Reliability, Validity and Utility of Inertial Sensor Systems for Postural Control Assessment in Sport Science and Medicine Applications: A Systematic Review

Effects of dominance and vision on unipedal balance tests in futsal players using a triaxial accelerometer

Optimal postural control improves performance and reduces the risk of injury in futsal. In this context, wearable accelerometers may detect velocity changes of the centre of mass during a task, enabling the analysis of postural control in different environments. This work aimed to determine the influence of vision and dominance on unipodal static postural balance in non-professional athletes. Twenty-four university male futsal players performed a unipodal balance test to assess their body sway using a triaxial accelerometer. To assess dominance, the preferred limb for kicking the ball was considered, while vision was manipulated by asking participants to close their eyes during the test. Root mean square (RMS) and sample entropy (SaEn) of centre of mass variables were analysed. For statistical analysis, a multivariate analysis of variance model was used. Our results suggest an effect of vision, but not of dominance nor the interaction between vision and limb dominance. Specifically, a higher-acceleration RMS in the mediolateral axis was observed, as well as an increased SaEn in the three axes. To conclude, unipodal postural demand in futsal players under visual input suppression was not influenced by their limb dominancy.

Postural Analysis Using Rasterstereography and Inertial Measurement Units in Volleyball Players: Different Roles as Indicators of Injury Predisposition

Background and Objectives: Acute and chronic injuries are frequent in volleyball. Biomechanics of sport-specific tasks can influence the risk of injury, which is also related to specific court positions. We investigated posture at raster-stereography, balance, and dynamic tasks using inertial motion units to find differences between roles, which can be predictive of a higher risk of injury. Materials and Methods: We cross-sectionally evaluated amateur volleyball athletes. Participants were divided into roles as outside hitters, setters, middle blockers, and opposite hitters. We excluded the "libero" position from our analysis. Results: Sixteen players were included in the analysis. A statistically significant difference was found in left lower limb stiffness among the outside hitter and setter groups. Conclusions: Differences in stiffness might be related to the different training and the different abilities among the two groups. Raster-stereography is extending its indications and should be implemented for non-invasive postural analysis. The use of inertial motion units provides objective measurements of variables that could go unrecognized within a clinical evaluation; its use should be considered in injury preventive programs.

Use of accelerometers and inertial measurement units to quantify movement of tactical athletes: A systematic review

The dynamic work environments of tactical athletes are difficult to replicate in a laboratory. Accelerometers and inertial measurement units provide a way to characterize movement in the field. This systematic review identified how accelerometers and inertial measurement units are currently being used to quantify movement patterns of tactical athletes. Seven research and military databases were searched, producing 26,228 potential articles with 78 articles included in this review. The articles studied military personnel (73.1%), firefighters (19.2%), paramedics (3.8%), and law enforcement officers (3.8%). Accelerometers were the most used type of sensor, and physical activity was the primarily reported outcome variable. Seventy of the studies had fair or poor quality. Research on firefighters, emergency medical services, and law enforcement officers was limited. Future research should strive to make quantified movement data more accessible and user-friendly for non-research personnel, thereby prompting increased use in tactical athlete groups, especially first responder agencies.

Wearable Sensors Detect Movement Differences in the Portable Warrior Test of Tactical Agility After mTBI in Service Members

INTRODUCTION

Assessment of functional recovery of service members following a concussion is central to their return to duty. Practical military-relevant performance-based tests are needed for identifying those who might need specialized rehabilitation, for evaluating the progress of recovery, and for making return-to-duty determinations. One such recently developed test is the 'Portable Warrior Test of Tactical Agility' (POWAR-TOTAL) assessment designed for use following concussion in an active duty population. This agility task involves maneuvers used in military training, such as rapid stand-to-prone and prone-to-stand transitions, combat rolls, and forward and backward running. The effect of concussion on the performance of such maneuvers has not been established.

MATERIALS AND METHODS

The Institutional Review Board-approved study was conducted at Ft. Bragg, North Carolina, on 57 healthy control (HC) service members (SMs) and 42 well-matched SMs who were diagnosed with concussion and were referred for physical therapy with the intent to return to duty. Each study participant performed five consecutive trials of the POWAR-TOTAL task at full exertion while wearing inertial sensors, which were used to identify the constituent task maneuvers, or phases, and measure their durations. Statistical analyses were performed on durations of three main phases: (1) rising from prone and running, (2) lowering from vertical to prone, and (3) combat rolls.

RESULTS

None of the three phases showed significant correlation with age (range 18-45 years) in either group. Gradual improvement in all three phase durations across five trials was observed in the HC group, but not in the concussed group. On average, control subjects performed significantly faster (P < .004 or less) than concussed subjects in all trials in the lowering and rolling phases, but less so in the rising/running phase. Membership in the concussed group had a strong effect on the lowering phase (Cohen's d = 1.05), medium effect on the rolling phase (d = 0.72), and small effect on the rising/running phase (d = 0.49). Individuals in the HC group who had a history of prior concussions were intermediate between the concussed group and the never-concussed group in the lowering and rolling phases. Duration of transitional movements (lowering from standing to prone and combat rolls) was better at differentiating individuals' performance by group (receiver operating characteristic area under the curve [AUC] = 0.83) than the duration of the entire POWAR-TOTAL task (AUC = 0.71).

