Orientation-Invariant Spatio-Temporal Gait Analysis Using Foot-Worn Inertial Sensors

Inertial sensors can potentially assist clinical decision making in gait-related disorders. Methods for objective spatio-temporal gait analysis usually assume the careful alignment of the sensors on the body, so that sensor data can be evaluated using the body coordinate system. Some studies infer sensor orientation by exploring the cyclic characteristics of walking. In addition to being unrealistic to assume that the sensor can be aligned perfectly with the body, the robustness of gait analysis with respect to differences in sensor orientation has not yet been investigated—potentially hindering use in clinical settings. To address this gap in the literature, we introduce an orientation-invariant gait analysis approach and propose a method to quantitatively assess robustness to changes in sensor orientation. We validate our results in a group of young adults, using an optical motion capture system as reference. Overall, good agreement between systems is achieved considering an extensive set of gait metrics. Gait speed is evaluated with a relative error of −3.1±9.2 cm/s, but precision improves when turning strides are excluded from the analysis, resulting in a relative error of −3.4±6.9 cm/s. We demonstrate the invariance of our approach by simulating rotations of the sensor on the foot.

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Towards a Mobile Gait Analysis for Patients with a Spinal Cord Injury: A Robust Algorithm Validated for Slow Walking Speeds

Sensors ◽

10.3390/s21217381 ◽

2021 ◽

Vol 21 (21) ◽

pp. 7381

Author(s):

Charlotte Werner ◽

Chris Awai Awai Easthope ◽

Armin Curt ◽

László Demkó

Keyword(s):

Spinal Cord ◽

Spinal Cord Injury ◽

Gait Analysis ◽

Clinical Decision Making ◽

Inertial Sensors ◽

Clinical Decision ◽

Cord Injury ◽

Spatio Temporal ◽

The Individual ◽

Walking Speeds

Spinal cord injury (SCI) patients suffer from diverse gait deficits depending on the severity of their injury. Gait assessments can objectively track the progress during rehabilitation and support clinical decision making, but a comprehensive gait analysis requires far more complex setups and time-consuming protocols that are not feasible in the daily clinical routine. As using inertial sensors for mobile gait analysis has started to gain ground, this work aimed to develop a sensor-based gait analysis for the specific population of SCI patients that measures the spatio-temporal parameters of typical gait laboratories for day-to-day clinical applications. The proposed algorithm uses shank-mounted inertial sensors and personalized thresholds to detect steps and gait events according to the individual gait profiles. The method was validated in nine SCI patients and 17 healthy controls walking on an instrumented treadmill while wearing reflective markers for motion capture used as a gold standard. The sensor-based algorithm (i) performed similarly well for the two cohorts and (ii) is robust enough to cover the diverse gait deficits of SCI patients, from slow (0.3 m/s) to preferred walking speeds.

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Comprehensive Validation of a Wearable Foot Sensor System for Estimating Spatiotemporal Gait Parameters by Simultaneous Three-Dimensional Optical Motion Analysis

10.21203/rs.3.rs-1035657/v1 ◽

2021 ◽

Author(s):

Kentaro Homan ◽

Keizo Yamamoto ◽

Ken Kadoya ◽

Naoki Ishida ◽

Norimasa Iwasaki

Keyword(s):

