Agreement between the spatiotemporal gait parameters from two different wearable devices and high-speed video analysis

Bilateral Asymmetry of Spatiotemporal Running Gait Parameters in U14 Athletes at Different Speeds

The assessment of leg asymmetries is gaining scientific interest due to its potential impact on performance and injury development. Athletes around puberty exhibit increased gait variability due to a non-established running pattern. This study aims to describe the asymmetries in the spatiotemporal running parameters in developmentally aged athletes. Forty athletes under 14 (U14) (22 females and 18 males) were assessed running on a treadmill at constant speeds of 12 and 14 km·h-1 for 3 min. Step length, step frequency, along with contact (CT) and flight time, both in absolute values and as a percentage of step time, were recorded using a RunScribe sensor attached to the laces of each shoe. U14 runners exhibited high bilateral symmetry in the spatiotemporal parameters of running, with mean asymmetry values (1-5.7%) lower than the intra-limb coefficient of variation (1.7-9.6%). Furthermore, bilateral asymmetries did not vary between the two speeds. An individual-based interpretation of asymmetries identified subjects with consistent asymmetries at both speeds, particularly in terms of CT and contact ratio (%, CT/step time). This study confirms the high symmetry of pubertal runners and paves the way for the application of portable running assessment technology to detect asymmetries on an individual basis.

Parameterization of Biomechanical Variables through Inertial Measurement Units (IMUs) in Occasional Healthy Runners

Running is one of the most popular sports practiced today and biomechanical variables are fundamental to understanding it. The main objectives of this study are to describe kinetic, kinematic, and spatiotemporal variables measured using four inertial measurement units (IMUs) in runners during treadmill running, investigate the relationships between these variables, and describe differences associated with different data sampling and averaging strategies. A total of 22 healthy recreational runners (M age = 28 ± 5.57 yrs) participated in treadmill measurements, running at their preferred speed (M = 10.1 ± 1.9 km/h) with a set-up of four IMUs placed on tibias and the lumbar area. Raw data was processed and analysed over selections spanning 30 s, 30 steps and 1 step. Very strong positive associations were obtained between the same family variables in all selections. The temporal variables were inversely associated with the step rate variable in the selection of 30 s and 30 steps of data. There were moderate associations between kinetic (forces) and kinematic (displacement) variables. There were no significant differences between the biomechanics variables in any selection. Our results suggest that a 4-IMU set-up, as presented in this study, is a viable approach for parameterization of the biomechanical variables in running, and also that there are no significant differences in the biomechanical variables studied independently, if we select data from 30 s, 30 steps or 1 step for processing and analysis. These results can assist in the methodological aspects of protocol design in future running research.

Reliability and validity of three portable devices for quantifying spatiotemporal parameters in runners of different athletic abilities during treadmill running

This study aimed to evaluate the validity and reliability of a wearable device and a phone application for measuring spatiotemporal parameters and their relationship with running economy (RE) by comparing them with photocell data in runners of different abilities. Twenty-three male runners were divided into well-trained and recreational groups and performed a 4-min running bout at 17 and 13 km·h-1 respectively. During the bout, were measured the spatiotemporal parameters with three devices (Stryd, Runmatic, and Optojump) and RE with a gas analyser. Pearson correlation showed perfect relationships for stride frequency (SF) and stride length (SL) between the devices, and moderate for flight time (FT) and contact time (CT). There were no correlations between the spatiotemporal parameters and RE measurements. Coefficient of variation was ~ 5% in all devices for CT, SF, and SL, and higher for FT (15-24%). CT was underestimated (15-16% with Runmatic and Stryd, respectively) and FT was overestimated (36-40%) compared to Optojump. Bland-Altman plots revealed that Runmatic could be a more accurate system than Stryd. In conclusion, both devices were valid tools for measuring spatiotemporal parameters during running at RE speed. Runmatic was more valid and reliable in comparison with Stryd. In addition, at lower running speeds the devices showed less reliability.