CONCLUSIONS

Inertial sensor analysis reveals that rapid transitional movements (such as lowering from vertical to prone position and combat rolls) are particularly discriminative between SMs recovering from concussion and their concussion-free peers. This analysis supports the validity of POWAR-TOTAL as a useful tool for therapists who serve military SMs.

Temperature Drift Compensation of a MEMS Accelerometer Based on DLSTM and ISSA

In order to improve the performance of a micro-electro-mechanical system (MEMS) accelerometer, three algorithms for compensating its temperature drift are proposed in this paper, including deep long short-term memory recurrent neural network (DLSTM-RNN, short DLSTM), DLSTM based on sparrow search algorithm (SSA), and DLSTM based on improved SSA (ISSA). Moreover, the piecewise linear approximation (PLA) method is employed in this paper as a comparison to evaluate the impact of the proposed algorithm. First, a temperature experiment is performed to obtain the MEMS accelerometer's temperature drift output (TDO). Then, we propose a real-time compensation model and a linear approximation model for neural network methods compensation and PLA method compensation, respectively. The real-time compensation model is a recursive method based on the TDO at the last moment. The linear approximation model considers the MEMS accelerometer's temperature and TDO as input and output, respectively. Next, the TDO is analyzed and optimized by the real-time compensation model and the three algorithms mentioned before. Moreover, the TDO is also compensated by the linear approximation model and PLA method as a comparison. The compensation results show that the three neural network methods and the PLA method effectively compensate for the temperature drift of the MEMS accelerometer, and the DLSTM + ISSA method achieves the best compensation effect. After compensation by DLSTM + ISSA, the three Allen variance coefficients of the MEMS accelerometer that bias instability, rate random walk, and rate ramp are improved from 5.43×10-4mg, 4.33×10-5mg/s12, 1.18×10-6mg/s to 2.77×10-5mg, 1.14×10-6mg/s12, 2.63×10-8mg/s, respectively, with an increase of 96.68% on average.

Using Wearable Inertial Sensors to Monitor Effectiveness of Different Types of Customized Orthoses during CrossFit® Training

BACKGROUND

Dynamic balance plays a key role in high-impact sports, such as CrossFit, where athletes are required to maintain balance in various weightlifting exercises. The loss of balance in these sport-specific movements may not only affect athlete performance, but also increase the risk of injuries.

OBJECTIVES

The aim of the study is to achieve greater insight into the balance and athlete position during the CrossFit training by means of inertial sensors, with a particular focus on the role of different custom foot orthoses (CFOs) in order to detect correlations with the role of the cavus foot.

METHODS

A total of 42 CrossFit^® athletes, aged 25 to 42 years, were enrolled in this study. One-way ANOVA tests with post-hoc analysis of variance were used to compare foot posture groups and effects of different types of customized foot orthoses.

RESULTS

When comparing the effects of CFOs with the respective balance basal level during the pistol squat exercise, we observed a significant (p = 0.0001) decrease in the sway area, antero-posterior displacement (APD) and medio-lateral displacement (MLD) compared to the basal using both types of CFOs.

CONCLUSION

No significant positive effects of CFOs were observed in some static tests. On the contrary, positive effects of CFOs and, in particular, postural insoles, are relevant to dynamic balance.

Ensemble averaging for categorical variables: Validation study of imputing lost data in 24-h recorded postures of inpatients

Acceleration sensors are widely used in consumer wearable devices and smartphones. Postures estimated from recorded accelerations are commonly used as features indicating the activities of patients in medical studies. However, recording for over 24 h is more likely to result in data losses than recording for a few hours, especially when consumer-grade wearable devices are used. Here, to impute postures over a period of 24 h, we propose an imputation method that uses ensemble averaging. This method outputs a time series of postures over 24 h with less lost data by calculating the ratios of postures taken at the same time of day during several measurement-session days. Whereas conventional imputation methods are based on approaches with groups of subjects having multiple variables, the proposed method imputes the lost data variables individually and does not require other variables except posture. We validated the method on 306 measurement data from 99 stroke inpatients in a hospital rehabilitation ward. First, to classify postures from acceleration data measured by a wearable sensor placed on the patient's trunk, we preliminary estimated possible thresholds for classifying postures as 'reclining' and 'sitting or standing' by investigating the valleys in the histogram of occurrences of trunk angles during a long-term recording. Next, the imputations of the proposed method were validated. The proposed method significantly reduced the missing data rate from 5.76% to 0.21%, outperforming a conventional method.

Head movement kinematics are altered during balance stability exercises in individuals with vestibular schwannoma

Background

Balance stabilization exercises are often prescribed to facilitate compensation in individuals with vestibular schwannoma (VS). However, both the assessment and prescription of these exercises are reliant on clinical observations and expert opinion rather than on quantitative evidence. The aim of this study was to quantify head motion kinematics in individuals with vestibular loss while they performed commonly prescribed balance stability exercises.

Methods

Using inertial measurement units, head movements of individuals with vestibular schwannoma were measured before and after surgical deafferentation and compared with age-matched controls.

