms (EEGs) and deteriorate the performance of brain-computer interfaces (BCIs). Although many artifact reduction techniques are available, most of the studies have focused on their reduction ability (i.e. reconstruction errors), and it has been missing to evaluate their effect on the performance of BCIs. This study aims at evaluating the performance of a state-of-the-art muscular artifact reduction technique on a scenario of a steady-state visual evoked potentials (SSVEPs)based BCI. The performance was evaluated based on a semisimulation setting using a benchmark dataset of SSVEPs artificially contaminated by muscular artifacts acquired from the trapezius. Our results showed that combining the artifact reduction method and the classification algorithm based on the task-related component analysis gained improved classification accuracy. Interestingly, the artifact reduction setting minimizing the reconstruction errors, i.e. elaborately recovering the true EEG waveforms, was inconsistent to the one maximizing the classification performance. The results suggest that artifact reduction methods should be tuned so as to tomaximize performance of BCIs.

Impedance Model of the Interaction Between Environment and Human Body and Its Modification Design.

This paper presents a model of environment-human body interaction, which is critical for us to perform balanced motions such as locomotion and activities of daily living while standing. Specifically, movement smoothness and stiffness are quantitatively represented by an impedance between environment and body (ENV-BODY impedance) based on the concept of mechanical impedance, which is commonly used in robotics. The ENV-BODY impedance model considers a spring and a damper to represent the behavior of the center of pressure with respect to the ground reaction force. The model parameters are obtained from experimentally measured motion data. In addition, real-time feedback is applied for intervening the ENV-BODY impedance model by either attenuating (in-phase mode) or amplifying (anti-phase mode) the displacement of the center of pressure. Experimental results show that the proposed ENV-BODY impedance model suitably reflects the relationship between ground reaction force and center of pressure during static standing, and reconstructs the center-of-pressure acceleration with average error of 4.1E-0l mm/s2 Furthermore, the stiffness is smaller at the in-phase than at the anti-phase mode, thus being consistent with the expected mechanical stability. This model could be applied to training programs for evaluating movement smoothness and roughness using real-time motion measurement/analysis and environment control technology.

Systematic Study of Photoluminescence Enhancement in Monolayer Molybdenum Disulfide by Acid Treatment.

Monolayer molybdenum disulfide (MoS2) is an atomically thin semiconducting material with a direct band gap. This physical property is attributable to atomically thin optical devices such as sensors, light-emitting devices, and photovoltaic cells. Recently, a near-unity photoluminescence (PL) quantum yield of a monolayer MoS2 was demonstrated via a treatment with a molecular acid, bis(trifluoromethane)sulfonimide (TFSI); however, the mechanism still remains a mystery. Here, we work on PL enhancement of monolayer MoS2 by treatment of Brønsted acids (TFSI and sulfuric acid (H2SO4)) to identify the importance of the protonated environment. In TFSI as an acid, different solvents-1,2-dichloroethane (DCE), acetonitrile, and water-were studied, as they show quite different acidity in solution. All of the solvents showed PL enhancement, and the highest was observed in DCE. This behavior in DCE would be due to the higher acidity than others have. Acids from different anions can also be studied in water as a common solvent. Both TFSI and H2SO4 showed similar PL enhancement (∼4-8 enhancement) at the same proton concentration, indicating that the proton is a key factor to enhance the PL intensity. Finally, we considered another cation, Li+ from Li2SO4, instead of H2SO4, in water. Although Li and H atoms showed similar binding energy on MoS2 from theoretical calculations, Li2SO4 treatment showed little PL enhancement; only coexisting H2SO4 reproduced the enhancement. This study demonstrated the importance of a protonated environment to increase the PL intensity of monolayer MoS2. The study will lead to a solution to achieve high optical quality and to implementation for atomically thin optical devices.

Evaluation of the Translation Distance of the Glenohumeral Joint and the Function of the Rotator Cuff on Its Translation: A Cadaveric Study.