Gait Variability at Different Walking Speeds

Gait variability (GV) is a crucial measure of inconsistency of muscular activities or body segmental movements during repeated tasks. Hence, GV might serve as a relevant and sensitive measure to quantify adjustments of walking control. However, it has not been clarified whether GV is associated with walking speed, a clarification needed to exploit effective better bilateral coordination level. For this aim, fourteen male students (age 22.4 ± 2.7 years, body mass 74.9 ± 6.8 kg, and body height 1.78 ± 0.05 m) took part in this study. After three days of walking 1 km each day at a self-selected speed (SS) on asphalt with an Apple Watch S. 7 (AppleTM, Cupertino, CA, USA), the participants were randomly evaluated on a treadmill at three different walking speed intensities for 10 min at each one, SS - 20%/SS + 20%/ SS, with 5 min of passive recovery in-between. Heart rate (HR) was monitored and normalized as %HRmax, while the rate of perceived exertion (RPE) (CR-10 scale) was asked after each trial. Kinematic analysis was performed, assessing the Contact Time (CT), Swing Time (ST), Stride Length (SL), Stride Cycle (SC), and Gait Variability as Phase Coordination Index (PCI). RPE and HR increased as the walking speed increased (p = 0.005 and p = 0.035, respectively). CT and SC decreased as the speed increased (p = 0.0001 and p = 0.013, respectively), while ST remained unchanged (p = 0.277). SL increased with higher walking speed (p = 0.0001). Conversely, PCI was 3.81 ± 0.88% (high variability) at 3.96 ± 0.47 km·h-1, 2.64 ± 0.75% (low variability) at SS (4.94 ± 0.58 km·h-1), and 3.36 ± 1.09% (high variability) at 5.94 ± 0.70 km·h-1 (p = 0.001). These results indicate that while the metabolic demand and kinematics variables change linearly with increasing speed, the most effective GV was observed at SS. Therefore, SS could be a new methodological approach to choose the individual walking speed, normalize the speed intensity, and avoid a gait pattern alteration.

Training Specificity in Trail Running: A Single-Arm Trial on the Influence of Weighted Vest on Power and Kinematics in Trained Trail Runners

Participants in trail running races must carry their equipment throughout the race. This additional load modifies running biomechanics. Novel running powermeters allow further analyses of key running metrics. This study aims to determine the acute effects of running with extra weights on running power generation and running kinematics at submaximal speed. Fifteen male amateur trail runners completed three treadmill running sessions with a weighted vest of 0-, 5-, or 10% of their body mass (BM), at 8, 10, 12, and 14 km·h^-1. Mean power output (MPO), leg spring stiffness (LSS), ground contact time (GCT), flight time (FT), step frequency (SF), step length (SL), vertical oscillation (VO), and duty factor (DF) were estimated with the Stryd wearable system. The one-way ANOVA revealed higher GCT and MPO and lower DF, VO, and FT for the +10% BM compared to the two other conditions (p < 0.001) for the running speeds evaluated (ES: 0.2-7.0). After post-hoc testing, LSS resulted to be higher for +5% BM than for the +10% and +0% BM conditions (ES: 0.2 and 0.4). Running with lighter loads (i.e., +5% BM) takes the principle of specificity in trail running one step further, enhancing running power generation and LSS.

Is Stryd critical power a meaningful parameter for runners?

Stryd is a foot pod that reliably estimates running power. Our objectives were to examine the efficacy of the website-generated Stryd critical power (CPSTRYD) as a meaningful parameter for runners. 20 runners performed their regular training while wearing Stryd for a minimum of 6 weeks to generate CPSTRYD. Runners completed laboratory graded exercise testing, and outdoor 1500 m and 5000 m time trails. CPSTRYD was most similar to the second ventilatory threshold (VT2) or the onset of blood lactate accumulation (OBLA) and is highly predictive of running performance. Stryd ground contact time (GCT) was a predictor of performance when comparing runners at the same submaximal treadmill speed. CPSTRYD generated from outdoor running is equivalent to that calculated using an established CP model. However, variance between different methods of CP estimation must be a consideration for runners and coaches. Stryd offers meaningful data for runners including a realistic estimate of CP.

Validation of an Ear-Worn Wearable Gait Analysis Device

Wearable devices capable of measuring gait parameters may provide a means to more economical gait analysis compared to conventional equipment comprising of a motion capture system and a forced treadmill. Beflex Coach (Beflex, Republic of Korea) is one such device but worn on the ear as Bluetooth earphones, unlike other wearables worn on the wrist, feet, or torso. In this study, the validity of the device was examined against a motion capture system and a forced treadmill for walking and running parameters. Five walking parameters (cadence, single support time, double support time, vertical oscillation (VO), and instantaneous vertical loading rate (IVLR)) and six running parameters (cadence, stance time, flight time, peak force, VO, and IVLR) were studied. Twenty young adults participated in walking or running on a forced treadmill at different speeds (walking: 0.8, 1.25, and 1.7 m/s for walking; running: 2, 2.5, and 3 m/s) while the two systems operated simultaneously. As a result, all parameters showed excellent associations (ICC > 0.75) and good agreements in Bland-Altman plots. The results of the study support the potential use of the ear-worn device as an inexpensive gait analysis equipment.