Results

We found that individuals with vestibular schwannoma experienced more variable head motion compared to healthy controls both pre- and postoperatively, particularly in absence of visual input, but that there was little difference between preoperative and postoperative kinematic measurements for our vestibular schwannoma group. We further found correlations between head motion kinematic measures during balance exercises, performed in the absence of visual input, and multiple clinical measurements for preoperative VS subjects. Subjects with higher head motion variability also had worse DVA scores, moved more slowly during the Timed up and Go and gait speed tests, and had lower scores on the functional gait assessment. In contrast, we did not find strong correlations between clinical measures and postoperative head kinematics for the same VS subjects.

Conclusions

Our data suggest that further development of such metrics based on the quantification of head motion has merit for the assessment and prescription of balance exercises, as demonstrated by the calculation of a “kinematic score” for identifying the most informative balance exercise (i.e., “Standing on foam eyes closed”).

Validity and reliability of the Output sport device for assessing drop jump performance

The devices for measuring plyometric exercise in field conditions are becoming increasingly prevalent in applied research and practice. However, before the use of a device in an applied setting, the validity and reliability of such an instrument must be determined. The study aimed to assess the validity and reliability of the Output Sport, an inertial measurement unit (IMU), through comparisons with a force plate for research purposes. A repeated measure test-retest study was performed. Reliability was assessed during single-session trials (i.e., intrasession reliability). A total of 34 national/university level athletes (13 females, 21 males) performed three drop jumps with a fall from 30 cm while both devices recorded ground contact time (GCT), flight time (FT), jump height (HJ), and reactive strength index (RSI). T-tests demonstrated that data collected from the IMU device were significantly different to the force platform for all reported variables (all p < 0.01). The intraclass correlation coefficients (ICC) demonstrated good-to-excellent reliability, but with a large range of confidence intervals (CI 95%) for GCT (0.825, 0.291–0.930), FT (0.928, 0.756–0.958), HJ (0.921, 0.773–0.964), and RSI (0.772, 0.151–0.907). The Bland-Altman test showed that the device overestimated contact times and underestimated the other variables. Upon landing, greater ground contact times (i.e., ≥0.355ms) were associated with higher reliability. These results suggest that a single IMU can be used to track changes somewhat accurately and reliably in jump metrics, especially when the GCT is greater than 0.355ms. It is recommended that before practitioners and trainers use the device as a cost-effective solution in the field, further research should be carried out to evaluate a range of data on the type of exercise to be performed.

Classification of Plank Techniques Using Wearable Sensors

The plank is a common core-stability exercise. Developing a wearable inertial sensor system for distinguishing between acceptable and aberrant plank techniques and detecting specific deviations from acceptable plank techniques can enhance performance and prevent injury. The purpose of this study was to develop an inertial measurement unit (IMU)-based plank technique quantification system. Nineteen healthy volunteers (age: 20.5 ± 0.8 years, BMI: 22.9 ± 1.4 kg/m²) performed the standard plank technique and six deviations with five IMUs positioned on the occiput, cervical spine, thoracic spine, sacrum, and right radius to record movements. The random forest method was employed to perform the classification. The proposed binary tree classification model achieved an accuracy of more than 86%. The average sensitivities were higher than 90%, and the specificities were higher than 91%, except for one deviation (83%). These results suggest that the five IMU-based systems can classify the plank technique as acceptable or aberrant with good accuracy, high sensitivity, and acceptable specificity, which has significant implications in monitoring plank biomechanics and enabling coaching practice.

MEMS Inertial Sensor Calibration Technology: Current Status and Future Trends

A review of various calibration techniques of MEMS inertial sensors is presented in this paper. MEMS inertial sensors are subject to various sources of error, so it is essential to correct these errors through calibration techniques to improve the accuracy and reliability of these sensors. In this paper, we first briefly describe the main characteristics of MEMS inertial sensors and then discuss some common error sources and the establishment of error models. A systematic review of calibration methods for inertial sensors, including gyroscopes and accelerometers, is conducted. We summarize the calibration schemes into two general categories: autonomous and nonautonomous calibration. A comprehensive overview of the latest progress made in MEMS inertial sensor calibration technology is presented, and the current state of the art and development prospects of MEMS inertial sensor calibration are analyzed with the aim of providing a reference for the future development of calibration technology.

Detecting Low Back Physiotherapy Exercises and Postures with Inertial Sensors and Machine Learning (Preprint)

Background

Objective

Methods

Results

Conclusions

Pose2Sim: An End-to-End Workflow for 3D Markerless Sports Kinematics—Part 2: Accuracy

Two-dimensional deep-learning pose estimation algorithms can suffer from biases in joint pose localizations, which are reflected in triangulated coordinates, and then in 3D joint angle estimation. Pose2Sim, our robust markerless kinematics workflow, comes with a physically consistent OpenSim skeletal model, meant to mitigate these errors. Its accuracy was concurrently validated against a reference marker-based method. Lower-limb joint angles were estimated over three tasks (walking, running, and cycling) performed multiple times by one participant. When averaged over all joint angles, the coefficient of multiple correlation (CMC) remained above 0.9 in the sagittal plane, except for the hip in running, which suffered from a systematic 15° offset (CMC = 0.65), and for the ankle in cycling, which was partially occluded (CMC = 0.75). When averaged over all joint angles and all degrees of freedom, mean errors were 3.0°, 4.1°, and 4.0°, in walking, running, and cycling, respectively; and range of motion errors were 2.7°, 2.3°, and 4.3°, respectively. Given the magnitude of error traditionally reported in joint angles computed from a marker-based optoelectronic system, Pose2Sim is deemed accurate enough for the analysis of lower-body kinematics in walking, cycling, and running.

