High resolution MEMS accelerometers to estimate VO2 and compare running mechanics between highly trained inter-collegiate and untrained runners

Highlighting Unseen Activity Through 48-Hour Continuous Measurement in Subacute Stroke Rehabilitation: Preliminary Cohort Study

BACKGROUND

Motor impairments not only lead to a significant reduction in patient activity levels but also trigger a further deterioration in motor function due to deconditioning, which is an issue that is particularly pronounced during hospitalization. This deconditioning can be countered by sustaining appropriate activity levels. Activities that occur outside of scheduled programs, often overlooked, are critical in this context. Wearable technology, such as smart clothing, provides a means to monitor these activities.

OBJECTIVE

This study aimed to observe activity levels in patients who had strokes during the subacute phase, focusing on both scheduled training sessions and other nontraining times in an inpatient rehabilitation environment. A smart clothing system is used to simultaneously measure heart rate and acceleration, offering insights into both the amount and intensity of the physical activity.

METHODS

In this preliminary cohort study, 11 individuals undergoing subacute stroke rehabilitation were enrolled. The 48-hour continuous measurement system, deployed at admission and reassessed 4 weeks later, monitored accelerometry data for physical activity (quantified with a moving SD of acceleration [MSDA]) and heart rate for intensity (quantified with percent heart rate reserve). The measurements were performed using a wearable activity monitoring system, the hitoe (NTT Corporation and Toray Industries, Inc) system comprising a measuring garment (wear or strap) with integrated electrodes, a data transmitter, and a smartphone. The Functional Independence Measure was used to assess the patients' daily activity levels. This study explored factors such as differences in activity during training and nontraining periods, correlations with activities of daily living (ADLs) and age, and changes observed after 4 weeks.

RESULTS

A significant increase was found in the daily total MSDA after the 4-week program, with the average percent heart rate reserve remaining consistent. Physical activity during training positively correlated with ADL levels both at admission (ρ=0.86, P<.001) and 4 weeks post admission (ρ=0.96, P<.001), whereas the correlation between age and MSDA was not significant during training periods at admission (ρ=-0.41, P=.21) or 4 weeks post admission (ρ=-0.25, P=.45). Conversely, nontraining activity showed a negative correlation with age, with significant negative correlations with age at admission (ρ=-0.82, P=.002) and 4 weeks post admission (ρ=-0.73, P=.01).

CONCLUSIONS

Inpatient rehabilitation activity levels were positively correlated with ADL levels. Further analysis revealed a strong positive correlation between scheduled training activities and ADL levels, whereas nontraining activities showed no such correlation. Instead, a negative correlation between nontraining activities and age was observed. These observations suggest the importance of providing activity opportunities for older patients, while it may also suggest the need for adjusting the activity amount to accommodate the potentially limited fitness levels of this demographic. Future studies with larger patient groups are warranted to validate and further elucidate these findings.

Reliability of Xsens inertial measurement unit in measuring trunk accelerations: a sex-based differences study during incremental treadmill running

Introduction

Inertial measurement units (IMUs) are utilized to measure trunk acceleration variables related to both running performances and rehabilitation purposes. This study examined both the reliability and sex-based differences of these variables during an incremental treadmill running test.

Methods

Eighteen endurance runners performed a test-retest on different days, and 30 runners (15 females) were recruited to analyze sex-based differences. Mediolateral (ML) and vertical (VT) trunk displacement and root mean square (RMS) accelerations were analyzed at 9, 15, and 21 km·h-1.

Results

No significant differences were found between test-retests [effect size (ES)<0.50)]. Higher intraclass correlation coefficients (ICCs) were found in the trunk displacement (0.85-0.96) compared to the RMS-based variables (0.71-0.94). Male runners showed greater VT displacement (ES = 0.90-1.0), while female runners displayed greater ML displacement, RMS ML and anteroposterior (AP), and resultant euclidean scalar (RES) (ES = 0.83-1.9).

Discussion

The IMU was found reliable for the analysis of the studied trunk acceleration-based variables. This is the first study that reports different results concerning acceleration (RMS) and trunk displacement variables for a same axis in the analysis of sex-based differences.

Assessment of Ground Contact Time in the Field: Evaluation of Validity and Reliability

ABSTRACT

Weber, JA, Hart, NH, Rantalainen, T, Connick, M, and Newton, RU. Assessment of ground contact time in the field: evaluation of validity and reliability. J Strength Cond Res 38(1): e34-e39, 2024-The capacity to measure the kinetic and kinematic components of running has been extensively investigated in laboratory settings. Many authors have produced work that is of high value to practitioners within sporting environments; however, the lack of field-based technology to assess features of running gait validly and reliably has prevented the application of these valuable works. This paper examines the validity and reliability of a practical field-based methodology for using commercial inertial measurement units (IMUs) to assess ground contact time (GCT). Validity was examined in the comparison of GCT measured from ground reaction force by a force plate and that determined by a lumbar mounted commercial IMU and analyzed using a commercially available system (SPEEDSIG). Reliability was assessed by a field-based examination of within and between-session variability in GCT measured using a commercially available system (SPEEDSIG). Significance was set at p ≤ 0.05. Results for validity (intraclass correlation [ICC] 0.83) and reliability (ICC 0.91) confirm that the described field-based methodology is qualified for use to determine GCT in a practical setting. The implications of this study are important as they offer sport practitioners (S&C coaches, rehab specialists, and physios) a scalable method to assess GCT in the field to develop greater understanding of their athletes and improve performance, injury prevention, and rehabilitation interventions. Furthermore, these results provide the foundation for further work that could provide greater detail describing individual running gait in the field.

Use of subject-specific models to detect fatigue-related changes in running biomechanics: a random forest approach

Running biomechanics are affected by fatiguing or prolonged runs. However, no evidence to date has conclusively linked this effect to running-related injury (RRI) development or performance implications. Previous investigations using subject-specific models in running have demonstrated higher accuracy than group-based models, however, this has been infrequently applied to fatigue. In this study, two experiments were conducted to determine whether subject-specific models outperformed group-based models to classify running biomechanics during non-fatigued and fatigued conditions. In the first experiment, 16 participants performed four treadmill runs at or around the maximal lactate steady state. In the second experiment, nine participants performed five prolonged runs using commercial wearable devices. For each experiment, two segments were extracted from each trial from early and late in the run. For each participant, a random forest model was applied with a leave-one-run-out cross-validation to classify between the early (non-fatigued) and late (fatigued) segments. Additionally, group-based classifiers with a leave-one-subject-out cross validation were constructed. For experiment 1, mean classification accuracies for the single-subject and group-based classifiers were 68.2 ± 8.2% and 57.0 ± 8.9%, respectively. For experiment 2, mean classification accuracies for the single-subject and group-based classifiers were 68.9 ± 17.1% and 61.5 ± 11.7%, respectively. Variable importance rankings were consistent within participants, but these rankings differed from each participant to those of the group. Although the classification accuracies were relatively low, these findings highlight the advantage of subject-specific classifiers to detect changes in running biomechanics with fatigue and indicate the potential of using big data and wearable technology approaches in future research to determine possible connections between biomechanics and RRI.

The impact of shape and attachment position of biologging devices in Northern Bald Ibises

Background

The impact of biologging devices on the aerodynamics or hydrodynamics of animals is still poorly understood. This stands in marked contrast to the ever more extensive use of such technologies in wild-living animals. Recently, increasing concerns have been raised about the impairing effects of these devices on the animals concerned. In the early days of biotelemetry, attention was focused solely on reducing weight, but now aerodynamic effects are also increasingly being considered. To investigate these effects, we trained Northern Bald Ibises to fly in a wind tunnel in which we measured heart rate and dynamic body acceleration (VeDBA) as proxies for energy expenditure in relation to different logger shapes and wind flow directions.

Results

Our data provide evidence that the position of biologging devices significantly influence the flight distances, and the shape of biologging devices has a considerable effect on heart rate and VeDBA, both of which have been used as proxies for energy expenditure. Unfavorable shape and positioning go beyond merely affecting the effort required during flapping flight. The energetically probably more important effect is that the devices impair the bird's ability to glide or soar and thus force them to perform the energetically much more demanding flapping flight more frequently. This effect was more pronounced in rising air than in horizontal airflow. A complementary study with wild Northern Bald Ibises during spring migration provides evidence that the position of the devices on the bird's back affects the length of the flight stages. Birds carrying the devices on the upper back, fixed by wing-loop harnesses, had significantly shorter flight stages compared to birds with a more caudally positioned device, fixed by leg-loop harnesses.