Wearables for Running Gait Analysis: A Systematic Review

BACKGROUND

Running gait assessment has traditionally been performed using subjective observation or expensive laboratory-based objective technologies, such as three-dimensional motion capture or force plates. However, recent developments in wearable devices allow for continuous monitoring and analysis of running mechanics in any environment. Objective measurement of running gait is an important (clinical) tool for injury assessment and provides measures that can be used to enhance performance.

OBJECTIVES

We aimed to systematically review the available literature investigating how wearable technology is being used for running gait analysis in adults.

METHODS

A systematic search of the literature was conducted in the following scientific databases: PubMed, Scopus, Web of Science and SPORTDiscus. Information was extracted from each included article regarding the type of study, participants, protocol, wearable device(s), main outcomes/measures, analysis and key findings.

RESULTS

A total of 131 articles were reviewed: 56 investigated the validity of wearable technology, 22 examined the reliability and 77 focused on applied use. Most studies used inertial measurement units (n = 62) [i.e. a combination of accelerometers, gyroscopes and magnetometers in a single unit] or solely accelerometers (n = 40), with one using gyroscopes alone and 31 using pressure sensors. On average, studies used one wearable device to examine running gait. Wearable locations were distributed among the shank, shoe and waist. The mean number of participants was 26 (± 27), with an average age of 28.3 (± 7.0) years. Most studies took place indoors (n = 93), using a treadmill (n = 62), with the main aims seeking to identify running gait outcomes or investigate the effects of injury, fatigue, intrinsic factors (e.g. age, sex, morphology) or footwear on running gait outcomes. Generally, wearables were found to be valid and reliable tools for assessing running gait compared to reference standards.

CONCLUSIONS

This comprehensive review highlighted that most studies that have examined running gait using wearable sensors have done so with young adult recreational runners, using one inertial measurement unit sensor, with participants running on a treadmill and reporting outcomes of ground contact time, stride length, stride frequency and tibial acceleration. Future studies are required to obtain consensus regarding terminology, protocols for testing validity and the reliability of devices and suitability of gait outcomes.

CLINICAL TRIAL REGISTRATION

CRD42021235527.

Validity and Reliability of Inertial Measurement Units on Lower Extremity Kinematics During Running: A Systematic Review and Meta-Analysis

Background

Inertial measurement units (IMUs) are useful in monitoring running and alerting running-related injuries in various sports settings. However, the quantitative summaries of the validity and reliability of the measurements from IMUs during running are still lacking. The purpose of this review was to investigate the concurrent validity and test–retest reliability of IMUs for measuring gait spatiotemporal outcomes and lower extremity kinematics of health adults during running.

Methods

PubMed, CINAHL, Embase, Scopus and Web of Science electronic databases were searched from inception until September 2021. The inclusion criteria were as follows: (1) evaluated the validity or reliability of measurements from IMUs, (2) measured specific kinematic outcomes, (3) compared measurements using IMUs with those obtained using reference systems, (4) collected data during running, (5) assessed human beings and (6) were published in English. Eligible articles were reviewed using a modified quality assessment. A meta-analysis was performed to assess the pooled correlation coefficients of validity and reliability.

Results

Twenty-five articles were included in the systematic review, and data from 12 were pooled for meta-analysis. The methodological quality of studies ranged from low to moderate. Concurrent validity is excellent for stride length (intraclass correlation coefficient (ICC) (95% confidence interval (CI)) = 0.937 (0.859, 0.972), p < 0.001), step frequency (ICC (95% CI) = 0.926 (0.896, 0.948), r (95% CI) = 0.989 (0.957, 0.997), p  < 0.001) and ankle angle in the sagittal plane (r (95% CI) = 0.939 (0.544, 0.993), p = 0.002), moderate to excellent for stance time (ICC (95% CI) = 0.664 (0.354, 0.845), r (95% CI) = 0.811 (0.701, 0.881), p < 0.001) and good for running speed (ICC (95% CI) = 0.848 (0.523, 0.958), p = 0.0003). The summary Fisher's Z value of flight time was not statistically significant (p = 0.13). Similarly, the stance time showed excellent test–retest reliability (ICC (95% CI) = 0.954 (0.903, 0.978), p < 0.001) and step frequency showed good test–retest reliability (ICC (95% CI) = 0.896 (0.837, 0.933), p < 0.001).