Concurrent validity of the inertial sensors for assessment of balance control during quiet standing in patients with chronic low back pain and asymptomatic individuals

The objective was to investigate the concurrent validity of inertial sensors for measuring balance control in patients with chronic low back pain and asymptomatic individuals. Thirty-nine patients with chronic low back and 39 age- and sex-matched asymptomatic individuals were included. Balance control analysis was performed in quiet standing with two inertial sensors positioned at the lumbar region and the sternum and compared to the results of a force plate. The variables analysed with either device were Root Mean Square (RMS), index of smoothness (JERK), trajectory length (PATH) and area (AREA). Spearman's correlation coefficient investigated the correlation. Patients with chronic low back pain showed moderate correlation with the inertial sensor positioned on the lumbar for RMS (r_s = 0.59; p < 0.01), PATH (r_s = 0.42, p = 0.01) and AREA (r_s = 0.59; p < 0.01) and weak correlation with the inertial sensor positioned on the sternum for PATH (r_s = 0.36, p = 0.04). The asymptomatic group showed statistically significant correlations for RMS for the lumbar (r_s = 0.38; p = 0.03) and sternum inertial sensor (r_s = 0.42; p = 0.02). Inertial sensors showed weak to moderate correlations compared to data obtained from a force plate.

Artificial Intelligence Based Body Sensor Network Framework-Narrative Review: Proposing an End-to-End Framework using Wearable Sensors, Real-Time Location Systems and Artificial Intelligence/Machine Learning Algorithms for Data Collection, Data Mining and Knowledge Discovery in Sports and Healthcare

With the rising amount of data in the sports and health sectors, a plethora of applications using big data mining have become possible. Multiple frameworks have been proposed to mine, store, preprocess, and analyze physiological vitals data using artificial intelligence and machine learning algorithms. Comparatively, less research has been done to collect potentially high volume, high-quality 'big data' in an organized, time-synchronized, and holistic manner to solve similar problems in multiple fields. Although a large number of data collection devices exist in the form of sensors. They are either highly specialized, univariate and fragmented in nature or exist in a lab setting. The current study aims to propose artificial intelligence-based body sensor network framework (AIBSNF), a framework for strategic use of body sensor networks (BSN), which combines with real-time location system (RTLS) and wearable biosensors to collect multivariate, low noise, and high-fidelity data. This facilitates gathering of time-synchronized location and physiological vitals data, which allows artificial intelligence and machine learning (AI/ML)-based time series analysis. The study gives a brief overview of wearable sensor technology, RTLS, and provides use cases of AI/ML algorithms in the field of sensor fusion. The study also elaborates sample scenarios using a specific sensor network consisting of pressure sensors (insoles), accelerometers, gyroscopes, ECG, EMG, and RTLS position detectors for particular applications in the field of health care and sports. The AIBSNF may provide a solid blueprint for conducting research and development, forming a smooth end-to-end pipeline from data collection using BSN, RTLS and final stage analytics based on AI/ML algorithms.

Scoring Performance on the Y-Balance Test Using a Deep Learning Approach

The Y Balance Test (YBT) is a dynamic balance assessment typically used in sports medicine. This work proposes a deep learning approach to automatically score this YBT by estimating the normalized reach distance (NRD) using a wearable sensor to register inertial signals during the movement. This paper evaluates several signal processing techniques to extract relevant information to feed the deep neural network. This evaluation was performed using a state-of-the-art human activity recognition system based on recurrent neural networks (RNNs). This deep neural network includes long short-term memory (LSTM) layers to learn features from time series by modeling temporal patterns and an additional fully connected layer to estimate the NRD (normalized by the leg length). All analyses were carried out using a dataset with YBT assessments from 407 subjects, including young and middle-aged volunteers and athletes from different sports. This dataset allowed developing a global and robust solution for scoring the YBT in a wide range of applications. The experimentation setup considered a 10-fold subject-wise cross-validation using training, validation, and testing subsets. The mean absolute percentage error (MAPE) obtained was 7.88 ± 0.20%. Moreover, this work proposes specific regression systems to estimate the NRD for each direction separately, obtaining an average MAPE of 7.33 ± 0.26%. This deep learning approach was compared to a previous work using dynamic time warping and k-NN algorithms, obtaining a relative MAPE reduction of 10%.

Wearable inertial sensors for human movement analysis: a five-year update

INTRODUCTION

The aim of the present review is to track the evolution of wearable IMUs from their use in supervised laboratory- and ambulatory-based settings to their application for long-term monitoring of human movement in unsupervised naturalistic settings.

