Agreement Level of Running Temporal Measurements, Kinetics, and Force-Time Curves Calculated from Inertial Measurement Units

Inertial measurement units (IMUs) and wearable sensors have enabled athlete monitoring and research to become more ecologically valid due to their small size and low cost. IMUs and accelerometers that are placed on the body close to the point of impact and that record at sufficiently high frequencies have demonstrated the highest validity when measuring temporal gait event moments such as ground contact time (GCT) and flight time (FT) as well as peak forces (PF) during upright running. While the use of IMUs has increased in the sport performance and athlete monitoring realm, the potential of the technology’s ability to estimate running force-time curves utilizing the two-mass model (TMM) remains unexplored. The purpose of this study was two-fold. First, was to determine the validity of measuring temporal gait events and peak forces utilizing a commercially available shank-mounted inertial measurement unit. Second, was to determine the validity of force-time curves generated from the TMM utilizing data from shank-mounted inertial measurement units. Ten subjects voluntarily completed submaximal treadmill tests equipped with a force plate while wearing shank-mounted IMUs on each leg. Using the raw data from the IMUs, GCT, FT, total step time (ST), PF, and two-mass model-based force-time (F-t) curves were generated for 25 steps at 8 different speeds. Paired sample T-tests were performed on the gait events and peak force between the IMU and treadmill with both individual step comparison and averages per each speed. 95% confidence intervals were calculated for each timepoint of the force time curves. No statistically significant differences (p \u3e 0.05) and nearly perfect relationships were observed for the step averages for each speed with FT, ST, and PF. Confidence intervals of the corrected mean difference suggest that F-t curves calculated from the TMM may not be valid when assessing the running population as a whole. When performing a sub-group analysis of skilled runners and recreational runners, F-t curves derived from shank-mounted IMUs may be more valid in skilled runners than recreational runners. In skilled runners, the 95% CI for the mean difference contained zero within the first 60% of the GCT duration, whereas the 95% CI recreational runners contained a zero-value in a smaller percentage of the GCT located only in the middle of the GCT at the curve peak height. The results of this study suggest that interchangeability between shank-mounted IMUs and force plates may be very limited when estimating temporal gait events and kinetics. While agreement was low between F-t curves after the peak in skilled runners, use of shank-mounted IMUs to estimate F-t curves may have several benefits still in skilled runners when assessing peak forces and force development from initial contact until peak force

Human Gait Model Development for Objective Analysis of Pre/Post Gait Characteristics Following Lumbar Spine Surgery

Although multiple advanced tools and methods are available for gait analysis, the gait and its related disorders are usually assessed by visual inspection in the clinical environment. This thesis aims to introduce a gait analysis system that provides an objective method for gait evaluation in clinics and overcomes the limitations of the current gait analysis systems. Early identification of foot drop, a common gait disorder, would become possible using the proposed methodology

Comparison of IMU set-ups for the estimation of gait spatio-temporal parameters in an elderly population

The increasing average age emphasizes the importance of gait analysis in elderly populations. Inertial Measurement Units (IMUs) represent a suitable wearable technology for the characterization of gait by estimating spatio-temporal parameters (STPs). However, the location of inertial sensors on the human body and the associated algorithms for the estimation of gait STPs play a fundamental role and are still open challenges. Accordingly, the aim of this work was to compare three IMUs set-ups (trunk, shanks, and ankles) and correspondent algorithms to a gold standard optoelectronic system for the estimation of gait STPs in a healthy elderly population. In total, 14 healthy elderly subjects walked barefoot at three different speeds. Gait parameters were assessed for each IMUs set-up and compared to those estimated with the gold standard. A statistical analysis based on Pearson correlation, Root Mean Square Error and Bland Altman plots was conducted to evaluate the accuracy of IMUs. Even though all tested set-ups produced accurate results, the IMU on the trunk performed better in terms of correlation (R ≥ 0.8), RMSE (0.01-0.06 s for temporal parameters, 0.03-0.04 for the limp index), and level of agreement (-0.01 s ≤ mean error ≤ 0.01 s, -0.02 s ≤ standard deviation error ≤ 0.02 s), also allowing simpler preparation of subjects and minor encumbrance during gait. From the promising results, a similar experiment might be conducted in pathological populations in the attempt to verify the accuracy of IMUs set-ups and algorithms also in non-physiological patterns

Feasibility of Sensor Technology for Balance Assessment in Home Rehabilitation Settings

