Gait events during turning can be detected using kinematic features originally proposed for the analysis of straight-line walking

Healthy older adults generate transverse-plane momenta required for 90° turns while walking during the same phases of gait as used in straight-line gait

BACKGROUND

Generation and regulation (control) of linear and angular momentum is a challenge during turning while walking which may be exacerbated by age-related changes. In healthy older adults, little is known about how momentum is controlled during turns, especially within each phase of gait. Each phase of gait affords unique mechanical contexts to control momenta and regulate balance. In healthy young adults, we found that the transverse-plane linear and angular momenta generation strategies observed within specific phases of gait during straight-line gait were also used during turns. Therefore, in this study, we investigated whether healthy older adults shared similar momentum control strategies specific to each gait phase during straight-line gait and turns.

METHODS

Nine healthy older adults completed straight-line gait and 90° leftward walking turns. We compared the change in transverse-plane whole-body linear and angular momentum across gait phases (left and right single and double support). We also compared the average leftward force and transverse-plane moment across gait phases.

RESULTS

We found that leftward linear momentum was generated most during right single support in straight-line gait and leftward turns. However, in contrast to straight-line gait, during leftward turns, average leftward force was applied across gait phases, with left single support generating significantly less leftward average force than other gait phases. Leftward angular momentum generation and average moment were greatest during left double support in both tasks. We observed some within-participant results that diverged from the group statistical findings, illustrating that although they are common, these momenta control strategies are not necessary.

CONCLUSIONS

Older adults generated transverse-plane linear and angular momentum during consistent phases of gait during straight-line gait and 90° turns, potentially indicating a shared control strategy. Understanding momentum control within each phase of gait can help design more specific targets in gait and balance training interventions.

The effect of motor experience on knee stability and inter-joint coordination when cutting at different angles

BACKGROUND

Most studies on cutting have focused on the biomechanics of the knee and lower-limb muscle activation characteristics, with less consideration given to the influence of motor experience on control strategies at the joint level. This study aimed to investigate the differences in knee stability and inter-joint coordination between high- and low-level athletes when cutting at different angles.

METHODS

A Vicon motion capture system and a Kistler force table were used to obtain kinematic and ground reaction force data during cutting. Joint dynamic stiffness and vector coding were used to assess knee stability and inter-joint coordination. Uncontrolled manifold analysis was used to clarify whether there was synergy among lower-limb joints to maintain postural stability during cutting.

RESULTS

During the load acceptance phase, skilled subjects had the smallest joint stiffness at 90° compared with novice subjects (P < 0.05). Compared with novice subjects, skilled subjects had smaller knee-hip ellipse areas at 90° and 135° (P < 0.05), but larger knee-ankle ellipse areas at 135° (P < 0.05). The synergy index in load acceptance was significantly higher (P < 0.05) for skilled subjects at 90° and 135°.

CONCLUSIONS

Advanced subjects can adjust joint control strategies to adapt to the demands of large-angle cutting on the change of direction. Advanced subjects can reduce knee stability for greater flexibility during cutting compared with novice subjects. By increasing the degree of synergy among the lower-limb joints, advanced athletes can maintain high postural stability.

BP neural network-based analysis of the applicability of NMF in side-step cutting

Background

Although the spatio-temporal structure of muscle activation in cutting have been studied extensively, including time-varying motor primitives and time-invariant motor modules under various conditions, the factorisation methods suitable for cutting are unclear, and the extent to which each factorisation method loses information about movement during dimensionality reduction is uncertain.

Research question

To clarify the extent to which NMF, PCA and ICA retain information about movement when downscaling, and to explore the factorisation method suitable for cutting.

Methods

The kinematic data during cutting was captured with a Vicon motion capture system, from which the kinematic features of the pelvic centre of mass were calculated. NMF, PCA and ICA were used to obtain muscle synergies based on sEMG of the cutting at different angles, respectively. A back propagation neural network was constructed using temporal component of synergy as input and the kinematics data of pelvic as output. Calculation of the Hurst index using fractal analysis based on the temporal component of muscle synergy.