AREAS COVERED

Four main emerging areas of application were identified and synthesized, namely, mobile health solutions (specifically, for the assessment of frailty, risk of falls, chronic neurological diseases, and for the monitoring and promotion of active living), occupational ergonomics, rehabilitation and telerehabilitation, and cognitive assessment. Findings from recent scientific literature in each of these areas was synthesized from an applied and/or clinical perspective with the purpose of providing clinical researchers and practitioners with practical guidance on contemporary uses of inertial sensors in applied clinical settings.

EXPERT OPINION

IMU-based wearable devices have undergone a rapid transition from use in laboratory-based clinical practice to unsupervised, applied settings. Successful use of wearable inertial sensing for assessing mobility, motor performance and movement disorders in applied settings will rely also on machine learning algorithms for managing the vast amounts of data generated by these sensors for extracting information that is both clinically relevant and interpretable by practitioners.

A comparison of head movements tests in force plate and accelerometer based posturography in patients with balance problems due to vestibular dysfunction

This study compares HS posturography on inertial sensors (MediPost) with force platform posturography in patients with unilateral vestibular dysfunction. The study group included 38 patients (age 50.6; SD 11.6) with unilateral vestibular weakness (UV) and 65 healthy volunteers (48.7; SD 11.5). HS tests were performed simultaneously on the force plate and with MediPost sensor attached at L4. Four conditions applied: eyes open/closed, firm/foam. The tests were performed twice, with the head moving at the frequency of 0.3 Hz (HS 0.3) and 0.6 Hz (HS 0.6). Mean sway velocity was significantly lower for MediPost than force plate in 4th condition both in UV and healthy group. For HS 0.3 the differences between devices were marginal; the highest sensitivity (87%) and specificity (95%) were in 4th condition. For HS 0.6 MediPost revealed lower sensitivity than force plate although the surface parameter improved results. MediPost IMU device and force platform posturography revealed a similar ability to differentiate between patients with balance problems in course of vestibular pathology and healthy participants, despite the differences observed between measuring methods. In some tests surface parameter may be more appropriate than sway velocity in improving MediPost sensitivity.

Utility of a Postural Stability/Perceptual Inhibition Dual Task for Identifying Concussion in Adolescents

CONTEXT

Research in the area of dual-task paradigms to assess sport-related concussion (SRC) status is growing, but additional assessment of this paradigm in adolescents is warranted.

DESIGN

This case-control study compared 49 adolescent athletes aged 12-20 years with diagnosed SRC to 49 age- and sex-matched controls on visual-spatial discrimination and perceptual inhibition (PIT) reaction time tasks performed while balancing on floor/foam pad conditions.

METHODS

The SRC group completed measures at a single time point between 1 and 10 days postinjury. Primary outcomes were dual-task reaction time, accuracy, and sway. General linear models evaluated differences between groups (P < .05). Logistic regression identified predictors of concussion from outcomes. Area under the curve evaluated discriminative ability of identifying SRC.

RESULTS

Results supported significantly higher anterior-posterior (AP) sway values in concussed participants for visual-spatial discrimination and PIT when balancing on the floor (P = .03) and foam pad (P = .03), as well as mediolateral sway values on the floor during visual-spatial discrimination (P = .01). Logistic regression analysis (R2 = .15; P = .001) of all dual-task outcomes identified AP postural sway during the PIT foam dual task as the only significant predictor of concussed status (ß = -2.4; P = .004). Total symptoms (area under the curve = 0.87; P < .001) and AP postural sway on foam (area under the curve = 0.70; P = .001) differentiated concussed from controls.

CONCLUSION

The AP postural sway on foam during a postural stability/PIT dual task can identify concussion in adolescents between 1 and 10 days from injury.

Evaluating the validity and reliability of inertial measurement units for determining knee and trunk kinematics during athletic landing and cutting movements

Inertial Measurement Units (IMUs) are promising alternatives to laboratory-based motion capture methods in biomechanical assessment of athletic movements. The aim of this study was to investigate the validity of an IMU system for determining knee and trunk kinematics during landing and cutting tasks for clinical and research applications in sporting populations. Twenty-seven participants performed five cutting and landing tasks while being recorded using a gold-standard optoelectronic motion capture system and an IMU system. Intra-class coefficients, Pearson's r, root-mean-square error (RMSE), bias, and Bland-Altman limits of agreements between the motion capture and IMU systems were quantified for knee and trunk sagittal- and frontal-plane range-of-motion (ROM) and peak angles. Our results indicate that IMU validity was task-, joint-, and plane-dependent. Based on good-to-excellent (ICC) correlation, reasonable accuracy (RMSE < 5°), bias within 2°, and limits of agreements within 10°, we recommend the use of this IMU system for knee sagittal-plane ROM estimations during cutting, trunk sagittal-plane peak angle estimation during the double-leg landing task, trunk sagittal-plane ROM estimation for almost all tasks, and trunk frontal-plane peak angle estimation for the right single-leg landing task. Due to poor comparisons with the optoelectronic system, we do not recommend this IMU system for knee frontal-plane kinematic estimations.

