Muscle contributions to mediolateral and anteroposterior foot placement during walking

Foot placement is critical to balance control during walking and is primarily controlled by muscle force generation. Although gluteus medius activity has been associated with mediolateral foot placement, how other muscles contribute to foot placement is not clear. Furthermore, although dynamic walking models have suggested that anteroposterior foot placement can be passively controlled, the extent to which muscles actively contribute to anteroposterior foot placement has not been determined. The objective of this study was to identify individual muscle contributions to mediolateral and anteroposterior foot placement during walking in healthy adults. Dynamic simulations of walking were developed for six older adults and a segmental power analysis was performed to determine the individual muscle contributions to the mediolateral and anteroposterior power delivered to the foot segment. The simulations revealed the ipsilateral swing limb gluteus medius, iliopsoas, rectus femoris and hamstrings and the contralateral stance limb gluteus medius and ankle plantarflexors were primary contributors to both mediolateral and anteroposterior foot placement. Muscle contributions to foot placement were found to be highly influenced by their contributions to pelvis power, which was dominated by those muscles crossing the hip joint. Thus, impaired balance control may be improved by focusing rehabilitation interventions on optimizing the coordination of those muscles crossing the hip joint and the ankle plantarflexors.     

Ambulatory estimation of mean step length during unconstrained walking by means of COG accelerometry

It has been reported that spatio-temporal gait parameters can be estimated using an accelerometer to calculate the vertical displacement of the body's centre of gravity. This method has the potential to produce realistic ambulatory estimations of those parameters during unconstrained walking. In this work, we want to evaluate the crude estimations of mean step length so obtained, for their possible application in the construction of an ambulatory walking distance measurement device. Two methods have been tested with a set of volunteers in 20 m excursions. Experimental results show that estimations of walking distance can be obtained with sufficient accuracy and precision for most practical applications (errors of 3.66 ± 6.24 and 0.96 ± 5.55%), the main difficulty being inter-individual variability (biggest deviations of 19.70 and 15.09% for each estimator). Also, the results indicate that an inverted pendulum model for the displacement during the single stance phase, and a constant displacement per step during double stance, constitute a valid model for the travelled distance with no need of further adjustments. It allows us to explain the main part of the erroneous distance estimations in different subjects as caused by fundamental limitations of the simple inverted pendulum approach.     

Bottom-up estimation of joint moments during manual lifting using orientation sensors instead of position sensors

L5/S1, hip and knee moments during manual lifting tasks are, in a laboratory environment, frequently established by bottom-up inverse dynamics, using force plates to measure ground reaction forces (GRFs) and an optoelectronic system to measure segment positions and orientations. For field measurements, alternative measurement systems are being developed. One alternative is the use of small body-mounted inertial/magnetic sensors (IMSs) and instrumented force shoes to measure segment orientation and GRFs, respectively. However, because IMSs measure segment orientations only, the positions of segments relative to each other and relative to the GRFs have to be determined by linking them, assuming fixed segment lengths and zero joint translation. This will affect the estimated joint positions and joint moments. This study investigated the effect of using segment orientations only (orientation-based method) instead of using orientations and positions (reference method) on three-dimensional joint moments. To compare analysis methods (and not measurement methods), GRFs were measured with a force plate and segment positions and/or orientations were measured using optoelectronic marker clusters for both analysis methods. Eleven male subjects lifted a box from floor level using three lifting techniques: a stoop, a semi-squat and a squat technique. The difference between the two analysis methods remained small for the knee moments: <4%. For the hip and L5/S1 moments, the differences were more substantial: up to 8% for the stoop and semi-squat techniques and up to 14% for the squat technique. In conclusion, joint moments during lifting can be estimated with good accuracy at the knee joint and with reasonable accuracy at the hip and L5/S1 joints using segment orientation and GRF data only.     