Conclusion

The attachment of biologging devices on birds affects their performance and behavior and thus may influence their fitness and mortality. Our results show that detrimental effects can be reduced with relatively little effort, in particular through a strictly aerodynamic design of the housing and increased consideration of aerodynamics when attaching the device to the body. In birds, the attachment of biologging devices via leg loops to the lower back is clearly preferable to the common attachment via wing loops on the upper back, even if this affects the efficiency of the solar panels. Nevertheless, the importance of drag reduction may vary between systems, as the benefits of having a biologging devices close to the center of gravity may outweigh the increase in drag that this involves. Overall, more research is required in this field. This is both in the interest of animal welfare and of avoiding biasing the quality of the collected data.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40317-023-00322-5.

The influence of midsole shear on running economy and smoothness with a 3D-printed midsole

The objectives of this study were to first determine whether a newly designed 3D-printed midsole, configured with a mechanism to increase anterior-posterior deformation, could increase anterior midsole shear during the stance phase of running. We then wanted to determine whether these shoes could affect running economy and smoothness. Two footwear conditions, differing in midsole technology, were used in this study. The control condition consisted of a thermoplastic polyurethane midsole (TPU-Control), whereas the prototype shoes (3D-Shear) were constructed with a 3D-printed lattice midsole designed for greater anterior foot displacement during early to mid-stance. Twenty male participants ran on a treadmill for 6 min in each condition, and data were collected during the final 2 min. Midsole shear was measured using 3D kinematic data; running smoothness was quantified with peak acceleration and jerk magnitudes from the foot, sacrum, and head; and running economy was determined with oxygen consumption data. As hypothesised, the anterior midsole shear was greater in the 3D-Shear condition compared to the TPU-Control. The 3D-Shear did not improve running economy. Runners exhibited significantly lower peak accelerations at the sacrum, along with lower magnitudes of jerk at the foot, sacrum, and head in the 3D-Shear condition, indicating smoother running patterns.

Empirical Evidence for Energy Efficiency Using Intermittent Gliding Flight in Northern Bald Ibises

Birds face exceptionally high energy demands during their flight. One visible feature of some species is alternating between flapping and gliding, which should allow them to save energy. To date, there is no empirical evidence of an energetic benefit to this. To understand the physiology behind the strategy, we equipped hand-raised Northern Bald Ibises (Geronticus eremita) with data loggers during human-guided migration. We monitored the position of the birds, wingbeats, overall dynamic body acceleration (ODBA), and heart rates as a proxy for energy expenditure. The energy expenditure was significantly affected by the length of flapping and gliding bouts. A pronounced decrease in heart rate was measured after already 1 s of gliding. Additionally, the heart rate at flapping bouts up to 30 s increased steadily but stabilized thereafter. The gilding proportion during intermittent flight affected the energy saving compared to continuous flapping. At a gliding proportion of about 20%, we measured a maximum of 11% saving based on heart rate measurement. At higher gliding proportions, the additional energy saving was negligible. Furthermore, as during flight, not all energy is used for mechanical work, we found a greater decrease rate of ODBA at different gliding proportions compared to heart rate. Nevertheless, the combination of the two methods is essential to determine birds’ movement and energy expenditure. This study provides empirical evidence that intermittent flight is energetically beneficial and can reduce the high costs of flights.

Validity of trunk acceleration measurement with a chest-worn monitor for assessment of physical activity intensity

Background

Recent advancements in wearable technology have enabled easy measurement of daily activities, potentially applicable in rehabilitation practice for various purposes such as maintaining and increasing patients’ activity levels. In this study, we aimed to examine the validity of trunk acceleration measurement using a chest monitor embedded in a smart clothing system (‘hitoe’ system), an emerging wearable system, in assessing the physical activity in an experimental setting with healthy subjects (Study 1) and in a clinical setting with post-stroke patients (Study 2).

Methods

Study 1 involved the participation of 14 healthy individuals. The trunk acceleration, heart rate (HR), and oxygen consumption were simultaneously measured during treadmill testing with a Bruce protocol. Trunk acceleration and HR were measured using the "hitoe" system, a smart clothing system with embedded chest sensors. Expiratory gas analysis was performed to measure oxygen consumption. Three parameters, moving average (MA), moving standard deviation (MSD), and moving root mean square (RMS), were calculated from the norm of the trunk acceleration. The relationships between these accelerometer-based parameters and oxygen consumption-based physical activity intensity measured with the percent VO2 reserve (%VO₂R) were examined. In Study 2, 48 h of simultaneous measurement of trunk acceleration and heart rate-based physical activity intensity in terms of percent heart rate reserve (%HRR) was conducted with the "hitoe" system in 136 post-stroke patients.

Results

The values of MA, MSD, RMS, and %VO₂R were significantly different between levels 1, 2, 3, and 4 in the Bruce protocol (P < 0.01). The average coefficients of determination for individual regression for %VO₂R versus MA, %VO₂R versus MSD, and %VO₂R versus RMS were 0.89 ± 0.05, 0.96 ± 0.03, and 0.91 ± 0.05, respectively. Among the parameters examined, MSD showed the best correlation with %VO₂R, indicating high validity of the parameter for assessing physical activity intensity. The 48-h measurement of MSD and %HRR in post-stroke patients showed significant within-individual correlation (P < 0.05) in 131 out of 136 patients (correlation coefficient: 0.60 ± 0.16).

Conclusions

The results support the validity of the MSD calculated from the trunk acceleration measured with a smart clothing system in assessing the physical activity intensity.

Trial registration: UMIN000034967. Registered 21 November 2018 (retrospectively registered).

Supplementary Information

The online version contains supplementary material available at 10.1186/s13102-022-00492-4.

Between-Day Reliability of Commonly Used IMU Features during a Fatiguing Run and the Effect of Speed

The purpose of this study was to determine if fatigue-related changes in biomechanics derived from an inertial measurement unit (IMU) placed at the center of mass (CoM) are reliable day-to-day. Sixteen runners performed two runs at maximal lactate steady state (MLSS) on a treadmill, one run 5% above MLSS speed, and one run 5% below MLSS speed while wearing a CoM-mounted IMU. Trials were performed to volitional exhaustion or a specified termination time. IMU features were derived from each axis and the resultant. Feature means were calculated for each subject during non-fatigued and fatigued states. Comparisons were performed between the two trials at MLSS and between all four trials. The only significant fatigue state × trial interaction was the 25th percentile of the results when comparing all trials. There were no main effects for trial for either comparison method. There were main effects for fatigue state for most features in both comparison methods. Reliability, measured by an intraclass coefficient (ICC), was good-to-excellent for most features. These results suggest that fatigue-related changes in biomechanics derived from a CoM-mounted IMU are reliable day-to-day when participants ran at or around MLSS and are not significantly affected by slight deviations in speed.

Insulin and cancer: a tangled web

For a century, since the pioneering work of Otto Warburg, the interwoven relationship between metabolism and cancer has been appreciated. More recently, with obesity rates rising in the U.S. and worldwide, epidemiologic evidence has supported a link between obesity and cancer. A substantial body of work seeks to mechanistically unpack the association between obesity, altered metabolism, and cancer. Without question, these relationships are multifactorial and cannot be distilled to a single obesity- and metabolism-altering hormone, substrate, or factor. However, it is important to understand the hormone-specific associations between metabolism and cancer. Here, we review the links between obesity, metabolic dysregulation, insulin, and cancer, with an emphasis on current investigational metabolic adjuncts to standard-of-care cancer treatment.

Is This the Real Life, or Is This Just Laboratory? A Scoping Review of IMU-Based Running Gait Analysis

Inertial measurement units (IMUs) can be used to monitor running biomechanics in real-world settings, but IMUs are often used within a laboratory. The purpose of this scoping review was to describe how IMUs are used to record running biomechanics in both laboratory and real-world conditions. We included peer-reviewed journal articles that used IMUs to assess gait quality during running. We extracted data on running conditions (indoor/outdoor, surface, speed, and distance), device type and location, metrics, participants, and purpose and study design. A total of 231 studies were included. Most (72%) studies were conducted indoors; and in 67% of all studies, the analyzed distance was only one step or stride or <200 m. The most common device type and location combination was a triaxial accelerometer on the shank (18% of device and location combinations). The most common analyzed metric was vertical/axial magnitude, which was reported in 64% of all studies. Most studies (56%) included recreational runners. For the past 20 years, studies using IMUs to record running biomechanics have mainly been conducted indoors, on a treadmill, at prescribed speeds, and over small distances. We suggest that future studies should move out of the lab to less controlled and more real-world environments.