Inertial Sensor Reliability and Validity for Static and Dynamic Balance in Healthy Adults: A Systematic Review

Compared to laboratory equipment inertial sensors are inexpensive and portable, permitting the measurement of postural sway and balance to be conducted in any setting. This systematic review investigated the inter-sensor and test-retest reliability, and concurrent and discriminant validity to measure static and dynamic balance in healthy adults. Medline, PubMed, Embase, Scopus, CINAHL, and Web of Science were searched to January 2021. Nineteen studies met the inclusion criteria. Meta-analysis was possible for reliability studies only and it was found that inertial sensors are reliable to measure static standing eyes open. A synthesis of the included studies shows moderate to good reliability for dynamic balance. Concurrent validity is moderate for both static and dynamic balance. Sensors discriminate old from young adults by amplitude of mediolateral sway, gait velocity, step length, and turn speed. Fallers are discriminated from non-fallers by sensor measures during walking, stepping, and sit to stand. The accuracy of discrimination is unable to be determined conclusively. Using inertial sensors to measure postural sway in healthy adults provides real-time data collected in the natural environment and enables discrimination between fallers and non-fallers. The ability of inertial sensors to identify differences in postural sway components related to altered performance in clinical tests can inform targeted interventions for the prevention of falls and near falls.

Quantification of muscles activations and joints range of motions during oil palm fresh fruit bunch harvesting and loose fruit collection

Although global demand for palm oil has been increasing, most activities in the oil palm plantations still rely heavily on manual labour, which includes fresh fruit bunch (FFB) harvesting and loose fruit (LF) collection. As a result, harvesters and/or collectors face ergonomic risks resulting in musculoskeletal disorder (MSD) due to awkward, extreme and repetitive posture during their daily work routines. Traditionally, indirect approaches were adopted to assess these risks using a survey or manual visual observations. In this study, a direct measurement approach was performed using Inertial Measurement Units, and surface Electromyography sensors. The instruments were attached to different body parts of the plantation workers to quantify their muscle activities and assess the ergonomics risks during FFB harvesting and LF collection. The results revealed that the workers generally displayed poor and discomfort posture in both activities. Biceps, multifidus and longissimus muscles were found to be heavily used during FFB harvesting. Longissimus, iliocostalis, and multifidus muscles were the most used muscles during LF collection. These findings can be beneficial in the design of various assistive tools which could improve workers' posture, reduce the risk of injury and MSD, and potentially improve their overall productivity and quality of life.

Concussion History and Balance Performance in Adolescent Rugby Union Players

BACKGROUND

Sports-related concussion is a worldwide problem. There is a concern that an initial concussion can cause prolonged subclinical disturbances to sensorimotor function that increase the risk of subsequent injury. The primary aim of this study was to examine whether a history of sports-related concussion has effects on static and dynamic balance performance in adolescent rugby players.

HYPOTHESIS

Dynamic balance would be worse in players with a history of concussion compared with those with no history of concussion.

STUDY DESIGN

Cross-sectional study; Level of evidence, 3.

METHODS

Male adolescent rugby players aged 14 to 18 years from 5 schools were recruited before the start of the 2018-2019 playing season. Participants completed questionnaires and physical tests, including dynamic Y balance and single-leg static balance (eyes closed) tests, while performing single and dual tasks. Dynamic balance was assessed using inertial sensor instrumentation. Dependent variables were normalized reach distance and the sample entropy (SEn) of the 3 axes (x, y, and z).

RESULTS

Of the 195 participants, 100 reported a history of concussion. Those with a history of concussion demonstrated higher SEn in all directions, with highest values during anterior (standardized mean difference [SMD], 0.4; 95% CI, 0.0-0.7; P = .027) and posteromedial (SMD, 0.5; 95% CI, 0.2-0.9; P = .004) reach directions compared with those with no history. There was no difference between groups (concussion history vs control) in traditional Y balance reach distances in the anterior or posteromedial directions or single-leg static balance during both single- (P = .47) and dual-task (P = .67) conditions.

CONCLUSION

Adolescent rugby union athletes with a history of concussion had poorer dynamic balance during performance tasks compared with healthy controls. Static single-leg balance tests, either single or dual task, may not be sensitive enough to detect sensorimotor deficits in those with a history of concussion.

Estimating Movement Smoothness From Inertial Measurement Units

Inertial measurement units (IMUs) are increasingly used to estimate movement quality and quantity to the infer the nature of motor behavior. The current literature contains several attempts to estimate movement smoothness using data from IMUs, many of which assume that the translational and rotational kinematics measured by IMUs can be directly used with the smoothness measures spectral arc length (SPARC) and log dimensionless jerk (LDLJ-V). However, there has been no investigation of the validity of these approaches. In this paper, we systematically evaluate the use of these measures on the kinematics measured by IMUs. We show that: (a) SPARC and LDLJ-V are valid measures of smoothness only when used with velocity; (b) SPARC and LDLJ-V applied on translational velocity reconstructed from IMU is highly error prone due to drift caused by integration of reconstruction errors; (c) SPARC can be applied directly on rotational velocities measured by a gyroscope, but LDLJ-V can be error prone. For discrete translational movements, we propose a modified version of the LDLJ-V measure, which can be applied to acceleration data (LDLJ-A). We evaluate the performance of these measures using simulated and experimental data. We demonstrate that the accuracy of LDLJ-A depends on the time profile of IMU orientation reconstruction error. Finally, we provide recommendations for how to appropriately apply these measures in practice under different scenarios, and highlight various factors to be aware of when performing smoothness analysis using IMU data.