Results

The quality of sEMG reconstruction is significantly higher with ICA (P < 0.01) than with NMF and PCA for the cutting. The NMF reconstruction has a high degree of preservation of movement, whereas the ICA loses movement information about the most of the swing phase, and the PCA loses information related to the change of direction. Hurst index less than 0.5 for all three angles of cutting.

Significance

NMF is suitable for extracting muscle synergies in all directions of cutting. Information related to movement may be lost when using PCA and ICA to extract the synergy of cutting. The high individual variability of muscle synergy in cutting may be responsible for the loss of movement information in muscle synergy.

Slowing gait during turning: how volition of modifying walking speed affects the gait pattern in healthy adults

Background

Turning during walking and volitionally modulating walking speed introduces complexity to gait and has been minimally explored.

Research question

How do the spatiotemporal parameters vary between young adults walking at a normal speed and a slower speed while making 90°, 180°, and 360° turns?

Methods

In a laboratory setting, the spatiotemporal parameters of 10 young adults were documented as they made turns at 90°, 180°, and 360°. A generalized linear model was utilized to determine the effect of both walking speed and turning amplitude.

Results

Young adults volitionally reducing their walking speed while turning at different turning amplitudes significantly decreased their cadence and spatial parameters while increasing their temporal parameters. In conditions of slower movement, the variability of certain spatial parameters decreased, while the variability of some temporal parameters increased.

Significance

This research broadens the understanding of turning biomechanics in relation to volitionally reducing walking speed. Cadence might be a pace gait constant synchronizing the rhythmic integration of several inputs to coordinate an ordered gait pattern output. Volition might up-regulate or down-regulate this pace gait constant (i.e., cadence) which creates the feeling of modulating walking speed.

Consequences of changing planned foot placement on balance control and forward progress

While walking humans generally plan foot placement two steps in advance. However, it is often necessary to rapidly alter foot placement position just before stepping due to the appearance of a new obstacle. While humans are quite capable of rapidly altering foot placement position, such changes can have major effects on centre of mass dynamics. We investigated how rapid changes to planned foot placement impact centre of mass dynamics, and how such changes influence the control of balance and forward progress, during both straight- and turning-gait. Thirteen young adults walked along a virtually projected walkway with precision footholds oriented either in a straight line or with a single 60°, 90° or 120° turn. On a subset of trials, participants were required to rapidly avoid stepping on select footholds. We found that if the centre of mass was disrupted such that it interfered with task success (i.e. staying upright and continuing along the planned path), walkers were more likely to sacrifice forward progress than the upright stability. Further, walkers appear to control centre of mass dynamics differently following inhibited steps during step turns than during spin turns, which may reflect a larger threat to task success when spin turns are interrupted.

Characteristics of muscle synergy and anticipatory synergy adjustments strategy when cutting in different angles

BACKGROUND

Cutting is a quick change of direction that challenges body balance and stability. As the cut-angle increases, the elite athlete can achieve higher performance by pre-adjusting the posture of the lower limb joints. However, it is unclear how the cut-angle affects the neuromuscular control of cutting and the step before cutting, which is essential for daily training and preventing injury in large-angle cutting.

RESEARCH QUESTION

The purpose of this study was to determine how neuromuscular control strategies change under different angles for cutting and the step before cutting METHODS: Non-negative matrix factorisation and K-means clustering were used to extract muscle synergy in the trunk and lower limbs of 12 athletes when cutting at different angles. Uncontrolled manifold analysis was used to clarify whether the muscle synergy fluctuations in the step before cutting were beneficial in stabilising the COP during the cutting.

RESULTS

This study found that the angle did not affect the number of muscle synergies either in the cutting or the step before the cutting. As the angle increases, the activation timing of synergy module 2 during cutting moves forward and is tightly integrated with module 1. The combined synergy at 90° accounted for the largest proportion of either cutting or the step before cutting and had a lower synergy index.