A support vector machine algorithm can successfully classify running ability when trained with wearable sensor data from anatomical locations typical of consumer technology

Greater understanding of differences in technique between runners may allow more beneficial feedback related to improving performance and decreasing injury risk. The purpose of this study was to develop and test a support vector machine classifier, which could automatically differentiate running technique between experienced and novice participants using only wearable sensor data. Three-dimensional linear accelerations and angular velocities were collected from six wearable sensors secured to current common smart device locations. Cross-validation was used to test the classification accuracy of models trained with a variety of combinations of sensor locations, with participants running at different speeds. Average classification accuracies ranged from 71.3% to 98.4% across the sensor combinations and running speeds tested. Models trained with only a single sensor location still showed effective classification. With the models trained with only upper arm data achieving an average accuracy of 96.4% across all tested running speeds. A post-hoc comparison of biomechanical variables between the two subgroups showed significant differences in upper body biomechanics throughout the stride. Both the methodology used to perform the classifications and the biomechanical differences identified could prove useful when aiming to shift a novice runner's technique towards movement patterns more akin to those with greater experience.

Does exhaustion modify acceleration running signature?

Previous studies have demonstrated the acceleration signal presents a typical running signature, which allows for the extraction of reliable information. However, few studies have focused on the exhaustion-induced variability of the acceleration signature during running. The present study included 10 participants who ran at a constant speed on a treadmill until exhaustion. The participants were equipped with three accelerometers, located at the lumbar spine, tibia, and foot. The results showed that all the participants kept a constant pace throughout the test (coefficient of variation <5%). Similarities between acceleration signatures were observed using the coefficient of multiple correlation. For the longitudinal axis of the lumbar spine, the longitudinal axis of the tibia, and the anteroposterior axis of the tibia, running signatures were not affected by exhaustion (coefficient of multiple correlation >0.8). For all the other axes, the signature was impacted within and between the states of exhaustion. Signatures were particularly different for the foot sensors, which makes it difficult to use to extract reliable information. The results showed that the coefficient of multiple correlation allowed the quantification of the variability of the running signature, and that each axis and measuring point varied in how they were influenced by exhaustion.

Fatigue-Related Changes in Running Gait Patterns Persist in the Days Following a Marathon Race

CONTEXT

The risk of experiencing an overuse running-related injury can increase with atypical running biomechanics associated with neuromuscular fatigue and/or training errors. While it is important to understand the changes in running biomechanics within a fatigue-inducing run, it may be more clinically relevant to assess gait patterns in the days following a marathon to better evaluate the effects of inadequate recovery on injury.

OBJECTIVE

To use center of mass (CoM) acceleration patterns to investigate changes in running patterns prior to (PRE) and at 2 (POST2) and 7 (POST7) days following a marathon race.

DESIGN

Pre-post intervention study.

SETTING

A 200-m oval track surface.

PARTICIPANTS

Seventeen recreational marathon runners (10 females, age = 34.2 [5.67] y; 7 males, age = 47.41 [15.32] y).

INTERVENTION

Marathon race.

MAIN OUTCOME MEASURES

An inertial measurement unit was placed near the CoM to collect triaxial acceleration data during overground running for PRE, POST2, and POST7 sessions. Twenty-two features were extracted from the acceleration waveforms to characterize different aspects of running gait. Lower-limb musculoskeletal pain was also recorded at each session with a visual analog scale.

RESULTS

At POST2, runners reported higher self-reported pain and exhibited elevated peak mediolateral acceleration with an increased mediolateral ratio of acceleration root mean square compared with PRE. At POST7, pain was reduced and more similar to PRE, with runners demonstrating increased stride regularity in the vertical direction and decreased peak resultant acceleration.

CONCLUSIONS

The observed changes in CoM motion at POST2 may be associated with atypical running biomechanics that can translate to greater mediolateral impulses, potentially increasing the risk of injury. This study demonstrates the use of an accelerometer as an effective tool to detect atypical CoM motion for runners due to fatigue, recovery, and musculoskeletal pain in real-world environments.

Correlation between running asymmetry, mechanical efficiency, and performance during a 10 km run

Running asymmetry is considered a matter of concern for performance and injury, but the association between asymmetry and performance remain unclear. There are different strategies to address asymmetries and its relationship with performance. Here we investigated the correlation between global symmetry index and mechanical efficiency during 10 km running. Thirteen amateur trained athletes (8 men and 5 women) performed a 10 km running at a fixed pace while a 3D accelerometer attached to the pelvic region recorded position data throughout the course of the run and gas exchanges were monitored breath by breath. Global symmetry index was determined for 3 directions, and mechanical efficiency was calculated as the ratio of external work output to energy expenditure determined from gas analysis. Global Symmetry Index and mechanical efficiency decreased (-55.5% and -44.8%, respectively) during the course of the 10 km run (p < 0.01). A positive correlation was observed between global symmetry index and efficiency (r = 0.66, p = 0.01). Asymmetry in the vertical direction had a relatively higher impact on the global symmetry index. The global symmetry index accounted for 43.1% of the variance in mechanical efficiency (p = 0.015). Symmetry, evaluated by the global symmetry index, directly correlates with mechanical efficiency during a 10 km run.

Physical and physiological demands of basketball small-sided games: the influence of defensive and time pressures

Different small-sided games (SSG) can be used by coaches to induce specific demands on athletes during team sports training. In basketball, defensive and time pressures are common stressors experienced by players during official matches. However, no studies have investigated the effect of changing these variables in SSG during training. We compared the physical and physiological demands of three basketball SSG performed in a half court with two hoops: 3vs3 with man-to-man defence in the half playing area, 3vs3 with man-to-man defence in the full playing area, and 3vs3 with a reduced shot-clock (3vs3HALF, 3vs3FULL, 3vs3RT, respectively). Twelve male U-17 basketball athletes formed four balanced teams. Each team played the three SSG against each other in a random order, totalling 18 SSG. During the SSG, the players wore triaxial accelerometers and heart rate monitors. SSG were filmed to record the players’ motor actions. The results showed that 3vs3FULL (p=0.004, d=0.42, small-to-moderate effect) and 3vs3RT (p=0.026, d=0.33, small-to-moderate effect) increased the time spent in higher acceleration zones compared to 3vs3HALF. Both 3vs3FULL and 3vs3RT presented more transition sprints compared to 3vs3HALF. The 3vs3FULL also presented more fakes and the 3vs3RT presented more jumps compared to the 3vs3HALF. Physiological responses presented no differences between the SSG formats. In conclusion, defensive and time pressures increase the physical demand in 3vs3 SSG performed in the half court. The three SSG investigated in this study presented mean heart rate values close to 90% of the maximum heart rate, which suggests that these SSG may be used to increase athletes’ aerobic performance.

Estimation of energy consumed by middle-aged recreational marathoners during a marathon using accelerometry-based devices

As long-distance races have substantially increased in popularity over the last few years, the improvement of training programs has become a matter of concern to runners, coaches and health professionals. Triaxial accelerometers have been proposed as a one of the most accurate tools to evaluate physical activity during free-living conditions. In this study, eighty-eight recreational marathon runners, aged 30–45 years, completed a marathon wearing a GENEActiv accelerometer on their non-dominant wrist. Energy consumed by each runner during the marathon was estimated based on both running speed and accelerometer output data, by applying the previously established GENEActiv cut-points for discriminating the six relative-intensity activity levels. Since accelerometry allowed to perform an individualized estimation of energy consumption, higher interpersonal differences in the number of calories consumed by a runner were observed after applying the accelerometry-based approach as compared to the speed-based method. Therefore, pacing analyses should include information of effort intensity distribution in order to adjust race pacing appropriately to achieve the marathon goal time. Several biomechanical and physiological parameters (maximum oxygen uptake, energy cost of running and running economy) were also inferred from accelerometer output data, which is of great value for coaches and doctors.