Estimation of stride length in level walking using an inertial measurement unit attached to the foot: a validation of the zero velocity assumption during stance

In a variety of applications, inertial sensors are used to estimate spatial parameters by double integrating over time their coordinate acceleration components. In human movement applications, the drift inherent to the accelerometer signals is often reduced by exploiting the cyclical nature of gait and under the hypothesis that the velocity of the sensor is zero at some point in stance. In this study, the validity of the latter hypothesis was investigated by determining the minimum velocity of progression of selected points of the foot and shank during the stance phase of the gait cycle while walking at three different speeds on level ground. The errors affecting the accuracy of the stride length estimation resulting from assuming a zero velocity at the beginning of the integration interval were evaluated on twenty healthy subjects. Results showed that the minimum velocity of the selected points on the foot and shank increased as gait speed increased. Whereas the average minimum velocity of the foot locations was lower than 0.011 m/s, the velocity of the shank locations were up to 0.049 m/s corresponding to a percent error of the stride length equal to 3.3%. The preferable foot locations for an inertial sensor resulted to be the calcaneus and the lateral aspect of the rearfoot. In estimating the stride length, the hypothesis that the velocity of the sensor can be set to zero sometimes during stance is acceptable only if the sensor is attached to the foot.     

Walking speed estimation using a shank-mounted inertial measurement unit

We studied the feasibility of estimating walking speed using a shank-mounted inertial measurement unit. Our approach took advantage of the inverted pendulum-like behavior of the stance leg during walking to identify a new method for dividing up walking into individual stride cycles and estimating the initial conditions for the direct integration of the accelerometer and gyroscope signals. To test its accuracy, we compared speed estimates to known values during walking overground and on a treadmill. The speed estimation method worked well across treadmill speeds and slopes yielding a root mean square speed estimation error of only 7%. It also worked well during overground walking with a 4% error in the estimated travel distance. This accuracy is comparable to that achieved from foot-mounted sensors, providing an alternative in sensor positioning for walking speed estimation. Shank mounted sensors may be of great benefit for estimating speed in walking with abnormal foot motion and for the embedded control of knee-mounted devices such as prostheses and energy harvesters.     

Estimation of minimum ground clearance (MGC) using body-worn inertial sensors

Objective assessment of balance and mobility in elderly populations using body-worn sensors has recently become a prevalent theme in falls-related research. Recent research by the authors identified mean absolute-valued vertical angular velocity measured using shank mounted inertial sensors during a timed-up-and-go test as having a strong association with falls history in a group of elderly adults. This study aimed to investigate the clinical relevance of this parameter by exploring the relationship between it and minimum ground clearance (MGC) measured with an optical motion capture system. MGC is an important variable when considering trip-related falls risk. This paper also presents a method of estimating properties of MGC during walking, across a range of speeds and gait patterns, using body-worn inertial sensors. We found that mean MGC and coefficient of variation (CV) MGC are correlated with mean absolute-valued vertical angular velocity and acceleration as measured by shank or foot mounted inertial sensors. Regression models generated using inertial sensor derived variables were used to robustly estimate the mean MGC and CV MGC measured by an optical marker-tracking system. Foot-mounted sensors were found to yield slightly better results than sensors on the shank. Different walking speeds and gait patterns were not found to influence the accuracy of the models. We conclude that these findings have the potential to evaluate a walking trial using body-worn inertial sensors, which could then be used to identify individuals with increased risk of unprovoked collisions with the ground during locomotion.     

Ground reaction force estimation using an insole-type pressure mat and joint kinematics during walking

Kinetic analysis of walking requires joint kinematics and ground reaction force (GRF) measurement, which are typically obtained from a force plate. GRF is difficult to measure in certain cases such as slope walking, stair climbing, and track running. Nevertheless, estimating GRF continues to be of great interest for simulating human walking. The purpose of the study was to develop reaction force models placed on the sole of the foot to estimate full GRF when only joint kinematics are provided (Type-I), and to estimate ground contact shear forces when both joint kinematics and foot pressure are provided (Type-II and Type-II-val). The GRF estimation models were attached to a commercial full body skeletal model using the AnyBody Modeling System, which has an inverse dynamics-based optimization solver. The anterior–posterior shear force and medial–lateral shear force could be estimated with approximate accuracies of 6% BW and 2% BW in all three methods, respectively. Vertical force could be estimated in the Type-I model with an accuracy of 13.75% BW. The accuracy of the force estimation was the highest during the mid-single-stance period with an average RMS for errors of 3.10% BW, 1.48% BW, and 7.48% BW for anterior–posterior force, medial–lateral force, and vertical force, respectively. The proposed GRF estimation models could predict full and partial GRF with high accuracy. The design of the contact elements of the proposed model should make it applicable to various activities where installation of a force measurement system is difficult, including track running and treadmill walking.     