Gait Analysis ◽

High Speed ◽

Inertial Sensors ◽

Three Dimensional ◽

Scientific Basis ◽

The Body ◽

Gait Parameters ◽

Optical Motion ◽

Analysis System ◽

Two Parameters

Abstract Background Use of a wearable gait analysis system (WGAS) is becoming common when conducting gait analysis studies due to its versatility. At the same time, its versatility raises a concern about its accuracy, because its calculations rely on assumptions embedded in its algorithms. The purpose of the present study was to validate all spatiotemporal gait parameters calculated by the WGAS by comparison with simultaneous measurements taken with an optical motion capture system (OMCS). Methods Ten young healthy volunteers wore two inertial sensors of the commercially available WGAS, Physilog®, on their feet and 23 markers for the OMCS on the lower part of the body. The participants performed at least three sets of 10-m walk tests at their self-paced speed in the laboratory equipped with 12 high-speed digital cameras with embedded force plates. To measure repeatability, all participants returned for a second day of testing within two weeks. Results All gait parameters calculated by the WGAS had a significant correlation with the ones determined by the OMCS. Bland and Altman analysis showed that the between-device agreement for all gait parameters was within clinically acceptable limits. The validity of the gait parameters generated by the WGAS was found to be excellent except for two parameters, swing width and maximal heel clearance. The repeatability of the WGAS was excellent when measured between sessions. Conclusion The present study showed that spatiotemporal gait parameters estimated by the WGAS were reasonably accurate and repeatable in healthy young adults, providing a scientific basis for applying this system to clinical studies.

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A Deep Learning Approach for Foot Trajectory Estimation in Gait Analysis Using Inertial Sensors

Sensors ◽

10.3390/s21227517 ◽

2021 ◽

Vol 21 (22) ◽

pp. 7517

Author(s):

Vânia Guimarães ◽

Inês Sousa ◽

Miguel Velhote Correia

Keyword(s):

Gait Analysis ◽

Inertial Sensors ◽

Inertial Sensor ◽

Sensor Data ◽

Coordinate Frame ◽

Complete Evaluation ◽

Gait Parameters ◽

Deep Recurrent Neural Network ◽

Optical Motion ◽

Frame Transformation

Gait performance is an important marker of motor and cognitive decline in older adults. An instrumented gait analysis resorting to inertial sensors allows the complete evaluation of spatiotemporal gait parameters, offering an alternative to laboratory-based assessments. To estimate gait parameters, foot trajectories are typically obtained by integrating acceleration two times. However, to deal with cumulative integration errors, additional error handling strategies are required. In this study, we propose an alternative approach based on a deep recurrent neural network to estimate heel and toe trajectories. We propose a coordinate frame transformation for stride trajectories that eliminates the dependency from previous strides and external inputs. Predicted trajectories are used to estimate an extensive set of spatiotemporal gait parameters. We evaluate the results in a dataset comprising foot-worn inertial sensor data acquired from a group of young adults, using an optical motion capture system as a reference. Heel and toe trajectories are predicted with low errors, in line with reference trajectories. A good agreement is also achieved between the reference and estimated gait parameters, in particular when turning strides are excluded from the analysis. The performance of the method is shown to be robust to imperfect sensor-foot alignment conditions.

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Ovarian tissue freezing and activation after thawing: an update

Middle East Fertility Society Journal ◽

10.1186/s43043-021-00056-5 ◽

2021 ◽

Vol 26 (1) ◽

Author(s):

Li-fan Peng

Keyword(s):

Granulosa Cells ◽

Clinical Decision Making ◽

Ovarian Function ◽

Ovarian Tissue ◽

Clinical Decision ◽

The Body ◽

Endocrine Function ◽

Ovarian Tissue Cryopreservation ◽

Main Body ◽

Tissue Cryopreservation

Abstract Background With the growth of women’s age, ovarian failure can be caused by various factors. For the women who need chemotherapy because of cancer factors, the preservation of fertility is more urgent. The treatment of cancer is also a process in which all tissues and organs of the body are severely damaged, especially in the reproductive system. Main body As a new fertility preservation technology, autologous ovarian tissue cryopreservation and transplantation is developing rapidly and showing great potentiality in preserving ovarian endocrine function of young cervical cancer patients. Vitrification and slow freezing are two common techniques applied for ovarian tissue cryopreservation. Thus, cryopreserved/thawed ovarian tissue and transplantation act as an important method to preserve ovarian function during radiotherapy and chemotherapy, and ovarian cryopreservation by vitrification is a very effective and extensively used method to cryopreserve ovaries. The morphology of oocytes and granulosa cells and the structure of organelles were observed under the microscope of histology; the hormone content in the stratified culture medium of granulosa cells with the diameter of follicle was used to evaluate the development potential of ovarian tissue, and finally the ovarian tissue stimulation was determined by the technique of ovarian tissue transplantation. Conclusions Although there are some limitations, the team members still carry out this review to provide some references and suggestions for clinical decision-making and further clinical research.