The increased use of sensor technology has been crucial in releasing the potential for remote rehabilitation. However, it is vital that human factors, that have potential to affect real-world use, are fully considered before sensors are adopted into remote rehabilitation practice. The smart sensor devices for rehabilitation and connected health (SENDoc) project assesses the human factors associated with sensors for remote rehabilitation of elders in the Northern Periphery of Europe. This article conducts a literature review of human factors and puts forward an objective scoring system to evaluate the feasibility of balance assessment technology for adaption into remote rehabilitation settings. The main factors that must be considered are: Deployment constraints, usability, comfort and accuracy. This article shows that improving accuracy, reliability and validity is the main goal of research focusing on developing novel balance assessment technology. However, other aspects of usability related to human factors such as practicality, comfort and ease of use need further consideration by researchers to help advance the technology to a state where it can be applied in remote rehabilitation settings

Wearables for Movement Analysis in Healthcare

Quantitative movement analysis is widely used in clinical practice and research to investigate movement disorders objectively and in a complete way. Conventionally, body segment kinematic and kinetic parameters are measured in gait laboratories using marker-based optoelectronic systems, force plates, and electromyographic systems. Although movement analyses are considered accurate, the availability of specific laboratories, high costs, and dependency on trained users sometimes limit its use in clinical practice. A variety of compact wearable sensors are available today and have allowed researchers and clinicians to pursue applications in which individuals are monitored in their homes and in community settings within different fields of study, such movement analysis. Wearable sensors may thus contribute to the implementation of quantitative movement analyses even during out-patient use to reduce evaluation times and to provide objective, quantifiable data on the patients’ capabilities, unobtrusively and continuously, for clinical purposes

Automated gait segmentation and tracking using inertial measurement units

Abstract. In this thesis, a methodology is presented to automate the labelling, event detection, segmentation, tracking, and parameter extraction of IMU gait data for sensors placed on the feet and shanks. The algorithms presented were tested using IMU data from three different styles of gait, normal gait, antalgic gait, and limited mobility gait. The algorithms developed were found effective for all of the simulated gait styles without mislabelling or detecting erroneous gait segments. The resultant gait trajectories and parameters were analyzed and were found to accurately depict the differences between each of the different styles of gait. The methodology presented can be used for the rapid and accurate processing of gait data for multiple styles of gait. This quantification of gait data can enable the collection of IMU gait data on a larger scale. This provides an accessible, low-cost option for out-of-laboratory gait data collection

最小限のウェアラブルセンサーを用いたマルチモーダルな定量的歩行評価

Tohoku University林部充弘課

Body sensor networks: smart monitoring solutions after reconstructive surgery

Advances in reconstructive surgery are providing treatment options in the face of major trauma and cancer. Body Sensor Networks (BSN) have the potential to offer smart solutions to a range of clinical challenges. The aim of this thesis was to review the current state of the art devices, then develop and apply bespoke technologies developed by the Hamlyn Centre BSN engineering team supported by the EPSRC ESPRIT programme to deliver post-operative monitoring options for patients undergoing reconstructive surgery. A wireless optical sensor was developed to provide a continuous monitoring solution for free tissue transplants (free flaps). By recording backscattered light from 2 different source wavelengths, we were able to estimate the oxygenation of the superficial microvasculature. In a custom-made upper limb pressure cuff model, forearm deoxygenation measured by our sensor and gold standard equipment showed strong correlations, with incremental reductions in response to increased cuff inflation durations. Such a device might allow early detection of flap failure, optimising the likelihood of flap salvage. An ear-worn activity recognition sensor was utilised to provide a platform capable of facilitating objective assessment of functional mobility. This work evolved from an initial feasibility study in a knee replacement cohort, to a larger clinical trial designed to establish a novel mobility score in patients recovering from open tibial fractures (OTF). The Hamlyn Mobility Score (HMS) assesses mobility over 3 activities of daily living: walking, stair climbing, and standing from a chair. Sensor-derived parameters including variation in both temporal and force aspects of gait were validated to measure differences in performance in line with fracture severity, which also matched questionnaire-based assessments. Monitoring the OTF cohort over 12 months with the HMS allowed functional recovery to be profiled in great detail. Further, a novel finding of continued improvements in walking quality after a plateau in walking quantity was demonstrated objectively. The methods described in this thesis provide an opportunity to revamp the recovery paradigm through continuous, objective patient monitoring along with self-directed, personalised rehabilitation strategies, which has the potential to improve both the quality and cost-effectiveness of reconstructive surgery services.Open Acces