Conclusions

Findings in the current review support IMUs measurement of running gait spatiotemporal parameters, but IMUs measurement of running kinematics on lower extremity joints needs to be reported with caution in healthy adults.

Trial Registration: PROSPERO Registration Number: CRD42021279395.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40798-022-00477-0.

Absolute agreement and consistency of the OptoGait system and Freemed platform for measuring walking gait

The gait cycle can be divided into four functional rocker units. Although the widespread use of the OptoGait (OG) system and the Freemed (FM) platform, their accuracy has not been tested. An observational study was completed with eighteen healthy volunteers to determine the accuracy of OG and FM for overground walking gait analysis. The pairwise comparison between data obtained from OG, FM and high-speed video analysis revealed significant differences for most of the measurements (p < 0.05). ICCs revealed an excellent absolute agreement between measurements (ICCs > 0.94) for all measures for OG systems compared to video-analysis. When considering FM vs. video-analysis, ICCs showed good absolute agreement for rocker 1 (ICC = 0.86) and 3 (ICC = 0.82), excellent for rocker 2 (ICC = 0.93) and poor (ICC < 0.5) for rocker 4. Bland-Altman plots (95% limits of agreement) revealed heteroscedasticity of error for OG in all variables for foot rockers (r² > 0.1) while no heteroscedasticity of error was found when using FM (r² < 0.1). This study indicates that the OG system and the FM platform can provide consistent foot rockers values when walking at a constant velocity. The differences between the systems assessed and their agreement and consistency values advise against their interchangeable use.

Validation of the RunScribe inertial measurement unit for walking gait measurement

Introduction

The use of portable gait measurement systems in research is appealing to collect real-world data at low-cost, low participant burden, and without requirement for dedicated lab space. Most commercially available inertial measurement units (IMU’s) designed for running only capture temporospatial data, the ability to capture biomechanics data such as shock and motion metrics with the RunScribe IMU makes it the closest to a lab alternative. The RunScribe system has been validated in running, however, is yet to be validated for walking.

Method

Qualisys motion capture, AMTI force plates, and Delsys Trigno accelerometers were used as gold standard lab measures for comparison against the RunScribe IMU. Twenty participants completed 10 footsteps per foot (20 total) measured by both systems simultaneously. Variables for validation included: Vertical Ground reaction force (GRF), instantaneous GRF rate, pronation excursion, pronation velocity, total shock, impact force, braking force. Interclass correlation (ICC) was used to determine agreement between the measurement systems, mean differences were used to evaluate group level accuracy.

Results

ICC results showed moderate agreement between measurement systems when both limbs were averaged. The greatest agreement was seen for GRF rate, pronation excursion, and pronation velocity (ICC = 0.627, 0.616, 0.539), low agreement was seen for GRF, total shock, impact shock, braking shock (ICC = 0.269, 0.351, 0.244, 0.180). However mean differences show the greatest level of accuracy for GRF, GRF rate, and impact shock.

Discussion

Results show mixed agreement between the RunScribe and gold standard lab measures, and varied agreement across left and right limbs. Kinematic variables showed the greatest agreement, however GRF had the lowest relative mean difference for group results. The results show acceptable levels of agreement for most variables, however further work must be done to assess the repeatability and sensitivity of the RunScribe to be applied within areas such as footwear testing and gait retraining protocols.

Application of the Force-velocity-power Concept to the 3-Min all-out Running Test

Force-velocity-power (FVP) profiling offers insights related to key factors that may enhance or hinder sprinting performances. Whether the same FVP principles could be applied to the sprinting portion of the 3-minute all-out test for running (3MT) has not been previously investigated. Twenty moderately trained participants volunteered for the study (age: 24.75 ± 3.58 yrs; height: 1.69±0.11 m; mass: 73.74±12.26 kg). After familiarization of all testing procedures, participants completed: (i) a 40-m all-out sprint test, and (ii) a 3MT. Theoretical maximal force and power, but not velocity, were significantly higher for the 40-m sprint test. Most FVP variables from the two tests were weakly to moderately correlated, with the exception of maximal velocity. Finally, maximal velocity and relative peak power were predictive of D', explaining approximately 51% of the variance in D'. Although similar maximal velocities are attained during both the 40-m sprint and the 3MT, the underlying mechanisms are markedly different. The FVP parameters obtained from either test are likely not interchangeable but do provide valuable insights regarding the potential mechanisms by which D' may be improved.