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Clinical decision making in spastic bilateral CP – Planning interventions using clinical gait analysis: A case study

Gait & Posture ◽

10.1016/j.gaitpost.2015.06.073 ◽

2015 ◽

Vol 42 ◽

pp. S37

Author(s):

M. Alvela ◽

M. Bergmann ◽

M.-L. Ööpik ◽

Ü. Kruus ◽

K. Englas ◽

...

Keyword(s):

Decision Making ◽

Gait Analysis ◽

Clinical Decision Making ◽

Clinical Decision ◽

Clinical Gait Analysis

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Awareness, Knowledge, and Utility of RCT Data vs RWE: Results From a Survey of US Cardiologists: Real-world Evidence in Clinical Decision Making

Clinical Medicine Insights Cardiology ◽

10.1177/1179546820953410 ◽

2020 ◽

Vol 14 ◽

pp. 117954682095341 ◽

Cited By ~ 1

Author(s):

Todd C Villines ◽

Mark J Cziraky ◽

Alpesh N Amin

Keyword(s):

Decision Making ◽

Clinical Practice ◽

Real World ◽

Randomized Clinical Trials ◽

Clinical Decision Making ◽

Clinical Decision ◽

The Body ◽

Representative Sampling ◽

Real World Evidence ◽

Wide Range

Real-world evidence (RWE) provides a potential rich source of additional information to the body of data available from randomized clinical trials (RCTs), but there is a need to understand the strengths and limitations of RWE before it can be applied to clinical practice. To gain insight into current thinking in clinical decision making and utility of different data sources, a representative sampling of US cardiologists selected from the current, active Fellows of the American College of Cardiology (ACC) were surveyed to evaluate their perceptions of findings from RCTs and RWE studies and their application in clinical practice. The survey was conducted online via the ACC web portal between 12 July and 11 August 2017. Of the 548 active ACC Fellows invited as panel members, 173 completed the survey (32% response), most of whom were board certified in general cardiology (n = 119, 69%) or interventional cardiology (n = 40, 23%). The survey results indicated a wide range of familiarity with and utilization of RWE amongst cardiologists. Most cardiologists were familiar with RWE and considered RWE in clinical practice at least some of the time. However, a significant minority of survey respondents had rarely or never applied RWE learnings in their clinical practice, and many did not feel confident in the results of RWE other than registry data. These survey findings suggest that additional education on how to assess and interpret RWE could help physicians to integrate data and learnings from RCTs and RWE to best guide clinical decision making.

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Switching and Combining Antipsychotics

CNS Spectrums ◽

10.1017/s1092852900027693 ◽

2010 ◽

Vol 15 (S6) ◽

pp. 8-11 ◽

Cited By ~ 5

Author(s):

Christoph U. Correll

Keyword(s):

Decision Making ◽

Individual Differences ◽

Clinical Decision Making ◽

Clinical Decision ◽

Individual Variability ◽

The Body ◽

Striatal Dopamine ◽

Caloric Content ◽

Pharmacokinetic Profiles ◽

Positron Emission

Pharmacologic knowledge can inform clinical decision-making, particularly the dosing and switching decisions made with antipsychotics. Of relevance are the pharmacokinetic (what does the body do to the drug) and the pharmacodynamic (what does the drug do to the body) properties of antipsychotics.The goal of antipsychotic dosing is to achieve sufficient dopa-mine blockade in areas where dopamine excess can lead to psychosis, mania, or aggression. Using positron emission topography, one investigation showed that response rates were considerably higher in patients who achieved >65% striatal dopamine blockade. Conversely, striatal dopamine blockade >80% predicted the emergence of extrapyramidal symptoms (EPS) or akathisia.There is, however, considerable intra-individual variability in achieving the desired 60% to 80% striatal dopamine blockade. Such variability is likely due to inter-individual differences in the absorption, distribution, metabolism and elimination of medications. At the same time, antipsychotics themselves differ in their general pharmacokinetic profiles. For example, ziprasidone absorption is ~50% less when ingested on an empty stomach than when taken with a meal; the degree of absorption depends on the caloric content, while the fat content is not relevant.

