Ground Reaction Force Data Research Articles

Chronic Pain Influences Lower Extremity Energetics During Landing Cutting in Patients with Chronic Ankle Instability.

Chronic ankle instability (CAI) patients exhibit altered movement patterns during jump landing/cutting movements. Persistent pain is one of the residual symptoms that may affect movements. Calculating joint energetics affected by chronic pain offers a novel method to understand how chronic pain influences energetics of lower extremity joints in CAI patients. To identify the effects of chronic pain on lower extremity energy dissipation and generation during jump landing and cutting in CAI patients. Cross-sectional Study. Laboratory. Fifteen CAI patients with higher pain (6 males, 9 females; age=22.1±2.1year; height=1.74±0.09m; mass=71.3±10.6kg, pain=66.9±9.4), 15 CAI patients with lower pain (6 males, 9 females; age=22.3±2.1year; height=1.74±0.08m; mass=70.1±10.7kg, pain=89.3±2.6), and 15 healthy controls (6 males, 9 females; age=21.3±1.7year; height=1.73±0.08m; mass=70±10.3kg, pain=100±0). Ground reaction force data were collected during 5 trials of maximal jump landing/cutting tasks. Joint power was defined as the product of angular velocity and joint moment. Energy dissipation and generation by the ankle, knee, and hip joints were calculated by integrating regions of the joint power curve. CAI patients with higher pain displayed less ankle energy dissipation (p=.013 and p=.018) and generation in the ankle (p=.002 and p=.028) than CAI patients with lower pain and healthy controls during the jump landing/cutting phase. CAI patients with higher pain showed more hip energy generation than CAI patients with lower pain (P=.038) and healthy controls (P=.013) during the cutting phase. CAI patients with higher pain changed both energy dissipation and generation in the lower extremities, reducing the burden of the ankle joint during jump landing/cutting and having a hip dominant compensatory strategy during the cutting phase. Our results suggest that chronic pain could be one of the factors that affect motor strategies in the CAI population.

Decreased proprioception is associated with inferior postural control during unplanned landing in individuals with chronic ankle instability

ABSTRACT Poor postural control during jump landing may increase ankle sprain incidences among people with chronic ankle instability (CAI). The effects of anticipation on it and its relationship with proprioception need further examination. Fifteen participants with CAI and 15 healthy controls were recruited to perform single-leg jump landings when knowing the landing side before (planned) or after (unplanned) take-off respectively, along with a step-down proprioception test differentiating four inclination platforms (inverted 12°, 14°, 16° and 18°). Ground reaction force data (peak force, loading rate and time of stabilisation) during landings and proprioception scores were collected and analysed. The CAI group exhibited a higher loading rate (59.6 ± 7.6 vs 49.4 ± 6.7 N/kg*seconds, p = 0.011) and longer medial-lateral time to stabilisation (4.82 ± 0.69 vs 4.11 ± 0.47 seconds, p = 0.023) compared to the control group during an unplanned landing. Furthermore, the above variables were negatively correlated with the step-down proprioception score only in the unplanned condition but not in the planned condition. CAI participants had inferior medial-lateral time-to-stabilisation and loading attenuation during unplanned jump landing than healthy controls, which were associated with decreased proprioception, highlighting the importance of addressing proprioception to improve balance control during unpredictable landing situations.

Limb dominance influences landing mechanics and neuromuscular control during drop vertical jump in patients with ACL reconstruction

