242 research outputs found

    The use of inertial measurement units for the determination of gait spatio-temporal parameters

    Get PDF
    The aim of this work was to develop a methodology whereby inertial measurement units (IMUs) could be used to obtain accurate and objective gait parameters within typical developed adults (TDA) and Parkinson’s disease (PD). The thesis comprised four studies, the first establishing the validity of the IMU method when measuring the vertical centre of mass (CoM) acceleration, velocity and position versus an optical motion capture system (OMCS) in TDA. The second study addressed the validity of the IMU and inverted pendulum model measurements within PD and also explored the inter-rater reliability of the measurement. In the third study the optimisation of the inverted pendulum model driven by IMU data was explored when comparing to standardised clinical tests within TDA and PD, and the fourth explored a novel phase plot analysis applied to CoM movement to explore gait in more detail. The validity study showed no significant difference for vertical acceleration and position between IMU and OMCS measurements within TDA. Vertical velocity however did show a significant difference, but the error was still less than 2.5%. ICCs for all three parameters ranged from 0.782 to 0.952, indicating an adequate test-retest reliability. Within PD there was no significant difference found for vertical CoM acceleration, velocity and position. ICCs for all three parameters ranged from 0.77 to 0.982. In addition, the reliability calculations found no difference for step time, stride length and walking speed for people with PD. Inter-rater reliability was found not to be different for the same parameters. The optimisation of the correction factor when using the inverted pendulum model showed no significant difference between TDA and PD. Furthermore the correction factor was found not to be related to walking speed. The fourth and final study found that phase plot analysis of variability could be performed on CoM vertical excursion. TDA and PD were shown to have, on average, different characteristics. This thesis demonstrated that CoM motion can be objectively measured within a clinical setting in people with PD by utilizing IMUs. Furthermore, in depth gait variability analysis can be performed by utilizing a phase plot method

    Validity and reliability of a portable gait analysis system for measuring spatiotemporal gait characteristics: comparison to an instrumented treadmill

    Get PDF
    Gait analysis serves as an important tool for clinicians and other health professionals to assess gait patterns related to functional limitations due to neurological or orthopedic conditions. The purpose of this study was to assess the validity of a body-worn inertial sensor system (RehaGait®) for measuring spatiotemporal gait characteristics compared to a stationary treadmill (Zebris) and the reliability of both systems at different walking speeds and slopes.; Gait analysis was performed during treadmill walking at different speeds (habitual walking speed (normal speed); 15 % above normal walking speed; 15 % below normal walking speed) and slopes (0 % slope; 15 % slope) in 22 healthy participants twice 1 week apart. Walking speed, stride length, cadence and stride time were computed from the inertial sensor system and the stationary treadmill and compared using repeated measures analysis of variance. Effect sizes of differences between systems were assessed using Cohen's d, and limits of agreement and systematic bias were computed.; The RehaGait® system slightly overestimated stride length (+2.7 %) and stride time (+0.8 %) and underestimate cadence (-1.5 %) with small effect sizes for all speeds and slopes (Cohen's d ≤ 0.44) except slow speed at 15 % slope (Cohen's d > 0.80). Walking speed obtained with the RehaGait® system closely matched the speed set on the treadmill tachometer. Intraclass correlation coefficients (ICC) were excellent for speed, cadence and stride time and for stride length at normal and fast speed at 0 % slope (ICC: .91-1.00). Good ICC values were found for stride length at slow speed at 0 % slope and all speeds at 15 % slope (ICC: .73-.90). Both devices had excellent reliability for most gait characteristics (ICC: .91-1.00) except good reliability for the RehaGait® for stride length at normal and fast speed at 0 % slope and at slow speed at 15 % slope (ICC: .80-.87).; Larger limits of agreement for walking at 15 % slope suggests that uphill walking may influence the reliability of the RehaGait® system. The RehaGait® is a valid and reliable tool for measuring spatiotemporal gait characteristics during level and inclined treadmill walking

    Validation of an Accelerometry Based Method of Human Gait Analysis

    Get PDF
    Gait analysis is the quantification of locomotion. Understanding the science behind the way we move is of interest to a wide variety of fields. Medical professionals might use gait analysis to track the rehabilitation progress of a patient. An engineer may want to design wearable robotics to augment a human operator. Use cases even extend into the sport and entertainment industries. Typically, a gait analysis is performed in a highly specialized laboratory containing cumbersome expensive equipment. The process is tedious and requires specially trained operators. Continued development of small and cheap inertial measurement units (IMUs) over an alternative to current methods of gait analysis. These devices are portable and simple to use allowing gait analysis to be done outside the laboratory in real world environments. Unfortunately, while current IMU based gait analysis systems are able to quantify a subject\u27s joint kinematics they are unable to measure joint kinetics as could be done in a traditional gait laboratory. A novel musculoskeletal model-based movement analysis system using accelerometers has been developed that can calculate both joint kinematics and joint kinetics. The aim of this master\u27s thesis is to validate this accelerometer based gait analysis against the industry standard optical motion capture gait analysi

    Assessing the Accuracy of an Algorithm for the Estimation of Spatial Gait Parameters Using Inertial Measurement Units: Application to Healthy Subject and Hemiparetic Stroke Survivor