SIGNIFICANCE

Muscle synergy can respond to large-angle cutting through flexible combinations. The muscle synergy for 90° cutting is less regular and has a lower degree of anticipatory synergy adjustments, which may result in poorer postural stability and an increased risk of lower limb joint injury during cutting.

A Scoping Review of the Validity and Reliability of Smartphone Accelerometers When Collecting Kinematic Gait Data

The aim of this scoping review is to evaluate and summarize the existing literature that considers the validity and/or reliability of smartphone accelerometer applications when compared to 'gold standard' kinematic data collection (for example, motion capture). An electronic keyword search was performed on three databases to identify appropriate research. This research was then examined for details of measures and methodology and general study characteristics to identify related themes. No restrictions were placed on the date of publication, type of smartphone, or participant demographics. In total, 21 papers were reviewed to synthesize themes and approaches used and to identify future research priorities. The validity and reliability of smartphone-based accelerometry data have been assessed against motion capture, pressure walkways, and IMUs as 'gold standard' technology and they have been found to be accurate and reliable. This suggests that smartphone accelerometers can provide a cheap and accurate alternative to gather kinematic data, which can be used in ecologically valid environments to potentially increase diversity in research participation. However, some studies suggest that body placement may affect the accuracy of the result, and that position data correlate better than actual acceleration values, which should be considered in any future implementation of smartphone technology. Future research comparing different capture frequencies and resulting noise, and different walking surfaces, would be useful.

A long short-term memory modeling-based compensation method for muscle synergy

Muscle synergy containing temporal and spatial patterns of muscle activity has been frequently used in prediction of kinematic characteristics. However, there is often some discrepancy between the predicted results based on muscle synergy and the actual movement performance. This study aims to propose a new method for compensating muscle synergy that allows the compensated synergy signal to predict kinematic characteristics more accurately. The study used the change of direction in running as background. Non-negative matrix factorisation was used to extract the muscle synergy during the change of direction at different angles. A non-linear association between synergy and the height of pelvic mass centre was established using long and short-term memory neural networks. Based on this model, the height fluctuations of the pelvic centre of mass are used as input and predict the fluctuations of the synergy which were used to compensate for the original synergy in different ways. The accuracy of the synergies compensated in different ways in predicting pelvic centre of mass movement was then assessed by back propagation neural networks. It was found that the compensated synergy significantly improves accuracy in predicting pelvic centre of mass displacement (R2, p < 0.05). The predicted results of all-compensation are significantly different from actual performance in the end-swing (p < 0.05). The predicted results of half-compensation do not differ significantly from the actual performance, and its damage to the original synergy is smaller and does not increase with angle compared to all-compensation. The all-compensation may be affected by individual variability and lead to increased errors. The half-compensation can improve the predictive accuracy of the synergy while reducing the adjustment to the original synergy.

Robust deep learning-based gait event detection across various pathologies

The correct estimation of gait events is essential for the interpretation and calculation of 3D gait analysis (3DGA) data. Depending on the severity of the underlying pathology and the availability of force plates, gait events can be set either manually by trained clinicians or detected by automated event detection algorithms. The downside of manually estimated events is the tedious and time-intensive work which leads to subjective assessments. For automated event detection algorithms, the drawback is, that there is no standardized method available. Algorithms show varying robustness and accuracy on different pathologies and are often dependent on setup or pathology-specific thresholds. In this paper, we aim at closing this gap by introducing a novel deep learning-based gait event detection algorithm called IntellEvent, which shows to be accurate and robust across multiple pathologies. For this study, we utilized a retrospective clinical 3DGA dataset of 1211 patients with four different pathologies (malrotation deformities of the lower limbs, club foot, infantile cerebral palsy (ICP), and ICP with only drop foot characteristics) and 61 healthy controls. We propose a recurrent neural network architecture based on long-short term memory (LSTM) and trained it with 3D position and velocity information to predict initial contact (IC) and foot off (FO) events. We compared IntellEvent to a state-of-the-art heuristic approach and a machine learning method called DeepEvent. IntellEvent outperforms both methods and detects IC events on average within 5.4 ms and FO events within 11.3 ms with a detection rate of ≥ 99% and ≥ 95%, respectively. Our investigation on generalizability across laboratories suggests that models trained on data from a different laboratory need to be applied with care due to setup variations or differences in capturing frequencies.