Wearable Sensors for Vital Signs Measurement: A Survey

With the outbreak of coronavirus disease-2019 (COVID-19) worldwide, developments in the medical field have aroused concerns within society. As science and technology develop, wearable medical sensors have become the main means of medical data acquisition. To analyze the intelligent development status of wearable medical sensors, the current work classifies and prospects the application status and functions of wireless communication wearable medical sensors, based on human physiological data acquisition in the medical field. By understanding its working principles, data acquisition modes and action modes, the work chiefly analyzes the application of wearable medical sensors in vascular infarction, respiratory intensity, body temperature, blood oxygen concentration, and sleep detection, and reflects the key role of wearable medical sensors in human physiological data acquisition. Further exploration and prospecting are made by investigating the improvement of information security performance of wearable medical sensors, the improvement of biological adaptability and biodegradability of new materials, and the integration of wearable medical sensors and intelligence-assisted rehabilitation. The research expects to provide a reference for the intelligent development of wearable medical sensors and real-time monitoring of human health in the follow-up medical field.

Reliability and validity of the Stryd Power Meter during different walking conditions

BACKGROUND

The Styrd Power Meter is gaining special interest for on-field gait analyses due to its low-cost and general availability. However, the reliability and validity of the Stryd during walking on positive slopes using different backpack loads have never been investigated.

RESEARCH QUESTION

Is the Stryd Power Meter reliable and valid for quantifying gait mechanics during walking on positive inclines and during level walking incorporating load carriage?

METHODS

Seventeen participants from a police force rescue team performed 8 submaximal walking trials for 5-min at 3.6 km·h^-1 during different positive slope (1%, 10% and 20%) and backpack load (0%, 10%, 20%, 30% and 40% of body mass) conditions. Two Stryd devices were utilized for reliability analyses. Validity of cadence and ground contact time (GCT) were analyzed against a gold standard device (Optojump).

RESULTS

The Stryd demonstrated acceptable reliability [mean bias: < 2.5%; effect size (ES): < 0.25; standard error of the mean: < 1.7%; r: > 0.76] for power, cadence, and GCT. Validity measures (mean bias: <0.8%; ES: <0.07; r: >0.96; Lin's Concordance Coefficient: 0.96; Mean Absolute Percent Error: <1%) for cadence were also found to be acceptable. The Stryd overestimated (P < 0.001; ES: >5.1) GCT in all the walking conditions. A significant systematic positive bias (P < 0.022; r = 0.56-0.76) was found in 7 conditions.

SIGNIFICANCE

The Stryd Power Meter appears to produce reliable measurements for power output, cadence and GCT. The Stryd produced valid measurements for cadence during walking on positive slopes and during level walking with a loaded backpack. However, the Stryd is not valid for measuring GCT during these walking conditions. This study adds novel data regarding the reliability and validity of this device and might be of particular interest for scientists, practitioners, and first responders seeking reliable devices to quantify gait mechanics during walking.

The reliability of wearable commercial sensors for outdoor assessment of running biomechanics: the effect of surface and running speed

The aim of this study was to investigate the reliability of running biomechanics assessment with a wearable commercial sensor (RunScribeTM). Participants performed multiple 200-m runs over sand, grass and asphalt ground at the estimated 5-km tempo, with an additional trial with 21-km tempo at the asphalt. Intra-session reliability was excellent for all variables at 5-km pace (intra-class coefficient correlation (ICC) asphalt: 0.90-0.99; macadam: 0.94-1.00; grass: 0.92-1.00), except for shock (good; ICC = 0.83), and contact time and total power output (moderate; ICC = 0.68-0.71). Coefficient of variation (CV) were mostly acceptable in all conditions, except for horizontal ground reaction force (GRF) rate in asphalt 5-km pace trial (CV = 24.5 %), power (CV = 14.3 %) and foot strike type (CV = 30.9 %) in 21-km pace trial, and horizontal GRF rate grass trial (CV = 15.7 %). Inter-session reliability was high or excellent for the majority of the outcomes (ICC≥0.85). Total power output (ICC = 0.56-0.65) and shock (ICC = 0.67-0.75) showed only moderate reliability across all conditions. Power (CV = 12.5-13.8 %), foot strike type (CV = 14.9-29.4 %) and horizontal ground reaction force rate (CV = 12.4-36.4 %) showed unacceptable CV.

