A Study on Reference Range of Healthy Subjects for Detection and Evaluation of Abnormal Foot Movement During Walking in Hemiplegic Subject Using Inertial Sensors

To assess the kinetic and kinematic characteristics of hemiplegic stroke patients' gait initiation patterns during the various gait initiation phases. Gait initiation was studied in 3 hemiplegic subjects with a spastic equinus varus foot and 3 control subjects. Temporal and kinetic analysis of gait initiation was performed with 2 AMTI force plates, and kinematic analysis of gait initiation with an ELITE optoelectronic system. A one-way ANOVA was performed directly on the phase durations, forces, centre of pressure displacements, stride length, and ankle motion range. Duration of the monopodal phase was shorter in hemiplegic patients when the affected leg rather than the sound one was used as the supporting leg. Propulsion forces were exerted by the hemiplegic patients' sound leg during the postural phase. Hemiplegic patients' body weight was supported more by the sound leg than by the affected leg. Knee was lifted higher on the affected side during the swing phase to compensate for the equinus. Initial contact was performed with a flat foot on the affected side. Quantitative data obtained on the gait initiation phase suggest that hemiplegic patients develop asymmetrical adaptive posturo-motor strategies to compensate for their impairments.

Measurement with a single inertial motion measurement unit (IMU) can be useful for monitoring gait information in rehabilitation at hospital or healthcare at home. This study focused on stride length estimation with an IMU because our preliminary study showed different estimation errors between some hemiplegic subjects. This was considered to be caused by differences of foot movements during walking between healthy subjects and paralyzed subjects. Therefore, this study aimed at evaluating estimation error of stride lengths under different calculation methods of rotation matrix that is needed to obtain foot orientation. Experimental results showed that the rotation matrix calculated from Euler angles could be effective for gaits of healthy subjects, but not for some of paralyzed subjects. The rotation matrix calculated from quaternion was shown to be effective for both healthy and paralyzed subjects. Mean absolute error of stride length estimation with the quaternion-based method was smaller than about 5% for healthy subjects and the non-paralyzed side of hemiplegic subjects and smaller than 6% for paralyzed side of the hemiplegic subjects. Average values of estimation error were less than -4% for 3 hemiplegic subjects. Stride length estimation method and correction method of integration error would be required to be evaluated with many motor disabled subjects.

Despite the prevalence of forefoot related problems in athletes, there are few comprehensive summaries on examination and intervention strategies for those with forefoot related symptoms. While many factors may contribute to pathology and injury, the presence of abnormal foot alignment can negatively affect lower extremity biomechanics and be associated with injuries. Physical therapists may use the characteristics associated abnormal pronation or abnormal supination to describe the movement system disorder and serve as a guide for evaluating and managing athletes with forefoot pathologies. Athletes with an abnormal pronation movement system diagnosis typically demonstrate foot hypermobility, have decreased strength of the tibialis posterior muscle, and present with a medially rotated lower extremity position. Athletes with abnormal supination movement system diagnosis typically demonstrate foot hypomobility, decreased strength of the fibularis muscles, and a laterally rotated lower extremity position. Interventions of manual therapy, taping, strengthening exercises, and neuromuscular reeducation can be directed at the identified impairments and abnormal movements. The purpose of this clinical commentary is to integrate a movement system approach in pathoanatomical, evaluation, and intervention considerations for athletes with common forefoot pathologies, including stress fractures, metatarsalgia, neuroma, turf toe, and sesamoiditis. By applying a prioritized, objective problem list and movement system diagnosis, emphasis is shifted from a pathoanatomical diagnosis-based treatment plan to a more impairment and movement focused treatment.Level of Evidence5

