Now showing 1 - 10 of 18
  • Publication
    Mobile App to Streamline the Development of Wearable Sensor-Based Exercise Biofeedback Systems: System Development and Evaluation
    Background: Biofeedback systems that use inertial measurement units (IMUs) have been shown recently to have the ability toobjectively assess exercise technique. However, there are a number of challenges in developing such systems; vast amounts ofIMU exercise datasets must be collected and manually labeled for each exercise variation, and naturally occurring techniquedeviations may not be well detected. One method of combatting these issues is through the development of personalized exercisetechnique classifiers.Objective: We aimed to create a tablet app for physiotherapists and personal trainers that would automate the development ofpersonalized multiple and single IMU-based exercise biofeedback systems for their clients. We also sought to complete apreliminary investigation of the accuracy of such individualized systems in a real-world evaluation.Methods: A tablet app was developed that automates the key steps in exercise technique classifier creation through synchronizingvideo and IMU data collection, automatic signal processing, data segmentation, data labeling of segmented videos by an exerciseprofessional, automatic feature computation, and classifier creation. Using a personalized single IMU-based classification system,15 volunteers (12 males, 3 females, age: 23.8 [standard deviation, SD 1.8] years, height: 1.79 [SD 0.07] m, body mass: 78.4 [SD9.6] kg) then completed 4 lower limb compound exercises. The real-world accuracy of the systems was evaluated.Results: The tablet app successfully automated the process of creating individualized exercise biofeedback systems. Thepersonalized systems achieved 89.50% (1074/1200) accuracy, with 90.00% (540/600) sensitivity and 89.00% (534/600) specificityfor assessing aberrant and acceptable technique with a single IMU positioned on the left thigh.Conclusions: A tablet app was developed that automates the process required to create a personalized exercise techniqueclassification system. This tool can be applied to any cyclical, repetitive exercise. The personalized classification model displayedexcellent system accuracy even when assessing acute deviations in compound exercises with a single IMU.
  • Publication
    Use of body worn sensors to predict ankle injuries using screening tools
    Background The Single Leg Squat (SLS) is an important screening tool in predicting those at an increased risk of ankle injuries as it relates to landing, running and cutting tasks. However, clinical analysis of this exercise is often completed visually with relatively poor intra-rater reliability. More detailed analysis of SLS completed in biomechanics laboratories is time-consuming and costly. Recent developments in body worn sensors may allow for quick assessments that produce valid and reliable data.Objective To explore a model for leveraging data obtained from wearable sensors to aid in ankle injury risk factor screening.Design A single case study design, with qualitative analysis of quantitative data.Setting University research laboratory.Participants A single participant (female, age = 24 years; height = 158 cm, body mass = 47 kg) was chosen. The participant was familiar with the SLS exercise and had completed it as part of their exercise routine for the past year.Interventions The participant completed 10 left SLS repetitions. These were recorded using the sensors and repetitions where the participant lost balance were noted. Loss of balance was defined as when the subject was unable to maintain single leg stance during the downward or upward phase of the movement and placed their other foot on the ground for support.Main outcome measurements Visual analysis showed signals from the wearable sensors (accelerometer Y and gyroscope Z) were altered when the participant lost their balance compared to signals obtained when the participant maintained balance.Conclusions These preliminary results indicate that body worn sensors may be able to automatize screening tools such as the SLS. An automated system for characterising and quantifying deviations from good form could be developed to aid clinicians and researchers. Such a system would provide objective and reliable data to clinicians and allow researchers to analyse movements quicker and in a more naturalistic setting.
  • Publication
    Evaluating the use of machine learning in the assessment of joint angle using a single inertial sensor
    Introduction: Joint angle measurement is an important objective marker in rehabilitation. Inertial measurement units may provide an accurate and reliable method of joint angle assessment. The objective of this study was to assess whether a single sensor with the application of machine learning algorithms could accurately measure hip and knee joint angle, and investigate the effect of inertial measurement unit orientation algorithms and person-specific variables on accuracy. Methods: Fourteen healthy participants completed eight rehabilitation exercises with kinematic data captured by a 3D motion capture system, used as the reference standard, and a wearable inertial measurement unit. Joint angle was calculated from the single inertial measurement unit using four machine learning models, and was compared to the reference standard to evaluate accuracy. Results: Average root-mean-squared error for the best performing algorithms across all exercises was 4.81 (SD ¼ 1.89). The use of an inertial measurement unit orientation algorithm as a pre-processing step improved accuracy; however, the addition of person-specific variables increased error with average RMSE 4.99 (SD ¼ 1.83). Conclusions: Hip and knee joint angle can be measured with a good degree of accuracy from a single inertial measurement unit using machine learning. This offers the ability to monitor and record dynamic joint angle with a single sensor outside of the clinic.