Seamless Temporal Gait Evaluation during Walking and Running Using Two IMU Sensors

In this study, we proposed a framework for extracting gait events and extensive temporal features, seamlessly, during walking and running on a treadmill by constructing a finite state machine (FSM) transition rules based on two IMU sensors attached to the back of the shoes. Detailed innerclass states were defined to recognize the double support phase on walking gait and the double flight phase on running gait. Further, an in-depth speed-based analysis of temporal gait features can be performed for each tested speed with an automatic speed change detection algorithm based on the moving average filter applied to motion intensity data. The results have demonstrated that the FSM can accurately distinguish walking gait and running gait while also extract a detailed gait phase, respectively. This finding may contribute to a more flexible gait analysis where a change in speed or transition from walk to run can be anticipated and recognized accordingly.

The effect of a decrease in stretch-shortening cycle function after cycling on subsequent running

OBJECTIVES

Increased cardiorespiratory responses and changes in muscle activity and running kinematics occur in running after cycling compared with isolated running. Nevertheless, little is known about the causes of these changes. Cycling exercise decreases the stretch-shortening cycle (SSC) function, which can influence subsequent running. This study aimed to clarify whether the decrease in SSC function after cycling causes cardiorespiratory and biomechanical changes in subsequent running.

DESIGN

Cross-sectional laboratory study. Participants were divided into two groups based on SSC function: an SSC dec group (those with decreased SSC function after cycling) and an SSC non-dec group (those without decreased SSC function after cycling).

METHODS

Eighteen participants (10 triathletes and 8 runners) completed maximal aerobic tests for running and cycling. After these sessions, a submaximal run-cycle-run test was performed to compare between control run (no preceding cycle) and transition run (preceded by cycling). A jump test was administered before and after the submaximal cycling. SSC function was calculated as the ratio of the jump height to the time spent in contact with the ground (reactive strength index). Gas exchange measures, heart rate, and gait parameters were collected throughout the test.

RESULTS

Oxygen uptake and ventilation were increased by cycling in the SSC dec group but not in the SSC non-dec group. In both groups, there were no significant differences in the gait parameters between control and transition runs.

CONCLUSIONS

The decrease in SSC function after cycling would increase cardiorespiratory responses in subsequent running.

Does Site Matter? Impact of Inertial Measurement Unit Placement on the Validity and Reliability of Stride Variables During Running: A Systematic Review and Meta-analysis

BACKGROUND

Inertial measurement units (IMUs) are used for running gait analysis in a variety of sports. These sensors have been attached at various locations to capture stride data. However, it is unclear if different placement sites affect the derived outcome measures.

OBJECTIVE

The aim of this systematic review and meta-analysis was to investigate the impact of placement on the validity and reliability of IMU-derived measures of running gait.

METHODS

Online databases SPORTDiscus with Full Text, CINAHL Complete, MEDLINE (EBSCOhost), EMBASE (Ovid) and Scopus were searched from the earliest record to 6 August 2020. Articles were included if they (1) used an IMU during running (2) reported spatiotemporal variables, peak ground reaction force (GRF) or vertical stiffness and (3) assessed validity or reliability. Meta-analyses were performed for a pooled validity estimate when (1) studies reported means and standard deviation for variables derived from the IMU and criterion (2) used the same IMU placement and (3) determined validity at a comparable running velocity (≤ 1 m·s^-1 difference).