PURPOSE: To evaluate the distance and position of humeral head translation during glenohumeral motion and to investigate the function of the rotator cuff in glenohumeral translation. METHODS: Using 9 cadavers, glenohumeral translation during passive pendulum motion was tracked by an optical motion capture system. Tension was applied to 5 compartments of the rotator cuff muscles, and 7 different conditions of rotator cuff dysfunction were sequentially simulated. Three-dimensional glenohumeral structure was reconstructed from the computed tomography images of the specimens, and the distance and position of glenohumeral translation were compared among the conditions. RESULTS: The average radius of glenohumeral translation was 10.6 ± 4.3 mm when static loading was applied to all rotator cuff muscles. The radius increased significantly in the models without traction force on the supraspinatus and total subscapularis tendons (P = .030). The position of the translation center did not change in the mediolateral direction (P = .587) and in the anteroposterior direction (P = .138), but it moved significantly superiorly in the models without supraspinatus and infraspinatus loading (P = .011) and in those without supraspinatus, infraspinatus, and teres minor loading (P < .001). CONCLUSIONS: The distance and position of humeral head translation during glenohumeral motion changed with rotator cuff deficiency. The present study indicated that the subscapularis plays an important role in maintaining the central position of the humeral head, and that the infraspinatus acts as a major depressor of the humeral head during shoulder motion. CLINICAL RELEVANCE: The results of this study suggest that extension of a tear into the subscapularis should be avoided to maintain the centering function of the glenohumeral joint in cases with rotator cuff tear.

Modeling and analysis of individual with lower extremity amputation locomotion using prosthetic feet and running-specific prostheses.

Prostheses have enabled individuals with lower extremity amputation (ILEAs) to accomplish many daily activities. Prosthetic feet allow ILEA to locomote and improves their quality of life. Carbon-fiber running-specific prostheses (RSPs) with energy storing capabilities support ILEAs to perform sprinting by partly providing spring-like properties in their amputated legs. Previous studies declare the spring-like RSP behavior and stiffness regulation during ILEA sprinting using RSP, though little is known about the behavior of the whole system that is a complex combination of human body and prostheses. This paper models this combined system with human and prosthetic foot and RSP using the digital human technology, then, analyzes the ILEA walking using the prosthetic foot and sprinting using RSP. We develop models that are combinations of human and prostheses by individualizing a linkage structure and inertial parameters of the digital human model. Then, locomotion of ILEA is analyzed based on measurements with optical motion capture system and force plates, and kinematics and dynamics computation. This modeling and computational technique can be applied to the locomotion of ILEA as well as a human motion using tools, and expanded to an analysis and improvement of system involving human.

Exploring optimal myoelectric feature indices for forearm control strategy using robust principal component analysis.

Forearm movements realize various functions needed in daily life. For reproduction of the motion sequences, active myoelectric devices have been developed. Usually, feature indices are extracted from observed signals in control strategy; however, the optimal combination of indices is still unclear. This paper introduces sparsity-inducing penalty term in principal component analysis (PCA) to explore optimal myoelectric feature indices. An electromyographic database including seven forearm movements from 30 subjects was used for performance comparison. Linear classifier with sparse features showed best performance (7.86±3.82% error rate) that was significantly better than linear classifier with all features because of recovering low rank matrix in original data. Furthermore, the sparse features had a large contribution of underlying data structure with less number of principal components than PCA. Root-mean-square, time-domain features, autoregressive coefficients, and Histogram purported to be important in projected feature space; therefore, the feature indices are important to myoelectric strategies.

Training Shoes do not Decrease the Negative Work of the Lower Extremity Joints.

Different types of running shoes may have different influence on the negative work of each lower extremity joint. Clarifying this influence can reduce the potential risk of muscle injury. The present study examined the difference in the negative work and associated kinetic and kinematic parameters of the lower extremity joints between training shoes and racing flats during the contact phase of running. Participants were asked to run on a runway at a speed of 3.0 m·s-1 for both training shoes and racing flats. The negative work and associated kinetic and kinematic parameters of each lower extremity joint were calculated. No difference was found in the negative work of the hip and ankle joints between the two types of running shoes. Meanwhile, the negative work of the knee joint was significantly greater for training shoes than for racing flats. This aspect was related to a longer duration of the negative power of the knee joint with the invariant amplitude of the negative power, moment, and angular velocity. These results suggest a higher potential risk of muscle injury around the knee joint for training shoes than for racing flats.