  • Publication
    Evaluating Performance of the Lunge Exercise with Multiple and Individual Inertial Measurement Units
    The lunge is an important component of lower limb rehabilitation, strengthening and injury risk screening. Completing the movement incorrectly alters muscle activation and increases stress on knee, hip and ankle joints. This study sought to investigate whether IMUs are capable of discriminating between correct and incorrect performance of the lunge. Eighty volunteers (57 males, 23 females, age: 24.68± 4.91 years, height: 1.75± 0.094m, body mass: 76.01±13.29kg) were fitted with five IMUs positioned on the lumbar spine, thighs and shanks. They then performed the lunge exercise with correct form and 11 specific deviations from acceptable form. Features were extracted from the labelled sensor data and used to train and evaluate random-forests classifiers. The system achieved 83% accuracy, 62% sensitivity and 90% specificity in binary classification with a single sensor placed on the right thigh and 90% accuracy, 80% sensitivity and 92% specificity using five IMUs. This multi-sensor set up can detect specific deviations with 70% accuracy. These results indicate that a single IMU has the potential to differentiate between correct and incorrect lunge form and using multiple IMUs adds the possibility of identifying specific deviations a user is making when completing the lunge.
  • Publication
    Inertial sensory data provides depth to clinical measures of dynamic balance
    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 individuals 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.
  • Publication
    Capturing concussion related changes in dynamic balance using the quantified Y Balance Test - a case series of six elite rugby union players
    This paper investigates design considerations and challenges of integrating on-chip antennas in nanoscale CMOS technology at millimeter-wave (mm-wave) to achieve a compact front-end receiver for 5G communication systems. Solutions to overcome these challenges are offered and realized in digital 28-nm CMOS. A monolithic on-chip antenna is designed and optimized in the presence of rigorous metal density rules and other back-end-of-the-line (BEoL) challenges of the nanoscale technology. The proposed antenna structure further exploits ground metallization on a PCB board acting as a reflector to increase its radiation efficiency and power gain by 37.3% and 9.8 dB, respectively, while decreasing the silicon area up to 30% compared to the previous works. The antenna is directly matched to a two-stage low noise amplifier (LNA) in a synergetic way as to give rise to an active integrated antenna (AIA) in order to avoid additional matching or interconnect losses. The LNA is followed by a double-balanced folded Gilbert cell mixer, which produces a lower intermediate frequency (IF) such that no probing is required for measurements. The measured total gain of the AIA is 14 dBi. Its total core area is 0.83 mm 2 while the total chip area, including the pad frame, is 1.55 × 0.85 mm 2.
      594Scopus© Citations 5
  • Publication
    Reliability, Validity and Utility of Inertial Sensor Systems for Postural Control Assessment in Sport Science and Medicine Applications: A Systematic Review
    Background Recent advances in mobile sensing and computing technology have provided a means to objectively and unobtrusively quantify postural control. This has resulted in the rapid development and evaluation of a series of wearable inertial sensor-based assessments. However, the validity, reliability and clinical utility of such systems is not fully understood. Objectives This systematic review aims to synthesise and evaluate studies that have investigated the ability of wearable inertial sensor systems to validly and reliably quantify postural control performance in sports science and medicine applications. Methods A systematic search strategy utilising the PRISMA guidelines was employed to identify eligible articles through ScienceDirect, Embase and PubMed databases. In total, 47 articles met the inclusion criteria and were evaluated and qualitatively synthesised under two main headings: measurement validity and measurement reliability. Furthermore, studies that investigated the utility of these systems in clinical populations were summarised and discussed. Results After duplicate removal, 4374 articles were identified with the search strategy, with 47 papers included in the final review. In total, 28 studies investigated validity in healthy populations, and 15 studies investigated validity in clinical populations; 13 investigated the measurement reliability of these sensor-based systems. Conclusions The application of wearable inertial sensors for sports science and medicine postural control applications is an evolving field. To date, research has primarily focused on evaluating the validity and reliability of a heterogeneous set of assessment protocols, in a laboratory environment. While researchers have begun to investigate their utility in clinical use cases such as concussion and musculoskeletal injury, most studies have leveraged small sample sizes, are of low quality and use a variety of descriptive variables, assessment protocols and sensor-mounting locations. Future research should evaluate the clinical utility of these systems in large high-quality prospective cohort studies to establish the role they may play in injury risk identification, diagnosis and management. This systematic review was registered with the International Prospective Register of Systematic Reviews on 10 August 2018 (PROSPERO registration: CRD42018106363):
      905Scopus© Citations 40
  • Publication
    Technology in Rehabilitation: Evaluating the Single Leg Squat Exercise with Wearable Inertial Measurement Units
    Background: The single leg squat (SLS) is a common lower limb rehabilitation exercise. It is also frequently used as an evaluative exercise to screen for an increased risk of lower limb injury. To date athlete / patient SLS technique has been assessed using expensive laboratory equipment or subjective clinical judgement; both of which are not without shortcomings. Inertial measurement units (IMUs) may offer a low cost solution for the objective evaluation of athlete / patient SLS technique. Objectives: The aims of this study were to determine if in combination or in isolation IMUs positioned on the lumbar spine, thigh and shank are capable of: (a) distinguishing between acceptable and aberrant SLS technique; (b) identifying specific deviations from acceptable SLS technique. Methods: Eighty-three healthy volunteers participated (60 males, 23 females, age: 24.68 + / − 4.91 years, height: 1.75 + / − 0.09 m, body mass: 76.01 + / − 13.29 kg). All participants performed 10 SLSs on their left leg. IMUs were positioned on participants’ lumbar spine, left shank and left thigh. These were utilized to record tri-axial accelerometer, gyroscope and magnetometer data during all repetitions of the SLS. SLS technique was labelled by a Chartered Physiotherapist using an evaluation framework. Features were extracted from the labelled sensor data. These features were used to train and evaluate a variety of random-forests classifiers that assessed SLS technique. Results: A three IMU system was moderately successful in detecting the overall quality of SLS performance (77 % accuracy, 77 % sensitivity and 78 % specificity). A single IMU worn on the shank can complete the same analysis with 76 % accuracy, 75 % sensitivity and 76 % specificity. Single sensors also produce competitive classification scores relative to multi-sensor systems in identifying specific deviations from acceptable SLS technique. Conclusions: A single IMU positioned on the shank can differentiate between acceptable and aberrant SLS technique with moderate levels of accuracy. It can also capably identify specific deviations from optimal SLS performance. IMUs may offer a low cost solution for the objective evaluation of SLS performance. Additionally, the classifiers described may provide useful input to an exercise biofeedback application.