RESULTS

Thirty-nine articles were included, where placement varied between the foot, tibia, hip, sacrum, lumbar spine (LS), torso and thoracic spine (TS). Initial contact, toe-off, contact time (CT), flight time (FT), step time, stride time, swing time, step frequency (SF), step length (SL), stride length, peak vertical and resultant GRF and vertical stiffness were analysed. Four variables (CT, FT, SF and SL) were meta-analysed, where CT was compared between the foot, tibia and LS placements and SF was compared between foot and LS. Foot placement data were meta-analysed for FT and SL. All data are the mean difference (MD [95%CI]). No significant difference was observed for any site compared to the criterion for CT (foot: - 11.47 ms [- 45.68, 22.74], p = 0.43; tibia: 22.34 ms [- 18.59, 63.27], p = 0.18; LS: - 48.74 ms [- 120.33, 22.85], p = 0.12), FT (foot: 11.93 ms [- 8.88, 32.74], p = 0.13), SF (foot: 0.45 step·min^-1 [- 1.75, 2.66], p = 0.47; LS: - 3.45 step·min^-1 [- 16.28, 9.39], p = 0.37) and SL (foot: 0.21 cm [- 1.76, 2.18], p = 0.69). Reliable derivations of CT (coefficient of variation [CV] < 9.9%), FT (CV < 11.6%) and SF (CV < 4.4%) were shown using foot- and LS-worn IMUs, while the CV was < 7.8% for foot-determined stride time, SL and stride length. Vertical GRF was reliable from the LS (CV = 4.2%) and TS (CV = 3.3%) using a spring-mass model, while vertical stiffness was moderately (r = 0.66) and nearly perfectly (r = 0.98) correlated with criterion measures from the TS.

CONCLUSION

Placement of IMUs on the foot, tibia and LS is suitable to derive valid and reliable stride data, suggesting measurement site may not be a critical factor. However, evidence regarding the ability to accurately detect stride events from the TS is unclear and this warrants further investigation.

[Kinematic parameters of gait in patients with supra- or subtentorial focus location during the early rehabilitation period after ischemic stroke]

OBJECTIVE

To study kinematic gait parameters during early rehabilitation period in patients with supra- or subtentorial ischemic stroke (IS).

MATERIAL AND METHODS

We examined 24 patients (11 women, 13 men, age 61.3±8.2) 4-6 weeks after stroke onset. 15 patients had supratentorial IS (middle cerebral artery location), 9 patients had subtentorial IS (brainstem and cerebellum). NIHSS score was 6.4±0.6/6.1±0.8, modified Ashwort scale score - 0.5±0.6/0.4±0.7, hand paresis - 3.4±0.9/3.7±0.7, leg paresis - 4.1±0.7/4.0±0.8 points. Kinematic gait parameters were recorded on video analysis system Physiomed Smart (Physiomed, Germany, Davis protocol).

RESULTS

Gait kinematic parameters in paretic and in unaffected leg were changed in both groups. Patients with supratentorial lesion had on paretic side exaggerated pelvic obliquity, an excessive internal rotation and amplitude of movements in the paretic hip joint, and an insufficient plantar extension on both sides. Patients with subtentorial stroke had exaggerated pelvic tilt forward, excessive flexion and insufficient extension of the hip joint, insufficient extension of the knee joint, excessive plantar flexion, and insufficient plantar extension on both sides.

CONCLUSION

Patients with supra- or subtentorial IS with muscle weakness less than 3-4 points and slightly changed or normal muscle tone differed in kinematic parameters in pelvic motions and in joints of paretic and unaffected lower extremity. These results highlight the importance of differentiating rehabilitation techniques according to supra- or subtentorial focus location and cerebellar involvement.

The use of a running power-meter for performance analysis in five-a-side football

BACKGROUND

Power output considers all movement aspects of the game of football and could have meaningful impact for teams.

PURPOSE & METHODS

To assess inter-reliability of ten power meters designed for running; and as a descriptor of individual and team performance during a five-a-side football match. The work aimed to assess inter-device reliability of running power-meters combined with data analysis from intermittent running, along with descriptives of player work rate, gait and team performance during a small-sided game of football.

METHODS

10 different running power meters inter-reliability were on a treadmill at 8, 10, 12, and 16 km h^-1 for 60 s in a random order. Football players (N = 10) performed the Yo-Yo ET1 with the running power meters to determine participants' endurance capability, while assessing the ability to record metrics of gait and power output during intermittent running. Following a period of 7-days participants took part in a 20 min small-sided game of football wearing the running power meters to provide descriptors of work and gait.

