Gait Parameters in Healthy Preschool and School Children Assessed Using Wireless Inertial Sensor

Gait Analysis in Patients with Symptomatic Pes Planovalgus Following Subtalar Arthroereisis with the Talus Screw

Background

Pes planovalgus is one of the most common pediatric skeletal deformities. There have been no studies to analyze in detail the spatiotemporal variables of gait following arthroereisis.

Purpose of the study

The purpose of our study was to assess gait parameters in patients with symptomatic flexible flatfoot following treatment with the talus screw.

Methods

This was a prospective study assessing the 22 patients treated surgically due to symptomatic flexible flatfoot with the talus screw. Patients underwent gait assessment with a G-Sensor. We analyzed the following gait parameters: gait cycle duration, step length, support phase duration, swing phase duration, double support duration, single support duration, cadence, velocity, step length.

Results

The post-operative gait parameter assessment for the operated and non-operated foot showed a significant difference only in terms of step length. Cadence increased from the pre-operative mean of 82.29 steps/min to a post-operative mean of 102.94 steps/min. Gait velocity increased significantly from 0.81 m/s before to 0.96 m/s after surgery.

Discussion

Arthroereisis with the talus screw helps improve gait parameters following surgery. Post-operatively, we observed increased gait velocity and cadence and decreased gait cycle duration in the operated limb.

Conclusion

Short-term biomechanical outcomes of pes planovalgus treatment with the talus screw are good.

Monitoring Activity and Gait in Children (MAGIC) using digital health technologies

BACKGROUND

Digital health technologies (DHTs) can collect gait and physical activity in adults, but limited studies have validated these in children. This study compared gait and physical activity metrics collected using DHTs to those collected by reference comparators during in-clinic sessions, to collect a normative accelerometry dataset, and to evaluate participants' comfort and their compliance in wearing the DHTs at-home.

METHODS

The MAGIC (Monitoring Activity and Gait in Children) study was an analytical validation study which enrolled 40, generally healthy participants aged 3-17 years. Gait and physical activity were collected using DHTs in a clinical setting and continuously at-home.

RESULTS

Overall good to excellent agreement was observed between gait metrics extracted with a gait algorithm from a lumbar-worn DHT compared to ground truth reference systems. Majority of participants either "agreed" or "strongly agreed" that wrist and lumbar DHTs were comfortable to wear at home, respectively, with 86% (wrist-worn DHT) and 68% (lumbar-worn DHT) wear-time compliance. Significant differences across age groups were observed in multiple gait and activity metrics obtained at home.

CONCLUSIONS

Our findings suggest that gait and physical activity data can be collected from DHTs in pediatric populations with high reliability and wear compliance, in-clinic and in home environments.

TRIAL REGISTRATION

ClinicalTrials.gov: NCT04823650 IMPACT: Digital health technologies (DHTs) have been used to collect gait and physical activity in adult populations, but limited studies have validated these metrics in children. The MAGIC study comprehensively validates the performance and feasibility of DHT-measured gait and physical activity in the pediatric population. Our findings suggest that reliable gait and physical activity data can be collected from DHTs in pediatric populations, with both high accuracy and wear compliance both in-clinic and in home environments. The identified across-age-group differences in gait and activity measurements highlighted their potential clinical value.

Jumping Motor Skills in Typically Developing Preschool Children Assessed Using a Battery of Tests

The preschool period is characterised by the improvement in motor skills. One of the developmental tasks in children is the ability to jump. Jumping plays an important role in the development of leg strength and balance. It is the gateway to more complex movements. In the physiotherapy clinic, we see a lot of difficulties in jumping performance in 5-7-year-old children. The aim of this study is to present the jumping ability, assessed by the Motor Proficiency Test (MOT) and the G-sensor examination of the vertical countermovement jump (CMJ) and countermovement jump with arms thrust (CMJAT) parameters. A total of 47 children (14 boys and 33 girls) were randomly recruited. The mean age was 5.5 years. The mean height was 113 cm and the mean weight was 19.7 kg. The children were divided into two groups according to their results. Children with low basic motor skills have the greatest difficulty with jumping tasks. In the CMJ jump, the take-off force was lower than in the CMJAT (p = 0.04). Most CMJAT parameters correlate with age, weight, and height. Height correlates most with children's jumping performance. This study may be useful for sport educators and developmental researchers. The topic should be further explored and the CMJ and CMJAT parameters may be established as a basis.

Study of foot support during gait in healthy children from neighbouring countries

BACKGROUND

Healthy children's gait support patterns play a critical role in their development and overall well-being. Therefore, in order to develop a correct gait, it is necessary to constantly update knowledge.

OBJECTIVE

To identify differences in gait support among children in neighbouring countries.

METHODS

44 healthy children from Poland and Lithuania (4-11 years old) participated in the study. The spatiotemporal and plantar pressure parameters of 88 neutrally aligned feet were analysed and compared.

RESULTS

Statistically significant differences between stance, single-limb support, double support, swing duration, cadence, and velocity, max. force and pressure in the forefoot, as well as in the times of occurrence of max. forces in all three zones. Defined that age is related (p< 0.05) to cadence (R= 0.32), swing phase (R= 0.53), max. force under the midfoot (R= 0.35) and the heel (R= 0.47), max. pressure under the forefoot (R=-0.52), midfoot (R=-0.63) and heel (R=-0.47).