ObjectivesThe purpose of this study was to compare the interlimb biomechanical differences in patients who had undergone anterior cruciate ligament reconstruction (ACLR) in either dominant (ACLR-D) or nondominant (ACLR-ND) limbs and healthy controls (CON) during drop vertical jump (DVJ) task. To investigate whether the dominant or nondominant limb influences the risk of re-injury in ACLR patients.MethodsThirty-three ACLR patients were divided into ACLR-D and ACLR-ND groups according to whether the surgical limb was dominant or nondominant. Seventeen healthy individuals were selected as the CON group. Three-dimensional kinematic data, ground reaction force (GRF) data, and surface electromyographic (EMG) data from the bilateral lower limbs of all participants were collected during the DVJ task. Two-way repeated-measures ANOVAs (limb × group) were performed on the variables of interest to examine the main effects of limb (dominant vs. nondominant) and group (ACLR-D, ACLR-ND, and CON), as well as the interaction between limb and group.ResultsThe nonsurgical limbs of ACLR group had significantly greater knee valgus angles, knee extension and valgus moments, peak posterior GRF (PPGRF), and peak vertical GRF (PVGRF) compared to the surgical limbs. The nonsurgical limbs of ACLR-ND patients demonstrated significantly greater knee extension and valgus moments, greater PPGRF and PVGRF, and reduced muscle activity in the vastus medialis and vastus lateralis compared to the CON group. The ACLR patients had reduced muscle activity in the quadriceps of the surgical limb and the hamstrings of the bilateral limbs compared to controls.ConclusionThe nonsurgical limbs of ACLR patients may suffer an increased risk of ACL injury due to altered landing mechanics and neuromuscular control strategies compared to the surgical limbs. Additionally, limb dominance influences movement patterns and neuromuscular control during DVJ task, the nonsurgical limbs of the ACLR-ND might be at higher risk of ACL injury compared to the ACLR-D group.

The Battle of the Equations: A Systematic Review of Jump Height Calculations Using Force Platforms.

Vertical jump height measures our ability to oppose gravity and lower body neuromuscular function in athletes and various clinical populations. Vertical jump tests are principally simple, time-efficient, and extensively used for assessing athletes and generally in sport science research. Using the force platform for jump height estimates is increasingly popular owing to technological advancements and its relative ease of use in diverse settings. However, ground reaction force data can be analyzed in multiple ways to estimate jump height, leading to distinct outcome values from the same jump. In the literature, four equations have been commonly described for estimating jump height using the force platform, where jump height can vary by up to 15cm when these equations are used on the same jump. There are advantages and disadvantages to each of the equations according to the intended use. Considerations of (i) the jump type, (ii) the reason for testing, and (iii) the definition of jump height should ideally determine which equation to apply. The different jump height equations can lead to confusion and inappropriate comparisons of jump heights. Considering the popularity of reporting jump height results, both in the literature and in practice, there is a significant need to understand how the different mathematical approaches influence jump height. This review aims to investigate how different equations affect the assessment of jump height using force platforms across various jump types, such as countermovement jumps, squat jumps, drop jumps, and loaded jumps.

Continuous Gait Phase Estimation for Multi-Locomotion Tasks Using Ground Reaction Force Data.

Existing studies on gait phase estimation generally involve walking experiments using inertial measurement units under limited walking conditions (WCs). In this study, a gait phase estimation algorithm is proposed that uses data from force sensing resistors (FSRs) and a Bi-LSTM model. The proposed algorithm estimates gait phases in real time under various WCs, e.g., walking on paved/unpaved roads, ascending and descending stairs, and ascending or descending on ramps. The performance of the proposed algorithm is evaluated by performing walking experiments on ten healthy adult participants. An average gait estimation accuracy exceeding 90% is observed with a small error (root mean square error = 0.794, R2 score = 0.906) across various WCs. These results demonstrate the wide applicability of the proposed gait phase estimation algorithm using various insole devices, e.g., in walking aid control, gait disturbance diagnosis in daily life, and motor ability analysis.

IoT-Based Wireless System for Gait Kinetics Monitoring in Multi-Device Therapeutic Interventions.

This study presents an IoT-based gait analysis system employing insole pressure sensors to assess gait kinetics. The system integrates piezoresistive sensors within a left foot insole, with data acquisition managed using an ESP32 board that communicates via Wi-Fi through an MQTT IoT framework. In this initial protocol study, we conducted a comparative analysis using the Zeno system, supported by PKMAS as the gold standard, to explore the correlation and agreement of data obtained from the insole system. Four volunteers (two males and two females, aged 24-28, without gait disorders) participated by walking along a 10 m Zeno system path, equipped with pressure sensors, while wearing the insole system. Vertical ground reaction force (vGRF) data were collected over four gait cycles. The preliminary results indicated a strong positive correlation (r = 0.87) between the insole and the reference system measurements. A Bland-Altman analysis further demonstrated a mean difference of approximately (0.011) between the two systems, suggesting a minimal yet significant bias. These findings suggest that piezoresistive sensors may offer a promising and cost-effective solution for gait disorder assessment and monitoring. However, operational factors such as high temperatures and sensor placement within the footwear can introduce noise or unwanted signal activation. The communication framework proved functional and reliable during this protocol, with plans for future expansion to multi-device applications. It is important to note that additional validation studies with larger sample sizes are required to confirm the system's reliability and robustness for clinical and research applications.