The Influence of Experience on Neuromuscular Control of the Body When Cutting at Different Angles

Cutting is an offensive technique commonly used in football and basketball to pass the opponent's defence by changing direction quickly in running. This paper aims to investigate the effect of experience and angle on the neuromuscular control strategies of the trunk and lower limbs during cutting. Non-negative matrix factorisation and K-means were used to extract muscle synergies (muscles that are activated in parallel) of 12 subjects with cut experience and 9 subjects without experience based on the sEMG signal collected from cutting at three cut angles (45°, 90°, and 135°), which was also mapped into the spinal motor output. Uncontrolled manifold analysis was used to establish the relationship between muscle synergies and COP. This study found that experienced subjects tended to use the lower limb muscles rather than the postural muscles as stabiliser muscles compared to novices. Experienced subjects can recruit an additional set of muscle synergy to cope with large-angle cuts. In addition, experienced subjects can activate the second muscle synergy, involving the hip and ankle stabilisation muscles, in advance to improve postural stability when cutting in large-angle. Synergy index of experienced subjects dropped rapidly before the quick stop and was relatively high during the change of direction. These results suggest that experience can modify the postural stabilisation mechanisms during cutting, and prompt the lower limb muscle synergy to produce anticipatory adjustment to improve postural stability in the anterior-posterior and internal-external directions.

Peak Tibiofemoral Contact Forces Estimated Using IMU-Based Approaches Are Not Significantly Different from Motion Capture-Based Estimations in Patients with Knee Osteoarthritis

Altered tibiofemoral contact forces represent a risk factor for osteoarthritis onset and progression, making optimization of the knee force distribution a target of treatment strategies. Musculoskeletal model-based simulations are a state-of-the-art method to estimate joint contact forces, but they typically require laboratory-based input and skilled operators. To overcome these limitations, ambulatory methods, relying on inertial measurement units, have been proposed to estimated ground reaction forces and, consequently, knee contact forces out-of-the-lab. This study proposes the use of a full inertial-capture-based musculoskeletal modelling workflow with an underlying probabilistic principal component analysis model trained on 1787 gait cycles in patients with knee osteoarthritis. As validation, five patients with knee osteoarthritis were instrumented with 17 inertial measurement units and 76 opto-reflective markers. Participants performed multiple overground walking trials while motion and inertial capture methods were synchronously recorded. Moderate to strong correlations were found for the inertial capture-based knee contact forces compared to motion capture with root mean square error between 0.15 and 0.40 of body weight. The results show that our workflow can inform and potentially assist clinical practitioners to monitor knee joint loading in physical therapy sessions and eventually assess long-term therapeutic effects in a clinical context.

Gait-phase specific transverse-plane momenta generation during pre-planned and late-cued 90 degree turns while walking

Turning while walking is ubiquitous and requires linear and angular momenta generation to redirect the body's trajectory and rotate towards the new direction of travel. This study examined strategies that healthy young adults used during each gait phase to generate transverse-plane momenta during pre-planned and late-cued 90° turns. During leftward turns, we expected that momenta would be generated most during the gait phases known to generate leftward linear and angular momenta during straight line gait. We found distinct roles of gait phases towards generating momenta during turns that partially supported our hypotheses. Supporting one hypothesis, the change in transverse-plane angular momentum and average moment were greater during double support with the left foot in front vs. other gait phases. Also, the change in leftward linear momentum and average leftward force were greater during right single support vs. other gait phases during straight-line gait and late-cued turns. However, during pre-planned turns, the average leftward force was not significantly greater during right single support vs. other gait phases. Overall, transverse-plane angular momentum generation during turns is similar to its generation during straight-line gait, suggesting that healthy young adults can leverage momenta control strategies used during straight-line gait during turns.