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Effect of Speed and Surface Type on Individual Rein and Combined Left–Right Circle Movement Asymmetry in Horses on the Lunge

Frontiers in Veterinary Science ◽

10.3389/fvets.2021.692031 ◽

2021 ◽

Vol 8 ◽

Author(s):

Thilo Pfau ◽

Emma Persson-Sjodin ◽

Harriet Gardner ◽

Olivia Orssten ◽

Elin Hernlund ◽

...

Keyword(s):

Gait Analysis ◽

Clinical Decision Making ◽

Linear Models ◽

Clinical Decision ◽

Diagnostic Process ◽

Limits Of Agreement ◽

Random Factor ◽

Speed Increase ◽

Straight Line ◽

Movement Asymmetry

Differences in movement asymmetry between surfaces and with increasing speed increase the complexity of incorporating gait analysis measurements from lunging into clinical decision making. This observational study sets out to quantify by means of quantitative gait analysis the influence of surface and speed on individual-rein movement asymmetry measurements and their averages across reins (average-rein measurements). Head, withers, and pelvic movement asymmetry was quantified in 27 horses, identified previously as presenting with considerable movement asymmetries on the straight, during trot in hand and on the lunge on two surfaces at two speeds. Mixed linear models (p < 0.05) with horse as the random factor and surface and speed category (and direction) as fixed factors analyzed the effects on 11 individual-rein and average-rein asymmetry measures. Limits of agreement quantified differences between individual-rein and average-rein measurements. A higher number of individual-rein asymmetry variables—particularly when the limb that contributed to movement asymmetry on the straight was on the inside of the circle—were affected by speed (nine variables, all p ≤ 0.047) and surface (three variables, all p ≤ 0.037) compared with average-rein asymmetry variables (two for speed, all p ≤ 0.003; two for surface, all p ≤ 0.046). Six variables were significantly different between straight-line and average-rein assessments (all p ≤ 0.031), and asymmetry values were smaller for average-rein assessments. Limits of agreement bias varied between +0.4 and +4.0 mm with standard deviations between 3.2 and 12.9 mm. Fewer average-rein variables were affected by speed highlighting the benefit of comparing left and right rein measurements. Only one asymmetry variable showed a surface difference for individual-rein and average-rein data, emphasizing the benefit of assessing surface differences on each rein individually. Variability in straight-line vs. average-rein measurements across horses and exercise conditions highlight the potential for average-rein measurements during the diagnostic process; further studies after diagnostic analgesia are needed.

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Human Motion Capture with Sparse Inertial Sensors and Video

10.51202/9783186866103 ◽

2020 ◽

Author(s):

Timo von Marcard

Keyword(s):

Global Optimization ◽

Optimization Problem ◽

Inertial Sensors ◽

Inertial Sensor ◽

Hybrid Approach ◽

Human Motion ◽

The Body ◽

Sensor Data ◽

Discrete Optimization Problem ◽

Global Optimization Problem

This thesis explores approaches to capture human motions with a small number of sensors. In the first part of this thesis an approach is presented that reconstructs the body pose from only six inertial sensors. Instead of relying on pre-recorded motion databases, a global optimization problem is solved to maximize the consistency of measurements and model over an entire recording sequence. The second part of this thesis deals with a hybrid approach to fuse visual information from a single hand-held camera with inertial sensor data. First, a discrete optimization problem is solved to automatically associate people detections in the video with inertial sensor data. Then, a global optimization problem is formulated to combine visual and inertial information. The propose approach enables capturing of multiple interacting people and works even if many more people are visible in the camera image. In addition, systematic inertial sensor errors can be compensated, leading to a substantial in...

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