Joint moments and contact forces in the foot during walking

The net force and moment of a joint have been widely used to understand joint disease in the foot. Meanwhile, it does not reflect the physiological forces on muscles and contact surfaces. The objective of the study is to estimate active moments by muscles, passive moments by connective tissues and joint contact forces in the foot joints during walking. Joint kinematics and external forces of ten healthy subjects (all males, 24.7 ± 1.2 years) were acquired during walking. The data were entered into the five-segment musculoskeletal foot model to calculate muscle forces and joint contact forces of the foot joints using an inverse dynamics-based optimization. Joint reaction forces and active, passive and net moments of each joint were calculated from muscle and ligament forces. The maximum joint reaction forces were 8.72, 4.31, 2.65, and 3.41 body weight (BW) for the ankle, Chopart’s, Lisfranc and metatarsophalangeal joints, respectively. Active and passive moments along with net moments were also obtained. The maximum net moments were 8.6, 8.4, 5.4 and 0.8%BW∙HT, respectively. While the trend of net moment was very similar between the four joints, the magnitudes and directions of the active and passive moments varied between joints. The active and passive moments during walking could reveal the roles of muscles and ligaments in each of the foot joints, which was not obvious in the net moment. This method may help narrow down the source of joint problems if applied to clinical studies.     

Strategy quantification using body worn inertial sensors in a reactive agility task

Agility performance is often evaluated using time-based metrics, which provide little information about which factors aid or limit success. The objective of this study was to better understand agility strategy by identifying biomechanical metrics that were sensitive to performance speed, which were calculated with data from an array of body-worn inertial sensors. Five metrics were defined (normalized number of foot contacts, stride length variance, arm swing variance, mean normalized stride frequency, and number of body rotations) that corresponded to agility terms defined by experts working in athletic, clinical, and military environments. Eighteen participants donned 13 sensors to complete a reactive agility task, which involved navigating a set of cones in response to a vocal cue. Participants were grouped into fast, medium, and slow performance based on their completion time. Participants in the fast group had the smallest number of foot contacts (normalizing by height), highest stride length variance (normalizing by height), highest forearm angular velocity variance, and highest stride frequency (normalizing by height). The number of body rotations was not sensitive to speed and may have been determined by hand and foot dominance while completing the agility task. The results of this study have the potential to inform the development of a composite agility score constructed from the list of significant metrics. By quantifying the agility terms previously defined by expert evaluators through an agility score, this study can assist in strategy development for training and rehabilitation across athletic, clinical, and military domains.     

The influence of footwear on foot motion during walking and running

There are evidences to suggest that wearing footwear constrains the natural barefoot motion during locomotion. Unlike prior studies that deduced foot motions from shoe sole displacement parameters, the aim of this study was to examine the effect of footwear motion on forefoot to rearfoot relative motion during walking and running. The use of a multi-segment foot model allowed accurate both shoe sole and foot motions (barefoot and shod) to be quantified. Two pairs of identical sandals with different midsole hardness were used. Ten healthy male subjects walked and ran in each of the shod condition.The results showed that for barefoot locomotion there was more eversion of the forefoot and it occurred faster than for shod locomotion. In this later condition, the range of eversion was reduced by 20% and the rate of eversion in late stance by 60% in comparison to the barefoot condition. The sole constrained both the torsional (eversion/inversion) and adduction range of motion of the foot. Interestingly, during the push-off phase of barefoot locomotion the rate and direction of forefoot torsion varied between individuals. However, most subjects displayed a forefoot inversion direction of motion while shod. Therefore, this experiment showed that the shoes not only restricted the natural motion of the barefoot but also appeared to impose a specific foot motion pattern on individuals during the push-off phase. These findings have implications for the matching of footwear design characteristics to individual natural foot function.     

Assessment of the measurement accuracy of inertial sensors during different tasks of daily living

The low cost and ease of use of inertial measurement units (IMUs) make them an attractive option for motion analysis tasks that cannot be easily measured in a laboratory. To date, only a limited amount of research has been conducted comparing commercial IMU systems to optoelectronic systems, the gold standard, for everyday tasks like stair climbing and inclined walking. In this paper, the 3D joint angles of the lower limbs are determined using both an IMU system and an optoelectronic system for twelve participants during stair ascent and descent, and inclined, declined and level walking. Three different datasets based on different hardware and anatomical models were collected for the same movement in an effort to determine the cause and quantify the errors involved with the analysis. Firstly, to calculate software errors, two different anatomical models were compared for one hardware system. Secondly, to calculate hardware errors, results were compared between two different measurement systems using the same anatomical model. Finally, the overall error between both systems with their native anatomical models was calculated. Statistical analysis was performed using statistical parametric mapping. When both systems were evaluated based on the same anatomical model, the number of trials with significant differences decreased markedly. Thus, the differences in joint angle measurement can mainly be attributed to the variability in the anatomical models used for calculations and not to the IMU hardware.     

