William Johnston

Objective Classification of Dynamic Balance Using a Single Wearable Sensor

4th International Congress on Sport Sciences Research and Technology Support 2016, Porto, Portugal, 7-9 November 2016

Wearable sensing and mobile devices: the future of post-concussion monitoring?

In the past decade, concussion has received large amounts of attention in public, medical and research circles. While our understanding of the nature and management of concussion has greatly improved, there are still major limitations which need to be addressed surrounding the identification of the injury, determining when an individual is safe to return to normal activity, and what factors may contribute to the development of post-concussion syndrome (PCS). The current model of concussion management involves a triage evaluation in the acute stage of injury, focusing on the classic signs and symptoms of concussion. Next, the clinician attempts to evaluate key components of cerebral function through clinical symptom evaluation, and traditional assessments of motor and neurocognitive function [1]. The development of the sports concussion assessment tool saw a massive leap forward in the strategies employed in the management of concussion, as it acknowledged the multifactorial nature of concussion, and provided a standardized means for clinicians to assess the many domains of cerebral function [2]. While these methods have demonstrated some promise in the acute stage, they are not designed for serial monitoring (particularly in instances where PCS develops) [3], and provide us with very little clinically relevant information that can assist clinicians in the return to learn/sport/performance process. The traditional model of concussion assessment coincides with a graduated return-to-play protocol. This protocol is simply dictated by the length of time since the injury, and symptom resolution with physiological exertion [4]; it does not reflect the athlete’s true readiness to return to sport, as determined by a multi-modal objective assessment of the variety of impairments that manifest following concussion or during PCS. Indeed, this methodology is fraught with a number of key limitations: these assessments represent the individual’s status at discrete points in time, are focused on quantifying parameters that are subject to a level of hourly and daily variability independent of the concussive injury, and do not acknowledge the heterogeneous and evolving nature of the injury. In addition, while we know that concussion affects short-term physical (such as balance and gait) and cognitive (such as memory and concentration) competencies, the evolving nature of PCS for these competencies is not well understood. There is a dearth of evidence quantifying exactly how an injury such as concussion, with widespread symptomatology, disturbs an individual’s capacity for physical activity. Improving the evidence base in these areas is vital considering recent evidence which has suggested that concussion has long term effects on physical competencies, with increased musculoskeletal injury rates being observed for 3/12 months’ post injury [5–7]. Furthermore, concern has been raised as to the long term effects of repeated concussions on cognitive Wearable sensing and mobile devices: the future of post-concussion monitoring?

Challenging concussed athletes: the future of balance assessment in concussion

The assessment and management of sports-related concussion has become a contentious issue in the field of sports medicine. The current consensus in concussion evaluation involves the use of a subjective examination, supported by multifactorial assessment batteries designed to target the various components of cerebral function. Balance assessment forms an important component of this multifactorial assessment, as it can provide an insight into the function of the sensorimotor subsystems post-concussion. In recent times, there has been a call to develop objective clinical assessments that can aid in the assessment and monitoring of concussion. However, traditional static balance assessments are derived from neurologically impaired populations, are subjective in nature, do not adequately challenge high functioning athletes and may not be capable of detecting subtle balance disturbances following a concussive event. In this review, we provide an overview of the importance of assessing motor function following a concussion, and the challenges facing clinicians in its assessment and monitoring. Additionally, we discuss the limitations of the current clinical methods employed in balance assessment, the role of technology in improving the objectivity of traditional assessments, and the potential role inexpensive portable technology may play in providing objective measures of more challenging dynamic tasks.

