Heel-strike Times Research Articles

Online Adaptive Prediction of Human Motion Intention Based on sEMG.

Accurate and reliable motion intention perception and prediction are keys to the exoskeleton control system. In this paper, a motion intention prediction algorithm based on sEMG signal is proposed to predict joint angle and heel strike time in advance. To ensure the accuracy and reliability of the prediction algorithm, the proposed method designs the sEMG feature extraction network and the online adaptation network. The feature extraction utilizes the convolution autoencoder network combined with muscle synergy characteristics to get the high-compression sEMG feature to aid motion prediction. The adaptation network ensures the proposed prediction method can still maintain a certain prediction accuracy even the sEMG signals distribution changes by adjusting some parameters of the feature extraction network and the prediction network online. Ten subjects were recruited to collect surface EMG data from nine muscles on the treadmill. The proposed prediction algorithm can predict the knee angle 101.25 ms in advance with 2.36 degrees accuracy. The proposed prediction algorithm also can predict the occurrence time of initial contact ms in advance. Meanwhile, the proposed feature extraction method can achieve accuracy of sEMG reconstruction and can guarantee accuracy even when the distribution of sEMG is changed without any adjustment. The online adaptation network enhances the accuracy of sEMG reconstruction of CAE to and decreases the angle prediction error from to . The proposed method achieves effective motion prediction in advance and alleviates the influence caused by the non-stationary of sEMG.

WeAllWalk

We introduce WeAllWalk, a dataset of inertial sensor time series collected from blind and sighted walkers using a long cane or a guide dog. Ten blind volunteers (seven using a long cane, one using a guide dog, and two alternating use of a long cane and of a guide dog) as well as five sighted volunteers contributed to the data collection. The participants walked through fairly long and complex indoor routes that included obstacles to be avoided and doors to be opened. Inertial data were recorded by two iPhone 6s carried by our participants in their pockets and carefully annotated. Ground-truth heel strike times were measured by two small inertial sensor units clipped to the participants’ shoes. We also present an in-depth comparative analysis of various step counting and turn detection algorithms as tested on WeAllWalk. This analysis reveals interesting differences between the achievable accuracy of step and turn detection across different communities of sighted and blind walkers.

Formulation and viscoelasticity of mineralised hydrogels for use in bone-cartilage interfacial reconstruction.

Articular cartilage is a viscoelastic tissue whose structural integrity is important in maintaining joint health. To restore the functionality of osteoarthritic joints it is vital that regenerative strategies mimic the dynamic loading response of cartilage and bone. Here, a rotating simplex model was employed to optimise the composition of agarose and gellan hydrogel constructs structured with hydroxyapatite (HA) with the aim of obtaining composites mechanically comparable to human cartilage in terms of their ability to dissipate energy. Addition of ceramic particles was found to reinforce both matrices up to a critical concentration (< 3w/v%). Beyond this, larger agglomerates were formed, as evidenced by micro computed tomography data, which acted as stress risers and reduced the ability of composites to dissipate energy demonstrated by a reduction in tan δ values. A maximum compressive modulus of 450.7±24.9 kPa was achieved with a composition of 5.8w/v% agarose and 0.5w/v% HA. Interestingly, when loaded dynamically (1-20Hz) this optimised formulation did not exhibit the highest complex modulus instead a sample with a higher concentration of mineral was identified (5.8w/v% agarose and 25w/v% HA). Thus, demonstrating the importance of examining the mechanical behaviour of biomaterials under conditions representative of physiological environments. While the complex moduli of the optimised gellan (1.0± 0.2MPa at 1Hz) and agarose (1.7 ± 0.2MPa at 1Hz) constructs did not match the complex moduli of healthy human cartilage samples (26.3 ± 6.5MPa at 1Hz), similar tan δ values were observed between 1 and 5Hz. This is promising since these frequencies represent the typical heel strike time of the general population. In summary, this study demonstrates the importance of considering more than just the strength of biomaterials since tissues like cartilage play a more complex role.

Faster Detection of Step Initiation for the Lower Limb Exoskeleton with Vertical GRF Events

We propose a new approach called as a peak time approach for faster detection of step initiation for the lower limb exoskeleton. As faster detection of step initiation is an important criterion in evaluating the lower limb exoskeleton, many studies have investigated approaches to detect step initiation faster, including using electromyography, the center of pressure, the heel-off time and the toe-off time. In this study, we will utilize vertical ground reaction force events to detect step initiation, and compare our approach with prior approaches. Additionally, we will predict the first step's heel strike time with vertical ground reaction force events from multiple regression equations to support our approach. The lower limb exoskeleton should assist the operator's movement much faster and more reliably with our approach.

‘Human paced’ walking: Followers adopt stride time dynamics of leaders

Isochronous cueing is widely used in gait rehabilitation even though it alters the stride-time dynamics toward anti-persistent rather than the persistent, fractal fluctuations characteristic of human walking. In the present experiment we tested an alternative cueing method: pacing by a human. To this end, we formed sixteen pairs of walkers based on their preferred stride frequency. Each pair consisted of a designated “leader” and a “follower” who was instructed to synchronize his or her steps to those of the leader. Heel strike times were detected with tiny footswitches, and Detrended Fluctuation Analysis (DFA) was applied to estimate fractal exponents of stride-time series. To ensure that the stride-time dynamics of the follower matched those of the leader, the latter was structurally modified by artificial cueing via either an isochronous metronome or a fractal metronome, in contrast to self-paced walking. Mean relative phases between followers and leaders were close to 0°, confirming that followers effectively synchronized their footfalls with those of the leaders. Mean fractal exponents were not statistically different between followers and leaders in any condition and highly correlated, suggesting that followers matched their stride-time structure to that of leaders. Our results open perspectives for alternative, more natural cueing protocols for gait rehabilitation.