Biomechanical Assessment of Exoskeleton Intervention for Injured and Recovering Workers: A Simulation Study of Bending Tasks

Exoskeletons, wearable devices designed to enhance physical activity, show promise in mitigating work-related musculoskeletal disorders and injuries. This study examines exoskeleton efficacy as ergonomic intervention for aiding injured workers with limited trunk mobility in returning to work. Six adult males participated in simulated bending tasks using a trunk mobility restrictor and a passive trunk exoskeleton. Lumbosacral joint loads and moments during bending tasks with and without the exoskeleton were biomechanically assessed using optical motion capture and ground reaction force data as model inputs. Results indicate significant reductions in compressive loads and subject moments at the lumbosacral joint with exoskeleton usage, particularly during full bending. Moreover, the exoskeleton’s supportive impact increases with greater trunk flexion angles. These findings underscore exoskeleton potential in facilitating the return to work for individuals with limited trunk mobility, emphasizing the need for further empirical validation in real-world settings.

Calibrating Low-Cost Smart Insole Sensors with Recurrent Neural Networks for Accurate Prediction of Center of Pressure.

This paper proposes a scheme for predicting ground reaction force (GRF) and center of pressure (CoP) using low-cost FSR sensors. GRF and CoP data are commonly collected from smart insoles to analyze the wearer's gait and diagnose balance issues. This approach can be utilized to improve a user's rehabilitation process and enable customized treatment plans for patients with specific diseases, making it a useful technology in many fields. However, the conventional measuring equipment for directly monitoring GRF and CoP values, such as F-Scan, is expensive, posing a challenge to commercialization in the industry. To solve this problem, this paper proposes a technology to predict relevant indicators using only low-cost Force Sensing Resistor (FSR) sensors instead of expensive equipment. In this study, data were collected from subjects simultaneously wearing a low-cost FSR Sensor and an F-Scan device, and the relationship between the collected data sets was analyzed using supervised learning techniques. Using the proposed technique, an artificial neural network was constructed that can derive a predicted value close to the actual F-Scan values using only the data from the FSR Sensor. In this process, GRF and CoP were calculated using six virtual forces instead of the pressure value of the entire sole. It was verified through various simulations that it is possible to achieve an improved prediction accuracy of more than 30% when using the proposed technique compared to conventional prediction techniques.

Validity and Test–Retest Reliability of a Smartphone App for Measuring Rising Time, Velocity, Power, and Inter-Limb Asymmetry During Single-Leg Sit-to-Stand Test in Female-Trained Athletes

ABSTRACT The aim was to determine the validity and test – retest reliability of the Sit to Stand App variables (rising time, vertical velocity, and power) for measuring single-leg sit-to-stand (STS) test compared to those derived from ground reaction force data. Twenty-seven female athletes performed the single-leg STS test over three consecutive sessions simultaneously recorded with a force plate and the smartphone app. Validity was assessed with Pearson’s correlation coefficient, intra-class correlation coefficient (ICC), and percentage error. Reliability was assessed with the ICC. Almost perfect correlations (r ≥ 0.95) and excellent agreement (ICC = 0.96–0.97) between the app and force plate measures with low percentage errors (≤7.3%) were found. The app showed good-to-excellent reliability (ICC = 0.88–0.92) with no differences in inter-limb asymmetry over three sessions. The app was highly valid and reliable for measuring single-leg STS performance. Practitioners can use this app to assess lower-limb performance in female athletes.

Self-Supervised Learning Improves Accuracy and Data Efficiency for IMU-Based Ground Reaction Force Estimation.