The accuracy of inertial measurement units (IMUs) in measuring foot motion in the sagittal plane has been previously compared to motion capture systems for healthy and impaired participants. Studies analyzing the accuracy of IMUs in measuring foot motion in the frontal plane are lacking. Drop foot patients use functional electrical stimulation (FES) to improve walking and reduce the risk of tripping and falling by improving foot dorsiflexion and inversion-eversion. Therefore, this study aims to evaluate if IMUs can estimate foot angles in the frontal and sagittal planes to help understand the effects of FES on drop foot patients in clinical settings. Two Gait Up sensors were used to estimate foot dorsi-plantar flexion and inversion-eversion angles in 13 unimpaired participants and 9 participants affected by drop foot while walking 6 m in a straight line. Unimpaired participants were asked to walk normally at three self-selected speeds and to simulate drop foot. Impaired participants walked with and without FES assistance. Foot angles estimated by the IMUs were compared with those measured from a motion capture system using curve RMSE and Bland Altman limits of agreement. Between participant groups, overall errors of 7.95° ± 3.98°, −1.12° ± 4.20°, and 1.38° ± 5.05° were obtained for the dorsi-plantar flexion range of motion, dorsi-plantar flexion at heel strike, and inversion-eversion at heel strike, respectively. The between-system comparison of their ability to detect dorsi-plantar flexion and inversion-eversion differences associated with FES use on drop foot patients provided limits of agreement too large for IMUs to be able to accurately detect the changes in foot kinematics following FES intervention. To the best of the authors' knowledge, this is the first study to evaluate IMU accuracy in the estimation of foot inversion-eversion and analyze the potential of using IMUs in clinical settings to assess gait for drop foot patients and evaluate the effects of FES. From the results, it can be concluded that IMUs do not currently represent an alternative to motion capture to evaluate foot kinematics in drop foot patients using FES.

In this paper we investigate the use of optimal control techniques to improve Functional Electrical Stimulation (FES) for drop foot correction on hemiplegic patients. A model of the foot and the tibialis anterior muscle, the contraction of which is controlled by electrical stimulation has been established and is used in the optimal control problem. The novelty in this work is the use of the ankle accelerations and shank orientations (so-called external states) in the model, which have been measured on hemiplegic patients in a previous experiment using Inertial Measurement Units (IMUs). The optimal control problem minimizes the square of muscle excitations which serves the overall goal of reducing energy consumption in the muscle. In a first step, an offline optimal control problem is solved for test purposes and shows the efficiency of the FES optimal control for drop foot correction. In a second step, a Nonlinear Model Predictive Control (NMPC) problem - or online optimal control problem, is solved in a simulated environment. While the ulitmate goal is to use NMPC on the real system, i.e. directly on the patient, this test in simulation was meant to show the feasibility of NMPC for online drop foot correction. In the optimization problem, a set of fixed constraints of foot orientation was applied. Then, an original adaptive constraint taking into account the current ankle height, was introduced and tested. Comparisons between results under fixed and adaptive constraints highlight the advantage of the adaptive constraints in terms of energy consumption, where its quadratic sum of controls, obtained by NMPC, was three times lower than with the fixed constraint. This feasibility study was a first step in application of NMPC on real hemiplegic patients for online FES-based drop foot correction. The adaptive constraints method presents a new and efficient approach in terms of muscular energy consumption minimization.

Running is a popular form of physical activity but can increase an individual's lower-extremity injury risk. Running gait analysis via inertial measurement units (IMUs) is a method for collecting important gait data that is related to developing lower-extremity injuries, such as increased load from low step rate (SR), and long stride length (SL). IMU data can be derived from both foot- and shank-placed IMUs, but foot-placed sensors (RunScribe IMUs) need validation against shank-placed sensors. Determine criterion validity of RunScribe foot-placed IMUs against MyoMotion shank-placed IMU for SR and SL. cross-sectional laboratory study. Nine participants (5 males, 4 females; age: 28.33 [5.78]; height: 1.75 [0.11]; mass: 74.06 [16.24]) volunteered for our study. Following a 5-minute warm-up, participants ran on a treadmill for 5minutes at a self-selected speed. After ∼2.5minutes, MyoMotion data were collected for 10seconds. The RunScribe IMUs collected data throughout the full duration of the run. Criterion validity of SR and SL between the foot- and shank-placed IMUs was determined using bivariate Pearson correlations, intraclass correlation coefficients (3,1), and Bland-Altman plots with 95% limits of agreement analysis. A very strong correlation for SR (r = .90, N = 9, P ≤ .001), and a strong correlation for SL (r = .80, N = 9, P < .001) were found between the foot and shank-placed IMUs. Excellent reliability was found for SR (intraclass correlation coefficient = .91, P ≤ .001, 95% CI, .639-.978), and good reliability was found for SL (intraclass correlation coefficient = .800, P = .003, 95% CI, .340-.951) between the foot and shank-placed IMUs. The mean difference of SR and SL was -2.111 and -0.142, respectively, indicating good agreement between the foot and shank-placed IMUs. Foot-placed RunScribe IMUs are a valid alternative for measuring SR and SL compared with shank-placed IMUs.