CONCLUSION

The results can help caregivers, as well as clinicians and researchers, understand how gait mechanics change with development and the growth course of the children of that country. Also, the results are important for the analysis and comparison of children's gait, as control reference data from the same country.

Validity of the Baiobit Inertial Measurements Unit for the Assessment of Vertical Double- and Single-Leg Countermovement Jumps in Athletes

Jump tests are simple, quick to execute, and considered the most reliable tool to measure lower extremities power and explosiveness in athletes. Wearable inertial sensors allow the assessment of jumping performance on any surface. The validity of inertial sensors measurements is a pivotal prerequisite to reliably implement their utilization in the clinical practice. Twenty-seven athletes (20 M/7 F, age: 27 ± 7 years old) performed five double-leg countermovement jumps (CMJs) and three single-leg CMJs per side with their hands on their hips. Jump height was measured/computed simultaneously with the optoelectronic system, force platforms, and the Baiobit inertial sensor system. The athletes completed the international physical activity questionnaire (IPAQ). When comparing the methods (Baiobit vs. force platforms), a non-statistically significant bias of 1.8 cm was found for two-leg CMJs and -0.6 cm for single-leg CMJs. The intraclass correlation coefficients (ICCs) was "excellent" for double-leg CMJs (ICC = 0.92, 95% CI = 0.89-0.94) and "good" for single-leg CMJs (ICC = 0.89, 95% CI = 0.85-0.91). When comparing the methods (Baiobit vs. force platforms + optoelectronic system), a non-statistically significant bias of -0.9 cm was found for two-leg CMJs and -1.2 cm for single-leg CMJs. The intraclass correlation coefficient (ICC) was "good" for both double-leg CMJs (ICC = 0.80, 95% CI = 0.73-0.85) and for single-leg CMJs (ICC = 0.86, 95% CI = 0.80-0.89). Baiobit tends to overestimate double- and single-leg CMJ height measurements; however, it can be recommended in the world of rehabilitation and sport analysis.

Gender Differences in Gait Parameters of Healthy Adult Individuals

Background and Purpose: Anatomical and biomechanical differences between male and female are also known to cause differences in gait patterns. However, the results of the studies are contradictory. Furthermore, these studies focused only on some of the spatiotemporal parameters, and pelvic movements were not analyzed. The aim of the present study is to reveal the difference in gait parameters between male and female. Methods: 44 female and 39 males were included in the study. BTS G-Walk system was used to evaluate the gait. After the accelerometer was placed, the participants were asked to walk 8 m. Spatiotemporal parameters and pelvic kinematics were recorded. Results: Given the spatiotemporal parameters, it was found that male and female were similar in terms of speed, % stride length and step length (p>0.05), while gait cycle duration, stride length, swing phase and single support phases were higher in male; and stance phase, first double support phases, cadence were found to be higher in female (p0.05), while pelvic tilt total range was higher in male and obliquity total range was higher in female (p

Performance of Deep Learning Models in Forecasting Gait Trajectories of Children with Neurological Disorders

Forecasted gait trajectories of children could be used as feedforward input to control lower limb robotic devices, such as exoskeletons and actuated orthotic devices (e.g., Powered Ankle Foot Orthosis—PAFO). Several studies have forecasted healthy gait trajectories, but, to the best of our knowledge, none have forecasted gait trajectories of children with pathological gait yet. These exhibit higher inter- and intra-subject variability compared to typically developing gait of healthy subjects. Pathological trajectories represent the typical gait patterns that rehabilitative exoskeletons and actuated orthoses would target. In this study, we implemented two deep learning models, a Long-Term Short Memory (LSTM) and a Convolutional Neural Network (CNN), to forecast hip, knee, and ankle trajectories in terms of corresponding Euler angles in the pitch, roll, and yaw form for children with neurological disorders, up to 200 ms in the future. The deep learning models implemented in our study are trained on data (available online) from children with neurological disorders collected by Gillette Children’s Speciality Healthcare over the years 1994–2017. The children’s ages range from 4 to 19 years old and the majority of them had cerebral palsy (73%), while the rest were a combination of neurological, developmental, orthopaedic, and genetic disorders (27%). Data were recorded with a motion capture system (VICON) with a sampling frequency of 120 Hz while walking for 15 m. We investigated a total of 35 combinations of input and output time-frames, with window sizes for input vectors ranging from 50–1000 ms, and output vectors from 8.33–200 ms. Results show that LSTMs outperform CNNs, and the gap in performance becomes greater the larger the input and output window sizes are. The maximum difference between the Mean Absolute Errors (MAEs) of the CNN and LSTM networks was 0.91 degrees. Results also show that the input size has no significant influence on mean prediction errors when the output window is 50 ms or smaller. For output window sizes greater than 50 ms, the larger the input window, the lower the error. Overall, we obtained MAEs ranging from 0.095–2.531 degrees for the LSTM network, and from 0.129–2.840 degrees for the CNN. This study establishes the feasibility of forecasting pathological gait trajectories of children which could be integrated with exoskeleton control systems and experimentally explores the characteristics of such intelligent systems under varying input and output window time-frames.