Recent deep learning techniques hold promise to enable IMU-driven kinetic assessment; however, they require large extents of ground reaction force (GRF) data to serve as labels for supervised model training. We thus propose using existing self-supervised learning (SSL) techniques to leverage large IMU datasets to pre-train deep learning models, which can improve the accuracy and data efficiency of IMU-based GRF estimation. We performed SSL by masking a random portion of the input IMU data and training a transformer model to reconstruct the masked portion. We systematically compared a series of masking ratios across three pre-training datasets that included real IMU data, synthetic IMU data, or a combination of the two. Finally, we built models that used pre-training and labeled data to estimate GRF during three prediction tasks: overground walking, treadmill walking, and drop landing. When using the same amount of labeled data, SSL pre-training significantly improved the accuracy of 3-axis GRF estimation during walking compared to baseline models trained by conventional supervised learning. Fine-tuning SSL model with 1-10% of walking data yielded comparable accuracy to training baseline model with 100% of walking data. The optimal masking ratio for SSL is 6.25-12.5%. SSL leveraged large real and synthetic IMU datasets to increase the accuracy and data efficiency of deep-learning-based GRF estimation, reducing the need for labeled data. This work, with its open-source code and models, may unlock broader use cases of IMU-driven kinetic assessment by mitigating the scarcity of GRF measurements in practical applications.

Biomechanics of step-off drop landings are affected by limb dominance and lead limb in task initiation

ABSTRACT This study examines the effects of limb dominance and lead limb in task initiation on the kinetics and kinematics of step-off drop landings. Nineteen male participants performed drop landings led by the dominant and non-dominant limbs at 45-cm and 60-cm drop heights. Ground reaction force (GRF) and lower body kinematic data were collected. Between-limb time differences at the initial ground contact were calculated to indicate temporal asymmetry. Statistical Parametric Mapping (SPM) was applied for waveform analysis while two-way repeated measures ANOVA was used for discrete parameters. SPM results revealed greater GRF and lesser ankle dorsiflexion in the lead limb compared to the trail limb in 3 out of 4 landing conditions. The dominant limb displayed a greater forefoot loading rate (45 cm: p=.009, η p 2 = 0.438; 60 cm: p=.035, η p 2 = 0.225) and greater ankle joint quasi-stiffness (45 cm: p < .001, η p 2 = 0.360; 60 cm: p < .001, η p 2 = 0.597) than the non-dominant limb. Not all 380 trials were lead-limb first landings, with a smaller between-limb time difference (p=.009, d = 0.60) at 60 cm (4.1 ± 2.3 ms) than 45 cm (5.6 ± 2.7 ms). In conclusion, the step-off drop landing is not an ideal protocol for examining bilateral asymmetry in lower limb biomechanics due to potential biases introduced by limb dominance and the step-off limb.

Ground Reaction Forces and Joint Moments Predict Metabolic Cost in Physical Performance: Harnessing the Power of Artificial Neural Networks

Understanding metabolic cost through biomechanical data, including ground reaction forces (GRFs) and joint moments, is vital for health, sports, and rehabilitation. The long stabilization time (2–5 min) of indirect calorimetry poses challenges in prolonged tests. This study investigated using artificial neural networks (ANNs) to predict metabolic costs from the GRF and joint moment time series. Data from 20 participants collected over 270 walking trials, including the GRF and joint moments, formed a detailed dataset. Two ANN models were crafted, netGRF for the GRF and netMoment for joint moments, and both underwent training, validation, and testing to validate their predictive accuracy for metabolic cost. NetGRF (six hidden layers, two input delays) showed significant correlations: 0.963 (training), 0.927 (validation), 0.883 (testing), p &lt; 0.001. NetMoment (three hidden layers, one input delay) had correlations of 0.920 (training), 0.956 (validation), 0.874 (testing), p &lt; 0.001. The models’ low mean squared errors reflect their precision. Using Partial Dependence Plots, we demonstrated how gait cycle phases affect metabolic cost predictions, pinpointing key phases. Our findings show that the GRF and joint moments data can accurately predict metabolic costs via ANN models, with netGRF being notably consistent. This emphasizes ANNs’ role in biomechanics as a crucial method for estimating metabolic costs, impacting sports science, rehabilitation, assistive technology development, and fostering personalized advancements.