Validity and reliability of smartphone use in assessing balance in patients with chronic ankle instability and healthy volunteers: A cross-sectional study

BACKGROUND

Chronic ankle instability (CAI) is associated with defective posture control and balance; thus, a proper assessment of these impairments is necessary for effective clinical decision-making. There is a need for portable, valid, and reliable methods to facilitate the easy collection of real-world data, such as mobile phones.

RESEARCH QUESTION

Is the smartphone "MyAnkle" application valid and reliable in assessing balance in patients with CAI and healthy volunteers?

METHODS

This was a cross-sectional study. Sixty-five participants completed two assessment sessions, including 31 patients (n = 41 ankles with CAI and 21 asymptomatic ankles) and 34 healthy volunteers (n = 68 ankles). In each session, dynamic single-leg stance balance was measured simultaneously using the "MyAnkle" application and the Biodex balance system (BBS) version 3. Testing was conducted at three levels of BBS difficulty-4 (D4, hard, loose platform), 6 (D6, moderate), and 8 (D8, easy, stiffer platform)-and repeated with opened and closed eyes. Both limbs were tested in a random order by two independent blinded assessors.

RESULTS

The two devices showed significant poor-to-moderate correlations when eyes were closed (p < 0.05). For discriminant validity, the application did not distinguish the two study groups in all tested conditions (p > 0.05), whereas the BBS weakly to moderately distinguished the dominant limbs in the two groups at all difficulty levels with eyes-open and at D8 with eyes-closed regardless to limb dominance. For reliability, a significantly poor to moderate inter-session reliability was noted for the two devices.

SIGNIFICANCE

"MyAnkle" application is valid in assessing balance in patients with CAI when the eyes are closed. However, similarly to BBS, its one-week test-retest reliability may be insufficient for accurate follow-up of balance changes and need to be interpreted with caution. Future studies need to establish its inter-tester reliability and its usefulness in telerehabilitation.

Single-Item Self-Report Measures of Team-Sport Athlete Wellbeing and Their Relationship With Training Load: A Systematic Review

BACKGROUND

Single-item athlete self-report measures consist of a single question to assess a dimension of wellbeing. These methods are recommended and frequently used for athlete monitoring, yet their uniformity has not been well assessed, and we have a limited understanding of their relationship with measures of training load.

OBJECTIVE

To investigate the applications and designs of single-item self-report measures used in monitoring team-sport athletes and present the relationship between these measures and measures of training load.

DATA SOURCES

PubMed, Scopus, and SPORTDiscus were searched between inception and March 2019.

STUDY SELECTION

Articles were included if they concerned adult athletes from field- or court-sport domains, if athlete well-being was measured using a single-item self-report, and if the relationship with a measure of modifiable training load was investigated over at least 7 days.

DATA EXTRACTION

Data related to participant characteristics, self-report measures, training load measures, and statistical analysis and outcomes were extracted by 2 authors (C.D. and C.D.).

DATA SYNTHESIS

A total of 21 studies were included in the analysis. A narrative synthesis was conducted. The measures used most frequently were muscle soreness, fatigue, sleep quality, stress, and mood. All measures presented various relationships with metrics of training load from no association to a very large association, and the associations were predominantly trivial to moderate in the studies with the largest numbers of observations. Relationships were largely negative associations.

CONCLUSIONS

The implications of this review should be considered by users in the application and clinical utility of single-item self-report measures in athlete monitoring. Great emphasis has been placed on examining the relationship between subjective and objective measures of training load. Although the relationship is still unclear, such an association may not be expected or useful. Researchers should consider the measurement properties of single-item self-report measures and seek to establish their relationship with clinically meaningful outcomes. As such, further study is required to inform practitioners on the appropriate objective application of data from single-item self-report measures.

Concussion Recovery Evaluation Using the Inertial Sensor Instrumented Y Balance Test

The current sports concussion assessment paradigm lacks reliability, has learning effects, and is not sufficiently challenging for athletes. As a result, subtle deficits in sensorimotor function may be unidentified, increasing the risk of future injury. This study examined if the inertial-sensor instrumented Y Balance test could capture concussion-induced alterations in dynamic movement control. A cohort of 226 elite Rugby Union, American football, and ice hockey athletes were evaluated using the inertial-sensor instrumented Y balance test. Dynamic balance performance was quantified using normalized reach distance, jerk magnitude root-mean-squared (Jerk Mag RMS), and gyroscope magnitude sample entropy (Gyro Mag SEn). Concussed athletes who consented to follow-up were evaluated 24 to 48 h post-injury, and at the point of return to full contact training (RTP). Seventeen athletes sustained a concussion and consented to both the 24- to 48-h and RTP follow-up testing. Twenty uninjured control athletes were re-tested 6 months following initial screening. Concussed athletes had reductions in normalized reach distance (Cohens D = 0.66-1.16) and Jerk Mag (Cohens D = 0.57-1.14) 24 to 48 h post-injury, which returned to pre-injury levels by the point of RTP. There was no significant difference in performance between the baseline and 6-month follow-up in the 20 uninjured athletes (Cohens D = 0.06-0.51). There was a statistically significant linear association between Jerk Mag RMS 24 to 48 h post-injury and the natural log of RTP duration (R² = 0.27 to 0.33). These results indicate that concussed athletes possessed alterations in dynamic movement control 24 to 48 h post-concussion, which typically returns to pre-injury levels by the point of RTP. Further, evaluation of dynamic movement control 24 to 48 h post-injury may aid in the evaluation of recovery prognosis.