Investigating the effects of maximal anaerobic fatigue on dynamic postural control using the Y-Balance Test

OBJECTIVES The Y Balance Test is one of the most commonly used dynamic balance assessments, providing an insight into the integration of the sensorimotor subsystems. In recent times, there has been an increase in interest surrounding its use in various clinical populations demonstrating alterations in motor function. Therefore, it is important to examine the effect physiological influences such as fatigue play in dynamic postural control, and establish a timeframe for its recovery. DESIGN Descriptive laboratory study. METHODS Twenty male and female (age 23.75±4.79years, height 174.12±8.45cm, mass 69.32±8.76kg) partaking in competitive sport, completed the Y Balance Test protocol at 0, 10 and 20min, prior to a modified 60s Wingate fatiguing protocol. Post-fatigue assessments were then completed at 0, 10 and 20 min post-fatiguing intervention. RESULTS Intraclass correlation coefficients demonstrated excellent intra-session reliability (0.976-0.982) across the three pre-fatigue YBT tests. Post-hoc paired sample t-tests demonstrated that all three reach directions demonstrated statistically significant differences between pre-fatigue and the first post-fatigue measurement (anterior; p=0.019, posteromedial; p=0.019 & posterolateral; p=0.003). The anterior reach direction returned to pre-fatigue levels within 10min (p=0.632). The posteromedial reach direction returned to pre-fatigue levels within 20min (p=0.236), while the posterolateral direction maintained a statistically significant difference at 20min (p=0.023). CONCLUSIONS Maximal anaerobic fatigue has a negative effect on normalised Y balance test scores in all three directions. Following the fatiguing protocol, dynamic postural control returns to pre-fatigue levels for the anterior (<10min), posteromedial (<20min) and posterolateral (>20min).

Validation of temporal gait metrics from three IMU locations to the gold standard force plate

The purpose of this work is to compare temporal gait parameters from three different IMU locations to the gold standard force platform. 33 subjects (12 F, 21 M) performed twenty gait trials each while wearing inertial measurement units (IMUs) on the trunk, both shanks and both feet. Data was simultaneously collected from a laboratory embedded force plate. Step times were derived from the raw IMU data at the three IMU locations using methods that have been shown to be accurate. Step times from all locations were valid compared to the force plate. Foot IMU step time was the most accurate (Pearson = .991, CI width = 3.00e2), the trunk IMU was the next most accurate (Pearson = .974, CI width = 4.85e2) and shank step time was the least accurate (Pearson = .958, CI width = 6.80e2). All three sensing locations result in valid estimations of step time compared to the gold standard force plate. These results suggest that the foot location would be most appropriate for clinical applications where very precise temporal parameter detection is required.

Inter-session Test-retest Reliability of the Quantified Y Balance Test

6th International Congress on Sport Sciences Research and Technology Support (icSPORTS 2018), Seville, Spain, 20-21 September 2018

Inertial Sensor Technology Can Capture Changes in Dynamic Balance Control during the Y Balance Test

Introduction: The Y Balance Test (YBT) is one of the most commonly utilised clinical dynamic balance assessments. Research has demonstrated the utility of the YBT in identifying balance deficits in individuals following lower limb injury. However, quantifying dynamic balance based on reach distances alone fails to provide potentially important information related to the quality of movement control and choice of movement strategy during the reaching action. The addition of an inertial sensor to capture more detailed motion data may allow for the inexpensive, accessible quantification of dynamic balance control during the YBT reach excursions. As such, the aim of this study was to compare baseline and fatigued dynamic balance control, using reach distances and 95EV (95% ellipsoid volume), and evaluate the ability of 95EV to capture alterations in dynamic balance control, which are not detected by YBT reach distances. Methods: As part of this descriptive laboratory study, 15 healthy participants completed repeated YBTs at 20, 10, and 0 min prior to and following a modified 60-s Wingate test that was used to introduce a short-term reduction in dynamic balance capability. Dynamic balance was assessed using the standard normalised reach distance method, while dynamic balance control during the reach attempts was simultaneously measured by means of the 95EV derived from an inertial sensor, worn at the level of the 4th lumbar vertebra. Results: Intraclass correlation coefficients for the inertial sensor-derived measures ranged from 0.76 to 0.92, demonstrating strong intrasession test-retest reliability. Statistically significant alterations (p < 0.05) in both reach distance and the inertial sensor-derived 95EV measure were observed immediately post-fatigue. However, reach distance deficits returned to baseline levels within 10 min, while 95EV remained significantly increased (p < 0.05) beyond 20 min for all 3 reach distances. Conclusion: These findings demonstrate the ability of an inertial sensor-derived measure to quantify alterations in dynamic balance control, which are not captured by traditional reach distances alone. This suggests that the addition of an inertial sensor to the YBT may provide clinicians and researchers with an accessible means to capture subtle alterations in motor function in the clinical setting.