The choice of reference frame alters interpretations of turning gait and stability

Humans regularly follow curvilinear trajectories during everyday ambulation. However, globally-defined and locally-defined reference frames fall out of alignment during turning gait, which complicates spatiotemporal and biomechanical analyses. Thus, the choice of the locally-defined reference frame is an important methodological consideration. This study investigated how different definitions of reference frame change the results and interpretations of common gait measures during turning. Nine healthy adults completed two walking trials around a circular track. Kinematic data were collected via motion capture and used to calculate step length, step width, anteroposterior margin of stability, and mediolateral margin of stability using three different locally-defined reference frames: walkway-fixed, body-fixed, and trajectory-fixed. Linear-mixed effects models compared the effect of reference frame on each gait measure, and the effect of reference frame on conclusions about a known effect of turning gait - asymmetrical stepping patterns. All four gait measures differed significantly across the three reference frames. A significant interaction of reference frame and step type (i.e. inside vs outside step) on step length (p < 0.001), anteroposterior margin of stability (p < 0.001), and mediolateral margin of stability (p < 0.001) indicated conclusions about asymmetry differed based on the choice of reference frame. The choice of reference frame will change the calculated gait measures and may alter the conclusions of studies investigating turning gait. Care should be taken when comparing studies that used different reference frames, as results cannot be easily harmonized. Future studies of turning gait need to justify and detail their choice of reference frame.

Spatiotemporal parameters during turning gait maneuvers of different amplitudes in young and elderly healthy adults: A descriptive and comparative study

BACKGROUND

Turning during walking adds complexity to gait and has been little investigated until now. Research question What are the differences in spatiotemporal parameters between young and elderly healthy adults performing quarter-turns (90°), half-turns (180°) and full-turns (360°)?

METHODS

The spatiotemporal parameters of 10 young and 10 elderly adults were recorded in a laboratory while turning at 90°, 180° and 360°. Two-way mixed ANOVA were performed to determine the effect of age and turning amplitude.

RESULTS

Elderly were slower and needed more steps and time to perform turns of larger amplitude than young adults. Cadence did not differ across age or across turning amplitude. Generally, in the elderly, the spatial parameters were smaller and the temporal parameters enhancing stability (i.e., double-support phase and stance/cycle ratio) were larger, especially for turns of larger amplitudes. In elderly adults, the variability of some spatial parameters was decreased, whereas the variability of some temporal parameters was increased. Stride width of the external leg showed the most substantial difference between groups. Most parameters differed between turning at 90° and turning at larger amplitudes (180°, 360°). Significance This study extends the characterization of turning biomechanics with respect to ageing. It also suggested paying particular attention to the turning amplitude. Finally, the age-related differences may pave the way for new selective rehabilitation protocols in the elderly.

Frontal plane balance during pre-planned and late-cued 90 degree turns while walking

This study evaluated frontal-plane dynamic balance control during 90° left turns while walking. Ten healthy young adults performed straight-line gait, pre-planned turns, and turns cued visually (late-cued turns). We quantified rotational balance control via the range of frontal-plane angular momentum (Hf) about the center of mass (COM), and the relative positioning of the COM and the feet using the horizontal distance from the COM to the lateral edge of the base of support (lateral distance) and the mediolateral margin of stability (MOSml). We hypothesized that the Hf range would increase and the lateral distance and MOSml minima would decrease during each turn type vs. straight-line gait and during late-cued vs. pre-planned turns. We found that the range of Hf was significantly greater during each turn type vs. straight-line gait and during late-cued vs. pre-planned turns. Also, the lateral distance minima were significantly smaller during turns vs. straight-line gait, and during pre-planned vs. late-cued turns. Our hypotheses about MOSml were partially supported because the MOSml minima patterns were specific to right or left steps and were not significantly different between straight-line gait and pre-planned turns overall, but the right step's MOSml minima were more negative during late-cued vs. pre-planned turns and between either turn and straight-line gait. Finally, we observed slower gait speeds, fewer footfalls, shorter turn phase duration, and different turn strategies used during late-cued vs. pre-planned turns. Overall, these findings reveal multifaceted control of frontal-plane balance during turns encountered during everyday mobility.