Decreased moment of inertia of the lower limb facilitates a rapid hip internal rotation in a simulated foot impact maneuver. A laboratory-controlled biomechanical study for a precursor mechanism of noncontact anterior cruciate ligament injury.

Anterior cruciate ligament injury frequently occurs in the deceleration with the knee-extended position. In addition, a rapid hip internal rotation is concomitantly observed. However, how the extended knee position induces the hip internal rotation is unclear. Sixteen healthy participants performed the simulated foot impact task on the experimental chair. To vary the knee flexion angle, the following four-foot placement positions relative to the pelvis segment, i.e.: 1) near; 2) middle; 3) far; and 4) far + heel strike, were tested. The reflective marker positions and the ground reaction force (GRF) data were collected. The moment of inertia of the entire lower limb around its long axis as well as the peak hip internal rotation angular velocity were calculated and compared among four conditions (Wilcoxon Signed-Rank Test with Bonferroni correction, P<0.0083). As the knee extended from the near to far + heel strike condition, the moment of inertia of the entire lower limb significantly decreased and hip internal rotation angular velocity significantly increased (P<0.001). The extended knee position with far foot placement from torso reduces the inertial resistance of the entire lower limb around its long axis and is vulnerable to the hip internal rotation.

The Modified Reactive Strength Index Is a Valid Measure of Lower-Body Explosiveness in Male and Female High School Athletes.

Witte, BC, Schouten, TC, Westphal, JA, VanZile, AW, Jones, DD, Widenhoefer, TL, Dobbs, WC, Jagim, AR, Luedke, JA, and Almonroeder, TG. The modified reactive strength index is a valid measure of lower-body explosiveness in male and female high school athletes. J Strength Cond Res 38(8): 1428-1432, 2024-The modified reactive strength index (mRSI) is a commonly used metric to quantify lower-body explosiveness during countermovement jump (CMJ) performance. However, few studies have attempted to examine its validity as a measure of explosiveness, particularly among high school athletes. The purpose of this study was to examine the validity of the mRSI as a measure of lower-body explosiveness among a relatively large sample of male and female high school athletes from various sports. As part of this study, male ( n = 132) and female ( n = 43) high school athletes performed CMJs, while ground reaction forces were recorded using a force platform. The vertical ground reaction force data collected during the CMJs were used to derive the following variables: peak force (PF), peak power, time to PF, time to take-off, peak rate of force development, and the mRSI. Principal component analysis was applied and reduced these variables into 2 components related to "force" and "speed." The mRSI loaded on both the force (loading = 0.82) and speed (loading = -0.46) components, indicating that it incorporates elements of both force and speed, although it loaded more strongly on the force component than the speed component. The observed pattern of cross-loading suggests that the mRSI is generally a valid measure of lower-body explosiveness for male and female high school athletes.

Weighted Vest Load Arrangement and Data Normalization Effects on Lower Limb Biomechanics During Countermovement Jump Landings

This paper assessed the weighted vest load arrangement and data normalization method effects on ground reaction forces (GRF), joint kinematics, and joint kinetics during the landing portion of the countermovement jump. Vertical GRF and sagittal kinematic data were obtained from 12 males and 12 females during countermovement jump-landings in 4 different loading arrangements (unloaded, 10% body mass load placed anteriorly, posteriorly, and split anterior/posterior). Two methods (body mass vs. mass*landing height) were used to normalize joint torques to determine whether common mass-normalization (type A) yielded different results than a jump-landing specific mass*landing height normalization (type B) in statistical significance. Mixed-model analyses of variance (α=0.05) and effect sizes (ES) were used to assess differences between sexes and loading conditions for each normalization method. Results show that for normalization A, significant statistical differences were found between sexes for peak vertical GRF, hip moment, and knee moment. Pooled sex peak vertical GRF and hip moments showed significant differences when comparing the unloaded with the back and front-loaded conditions. For normalization B, the peak vertical GRF also showed significant differences between men and women but with smaller effect sizes. Only the hip moment showed significant differences for both normalization methods but changed the magnitude of its effect sizes. Results suggest that different normalization methods could be considered for joint moments or GRF depending on the nature of the statistical significance of jump height.