Quantifying physical functional trajectory in hospitalized older adults using body worn inertial sensors

Acute medical illness requiring hospitalization usually is a critical event in the trajectory leading to disability in older adults. Functional decline frequently occurs during hospitalization, resulting in a loss of Independence in activities of daily living after discharge. The aim of the study was to assess the functional decline in different ADLs of hospitalized elderly patients in an Acute Care for Elderly (ACE) unit incorporating a body-worn inertial sensor and accompanying custom algorithms. 38 hospitalized older adults (age ≥ 75) were included. The patients completed different functional tasks, including a balance test, Gait Velocity Test (GVT), verbal and arithmetic dual-task gait, and a sit-to-stand ability test at admission and discharge. Movement-related parameters were acquired from a unique tri-axial inertial sensor unit. Maximal muscle strength and muscle power output endpoints were also assessed. The results indicated that significant improvements (p < 0.05) were found at discharge compared with the admission values for gait variability and spatiotemporal parameters in the 4- and 6-meter GVT. These significant gains were also obtained in the verbal GVT. In contrast, a significant reduction was found in the functional status measured with the Barthel Index scale. Regarding to the sit-to-stand ability, lower peak power was observed in the sit-to-stand phase of the task at discharge. In conclusion, inertial sensor unit and our custom, validated, algorithms represent a feasible tool for measuring and monitoring functional trajectory during hospitalization in older adults and they are sensitive to detect differences in movement pattern parameters in different ADLs such as walking and the ability to stand from a seated position.     

Functional calibration procedure for 3D knee joint angle description using inertial sensors

Measurement of three-dimensional (3D) knee joint angle outside a laboratory is of benefit in clinical examination and therapeutic treatment comparison. Although several motion capture devices exist, there is a need for an ambulatory system that could be used in routine practice. Up-to-date, inertial measurement units (IMUs) have proven to be suitable for unconstrained measurement of knee joint differential orientation. Nevertheless, this differential orientation should be converted into three reliable and clinically interpretable angles. Thus, the aim of this study was to propose a new calibration procedure adapted for the joint coordinate system (JCS), which required only IMUs data. The repeatability of the calibration procedure, as well as the errors in the measurement of 3D knee angle during gait in comparison to a reference system were assessed on eight healthy subjects. The new procedure relying on active and passive movements reported a high repeatability of the mean values (offset<1°) and angular patterns (SD<0.3° and CMC>0.9). In comparison to the reference system, this functional procedure showed high precision (SD<2° and CC>0.75) and moderate accuracy (between 4.0° and 8.1°) for the three knee angle. The combination of the inertial-based system with the functional calibration procedure proposed here resulted in a promising tool for the measurement of 3D knee joint angle. Moreover, this method could be adapted to measure other complex joint, such as ankle or elbow.     

3D gait assessment in young and elderly subjects using foot-worn inertial sensors

This study describes the validation of a new wearable system for assessment of 3D spatial parameters of gait. The new method is based on the detection of temporal parameters, coupled to optimized fusion and de-drifted integration of inertial signals. Composed of two wirelesses inertial modules attached on feet, the system provides stride length, stride velocity, foot clearance, and turning angle parameters at each gait cycle, based on the computation of 3D foot kinematics. Accuracy and precision of the proposed system were compared to an optical motion capture system as reference. Its repeatability across measurements (test-retest reliability) was also evaluated. Measurements were performed in 10 young (mean age 26.1±2.8 years) and 10 elderly volunteers (mean age 71.6±4.6 years) who were asked to perform U-shaped and 8-shaped walking trials, and then a 6-min walking test (6 MWT). A total of 974 gait cycles were used to compare gait parameters with the reference system. Mean accuracy±precision was 1.5±6.8 cm for stride length, 1.4±5.6 cm/s for stride velocity, 1.9±2.0 cm for foot clearance, and 1.6±6.1° for turning angle. Difference in gait performance was observed between young and elderly volunteers during the 6 MWT particularly in foot clearance. The proposed method allows to analyze various aspects of gait, including turns, gait initiation and termination, or inter-cycle variability. The system is lightweight, easy to wear and use, and suitable for clinical application requiring objective evaluation of gait outside of the lab environment.     