An Algorithm for Accurate Marker-Based Gait Event Detection in Healthy and Pathological Populations During Complex Motor Tasks

There is growing interest in the quantification of gait as part of complex motor tasks. This requires gait events (GEs) to be detected under conditions different from straight walking. This study aimed to propose and validate a new marker-based GE detection method, which is also suitable for curvilinear walking and step negotiation. The method was first tested against existing algorithms using data from healthy young adults (YA, n = 20) and then assessed in data from 10 individuals from the following five cohorts: older adults, chronic obstructive pulmonary disease, multiple sclerosis, Parkinson’s disease, and proximal femur fracture. The propagation of the errors associated with GE detection on the calculation of stride length, duration, speed, and stance/swing durations was investigated. All participants performed a variety of motor tasks including curvilinear walking and step negotiation, while reference GEs were identified using a validated methodology exploiting pressure insole signals. Sensitivity, positive predictive values (PPV), F1-score, bias, precision, and accuracy were calculated. Absolute agreement [intraclass correlation coefficient (ICC2,1)] between marker-based and pressure insole stride parameters was also tested. In the YA cohort, the proposed method outperformed the existing ones, with sensitivity, PPV, and F1 scores ≥ 99% for both GEs and conditions, with a virtually null bias (&lt;10 ms). Overall, temporal inaccuracies minimally impacted stride duration, length, and speed (median absolute errors ≤1%). Similar algorithm performances were obtained for all the other five cohorts in GE detection and propagation to the stride parameters, where an excellent absolute agreement with the pressure insoles was also found (ICC2,1=0.817− 0.999). In conclusion, the proposed method accurately detects GE from marker data under different walking conditions and for a variety of gait impairments.

A data-driven approach for detecting gait events during turning in people with Parkinson's disease and freezing of gait

BACKGROUND

Manual annotation of initial contact (IC) and end contact (EC) is a time consuming process. There are currently no robust techniques available to automate this process for Parkinson's disease (PD) patients with freezing of gait (FOG).

OBJECTIVE

To determine the validity of a data-driven approach for automated gait event detection.

METHODS

15 freezers were asked to complete several straight-line and 360 degree turning trials in a 3D gait laboratory during the off-period of their medication cycle. Trials that contained a freezing episode were indicated as freezing trials (FOG) and trials without a freezing episode were termed as functional gait (FG). Furthermore, the highly varied gait data between onset and termination of a FOG episode was excluded. A Temporal Convolutional Neural network (TCN) was trained end-to-end with lower extremity kinematics. A Bland-Altman analysis was performed to evaluate the agreement between the results of the proposed model and the manual annotations.

RESULTS

For FOG-trials, F1 scores of 0.995 and 0.992 were obtained for IC and EC, respectively. For FG-trials, F1 scores of 0.997 and 0.999 were obtained for IC and EC, respectively. The Bland-Altman plots indicated excellent timing agreement, with on average 39% and 47% of the model predictions occurring within 10 ms from the manual annotations for FOG-trials and FG-trials, respectively.

SIGNIFICANCE

These results indicate that our data-driven approach for detecting gait events in PD patients with FOG is sufficiently accurate and reliable for clinical applications.