RESULTS

Good inter-device reliability for the power meters (CV 1.67, range 1.51-1.94 %) during continuous treadmill running were found. Overall mean ± SD results for Yo-Yo ET1 power output 263 ± 36W, power:weight 3.59 ± 0.34W∙kg^-1 significantly (p < 0.05) increased with successive stages, while ground-contact time 234 ± 17 ms, and vertical oscillation 90.7 ± 27 mm did not change (p > 0.05). Descriptive analysis of the small-sided game presented mean ± SD absolute and relative power outputs of 148 ± 44W and 1.98 ± 0.53W∙kg^-1, equating to 54 ± 21 %W_max and 74 ± 5%HR_max. Characteristics of gait included cadence 125 ± 22 rpm, ground contact time 266 ± 19 ms, and vertical oscillation 76.7 ± 7 mm. The winning team worked relatively harder than the losing team (53.3 ± 0.7 %W_max vs 46.7 ± 0.4 %W_max, p < 0.0001) with more time (398 s vs 141 s) spent above 70 %W_max.

SIGNIFICANCE

As such, the use of a running power-meter is a useful tool for comparing work rate and aspects of gait between team members while more research is required to investigate relative work rate (%W_max) within the field.

Validation of low-cost system for gait assessment in children with ataxia

BACKGROUND

Ataxic syndromes include several rare, inherited and acquired conditions. One of the main issues is the absence of specific, and sensitive automatic evaluation tools and digital outcome measures to obtain a continuous monitoring of subjects' motor ability.

OBJECTIVES

This study aims to test the usability of the Kinect system for assessing ataxia severity, exploring the potentiality of clustering algorithms and validating this system with a standard motion capture system.

METHODS

Gait evaluation was performed by standardized gait analysis and by Kinect v2 during the same day in a cohort of young patient (mean age of 13.8±7.2). We analyzed the gait spatio-temporal parameters and we looked at the differences between the two systems through correlation and agreement tests. As well, we tested for possible correlations with the SARA scale as well. Finally, standard classification algorithm and principal components analysis were used to discern disease severity and groups.

RESULTS

We found biases and linear relationships between all the parameters. Significant correlations emerged between the SARA and the Speed, the Stride Length and the Step Length. PCA results, highlighting that a machine learning approach combined with Kinect-based evaluation shows great potential to automatically assess disease severity and diagnosis.

CONCLUSIONS

The spatio-temporal parameters measured by Kinect cannot be used interchangeably with those parameters acquired with standard motion capture system in clinical practice but can still provide fundamental information. Specifically, these results might bring to the development of a novel system to perform easy and quick evaluation of gait in young patients with ataxia, useful for patients stratification in terms of clinical severity and diagnosis.

Critical speed and finite distance capacity: norms for athletic and non-athletic groups

PURPOSE

Two parameters in particular span both health and performance; critical speed (CS) and finite distance capacity (D'). The purpose of the present study was to: (1) classify performance norms, (2) distinguish athletic from non-athletic individuals using the 3-min all-out test (3MT) for running, and (3) introduce a deterministic model highlighting the relationship between variables of the 3MT.

METHODS

Athletic (n = 43) and non-athletic (n = 25) individuals participated in the study. All participants completed a treadmill graded exercise test (GXT) with verification bout and a 3MT on an outdoor sprinting track.

RESULTS

Meaningful differences between non-athletic and athletic individuals (denoted by mean difference scores, p value and Cohen's d with 95% confidence intervals) were evident for CS (- 0.74 m s^-1, p < 0.001, d = - 1.41 [1.97, - 0.87]), exponential growth time constant ([Formula: see text]; 2.75 s, p < 0.001, d = - 1.29 [- 1.45, - 0.42]), time to maximal speed ([Formula: see text]; - 2.80 s, p < 0.001, d = - 0.98 [- 1.51, - 0.47]), maximal speed ([Formula: see text]; - 1.36 m s^-1, p < 0.001, d = - 1.56 [- 2.13, - 1.01]), gas exchange threshold (GET; - 5.62 ml kg^-1 min^-1, p < 0.001, d = - 0.97 [- 1.50, - 0.45]), distance covered in the first minute (1st min; - 81.69 m, p < 0.001, d = - 1.91 [- 2.52, - 1.33]), distance covered in the second minute (2nd min; - 52.02 m, p < 0.001, d = - 1.71 [- 2.30, - 1.15]) and maximal distance (- 153.78 m, p < 0.001, d = - 1.27 [- 1.82, - 0.74]). The correlation coefficient between key physiological and performance variables are shown in the form of a deterministic model created from the data derived from the 3MT.

CONCLUSIONS

Coaches and clinicians may benefit from the use of normative data to potentially identify exceptional or irregular occurrences in 3MT performances.