Relationship between Lower Limb Kinematics and Upper Trunk Acceleration in Recreational Runners

Upper trunk (UT) kinematics in runners and its relationship with lower limbs has been poorly investigated, although it is acknowledged that dynamic stability of the upper body is a primary objective of human locomotion. This study aimed to explore UT kinematics according to gender and level of training and in relation to lower limb run patterns described through the presence of: overstriding, crossover, excessive protonation, and pelvic drop. Lower body variables chosen to describe running pattern were those that are frequently modified during gait-retraining with the goal of reducing injury risk. Eighty-seven recreational runners (28 females and 59 males, age 41 ± 10 years) performed a one minute run test on a treadmill at self-selected speed. UT kinematics was measured using an inertial measurement unit, while run features were assessed through an optoelectronic system and video analysis. Accelerations and root-mean-square on mediolateral and anteroposterior axes, normalized using the vertical component of the acceleration, were estimated to describe UT stability. Results showed no significant differences in the normalized UT acceleration root-mean-square according to gender and level of training as well as according to the presence of overstriding, crossover, and excessive protonation. The only running strategy studied in this work that showed a significant relationship with UT stability was the presence of excessive pelvic drop. The latter was significantly associated (p=0.020) to a decrease in the normalized acceleration root-mean-square along the mediolateral direction. Although the excessive pelvic drop seemed to have a positive effect in stabilizing the upper body, concerns remain on the effect of a poor control of the pelvis on the biomechanics of lower limbs. Results obtained confirm the hypothesis that the lower body is able to respond to varying impact load conditions to maintain UT stability.

Behavioural compass: animal behaviour recognition using magnetometers

BACKGROUND

Animal-borne data loggers today often house several sensors recording simultaneously at high frequency. This offers opportunities to gain fine-scale insights into behaviour from individual-sensor as well as integrated multi-sensor data. In the context of behaviour recognition, even though accelerometers have been used extensively, magnetometers have recently been shown to detect specific behaviours that accelerometers miss. The prevalent constraint of limited training data necessitates the importance of identifying behaviours with high robustness to data from new individuals, and may require fusing data from both these sensors. However, no study yet has developed an end-to-end approach to recognise common animal behaviours such as foraging, locomotion, and resting from magnetometer data in a common classification framework capable of accommodating and comparing data from both sensors.

METHODS

We address this by first leveraging magnetometers' similarity to accelerometers to develop biomechanical descriptors of movement: we use the static component given by sensor tilt with respect to Earth's local magnetic field to estimate posture, and the dynamic component given by change in sensor tilt with time to characterise movement intensity and periodicity. We use these descriptors within an existing hybrid scheme that combines biomechanics and machine learning to recognise behaviour. We showcase the utility of our method on triaxial magnetometer data collected on ten wild Kalahari meerkats (Suricata suricatta), with annotated video recordings of each individual serving as groundtruth. Finally, we compare our results with accelerometer-based behaviour recognition.

RESULTS

The overall recognition accuracy of > 94% obtained with magnetometer data was found to be comparable to that achieved using accelerometer data. Interestingly, higher robustness to inter-individual variability in dynamic behaviour was achieved with the magnetometer, while the accelerometer was better at estimating posture.

CONCLUSIONS

Magnetometers were found to accurately identify common behaviours, and were particularly robust to dynamic behaviour recognition. The use of biomechanical considerations to summarise magnetometer data makes the hybrid scheme capable of accommodating data from either or both sensors within the same framework according to each sensor's strengths. This provides future studies with a method to assess the added benefit of using magnetometers for behaviour recognition.

Anaerobic capacity assessment in elite swimmers through inertial sensors

OBJECTIVE

The present study aimed to assess if changes in speed and stroke parameters, as measured by an inertial sensor during a maximal effort swimming test, could provide an effective detection of anaerobic capacity in elite swimmers.

APPROACH

Fourteen elite swimmers performed a 75 m maximal swimming test. Changes in speed and stroke parameters, estimated by a body-worn inertial sensor, were analysed to provide insight into stroke mechanics during swimming. Their relationships with the output of the Wingate Anaerobic Test were analysed. Best times in competition were also considered to assess swimmer's performance.

MAIN RESULTS

Mean power measured using the Wingate cycle ergometer test highly correlated with mean speed attained by the swimmers during the proposed 75 m swimming test (R range: .700-.809, p   <  .05). Mean power in the Wingate Anaerobic Test and mean speed in the 75 m swimming test highly correlated with best times attained by the swimmers (R range: .736-.855, p   <  .01; R range: .659-.952, p   <  .05, for Wingate and 75 m swimming test, respectively). Moreover, stroke variables were investigated: in this regard, a significant decrease in stroke rate and swimming speed and a significant increase in stroke length were observed between the first and the third lap (p   <  .01).

SIGNIFICANCE

The present in-water free swimming test provided insight into specific physiological/mechanical aspects of elite swimmers. The correlation of the swimming and the Wingate tests with swimmer's performance in competition confirms that they both reflect the skills and anaerobic qualities a swimmer uses in a race. The wearable inertial sensor could represent a feasible solution to evaluate stroke parameters, allowing a timely follow-up of variations in swimming biomechanics along the course of the test and the identification of differences in biomechanical strategy between swimmers. This analysis is of great interest for swimmers and coaches to characterise swimmer's technique weakness and strength, and to plan individual race pacing strategy.

Effect of running speed on temporal and frequency indicators from wearable MEMS accelerometers

Amplified by the development of new technologies, the interest in personal performance has been growing over the last years. Acceleration has proved to be an easy variable to collect, and was addressed in several works. However, few of them evaluate the effect of running speed on relevant indicators. The influence of the sensors location on the measurement is rarely studied as well. This study is dedicated to investigating the effect of running speed on acceleration measured at three different positions on 18 volunteers. All participants were equipped with three inertial measurement units: on the dorsal surface of the right foot (Fo), at the centre of gravity of the tibia (Ti), at the L4-L5 lumbar (Lu). The test was performed on a treadmill at nine randomised speeds between 8 and 18 km/h. Ten accelerometric variables were calculated. Linear regressions were used to calculate speed from the indicators calculated on (Lu), (Ti), (Fo). Indicators associated to signal energy were highly correlated with speed (r2>0.90). Median frequency appears to be affected by the frequency resolution. Finally, the measurement points closest to the impact zone result in the most correlated indicators.

A time to exhaustion model during prolonged running based on wearable accelerometers

Defining relationships between running mechanisms and fatigue can be a major asset for optimising training. This article proposes a biomechanical model of time to exhaustion according to indicators derived from accelerometry data collected from the body. Ten volunteers were recruited for this study. The participants were equipped with 3 accelerometers: on the right foot, at the tibia and at the L4-L5 lumbar spine. A running test was performed on a treadmill at 13.5 km/h until exhaustion. Thirty-one variables were deployed during the test. Multiple linear regressions were calculated to explain the time to exhaustion from the indicators calculated on the lumbar, tibia and foot individually and simultaneously. Time to exhaustion was predicted for simultaneous measurement points with r 2 = 0.792 and 21 indicators; for the lumbar with r 2 = 0.568 and 11 indicators; for the tibia with r 2 = 558 and 11 indicators; and for the foot with r 2 = 0.626 and 12 indicators. This study allows the accurate modelling of the time to exhaustion during a running-based test using indicators from accelerometer measurements. The individual models highlight that the location of the measurement point is important and that each location provides different information. Future studies should focus on homogeneous populations to improve predictions and errors.

Energy expenditure associated with walking speed and angle of turn in children

Purpose

Recent studies have suggested that turning is power intensive. Given the sporadic and irregular movement patterns of children, such findings have important implications for the assessment of true energy expenditure associated with habitual physical activity. The purpose of this study was to investigate the influence of walking speed and angle, and their interaction, on the energy expenditure of healthy children.

Methods

20 children (10.1 ± 0.5 years; 10 boys) participated in the study. On two separate days, participants completed a turning protocol involving 3-min bouts of walking at one of the 16 speed (2.5, 3.5, 4.5, and 5.5 km h^− 1) and angle (0°, 45°, 90°, and 180°) combinations, interspersed by 3 min seated rest. The movement involved 5 m straight walking interspaced with prescribed turns with speed dictated by a digital, auditory metronome. Breath-by-breath gas exchange was measured, in addition to tri-axial acceleration and magnetic field intensity recorded at 100 Hz.