The purpose of this study was to test stride length measurement only with inertial sensors to for the simple gait evaluation system developed in our previous study to support rehabilitation, healthcare and so on. In this paper, a calculation method of the stride length was developed, in which acceleration and angular velocity signals of the foot were used. The integration period of the acceleration for calculation of each stride length was automatically detected by the acceleration signal. First, the measurement method was evaluated in 10 m walking of 6 neurologically intact subjects. The average values of error and absolute error of measured stride lengths were 0.38±4.77% and 3.36±3.04%, respectively. Correlation coefficient of the measured length with the reference data was 0.910 and the slope of the regression equation was 0.978. Then, stride lengths of a hemiplegic subject were measured in 10 m walking with and without FES-assisted foot drop correction. Although there was no difference in stride length between with and without the FES-assist, the calculated data from inertial sensor signals supported that the time for 10 m walking measured by therapists decreased when the subject walked with the FES-assist. It was expected that the stride length measurement only with inertial sensor would be practical, and it can be implemented easily.

Gait Improvement in Patients with Cerebral Palsy by Visual and Auditory Feedback

A Basic Study on Evaluation of Abnormal Foot Movements in Hemiplegic Gait Using Inertial Sensors

Inertial measurement units (IMUs) fixed to the lower limbs have been reported to provide accurate estimates of stride lengths (SLs) during walking. Due to technical challenges, validation of such estimates in running is generally limited to speeds (well) below 5 m·s−1. However, athletes sprinting at (sub)maximal effort already surpass 5 m·s−1 after a few strides. The present study aimed to develop and validate IMU-derived SLs during maximal linear overground sprints. Recreational athletes (n = 21) completed two sets of three 35 m sprints executed at 60, 80, and 100% of subjective effort, with an IMU on the instep of each shoe. Reference SLs from start to ~30 m were obtained with a series of video cameras. SLs from IMUs were obtained by double integration of horizontal acceleration with a zero-velocity update, corrected for acceleration artefacts at touch-down of the feet. Peak sprint speeds (mean ± SD) reached at the three levels of effort were 7.02 ± 0.80, 7.65 ± 0.77, and 8.42 ± 0.85 m·s−1, respectively. Biases (±Limits of Agreement) of SLs obtained from all participants during sprints at 60, 80, and 100% effort were 0.01% (±6.33%), −0.75% (±6.39%), and −2.51% (±8.54%), respectively. In conclusion, in recreational athletes wearing IMUs tightly fixed to their shoes, stride length can be estimated with reasonable accuracy during maximal linear sprint acceleration.

Gait Deviations Identified During the Six-Minute Walk Test Using Inertial Measurement Units in Patients with Multiple Sclerosis

One possible modality to profile gait speed and stride length includes using wearable technologies. Wearable technology using global positioning system (GPS) receivers may not be a feasible means to measure gait speed. An alternative may include a local positioning system (LPS). Considering that LPS wearables are not good at determining gait events such as heel strikes, applying sensor fusion with an inertial measurement unit (IMU) may be beneficial. Speed and stride length determined from an ultrawide bandwidth LPS equipped with an IMU were compared to video motion capture (i.e., the “gold standard”) as the criterion standard. Ninety participants performed trials at three self-selected walk, run and sprint speeds. After processing location, speed and acceleration data from the measurement systems, speed between the last five meters and stride length in the last stride of the trial were analyzed. Small biases and strong positive intraclass correlations (0.9–1.0) between the LPS and “the gold standard” were found. The significance of the study is that the LPS can be a valid method to determine speed and stride length. Variability of speed and stride length can be reduced when exploring data processing methods that can better extract speed and stride length measurements.