Interlimb kinetic asymmetries during the tuck jump assessment are more exposed following kinetic stabilization

ObjectiveTo analyse interlimb kinetics and asymmetries during the tuck jump assessment (TJA), before and after kinetic stabilization, to identify injury risk in healthy female athletes. DesignCross-sectional study. SettingLaboratory. ParticipantsTwenty-five healthy females (age 21.0 ± 1.83 yrs; height 1.68 ± 0.06 m; body mass 69.4 ± 10.7 kg). Main outcome measuresKinetics were measured during 10-s trials of the TJA and absolute asymmetries compared, before and after kinetic stabilization using paired sample t-tests. Statistical parametric mapping (SPM) compared vertical ground reaction force (VGRF) data for each limb during the jumping cycles before and after stabilization. ResultsSmall to moderate increases in interlimb asymmetries were observed after stabilization for VGRF, relative vertical leg stiffness, average loading rate, total and propulsive impulse, peak braking and propulsive force (p < 0.05). SPM revealed significant interlimb differences between 77-98% and 83–99% of ground contact for the jumping cycles pre- and post-stabilization respectively. ConclusionsLarger asymmetries were evident after kinetic stabilization, with increased VGRF in the non-dominant limb. We speculate that participants sacrificed interlimb landing symmetry to achieve kinetic stability, which may reflect a primal landing strategy that forgoes movement quality. Assessing lower limb biomechanics using the TJA should involve examining kinetic stability and interlimb kinetic asymmetries.

Effects of Metatarsal Foot Orthosis on Biomechanical 3D Ground Reaction Force in Individuals with Morton Foot Syndrome during Gait: A Cross-Sectional Study.

Morton's foot syndrome (MFS) is characterized by a distally longer head of the second metatarsal bone compared to the head of the first metatarsal bone. Few studies have investigated the effects of a foot orthosis on kinetic characteristics, such as ground reaction force (GRF), during walking in individuals with MFS. This study aimed to verify dynamic GRF using a 3D motion analysis system, including two platforms with and without a foot orthosis condition. Kinetic GRF data of 26 participants with MFS were collected using a motion analysis system and a force platform. Participants were asked to walk wearing standard shoes or shoes with a pad-type foot orthosis. Repeated-measures analysis of variance (ANOVA) was used to compare the kinetic GRF data in the stance phase during gait according to the side of the leg and orthotic conditions for MFS. The late sagittal and frontal peak forces showed that the presence of a foot orthosis condition significantly increased the GRF when compared with the absence of a foot orthosis condition for both sides of the feet (p < 0.05). In addition, the second vertical peak force of the GRF showed that the presence of a foot orthosis condition significantly increased the GFR when compared with the absence of a foot orthosis condition on the side of the right foot (p = 0.023). Significant effects were observed in the late sagittal and frontal peak GRFs when wearing the pad-type foot orthosis in individuals with MFS during gait. Thus, even if there are no signs and symptoms of MFS in patients diagnosed with the disease condition, clinical interventions, such as a foot orthosis, that can be simply applied to shoe insoles are needed to manage and prevent various musculoskeletal disorders that may develop in the future. It was hypothesized that when wearing a foot orthosis, the participants would walk with increased GRF during gait compared to those without an orthosis.

The influence of jump-landing direction on dynamic postural stability following anterior cruciate ligament reconstruction