Results

Mixed models revealed a significant main effect for speed (p < 0.006) and angle (p < 0.006), with no significant interaction between speed and angle (p > 0.006). Significant differences to straight-line walking energy expenditure within speed were established for 3.5 and 5.5 km h^− 1 for 180° turns (~ 13% and ~ 30% increase, respectively).

Conclusion

These findings highlight the importance of accounting for the magnitude and frequency of turns completed when estimating children’s habitual physical activity and have significant implications for the assessment of daily energy expenditure.

Late-cueing of gait tasks on an uneven brick surface impacts coordination and center of mass control in older adults

BACKGROUND

Changing directions while walking (turning gait), often with little planning time, is essential to navigating irregular surfaces in the built-environment. It is unclear how older adults reorient their bodies under these constraints and whether adaptations are related to declines in physiological characteristics.

RESEARCH QUESTION

The aims of this study were to (1) investigate whether surface irregularity, late-cueing, and age negatively affect coordination, kinematics, and center of mass (COM) movement during 90° turning gait and (2) determine if adaptations correlate with declines in strength, balance, and reaction-time.

METHODS

Eighteen young (18-35 years) and sixteen older (65+ years) healthy adults participated in the study. Retro-reflective marker and trunk-accelerometry data were used to compute upper-body segmental reorientation timing, upper-body kinematics, and COM movement characteristics. Balance scores, lower-limb strength, and choice-reaction-times were also recorded.

RESULTS

Young and older adults maintained a cranial-caudal (head, shoulders, pelvis) reorientation sequence (p ≤ 0.018), lowered head pitch (uneven surface; young p = 0.035 and old p < 0.001), increased maximum COM acceleration (uneven surface and late-cueing; p ≤ 0.002), and decreased COM smoothness (uneven surface; p < 0.001). Young adults increased shoulder roll (uneven surface and late-cueing; p ≤ 0.008). Reduced stride regularity (late-cueing) was observed in older (p < 0.001), compared to young (p = 0.017), adults. Declines in strength (p ≤ 0.040) and balance (p = 0.018) were correlated with gait adaptations of older adults.

SIGNIFICANCE

Late-cueing on an uneven surface is challenging for older adults. These challenges are exacerbated by strength and balance deficits.

Use of baseline pelvic acceleration during running for classifying response to muscle strengthening treatment in patellofemoral pain: A preliminary study

BACKGROUND

Objectively identifying patients at baseline who may not respond well to a generic muscle strengthening intervention could improve clinical practice by optimizing treatment strategies. The purpose of this study was to determine whether pelvic acceleration measures during running, and clinical and demographic variables could classify patellofemoral pain patients according to their response to a 6-week hip/core and knee exercise-based rehabilitation protocol.

METHODS

Forty-one individuals with patellofemoral pain participated in a 6-week exercise intervention program and were sub-grouped into treatment Responders (n = 28) and Non-responders (n = 13) based on self-reported pain and function measures. Baseline pelvic acceleration measures were reduced using a principal component analysis and combined with patient reported outcome measures and demographic variables in a support vector machine to retrospectively classify patient treatment response.

FINDINGS

The final classification model had 85.4% classification accuracy, which was significantly better than treatment success rate, with excellent detection rates for Responders (recall: 96.4%), but 23.1% of misclassifications among Non-responders (precision: 90.0%). Thus, it resulted in an F1-score of 0.93 and a Matthews correlation coefficient of 0.69.

INTERPRETATION

Overall, the classifier successfully separated patellofemoral pain patients into exercise-based treatment Responders and Non-responders based on a combination of three components of the pelvic accelerations. While this model requires independent validation, it has the potential for further development and to be applied in clinical practice and improve treatment strategies for patellofemoral pain.

The Effect of Match Schedule on Accelerometry-Derived Exercise Dose during Training Sessions throughout a Competitive Basketball Season

Accelerometry-derived exercise dose (intensity × duration) was assessed throughout a competitive basketball season. Nine elite basketballers wore accelerometers during a Yo-Yo intermittent recovery test (Yo-Yo-IR1) and during three two-week blocks of training that represented phases of the season defined as easy, medium, and hard based on difficulty of match schedule. Exercise dose was determined using accumulated impulse (accelerometry-derived average net force × duration). Relative exercise intensity was quantified using linear relationships between average net force and oxygen consumption during the Yo-Yo-IR1. Time spent in different intensity zones was computed. Influences of match schedule difficulty and playing position were evaluated. Exercise dose reduced for recovery and pre-match tapering sessions during the medium match schedule. Exercise dose did not vary during the hard match schedule. Exercise dose was not different between playing positions. The majority of activity during training was spent performing sedentary behaviour or very light intensity activity (64.3 ± 6.1%). Front-court players performed a greater proportion of very light intensity activity (mean difference: 6.8 ± 2.8%), whereas back-court players performed more supramaximal intensity activity (mean difference: 4.5 ± 1.0%). No positional differences existed in the proportion of time in all other intensity zones. Objective evaluation of exercise dose might allow coaches to better prescribe and monitor the demands of basketball training.

Data fusion of body-worn accelerometers and heart rate to predict VO2max during submaximal running

Maximal oxygen uptake (VO2max) is often used to assess an individual's cardiorespiratory fitness. However, measuring this variable requires an athlete to perform a maximal exercise test which may be impractical, since this test requires trained staff and specialized equipment, and may be hard to incorporate regularly into training programs. The aim of this study is to develop a new model for predicting VO2max by exploiting its relationship to heart rate and accelerometer features extracted during submaximal running. To do so, we analyzed data collected from 31 recreational runners (15 men and 16 women) aged 19-26 years who performed a maximal incremental test on a treadmill. During this test, the subjects' heart rate and acceleration at three locations (the upper back, the lower back and the tibia) were continuously measured. We extracted a wide variety of features from the measurements of the warm-up and the first three stages of the test and employed a data-driven approach to select the most relevant ones. Furthermore, we evaluated the utility of combining different types of features. Empirically, we found that combining heart rate and accelerometer features resulted in the best model with a mean absolute error of 2.33 ml ⋅ kg-1 ⋅ min-1 and a mean absolute percentage error of 4.92%. The model includes four features: gender, body mass, the inverse of the average heart rate and the inverse of the variance of the total tibia acceleration during the warm-up stage of the treadmill test. Our model provides a practical tool for recreational runners in the same age range to estimate their VO2max from submaximal running on a treadmill. It requires two body-worn sensors: a heart rate monitor and an accelerometer positioned on the tibia.

Running patterns for male and female competitive and recreational runners based on accelerometer data

The purpose of this study was to classify runners in sex-specific groups as either competitive or recreational based on center of mass (CoM) accelerations. Forty-one runners participated in the study (25 male and 16 female), and were labeled as competitive or recreational based on age, sex, and race performance. Three-dimensional acceleration data were collected during a 5-minute treadmill run, and 24 features were extracted. Support vector machine classification models were used to examine the utility of the features in discriminating between competitive and recreational runners within each sex-specific subgroup. Competitive and recreational runners could be classified with 82.63 % and 80.4 % in the male and female models, respectively. Dominant features in both models were related to regularity and variability, with competitive runners exhibiting more consistent running gait patterns, but the specific features were slightly different in each sex-specific model. Therefore, it is important to separate runners into sex-specific competitive and recreational subgroups for future running biomechanical studies. In conclusion, we have demonstrated the ability to analyze running biomechanics in competitive and recreational runners using only CoM acceleration patterns. A runner, clinician, or coach may use this information to monitor how running patterns change as a result of training.

Runners with patellofemoral pain demonstrate sub-groups of pelvic acceleration profiles using hierarchical cluster analysis: an exploratory cross-sectional study

Background

Previous studies have suggested that distinct and homogenous sub-groups of gait patterns exist among runners with patellofemoral pain (PFP), based on gait analysis. However, acquisition of 3D kinematic data using optical systems is time consuming and prone to marker placement errors. In contrast, axial segment acceleration data can represent an overall running pattern, being easy to acquire and not influenced by marker placement error. Therefore, the purpose of this study was to determine if pelvic acceleration patterns during running could be used to classify PFP patients into homogeneous sub-groups. A secondary purpose was to analyze lower limb kinematic data to investigate the practical implications of clustering these subjects based on 3D pelvic acceleration data.