Sport Biomechanics Applications Using Inertial, Force, and EMG Sensors: A Literature Overview

In the last few decades, a number of technological developments have advanced the spread of wearable sensors for the assessment of human motion. These sensors have been also developed to assess athletes' performance, providing useful guidelines for coaching, as well as for injury prevention. The data from these sensors provides key performance outcomes as well as more detailed kinematic, kinetic, and electromyographic data that provides insight into how the performance was obtained. From this perspective, inertial sensors, force sensors, and electromyography appear to be the most appropriate wearable sensors to use. Several studies were conducted to verify the feasibility of using wearable sensors for sport applications by using both commercially available and customized sensors. The present study seeks to provide an overview of sport biomechanics applications found from recent literature using wearable sensors, highlighting some information related to the used sensors and analysis methods. From the literature review results, it appears that inertial sensors are the most widespread sensors for assessing athletes' performance; however, there still exist applications for force sensors and electromyography in this context. The main sport assessed in the studies was running, even though the range of sports examined was quite high. The provided overview can be useful for researchers, athletes, and coaches to understand the technologies currently available for sport performance assessment.

Athletes with a concussion history in the last two years have impairments in dynamic balance performance

The purpose of this study was to determine if National Collegiate Athletics Association Division 1 American Football and Ice Hockey athletes with a history of concussion have impaired dynamic balance control when compared to healthy control athletes. This cross-sectional observational study recruited 146 athletes; 90 control athletes and 56 athletes with a history of concussion. Athletes were tested during a pre-season evaluation using the inertial-sensor instrumented Y Balance Test. Independent variables were normalized reach distance, gyroscope magnitude sample entropy, and jerk magnitude root mean square. Kruskal-Wallis H test and Dunn-Bonferroni analysis demonstrated that individuals with a concussion history within the last 2 years have statistically significantly lower jerk magnitude root mean square in the posteromedial (Z = 23.22, P = .015) and posterolateral (Z = 24.64, P = .010) reach directions, when compared to the control group. There was no significant difference between those who sustained a concussion longer than two years ago and the control group for the posteromedial (Z = -1.25; P = .889) and posterolateral (Z = 6.44; P = .469) directions. These findings show that athletes with a concussion history within the last two years possess dynamic balance deficits, when compared to healthy control athletes. Conversely, athletes whose injury occurred greater than 2 years ago possessed comparable performance to the healthy controls. This suggests that sensorimotor control deficits may persist beyond clinical recovery, for up to 2 years. Therefore, clinicians should integrate balance training interventions into the return-to-play process to accelerate sensorimotor recovery and mitigate the risk of future injury.

Impact of Visual Biofeedback of Trunk Sway Smoothness on Motor Learning during Unipedal Stance

The assessment of trunk sway smoothness using an accelerometer sensor embedded in a smartphone could be a biomarker for tracking motor learning. This study aimed to determine the reliability of trunk sway smoothness and the effect of visual biofeedback of sway smoothness on motor learning in healthy people during unipedal stance training using an iPhone 5 measurement system. In the first experiment, trunk sway smoothness in the reliability group (n = 11) was assessed on two days, separated by one week. In the second, the biofeedback group (n = 12) and no-biofeedback group (n = 12) were compared during 7 days of unipedal stance test training and one more day of retention (without biofeedback). The intraclass correlation coefficient score 0.98 (0.93–0.99) showed that this method has excellent test–retest reliability. Based on the power law of practice, the biofeedback group showed greater improvement during training days (p = 0.003). Two-way mixed analysis of variance indicates a significant difference between groups (p < 0.001) and between days (p < 0.001), as well as significant interaction (p < 0.001). Post hoc analysis shows better performance in the biofeedback group from training days 2 and 7, as well as on the retention day (p < 0.001). Motor learning objectification through visual biofeedback of trunk sway smoothness enhances postural control learning and is useful and reliable for assessing motor learning.

Capturing concussion related changes in dynamic balance using the Quantified Y Balance Test - a case series of six elite rugby union players

Concussion is one of the most common injuries reported across a myriad of sports. Recent evidence suggests that individuals may possess sensorimotor deficits beyond clinical recovery, predisposing them to further injury. This preliminary prospective case series aimed to determine if an inertial sensor instrumented Y balance test can capture changes in dynamic balance, regardless of apparent `clinical recovery', in six concussed elite rugby union players. The findings from this case series demonstrate that the inertial sensor-based measures can detect clinically meaningful changes in dynamic balance performance, not captured by the traditional clinical scoring methods, 48-hours post-injury and at the point of `clinical recovery' (return to play). Further research should investigate the role such instrumented dynamic balance assessments may play in the management of sports-related concussion.