    Get PDF
    We have reviewed and assessed the reliability of a dead reckon- ing and drift correction algorithm for the estimation of spatial gait parameters using Inertial Measurement Units (IMUs). In particular, we are interested in obtaining accurate stride lengths measurements in order to assess the effects of a wearable haptic cueing device designed to assist people with neurological health conditions during gait rehabilitation. To assess the accuracy of the stride lengths estimates, we compared the output of the algorithm with measurements obtained using a high-end marker-based motion capture system, here adopted as a gold standard. In addition, we introduce an alternative method for detecting initial impact events (i.e. the instants at which one foot contacts the ground, here used for de- limiting strides) using accelerometer data. Our method, based on a kinematic feature we named ‘jerkage’, has proved more robust than detecting peaks on raw accelerometer data. We argue that the resulting measurements of stride lengths are accurate enough to provide trend data needed to support worthwhile gait rehabilitation applications. This approach has potential to assist physiotherapists and patients without access to fully-equipped movement labs. More specifically, it has applications for collecting data to guide and assess gait rehabilitation both outdoors and at home

    Automating the timed up and go test using a depth camera

    Get PDF
    Fall prevention is a human, economic and social issue. The Timed Up and Go (TUG) test is widely used to identify individuals with a high fall risk. However, this test has been criticized because its “diagnostic” is too dependent on the conditions in which it is performed and on the healthcare professionals running it. We used the Microsoft Kinect ambient sensor to automate this test in order to reduce the subjectivity of outcome measures and to provide additional information about patient performance. Each phase of the TUG test was automatically identified from the depth images of the Kinect. Our algorithms accurately measured and assessed the elements usually measured by healthcare professionals. Specifically, average TUG test durations provided by our system differed by only 0.001 s from those measured by clinicians. In addition, our system automatically extracted several additional parameters that allowed us to accurately discriminate low and high fall risk individuals. These additional parameters notably related to the gait and turn pattern, the sitting position and the duration of each phase. Coupling our algorithms to the Kinect ambient sensor can therefore reliably be used to automate the TUG test and perform a more objective, robust and detailed assessment of fall risk

    Wearable inertial sensors for human movement analysis

    Get PDF
    Introduction: The present review aims to provide an overview of the most common uses of wearable inertial sensors in the field of clinical human movement analysis.Areas covered: Six main areas of application are analysed: gait analysis, stabilometry, instrumented clinical tests, upper body mobility assessment, daily-life activity monitoring and tremor assessment. Each area is analyzed both from a methodological and applicative point of view. The focus on the methodological approaches is meant to provide an idea of the computational complexity behind a variable/parameter/index of interest so that the reader is aware of the reliability of the approach. The focus on the application is meant to provide a practical guide for advising clinicians on how inertial sensors can help them in their clinical practice.Expert commentary: Less expensive and more easy to use than other systems used in human movement analysis, wearable sensors have evolved to the point that they can be considered ready for being part of routine clinical routine

    Measuring gait kinematics in patients with severe hip osteoarthritis using wearable sensors

    Get PDF
    Background The popularity of inertial sensors in gait analysis is steadily rising. To date, an application of a wearable inertial sensor system for assessing gait in hip osteoarthritis (OA) has not been reported. Research question: Can the known kinematic differences between patients with hip OA and asymptomatic control subjects be measured using the inertial sensor system RehaGait®? Methods The patients group consisted of 22 patients with unilateral hip OA scheduled for total hip replacement. Forty-five age matched healthy control subjects served as control group. All subjects walked for a distance of 20 m at their self-selected speed. Spatiotemporal parameters and sagittal kinematics at the hip, knee, and ankle including range of motion (ROM) were measured using the RehaGait® system. Results Patients with hip OA walked at a slower walking speed (−0.18 m/s, P < 0.001) and with shorter stride length (−0.16 m, P < 0.001), smaller hip ROM during stance (−11.6°, P < 0.001) and swing (−11.3°, P < 0.001) and smaller knee ROM during terminal stance and swing (−9.0° and−11.5°, P < 0.001). Patients had a smaller hip ROM during stance and swing and smaller knee ROM during terminal stance and swing in the affected compared to the unaffected side (P < 0.001). Significance The differences in spatiotemporal and kinematic gait parameters between patients with hip OA and age matched control subjects assessed using the inertial sensor system agree with those documented for camera-based systems. Hence, the RehaGait® system can measure gait kinematics characteristic for hip OA, and its use in daily clinical practice is feasible

    Gait analysis in neurological populations: Progression in the use of wearables

    Get PDF
    Gait assessment is an essential tool for clinical applications not only to diagnose different neurological conditions but also to monitor disease progression as it contributes to the understanding of underlying deficits. There are established methods and models for data collection and interpretation of gait assessment within different pathologies. This narrative review aims to depict the evolution of gait assessment from observation and rating scales to wearable sensors and laboratory technologies, and provide possible future directions. In this context, we first present an extensive review of current clinical outcomes and gait models. Then, we demonstrate commercially available wearable technologies with their technical capabilities along with their use in gait assessment studies for various neurological conditions. In the next sections, a descriptive knowledge for existing inertial based algorithms and a sign based guide that shows the outcomes of previous neurological gait assessment studies are presented. Finally, we state a discussion for the use of wearables in gait assessment and speculate the possible research directions by revealing the limitations and knowledge gaps in the literature

    Using wearable inertial sensors to compare different versions of the dual task paradigm during walking

    Get PDF
    The dual task paradigm (DTP), where performance of a walking task co-occurs with a cognitive task to assess performance decrement, has been controversially mooted as a more suitable task to test safety from falls in outdoor and urban environments than simple walking in a hospital corridor. There are a variety of different cognitive tasks that have been used in the DTP, and we wanted to assess the use of a secondary task that requires mental tracking (the alternate letter alphabet task) against a more automatic working memory task (counting backward by ones). In this study we validated the x-io x-IMU wearable inertial sensors, used them to record healthy walking, and then used dynamic time warping to assess the elements of the gait cycle. In the timed 25 foot walk (T25FW) the alternate letter alphabet task lengthened the stride time significantly compared to ordinary walking, while counting backward did not. We conclude that adding a mental tracking task in a DTP will elicit performance decrement in healthy volunteers
    corecore