Methods

A hierarchical cluster analysis was used to determine sub-groups of similar running profiles among 110 PFP subjects, separately for males (n = 44) and females (n = 66), using pelvic acceleration data (reduced with principal component analysis) during treadmill running acquired with optical motion capture system. In a secondary analysis, peak joint angles were compared between clusters (α = 0.05) to provide clinical context and deeper understanding of variables that separated clusters.

Results

The results reveal two distinct running gait sub-groups (C1 and C2) for female subjects and no sub-groups were identified for males. Two pelvic acceleration components were different between clusters (PC1 and PC5; p < 0.001). While females in C1 presented similar acceleration patterns to males, C2 presented greater vertical and anterior peak accelerations. All females presented higher and delayed mediolateral acceleration peaks than males. Males presented greater ankle eversion (p < 0.001), lower knee abduction (p = 0.007) and hip adduction (p = 0.002) than all females, and lower hip internal rotation than C1 (p = 0.007).

Conclusions

Two distinct and homogeneous kinematic PFP sub-groups were identified for female subjects, but not for males. The results suggest that differences in running gait patterns between clusters occur mainly due to sex-related factors, but there are subtle differences among female subjects. This study shows the potential use of pelvic acceleration patterns, which can be acquired with accessible wearable technology (i.e. accelerometers).

Trends Supporting the In-Field Use of Wearable Inertial Sensors for Sport Performance Evaluation: A Systematic Review

Recent technological developments have led to the production of inexpensive, non-invasive, miniature magneto-inertial sensors, ideal for obtaining sport performance measures during training or competition. This systematic review evaluates current evidence and the future potential of their use in sport performance evaluation. Articles published in English (April 2017) were searched in Web-of-Science, Scopus, Pubmed, and Sport-Discus databases. A keyword search of titles, abstracts and keywords which included studies using accelerometers, gyroscopes and/or magnetometers to analyse sport motor-tasks performed by athletes (excluding risk of injury, physical activity, and energy expenditure) resulted in 2040 papers. Papers and reference list screening led to the selection of 286 studies and 23 reviews. Information on sport, motor-tasks, participants, device characteristics, sensor position and fixing, experimental setting and performance indicators was extracted. The selected papers dealt with motor capacity assessment (51 papers), technique analysis (163), activity classification (19), and physical demands assessment (61). Focus was placed mainly on elite and sub-elite athletes (59%) performing their sport in-field during training (62%) and competition (7%). Measuring movement outdoors created opportunities in winter sports (8%), water sports (16%), team sports (25%), and other outdoor activities (27%). Indications on the reliability of sensor-based performance indicators are provided, together with critical considerations and future trends.

Differences in Spatiotemporal Parameters Between Trained Runners and Untrained Participants

Gómez-Molina, J, Ogueta-Alday, A, Stickley, C, Tobalina, JC, Cabrejas-Ugartondo, J, and García-López, J. Differences in spatiotemporal parameters between trained runners and untrained participants. J Strength Cond Res 31(8): 2169-2175, 2017-The aim of this study was to compare the spatiotemporal parameters of trained runners and untrained participants with the same foot strike pattern (rearfoot) during running at controlled speeds. Twenty-one participants were classified in 2 groups according to their training experience: Trained (n = 10, amateur runners with long distance training experience) and Untrained (n = 11, healthy untrained participants). Anthropometric variables were recorded, and the participants performed both a submaximal (between 9 and 15 km·h) and a graded exercise running test (from 6 km·h until exhaustion) on a treadmill. Physiological (V[Combining Dot Above]O2max, heart rate, running economy [RE], peak speed …) and biomechanical variables (contact and flight times, step rate, and length) were simultaneously registered. Trained runners showed higher step rate and shorter step length than the Untrained group at the same running speeds (between 4 and 7%, p ≤ 0.05) and at the same physiological intensities (between 7 and 11%, p ≤ 0.05). However, there were no differences in contact and flight times between groups. Significant differences (p ≤ 0.05) and large effect sizes (Cohen's d) between groups were found for body mass, sum of 6 skinfolds, V[Combining Dot Above]O2max, peak speed, and ventilatory threshold and respiratory compensation threshold speeds. The Trained group also showed a ∼7% better RE (ml·kg·km) than the Untrained group. In conclusion, adopting higher step rate and shorter step length may be an adaptive mechanism of the Trained group to reduce injury risk and possibly improve RE. However, contact and flight times were consistent regardless of training level.

Influence of outdoor running fatigue and medial tibial stress syndrome on accelerometer-based loading and stability

Medial tibial stress syndrome (MTSS) is a common overuse running injury with pathomechanics likely to be exaggerated by fatigue. Wearable accelerometry provides a novel alternative to assess biomechanical parameters continuously while running in more ecologically valid settings. The purpose of this study was to determine the influence of outdoor running fatigue and MTSS on both dynamic loading and dynamic stability derived from trunk and tibial accelerometery. Runners with (n=14) and without (n=16) history of MTSS performed an outdoor fatigue run of 3200m. Accelerometer-based measures averaged per lap included dynamic loading of the trunk and tibia (i.e. axial peak positive acceleration, signal power magnitude, and shock attenuation) as well as dynamic trunk stability (i.e. tri-axial root mean square ratio, step and stride regularity, and sample entropy). Regression coefficients from generalised estimating equations were used to evaluate group by fatigue interactions. No evidence could be found for dynamic loading being higher with fatigue in runners with MTSS history (all measures p>0.05). One significant group by running fatigue interaction effect was detected for dynamic stability. Specifically, in MTSS only, decreases mediolateral sample entropy i.e. loss of complexity was associated with running fatigue (p<0.01). The current results indicate that entire acceleration waveform signals reflecting mediolateral trunk control is related to MTSS history, a compensation that went undetected in the non-fatigued running state. We suggest that a practical outdoor running fatigue protocol that concurrently captures trunk accelerometry-based movement complexity warrants further prospective investigation as an in-situ screening tool for MTSS individuals.

Energy cost of running instability evaluated with wearable trunk accelerometry

Maintaining stability under dynamic conditions is an inherent challenge to bipedal running. This challenge may impose an energetic cost (Ec) thus hampering endurance running performance, yet the underlying mechanisms are not clear. Wireless triaxial trunk accelerometry is a simple tool that could be used to unobtrusively evaluate these mechanisms. Here, we test a cost of instability hypothesis by examining the contribution of trunk accelerometry-based measures (triaxial root mean square, step and stride regularity, and sample entropy) to interindividual variance in Ec (J/m) during treadmill running. Accelerometry and indirect calorimetry data were collected concurrently from 30 recreational runners (16 men; 14 women) running at their highest steady-state running speed (80.65 ± 5.99% V̇o_2max). After reducing dimensionality with factor analysis, the effect of dynamic stability features on Ec was evaluated using hierarchical multiple regression analysis. Three accelerometry-based measures could explain an additional 10.4% of interindividual variance in Ec after controlling for body mass, attributed to anteroposterior stride regularity (5.2%), anteroposterior root mean square ratio (3.2%), and mediolateral sample entropy (2.0%). Our results lend support to a cost of instability hypothesis, with trunk acceleration waveform signals that are 1) more consistent between strides anteroposterioly, 2) larger in amplitude variability anteroposterioly, and 3) more complex mediolaterally and are energetically advantageous to endurance running performance. This study shows that wearable trunk accelerometry is a useful tool for understanding the Ec of running and that running stability is important for economy in recreational runners. NEW & NOTEWORTHY This study evaluates and more directly lends support to a cost of instability hypothesis between runners. Moreover, this hypothesis was tested using a minimalist setup including a single triaxial trunk mounted accelerometer, with potential transferability to biomechanical and performance analyses in typical outdoor settings.

Human runners exhibit a least variable gait speed

This study characterises the relationship between gait variability and speed in runners using data from trunk accelerations in each axis. Twelve participants of varying fitness ran on the treadmill with three sessions of six randomly ordered self-selected speeds. A VO_2max test was conducted on the fourth session. Running gait was tracked with inertial sensors. The occurrence of a mid-range speed was analysed for the anterior-posterior, vertical and lateral directional coefficient of variation (CV) of root mean square (RMS) acceleration data. One participant with noisy gait signals was omitted. The results show all remaining participants consistently showed significant quadratic U-shaped relationships between vertical RMS CV acceleration and speed. Neither anterior-posterior nor lateral RMS CV acceleration were clearly related to speed. These least variable gait speeds were similar to estimates of optimal speed derived from minimum cost of transport with speed. In conclusion, there exists a mid-range speed for each runner with the least variable gait in the vertical direction, and this occurred significantly more often than would be expected by chance (P < 0.05). However, there are no prominent patterns for the anterior-posterior and lateral directions. This finding supports anecdotal evidence from runners and coaches concerning gait consistency.