BackgroundStudies using inertial measurement units (IMUs) for gait assessment have shown promising results regarding accuracy of gait event detection and spatiotemporal parameters. However, performance of such algorithms is challenged in irregular walking patterns, such as in individuals with gait deficits. Based on the literature, we developed an algorithm to detect initial contact (IC) and terminal contact (TC) and calculate spatiotemporal gait parameters. We evaluated the validity of this algorithm for regular and irregular gait patterns against a 3D optical motion capture system (OMCS).MethodsTwenty healthy participants (aged 59 ± 12 years) and 10 people in the chronic phase after stroke (aged 61 ± 11 years) were equipped with 4 IMUs: on both feet, sternum and lower back (MTw Awinda, Xsens) and 26 reflective makers. Participants walked on an instrumented treadmill for 2 minutes (i) with their preferred stride lengths and (ii) once with irregular stride lengths (±20% deviation) induced by light projected stepping stones. Accuracy of the algorithm was evaluated on stride-by-stride agreement of IC, TC, stride time, length and velocity with OMCS. Bland-Altman-like plots were made for the spatiotemporal parameters, while differences in detection of IC and TC time instances were shown in histogram plots. Performance of the algorithm was compared between regular and irregular gait with a linear mixed model. This was done by comparing the performance in healthy participants in the regular vs irregular walking condition, and by comparing the agreement in healthy participants with stroke participants in the regular walking condition.ResultsFor each condition at least 1,500 strides were included for analysis. Compared to OMCS, IMU-based IC detection in both groups and condition was on average 9–17 (SD ranging from 7 to 35) ms, while IMU-based TC was on average 15–24 (SD ranging from 12 to 35) ms earlier. When comparing regular and irregular gait in healthy participants, the difference between methods was 2.5 ms higher for IC, 3.4 ms lower for TC, 0.3 cm lower for stride length, and 0.4 cm/s higher for stride velocity in the irregular walking condition. No difference was found on stride time. When comparing the differences between methods between healthy and stroke participants, the difference between methods was 7.6 ms lower for IC, 3.8 cm lower for stride length, and 3.4 cm/s lower for stride velocity in stroke participants. No differences were found on differences between methods on TC detection and stride time between stroke and healthy participants.ConclusionsSmall irrelevant differences were found on gait event detection and spatiotemporal parameters due to irregular walking by imposing irregular stride lengths or pathological (stroke) gait. Furthermore, IMUs seem equally good compared to OMCS to assess gait variability based on stride time, but less accurate based on stride length.

The purpose of the present study was to evaluate the relationship between the ability to utilize continuous weight shift (CWS) from side to side and measurements related to locomotion performance. Tests were performed on 17 hemiplegic subjects (age: 68 /spl plusmn/11 years) and 16 healthy subjects (age: 23.3 /spl plusmn/ 5.4 years). Measurements comprised CWS ability, maximum walking speed, stride length, cadence, and one-footed standing duration. CWS ability was evaluated with displacement from center of stance (CWS index) during continuous CWS exercise. CWS index was 16.8/spl plusmn/ 1.9 cm in healthy subjects (range: 14.1 to 21.0 cm), 13.6/spl plusmn/ 5.5 cm in hemiplegic patients (range: 4.4 to 24.1 cm). A positive correlation was identified between CWS index and maximum walking speed (r = 0.60, p<0.05) in hemiplegic patients. The scatter plot between CWS index and one-footed standing indicated the characteristic distribution; there was a boundary near 15 cm for CWS index. One-footed standing for hemiplegic subjects with reach greater than 15 cm was almost above 30 s on both sides. CWS exercises should lead to improved walking ability and decreased falls in hemiplegic patients.

Zero-velocity assumption has been used for estimation of foot trajectory and stride length during running from the data of foot-mounted inertial measurement units (IMUs). Although the assumption provides a reasonable initialization for foot trajectory and stride length estimation, the other source of errors related to the IMU’s orientation still remains. The purpose of this study was to develop an improved foot trajectory and stride length estimation method for the level ground running based on the displacement of the foot. Seventy-nine runners performed running trials at 5 different paces and their running motions were captured using a motion capture system. The accelerations and angular velocities of left and right feet were measured with two IMUs mounted on the dorsum of each foot. In this study, foot trajectory and stride length were estimated using zero-velocity assumption with IMU data, and the orientation of IMU was estimated to calculate the mediolateral and vertical distance of the foot between two consecutive midstance events. Calculated foot trajectory and stride length were compared with motion capture data. The results show that the method used in this study can provide accurate estimation of foot trajectory and stride length for level ground running across a range of running speeds.