BackgroundTraditional testing prior to return to sport following anterior cruciate ligament reconstruction typically involves jump-landing tasks in the forward direction. As injury is most likely the result of multiplanar neuromuscular control deficits, assessment of dynamic postural stability using landing tasks that require multiplanar stabilization may be more appropriate. The purpose of this study was to examine how dynamic postural stability is affected when performing jump-landing tasks in three different directions. MethodsFifteen athletes [11 females (18.0 ± 3.0 years) and 4 males (18.5 ± 3.1 years)] following anterior cruciate ligament reconstruction performed a series of single-limb jump-landing tasks in 3 directions. Individual directional stability indices and a composite dynamic postural stability index were calculated using ground reaction force data and were compared using separate one-way repeated measures ANOVAs. FindingsAll directional stability indices demonstrated a significant main effect for jump-landing direction (medial-lateral P < 0.001, η2p = 0.95; anterior-posterior P < 0.001, η2p = 0.97; vertical P = 0.021, η2p = 0.24). The diagonal jump-landing direction produced increased medial-lateral stability and vertical stability scores, while the forward and diagonal jump-landing directions produced increased anterior-posterior stability scores. There was no significant effect for the composite dynamic stability index score. InterpretationJump-landing direction affects dynamic postural stability in all 3 planes of movement in athletes following anterior cruciate ligament reconstruction. Results indicate the potential need to incorporate multiple jump-landing directions to better assess dynamic postural stability prior to return to sport.

A Novel Gait Event Detection Algorithm Using a Thigh-Worn Inertial Measurement Unit and Joint Angle Information.

This paper describes the development and evaluation of a novel, threshold-based gait event detection algorithm utilizing only one thigh inertial measurement unit (IMU) and unilateral, sagittal plane hip and knee joint angles. The algorithm was designed to detect heel strike (HS) and toe off (TO) gait events, with the eventual goal of detection in a real-time exoskeletal control system. The data used in the development and evaluation of the algorithm were obtained from two gait databases, each containing synchronized IMU and ground reaction force (GRF) data. All database subjects were healthy individuals walking in either a level-ground, urban environment or a treadmill lab environment. Inertial measurements used were three-dimensional thigh accelerations and three-dimensional thigh angular velocities. Parameters for the TO algorithm were identified on a per-subject basis. The GRF data were utilized to validate the algorithm's timing accuracy and quantify the fidelity of the algorithm, measured by the F1-Score. Across all participants, the algorithm reported a mean timing error of -41±20 ms with an F1-Score of 0.988 for HS. For TO, the algorithm reported a mean timing error of -1.4±21 ms with an F1-Score of 0.991. The results of this evaluation suggest that this algorithm is a promising solution to inertial based gait event detection; however, further refinement and real-time evaluation are required for use in exoskeletal control.

Achilles Tendon Loading during Running Estimated Via Shear Wave Tensiometry: A Step Toward Wearable Kinetic Analysis.

Understanding muscle-tendon forces (e.g., triceps surae and Achilles tendon) during locomotion may aid in the assessment of human performance, injury risk, and rehabilitation progress. Shear wave tensiometry is a noninvasive technique for assessing in vivo tendon forces that has been recently adapted to a wearable technology. However, previous laboratory-based and outdoor tensiometry studies have not evaluated running. This study was undertaken to assess the capacity for shear wave tensiometry to produce valid measures of Achilles tendon loading during running at a range of speeds. Participants walked (1.34 m·s -1 ) and ran (2.68, 3.35, and 4.47 m·s -1 ) on an instrumented treadmill while shear wave tensiometers recorded Achilles tendon wave speeds simultaneously with whole-body kinematic and ground reaction force data. A simple isometric task allowed for the participant-specific conversion of Achilles tendon wave speeds to forces. Achilles tendon forces were compared with ankle torque measures obtained independently via inverse dynamics analyses. Differences in Achilles tendon wave speed, Achilles tendon force, and ankle torque across walking and running speeds were analyzed with linear mixed-effects models. Achilles tendon wave speed, Achilles tendon force, and ankle torque exhibited similar temporal patterns across the stance phase of walking and running. Significant monotonic increases in peak Achilles tendon wave speed (56.0-83.8 m·s -1 ), Achilles tendon force (44.0-98.7 N·kg -1 ), and ankle torque (1.72-3.68 N·m·(kg -1 )) were observed with increasing locomotion speed (1.34-4.47 m·s -1 ). Tensiometry estimates of peak Achilles tendon force during running (8.2-10.1 body weights) were within the range of those estimated previously via indirect methods. These results set the stage for using tensiometry to evaluate Achilles tendon loading during unobstructed athletic movements, such as running, performed in the field.