Surface effects on dynamic stability and loading during outdoor running using wireless trunk accelerometry

Despite frequently declared benefits of using wireless accelerometers to assess running gait in real-world settings, available research is limited. The purpose of this study was to investigate outdoor surface effects on dynamic stability and dynamic loading during running using tri-axial trunk accelerometry. Twenty eight runners (11 highly-trained, 17 recreational) performed outdoor running on three outdoor training surfaces (concrete road, synthetic track and woodchip trail) at self-selected comfortable running speeds. Dynamic postural stability (tri-axial acceleration root mean square (RMS) ratio, step and stride regularity, sample entropy), dynamic loading (impact and breaking peak amplitudes and median frequencies), as well as spatio-temporal running gait measures (step frequency, stance time) were derived from trunk accelerations sampled at 1024Hz. Results from generalized estimating equations (GEE) analysis showed that compared to concrete road, woodchip trail had several significant effects on dynamic stability (higher AP ratio of acceleration RMS, lower ML inter-step and inter-stride regularity), on dynamic loading (downward shift in vertical and AP median frequency), and reduced step frequency (p<0.05). Surface effects were unaffected when both running level and running speed were added as potential confounders. Results suggest that woodchip trails disrupt aspects of dynamic stability and loading that are detectable using a single trunk accelerometer. These results provide further insight into how runners adapt their locomotor biomechanics on outdoor surfaces in situ.

Multiscale entropy: A tool for understanding the complexity of postural control

Clinical disorders often are characterized by a breakdown in dynamical processes that contribute to the control of upright standing. Disruption to a large number of physiological processes operating at different time scales can lead to alterations in postural center of pressure (CoP) fluctuations. Multiscale entropy (MSE) has been used to identify differences in fluctuations of postural CoP time series between groups with and without known physiological impairments at multiple time scales. The purpose of this paper is to: 1) review basic elements and current developments in entropy techniques used to assess physiological complexity; and 2) identify how MSE can provide insights into the complexity of physiological systems operating at multiple time scales that underlie the control of posture. We review and synthesize evidence from the literature providing support for MSE as a valuable tool to evaluate the breakdown in the physiological processes that accompany changes due to aging and disease in postural control. This evidence emerges from observed lower MSE values in individuals with multiple sclerosis, idiopathic scoliosis, and in older individuals with sensory impairments. Finally, we suggest some future applications of MSE that will allow for further insight into how physiological deficits impact the complexity of postural fluctuations; this information may improve the development and evaluation of new therapeutic interventions.

A wireless accelerometer node for reliable and valid measurement of lumbar accelerations during treadmill running

This study investigated the reliability of a wireless accelerometer and its agreement with optical motion capture for the measurement of root mean square (RMS) acceleration during running. RMS acceleration provides a whole-body metric of movement mechanics and economy. Fifteen healthy college-age participants performed treadmill running for two 60-s trials at 2.22, 2.78, and 3.33 m/s and one trial of 150 s (five 30-s epochs) at 2.78 m/s. We assessed between-trial and within-trial reliability, and agreement in each axis between a trunk-mounted wireless accelerometer and a reflective marker on the accelerometer measured by optical motion capture. Intraclass correlations assessing between-trial repeatability were 0.89-0.97, depending on the axis, and intraclass correlations assessing within-trial repeatability were 0.99-1.00. Bland-Altman analyses assessing agreement indicated mean difference values between -0.03 and 0.03 g, depending on the axis. Anterio-posterior acceleration had the greatest limits of agreement (LOA) (±0.12 g) and vertical acceleration had the smallest LOA (±0.03 g). For measuring RMS acceleration of the trunk, this wireless accelerometer node provides repeatable and valid measurement compared with the standard laboratory method of optical motion capture.

Wireless Tri-Axial Trunk Accelerometry Detects Deviations in Dynamic Center of Mass Motion Due to Running-Induced Fatigue

Small wireless trunk accelerometers have become a popular approach to unobtrusively quantify human locomotion and provide insights into both gait rehabilitation and sports performance. However, limited evidence exists as to which trunk accelerometry measures are suitable for the purpose of detecting movement compensations while running, and specifically in response to fatigue. The aim of this study was therefore to detect deviations in the dynamic center of mass (CoM) motion due to running-induced fatigue using tri-axial trunk accelerometry. Twenty runners aged 18–25 years completed an indoor treadmill running protocol to volitional exhaustion at speeds equivalent to their 3.2 km time trial performance. The following dependent measures were extracted from tri-axial trunk accelerations of 20 running steps before and after the treadmill fatigue protocol: the tri-axial ratio of acceleration root mean square (RMS) to the resultant vector RMS, step and stride regularity (autocorrelation procedure), and sample entropy. Running-induced fatigue increased mediolateral and anteroposterior ratios of acceleration RMS (p < .05), decreased the anteroposterior step regularity (p < .05), and increased the anteroposterior sample entropy (p < .05) of trunk accelerometry patterns. Our findings indicate that treadmill running-induced fatigue might reveal itself in a greater contribution of variability in horizontal plane trunk accelerations, with anteroposterior trunk accelerations that are less regular from step-to-step and are less predictable. It appears that trunk accelerometry parameters can be used to detect deviations in dynamic CoM motion induced by treadmill running fatigue, yet it is unknown how robust or generalizable these parameters are to outdoor running environments.

Validation of Cut-Points for Evaluating the Intensity of Physical Activity with Accelerometry-Based Mean Amplitude Deviation (MAD)

Purpose

Our recent study of three accelerometer brands in various ambulatory activities showed that the mean amplitude deviation (MAD) of the resultant acceleration signal performed best in separating different intensity levels and provided excellent agreement between the three devices. The objective of this study was to derive a regression model that estimates oxygen consumption (VO2) from MAD values and validate the MAD-based cut-points for light, moderate and vigorous locomotion against VO₂ within a wide range of speeds.

Methods

29 participants performed a pace-conducted non-stop test on a 200 m long indoor track. The initial speed was 0.6 m/s and it was increased by 0.4 m/s every 2.5 minutes until volitional exhaustion. The participants could freely decide whether they preferred to walk or run. During the test they carried a hip-mounted tri-axial accelerometer and mobile metabolic analyzer. The MAD was calculated from the raw acceleration data and compared to directly measured incident VO₂. Cut-point between light and moderate activity was set to 3.0 metabolic equivalent (MET, 1 MET = 3.5 ml · kg^-1 · min^-1) and between moderate and vigorous activity to 6.0 MET as per standard use.

Results

The MAD and VO₂ showed a very strong association. Within individuals, the range of r values was from 0.927 to 0.991 providing the mean r = 0.969. The optimal MAD cut-point for 3.0 MET was 91 mg (milligravity) and 414 mg for 6.0 MET.

Conclusion

The present study showed that the MAD is a valid method in terms of the VO₂ within a wide range of ambulatory activities from slow walking to fast running. Being a device-independent trait, the MAD facilitates directly comparable, accurate results on the intensity of physical activity with all accelerometers providing tri-axial raw data.

Index of mechanical efficiency in competitive and recreational long distance runners

The purpose of this investigation was to compare external work and net energy expenditure during a bout of repetitive stretch-shortening cycles between competitive and recreational long-distance runners. Participants were divided into either competitive or recreational runners based on their maximal oxygen consumption and self-reported 1600 m times. The stretch-shortening cycle involved a repetitive hopping protocol on a force plate while measuring oxygen consumption and lactate accumulation for a total of 10 min. External work and net energy expenditure were calculated for 3 min after steady state was achieved and the ratio between these variables was utilised as an index of mechanical efficiency. Lower extremity stiffness was calculated during this interval as well. Net energy expenditure was significantly lower in competitive runners (152.6 ± 33.3 kJ) in comparison to recreational runners (200.6 ± 41.4 kJ) (P = 0.02) given similar amounts of external work performed in both groups (competitive runners = 65.6 ± 20.1 kJ, recreational runners = 68.8 ± 12.1 kJ) (P = 0.67). Index of mechanical efficiency was significantly different between competitive runners (43.2 ± 9.0%) and recreational runners (34.8 ± 5.3%) (P = 0.03). No significant differences were found in lower extremity stiffness (P = 0.64). Competitive distance runners can perform similar levels of external work with lower net energy expenditure and thus a higher index of mechanical efficiency during repetitive stretch-shortening cycles in comparison to recreational runners with similar values of lower extremity stiffness. This ability could possibly be due differences in muscle-tendon length changes, muscle pre-activation, cross-bridge potentiation and short-latency reflex responses as a result of training which should be considered for future investigation.