The influence of feature selection methods on exercise classification with inertial measurement units

Inertial measurement unit (IMU) based systems are becoming increasingly popular in the classification of human movement. While research in the area has established the utility of various machine learning classification methods, there is a paucity of evidence investigating the effect of feature selection on classification efficacy. The aim of this study was therefore to investigate the influence of feature selection methodology on the classification accuracy of human movement data. The efficacy of four commonly used feature selection and classification methods were compared using four IMU human movement data sets. Optimisation of classification and features selection methodologies resulted in an overall improvement in F1 score of between 1–8% for all four data sets. The findings from this study illustrate the need for researchers to consider the effect classification and feature selection methodologies may have on system efficacy.

Validation and comparison of shank and lumbar-worn IMUs for step time estimation

Abstract Gait assessment is frequently used as an outcome measure to determine changes in an individual’s mobility and disease processes. Inertial measurement units (IMUs) are quickly becoming commonplace in gait analysis. The purpose of this study was to determine and compare the validity of shank and lumbar IMU mounting locations in the estimation of temporal gait features. Thirty-seven adults performed 20 walking trials each over a gold standard force platform while wearing shank and lumbar-mounted IMUs. Data from the IMUs were used to estimate step times using previously published algorithms and were compared with those derived from the force platform. There was an excellent level of correlation between the force platform and shank (r=0.95) and lumbar-mounted (r=0.99) IMUs. Bland-Altman analysis demonstrated high levels of agreement between the IMU and the force platform step times. Confidence interval widths were 0.0782 s for the shank and 0.0367 s for the lumbar. Both IMU mounting locations provided accurate step time estimations, with the lumbar demonstrating a marginally superior level of agreement with the force platform. This validation indicates that the IMU system is capable of providing step time estimates within 2% of the gold standard force platform measurement.

Inertial sensory data provides depth to clinical measures of dynamic balance

Study Design Case Study. Objectives Establish the role a single inertial sensor may play in the objective quantification of dynamic postural stability following acute ankle injuries. Background The Y Balance test (YBT) is one of the most commonly utilised clinical dynamic balance assessments. Research has demonstrated the utility of the YBT in identifying balance deficits in those with acute ankle injuries and chronic ankle instability. However, reach distances fail to provide information relating to the quality of balance strategy and dynamic stability. Motion capture systems are often employed to provide micro-level detail pertaining to an individual’s postural stability. However, such systems are expensive, lack accessibility, hinder natural movement and require extensive processing expertise. The addition of inertial sensors may allow for the inexpensive, accessible quantification of postural stability in an unconstrained environment. Case Description Forty-two elite under-20 rugby union players were recruited as part of a wider study. Two athletes were identified to have sustained acute ankle injuries two weeks previously; one lateral ankle sprain and one deltoid ligament sprain. A single inertial sensor was mounted at the level of the 4th lumbar vertebra. Participants completed four practice YBTs bilaterally, prior to completing 3 recorded YBTs. Reach distance and inertial sensor data were recorded for each reach excursion. Outcomes When compared to the group mean, both athletes demonstrated no clinically meaningful reduction in reach distances for all three reach directions. However, both athletes demonstrated a higher 95% ellipsoid volume of sway than the healthy control group for all three directions of the YBT when completed on their affected limb. Conclusions Preliminary analysis suggests that inertial sensor data may provide information relating to the quality of dynamic postural stability following an acute ankle injury. Further investigation is required to establish the role that such measures may play in the assessment and management of ankle injuries.