Gait posture estimation using wearable acceleration and gyro sensors

A method for gait analysis using wearable acceleration sensors and gyro sensors is proposed in this work. The volunteers wore sensor units that included a tri-axis acceleration sensor and three single axis gyro sensors. The angular velocity data measured by the gyro sensors were used to estimate the translational acceleration in the gait analysis. The translational acceleration was then subtracted from the acceleration sensor measurements to obtain the gravitational acceleration, giving the orientation of the lower limb segments. Segment orientation along with body measurements were used to obtain the positions of hip, knee, and ankle joints to create stick figure models of the volunteers. This method can measure the three-dimensional positions of joint centers of the hip, knee, and ankle during movement. Experiments were carried out on the normal gait of three healthy volunteers. As a result, the flexion–extension (F–E) and the adduction–abduction (A–A) joint angles of the hips and the flexion–extension (F–E) joint angles of the knees were calculated and compared with a camera motion capture system. The correlation coefficients were above 0.88 for the hip F–E, higher than 0.72 for the hip A–A, better than 0.92 for the knee F–E. A moving stick figure model of each volunteer was created to visually confirm the walking posture. Further, the knee and ankle joint trajectories in the horizontal plane showed that the left and right legs were bilaterally symmetric.     

In vitro study of foot kinematics using a dynamic walking cadaver model

There is a dearth of information on navicular, cuboid, cuneiform and metatarsal kinematics during walking and our objective was to study the kinematic contributions these bones might make to foot function. A dynamic cadaver model of walking was used to apply forces to cadaver feet and mobilise them in a manner similar to in vivo. Kinematic data were recorded from 13 cadaver feet. Given limitations to the simulation, the data describe what the cadaver feet were capable of in response to the forces applied, rather than exactly how they performed in vivo. The talonavicular joint was more mobile than the calcaneocuboid joint. The range of motion between cuneiforms and navicular was similar to that between talus and navicular. Metatarsals four and five were more mobile relative to the cuboid than metatarsals one, two and three relative to the cuneiforms. This work has confirmed the complexity of rear, mid and forefoot kinematics. The data demonstrate the potential for often-ignored foot joints to contribute significantly to the overall kinematic function of the foot. Previous emphasis on the ankle and sub talar joints as the principal articulating components of the foot has neglected more distal articulations. The results also demonstrate the extent to which the rigid segment assumptions of previous foot kinematics research have over simplified the foot.     

A fast estimation of biochemical oxygen demand using microbial sensors

Summary Microbial amperometric sensors for biochemical oxygen demand (BOD) determination using Bacillus subtilis or Trichosporon cutaneum cells immobilized in polyvinylalcohol have been developed. These sensors allow BOD measurements with very short response times (15–30s), a level of precision of ±5% and an operation stability of 30 days. A linear range was obtained for a B. subtilis-based sensor up to 20 mg/l BOD and for a T. cutaneum-based sensor up to 100 mg/l BOD using a glucose/glutamic acid standard.     

Mechanical energy and effective foot mass during impact loading of walking and running

The human heel pad is considered an important structure for attenuation of the transient force caused by heel-strike. Although the mechanical properties of heel pads are relatively well understood, the mechanical energy (Etot) absorbed by the heel pad during the impact phase has never been documented directly because data on the effective foot mass (Meff) was previously unavailable during normal forward locomotion. In this study, we use the impulse-momentum method (IMM) for calculating Meff from moving subjects. Mass-spring-damper models were developed to evaluate errors and to examine the effects of pad property, upper body mass, and effective leg spring on Meff. We simultaneously collected ground reaction forces, pad deformation, and lower limb kinematics during impact phase of barefoot walking, running, and crouched walking. The latter was included to examine the effect of knee angle on Meff. The magnitude of Meff as a percentage of body mass (M(B)) varies with knee angle at impact and significantly differs among gaits: 6.3%M(B) in walking, 5.3%M(B) in running, and 3.7%M(B) in crouched walking. Our modeling results suggested that Meff is insensitive to heel pad resilience and effective leg stiffness. At the instant prior to heel strike, Etot ranges from 0.24 to 3.99 J. The combination of video and forceplate data used in this study allows analyses of Etot and Etot as a function of heel-strike kinematics during normal locomotion. Relationship between Meff and knee angle provides insights into how changes in posture moderate impact transients at different gaits.