Contributions of lower extremity kinematics to trunk accelerations during moderate treadmill running

Background

Trunk accelerations during running provide useful information about movement economy and injury risk. However, there is a lack of data regarding the key biomechanical contributors to these accelerations. The purpose was to establish the biomechanical variables associated with root mean square (RMS) accelerations of the trunk.

Methods

Eighteen healthy males (24.0 ± 4.2 yr; 1.78 ± 0.07 m; 79.7 ± 14.8 kg) performed treadmill running with high resolution accelerometer measurement at the lumbar spine and full-body optical motion capture. We collected 60 sec of data at three speeds (2.22, 2.78, 3.33 m∙s⁻¹). RMS was calculated for medio-lateral (ML), anterio-posterior (AP), vertical (VT), and the resultant Euclidean scalar (RES) acceleration. From motion capture, we calculated 14 kinematic variables, including mean sagittal plane joint angles at foot contact, mid-stance, and toe-off. Principal components analysis (PCA) was used to form independent components comprised of combinations of the original variables. Stepwise regressions were performed on the original variables and the components to determine contributions to RMS acceleration in each axis.

Results

Significant speed effects were found for RMS-accelerations in all axes (p < 0.05). Regressions of the original variables indicated from 4 to 5 variables associated with accelerations in each axis (R² = 0.71 to 0.82, p < 0.001). The most prominent contributing variables were associated with the late flight and early stance phase. PCA reduced the data into four components. Component 1 included all hip angles before mid-stance and component 2 was primarily associated with propulsion. Regressions indicated key contributions from components 1 and 2 to ML, VT, and RES acceleration (p < 0.05).

Conclusions

The variables with highest contribution were prior to mid-stance and mechanically relate to shock absorption and attenuation of peak forces. Trunk acceleration magnitude is associated with global running variables, ranging from energy expenditure to forces lending to the mechanics of injury. These data begin to delineate running gait events and offer relationships of running mechanics to those structures more proximal in the kinetic chain. These relationships may provide insight for technique modification to maximize running economy or prevent injury.

Electronic supplementary material

The online version of this article (doi:10.1186/1743-0003-11-162) contains supplementary material, which is available to authorized users.

Classification accuracy of a single tri-axial accelerometer for training background and experience level in runners

Accelerometers are increasingly used tools for gait analysis, but there remains a lack of research on their application to running and their ability to classify running patterns. The purpose of this study was to conduct an exploratory examination into the capability of a tri-axial accelerometer to classify runners of different training backgrounds and experience levels, according to their 3-dimensional (3D) accelerometer data patterns. Training background was examined with 14 competitive soccer players and 12 experienced marathon runners, and experience level was examined with 16 first-time and the same 12 experienced marathon runners. Discrete variables were extracted from 3D accelerations during a short run using root mean square, wavelet transformation, and autocorrelation procedures. A principal component analysis (PCA) was conducted on all variables, including gait speed to account for covariance. Eight PCs were retained, explaining 88% of the variance in the data. A stepwise discriminant analysis of PCs was used to determine the binary classification accuracy for training background and experience level, with and without the PC of Speed. With Speed, the accelerometer correctly classified 96% of runners for both training background and experience level. Without Speed, the accelerometer correctly classified 85% of runners based on training background, but only 68% based on experience level. These findings suggest that the accelerometer is effective in classifying athletes of different training backgrounds, but is less effective for classifying runners of different experience levels where gait speed is the primary discriminator.

PlayerLoad™: reliability, convergent validity, and influence of unit position during treadmill running

PURPOSE

The study aimed to establish the test-retest reliability and convergent validity of PlayerLoad™ (triaxial-accelerometer data) during a standardized bout of treadmill running.

METHODS

Forty-four team-sport players performed 2 standardized incremental treadmill running tests (7-16 km/h) 7 d apart. Players' oxygen uptake (VO2; n = 20), heart rate (n = 44), and triaxialaccelerometer data (PlayerLoad; n = 44) measured at both the scapulae and at the center of mass (COM), were recorded. Accelerometer data from the individual component planes of PlayerLoad (anteroposterior [PLAP], mediolateral [PLML], and vertical [PLV]) were also examined.

RESULTS

Moderate to high test-retest reliability was observed for PlayerLoad and its individual planes (ICC .80-.97, CV 4.2-14.8%) at both unit locations. PlayerLoad was significantly higher at COM vs scapulae (223.4 ± 42.6 vs 185.5 ± 26.3 arbitrary units; P = .001). The percentage contributions of individual planes to PlayerLoad were higher for PLML at the COM (scapulae 20.4% ± 3.8%, COM 26.5% ± 4.9%; P = .001) but lower for PLV (scapulae 55.7% ± 5.3%, COM 49.5% ± 6.9%; P = .001). Between-subjects correlations between PlayerLoad and VO2, and between PlayerLoad and heart rate were trivial to moderate (r = -.43 to .33), whereas within-subject correlations were nearly perfect (r = .92-.98).

CONCLUSIONS

PlayerLoad had a moderate to high degree of test-retest reliability and demonstrated convergent validity with measures of exercise intensity on an individual basis. However, caution should be applied in making between-athletes contrasts in loading and when using recordings from the scapulae to identify lower-limb movement patterns.

Anatomically asymmetrical runners move more asymmetrically at the same metabolic cost

We hypothesized that, as occurring in cars, body structural asymmetries could generate asymmetry in the kinematics/dynamics of locomotion, ending up in a higher metabolic cost of transport, i.e. more ‘fuel’ needed to travel a given distance. Previous studies found the asymmetries in horses’ body negatively correlated with galloping performance. In this investigation, we analyzed anatomical differences between the left and right lower limbs as a whole by performing 3D cross-correlation of Magnetic Resonance Images of 19 male runners, clustered as Untrained Runners, Occasional Runners and Skilled Runners. Running kinematics of their body centre of mass were obtained from the body segments coordinates measured by a 3D motion capture system at incremental running velocities on a treadmill. A recent mathematical procedure quantified the asymmetry of the body centre of mass trajectory between the left and right steps. During the same sessions, runners’ metabolic consumption was measured and the cost of transport was calculated. No correlations were found between anatomical/kinematic variables and the metabolic cost of transport, regardless of the training experience. However, anatomical symmetry significant correlated to the kinematic symmetry, and the most trained subjects showed the highest level of kinematic symmetry during running. Results suggest that despite the significant effects of anatomical asymmetry on kinematics, either those changes are too small to affect economy or some plastic compensation in the locomotor system mitigates the hypothesized change in energy expenditure of running.

Acceleration patterns in the lower and upper trunk during running

The purpose of the present study was to relate 3D acceleration patterns of the lower and upper trunk during running to running gait cycle, assess the validity of stride duration estimated from acceleration patterns, investigate speed-dependent changes in acceleration, and examine the test-retest reliability of these parameters. Thirteen healthy young men performed two running trials each on a treadmill and on land at three speeds (slow, preferred, and fast). The 3D accelerations were measured at the L3 spinous process (lower trunk) and the ensiform process (upper trunk) and synchronised with digital video data. The amplitude and root mean square of acceleration and stride duration were calculated and then analysed by three-way analysis of variance to test effects of running conditions, device location, and running speed. Bland-Altman analysis was used to evaluate the test-retest reliability. Marked changes in acceleration were observed in relation to foot strike during running. Stride durations calculated from the vertical accelerations were nearly equal to those estimated from video data. There were significant speed effects on all parameters, and the low test-retest reliability was confirmed in the anterior-posterior acceleration during treadmill running and the anterior-posterior acceleration at slow speed during treadmill and overground running.