Now showing 1 - 6 of 6
  • 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
    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.
      420Scopus© Citations 7
  • Publication
    Leveraging IMU Data for Accurate Exercise Performance Classification and Musculoskeletal Injury Risk Screening
    Inertial measurement units (IMUs) are becoming increasingly prevalent as a method for low cost and portable biomechanical analysis. However, to date they have not tended to be accepted into routine clinical practice. This is often due to the disconnect between translating the data collected by the sensors into meaningful and actionable information for end users. This paper outlines the work completed by our group in attempting to achieve this. We discuss the conceptual framework involved in our work, the methodological approach taken in analysing sensor signals and discuss possible application models. The work completed by our group indicates that IMU based systems have the potential to bridge the gap between laboratory and clinical movement analysis. Future work will focus on collecting a diverse range of movement data and using more sophisticated data analysis techniques to refine systems.
      627Scopus© Citations 23
  • Publication
    Evaluating Squat Performance with a Single Inertial Measurement Unit
    Inertial measurement units (IMUs) may be used during exercise performance to assess form and technique. To maximise practicality and minimise cost a single-sensor system is most desirable. This study sought to investigate whether a single lumbar-worn IMU is capable of identifying seven commonly observed squatting deviations. Twenty-two volunteers (18 males, 4 females, age: 26.09±3.98 years, height: 1.75±0.14m, body mass: 75.2±14.2 kg) performed the squat exercise correctly and with 7 induced deviations. IMU signal features were extracted for each condition. Statistical analysis and leave one subject out classifier evaluation were used to assess the ability of a single sensor to evaluate performance. Binary level classification was able to distinguish between correct and incorrect squatting performance with a sensitivity of 64.41%, specificity of 88.01% and accuracy of 80.45%. Multi-label classification was able to distinguish between specific squat deviations with a sensitivity of 59.65%, specificity of 94.84% and accuracy of 56.55%. These results indicate that a single IMU can successfully discriminate between squatting deviations. A larger data set must be collected and more complex classification techniques developed in order to create a more robust exercise analysis IMU-based system.
      1004Scopus© Citations 28
  • Publication
    Objective Classification of Dynamic Balance Using a Single Wearable Sensor
    (SCITEPRESS – Science and Technology Publications, 2016-11-09) ; ; ; ; ;
    The Y Balance Test (YBT) is one of the most commonly used dynamic balance assessments in clinical and research settings. This study sought to investigate the ability of a single lumbar inertial measurement unit (IMU) to discriminate between the three YBT reach directions, and between pre and post-fatigue balance performance during the YBT. Fifteen subjects (age: 234, weight: 67.58, height: 1758, BMI: 222) were fitted with a lumbar IMU. Three YBTs were performed on the dominant leg at 0, 10 and 20 minutes. A modified Wingate fatiguing intervention was conducted to introduce a balance deficit. This was followed immediately by three post-fatigue YBTs. Features were extracted from the IMU, and used to train and evaluate the random-forest classifiers. Reach direction classification achieved an accuracy of 97.80%, sensitivity of 97.860.89% and specificity of 98.900.56%. Normal and abnormal balance performance, as influenced by fatigue, was classified with an accuracy of 61.90%-71.43%, sensitivity of 61.90%-69.04% and specificity of 61.90%-78.57% depending on which reach direction was chosen. These results demonstrate that a single lumbar IMU is capable of accurately distinguishing between the different YBT reach directions and can classify between pre and post-fatigue balance with moderate levels of accuracy.
      734Scopus© Citations 16
  • 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.
      608Scopus© Citations 5