The Faster Detection of the Step Initiation and the Prediction of the First Step’s Heel Strike Time with the Vertical GRF

A new approach for the detection of the step initiation in the lower extremity exoskeleton is presented. As the detection of the step initiation is the important factor for the lower extremity exoskeleton to shadow the operator’s movement as soon as possible, many studies have been done to detect it faster by using heel-off time or toe-off time. We detect the step initiation faster than other approaches with the vertical ground reaction forces. Also, we predict the first step’s heel strike time with the regression equations based on the vertical ground reaction forces as soon as we detect the step initiation. It could enable the lower extremity exoskeleton to shadow the operator’s movement much faster.

Two simple methods for determining gait events during treadmill and overground walking using kinematic data

The determination of gait events such as heel strike and toe-off provide the basis for defining stance and swing phases of gait cycles. Two algorithms for determining event times for treadmill and overground walking based solely on kinematic data are presented. Kinematic data from treadmill walking trials lasting 20–45 s were collected from three subject populations (healthy young, n = 7; multiple sclerosis, n = 7; stroke, n = 4). Overground walking trials consisted of approximately eight successful passes over two force plates for a healthy subject population ( n = 5). Time of heel strike and toe-off were determined using the two new computational techniques and compared to events detected using vertical ground reaction force (GRF) as a gold standard. The two algorithms determined 94% of the treadmill events from healthy subjects within one frame (0.0167 s) of the GRF events. In the impaired populations, 89% of treadmill events were within two frames (0.0334 s) of the GRF events. For overground trials, 98% of events were within two frames. Automatic event detection from the two kinematic-based algorithms will aid researchers by accurately determining gait events during the analysis of treadmill and overground walking.

Altered Neuromuscular Control and Ankle Joint Kinematics during Walking in Subjects with Functional Instability of the Ankle Joint

Background The ankle joint requires very precise neuromuscular control during the transition from terminal swing to the early stance phase of the gait cycle. Altered ankle joint arthrokinematics and muscular activity have been cited as potential factors that may lead to an inversion sprain during the aforementioned time periods. However, to date, no study has investigated patterns of muscle activity and 3D joint kinematics simultaneously in a group of subjects with functional instability compared with a noninjured control group during these phases of the gait cycle. Purpose To compare the patterns of lower limb 3D joint kinematics and electromyographic activity during treadmill walking in a group of subjects with functional instability with those observed in a control group. Study Design Controlled laboratory study. Methods Three-dimensional angular velocities and displacements of the hip, knee, and ankle joints, as well as surface electromyography of the rectus femoris, peroneus longus, tibialis anterior, and soleus muscles, were recorded simultaneously while subjects walked on a treadmill at a velocity of 4 km/h. Results Before heel strike, subjects with functional instability exhibited a decrease in vertical foot-floor clearance (12.62 vs 22.84 mm; P <. 05), as well as exhibiting a more inverted position of the ankle joint before, at, and immediately after heel strike (1.69°, 2.10°, and -0.09° vs -1.43°, -1.43°, and -2.78°, respectively [minus value = eversion]; P <. 05) compared with controls. Subjects with functional instability were also observed to have an increase in peroneus longus integral electromyography during the post–heel strike time period (107.91%[.dotmath]millisecond vs 64.53%[.dotmath]millisecond; P <. 01). Conclusion The altered kinematics observed in this study could explain the reason subjects with functional instability experience repeated episodes of ankle inversion injury in situations with only slight or no external provocation. It is hypothesized that the observed increase in peroneus longus activity may be the result of a change in preprogrammed feed-forward motor control.

Differences in gait parameters at a preferred walking speed in healthy subjects due to age, height and body weight.

The objective of our cross-sectional study was to investigate the changes associated with age and gender in walking speed, stride length and cadence of healthy women and men over the adult age range, and establish the effects of anthropometric indices such as height and body weight. We examined 118 women and 121 men (age range, 19-90 years). Subjects walked at their preferred speed over a 12-meter walkway crossing two Kistler force plates: cadence was calculated from heel strike times recorded from the Kistler force plates; walking speed was measured using an infrared reflecting system; and stride length was calculated from the walking speed and cadence. Older healthy subjects had lower values for walking speed and stride length than younger subjects. While there is little difference in the percentage reduction between women and men over the adult age range. the absolute values for walking speed are lower in women than men at all ages. In women, the percentage of explained variance for decline in walking speed was 30%, and for decline in stride length 400%. If body weight was also taken into account, the percentage of explained variance for walking speed was 37%, and for stride length 59%. A similar calculation for men yields 34% for decline in walking speed, and 42% for decline in stride length. Cadence was not associated with age, height and body weight. The standard errors for the estimates of walking speed in both women and men, respectively, are reduced by 8% and 3% using the multiple regression technique. The corresponding standard errors for stride length were reduced by, respectively, 19% and 13% if height in either sexes, or height and body weight in women, were taken into account. In conclusion, preferred walking speed and stride length decline with age in healthy people. Lower values found in old healthy subjects partly contributed to the difference in height and body weight between old and young subjects. Cadence was not correlated with age, height and body weight.