Lumbar and thoracic kinematics during step-up: Comparison of three-dimensional angles between patients with chronic low back pain and asymptomatic individuals

While alterations in spinal kinematics have been repeatedly observed in patients with chronic low back pain (CLBP), their exact nature is still unknown. Specifically, there is a need for comprehensive assessments of multisegment spinal angles during daily-life activities. The purpose of this exploratory study was to characterize three-dimensional angles at the lower lumbar, upper lumbar, lower thoracic, and upper thoracic joints in CLBP patients and asymptomatic controls during stepping up with three different step heights. Spinal angles of 10 patients with nonspecific CLBP (six males; 38.7 ± 7.2 years old, 22.3 ± 1.6 kg/m² ) and 11 asymptomatic individuals (six males; 36.7 ± 5.4 years old, 22.9 ± 3.8 kg/m² ) were measured in a laboratory using a camera-based motion capture system. Seven out of the 12 angle curves had characteristic patterns, leading to the identification of 20 characteristic peaks. Comparing peak amplitudes between groups revealed statistically significantly smaller sagittal- and frontal-plane angles in the patient group at the upper lumbar joint with the two higher steps and at the lower lumbar joint with the higher step. Significantly reduced angles were also observed in sagittal plane at the upper thoracic joint with the two smaller steps. Moreover, a higher number of significant differences between groups was detected with the two higher steps than with the smallest step. In conclusion, this study showed the value of a comprehensive description of spinal angles during step-up tasks and provided insights into the alterations with CLBP. These preliminary results support prior research suggesting that CLBP rehabilitation should facilitate larger amplitudes of motion during functional activities.

Comparison of three kinematic gait event detection methods during overground and treadmill walking for individuals post stroke

Detecting gait events using ground reaction forces (i.e. kinetic detection) is the gold standard, but it is not always possible. Kinematic methods exist; however, accuracy of these methods in stroke survivors during treadmill and overground walking is unknown. Thus, this study compared the accuracy of three kinematic methods during overground and treadmill walking in stroke survivors. Heel strike and toe off were calculated bilaterally using three kinematic methods (horizontal sacral-heel distance, horizontal ankle-heel distance, and horizontal velocity) and a kinetic method for ten stroke survivors. We calculated true and absolute error for each kinematic method relative to the kinetic method to evaluate accuracy. Repeated-measures ANOVAs compared the absolute error between the different methods for each condition. There was a significant effect of method for all conditions except heel strike during treadmill walking. Post hoc tests showed ankle-heel distance detected heel strike with significantly less error than the other methods during overground walking (p < 0.05). Ankle-heel distance identified 93.0% and 77.8% of gait events within 50 ms of the kinetic event for overground and treadmill walking, respectively. Sacral-heel distance detected toe-off with significantly less error than the other methods during overground and treadmill walking (p < 0.05) and identified 87.2% and 90.3% of gait events within 50 ms of the kinetic event for overground and treadmill walking, respectively. Results suggest that ankle-heel distance and sacral-heel distance accurately detect heel strike and toe-off, respectively, in stroke survivors.

A Determination Method for Gait Event Based on Acceleration Sensors

A gait event is a crucial step towards the effective assessment and rehabilitation of motor dysfunctions. However, for the data acquisition of a three-dimensional motion capture (3D Mo-Cap) system, the high cost of setups, such as the high standard laboratory environment, limits widespread clinical application. Inertial sensors are increasingly being used to recognize and classify physical activities in a variety of applications. Inertial sensors are now sufficiently small in size and light in weight to be part of a body sensor network for the collection of human gait data. The acceleration signal has found important applications in human gait recognition. In this paper, using the experimental data from the heel and toe, first the wavelet method was used to remove noise from the acceleration signal, then, based on the threshold of comprehensive change rate of the acceleration signal, the signal was primarily segmented. Subsequently, the vertical acceleration signals, from heel and toe, were integrated twice, to compute their respective vertical displacement. Four gait events were determined in the segmented signal, based on the characteristics of the vertical displacement of heel and toe. The results indicated that the gait events were consistent with the synchronous record of the motion capture system. The method has achieved gait event subdivision, while it has also ensured the accuracy of the defined gait events. The work acts as a valuable reference, to further study gait recognition.