      586Scopus© Citations 30
  • Publication
    Inter-session test-retest reliability of the quantified Y balance test
    The Y Balance test is the most common dynamic balance assessment used in clinical practice and research. However, the traditional measure of performance, the reach distance, fails to provide detailed information pertaining to the control of balance during the reach task. Recent research has demonstrated that a single wearable inertial sensor can capture detailed information pertaining to balance performance during the Y balance test, not captured by the traditional reach distances. To date, no research has been conducted investigating the inter-session test-retest reliability of the inertial sensor instrumented YBT. Thirty -two young healthy adults, aged between 18-40 were recruited as part of this study. Participants completed the quantified YBT protocol during two testing sessions, separated by 7-10 days. The findings from this study demonstrated that 26/36 (anterior), 31/36 (posteromedial) and 33/36 (posterolateral) quantified variables demonstrated good-excellent intra-session test-retest reliability. These findings suggest that the inertial sensor quantified YBT can provide a reliable measure of dynamic balance performance. Further research is required to investigate the capability of the quantified YBT to identify individuals at risk of injury/ disease and track recovery/ response to intervention.
      374Scopus© Citations 7
  • Publication
    Technology in Rehabilitation: Comparing Personalised and Global Classification Methodologies in Evaluating the Squat Exercise with Wearable IMUs
    BACKGROUND: The barbell squat is a popularly used lower limb rehabilitation exercise. It is also an integral exercise in injury risk screening protocols. To date athlete/patient technique has been assessed using expensive laboratory equipment or subjective clinical judgement; both of which are not without shortcomings. Inertial measurement units (IMUs) may offer a low cost solution for the objective evaluation of athlete/patient technique. However, it is not yet known if global classification techniques are effective in identifying naturally occurring, minor deviations in barbell squat technique.OBJECTIVES: The aims of this study were to: (a) determine if in combination or in isolation, IMUs positioned on the lumbar spine, thigh and shank are capable of distinguishing between acceptable and aberrant barbell squat technique; (b) determine the capabilities of an IMU system at identifying specific natural deviations from acceptable barbell squat technique; and (c) compare a personalised (N=1) classifier to a global classifier in identifying the above. METHODS: Fifty-five healthy volunteers (37 males, 18 females, age = 24.21 +/- 5.25 years, height = 1.75 +/- 0.1 m, body mass = 75.09 +/- 13.56 kg) participated in the study. All participants performed a barbell squat 3-repetition maximum max strength test. IMUs were positioned on participants' lumbar spine, both shanks and both thighs; these were utilized to record tri-axial accelerometer, gyroscope and magnetometer data during all repetitions of the barbell squat exercise. Technique was assessed and labelled by a Chartered Physiotherapist using an evaluation framework. Features were extracted from the labelled IMU data. These features were used to train and evaluate both global and personalised random forests classifiers.RESULTS: Global classification techniques produced poor accuracy (AC), sensitivity (SE) and specificity (SP) scores in binary classification even with a 5 IMU set-up in both binary (AC: 64%, SE: 70%, SP: 28%) and multi-class classification (AC: 59%, SE: 24%, SP: 84%). However, utilising personalised classification techniques even with a single IMU positioned on the left thigh produced good binary classification scores (AC: 81%, SE: 81%, SP: 84%) and moderate-to-good multi-class scores (AC: 69%, SE: 70%, SP: 89%).CONCLUSIONS: There are a number of challenges in developing global classification exercise technique evaluation systems for rehabilitation exercises such as the barbell squat. Building large, balanced data sets to train such systems is difficult and time intensive. Minor, naturally occurring deviations may not be detected utilising global classification approaches. Personalised classification approaches allow for higher accuracy and greater system efficiency for end-users in detecting naturally occurring barbell squat technique deviations. Applying this approach also allows for a single-IMU set up to achieve similar accuracy to a multi-IMU setup, which reduces total system cost and maximises system usability.
      413Scopus© Citations 11