Agreement between the inertial measurement unit and optoelectronic system to measure postural sway

2021 ◽  
pp. 1-6
Author(s):  
Alessandro Vagnini ◽  
Roberta Furone ◽  
Giulia Zanotti ◽  
Paola Adamo ◽  
Federico Temporiti ◽  
...  
Keyword(s):  
Inertial Measurement Unit ◽  
Postural Sway ◽  
Measurement Unit ◽  
Confidence Ellipse ◽  
Optoelectronic System ◽  
Inertial Measurement ◽  
Measurement Units ◽  
User Friendly ◽  
Anterior Posterior ◽  
Good Agreement

BACKGROUND: Optoelectronic systems and force platforms represent the gold standard for postural sway assessment, but pose disadvantages in terms of equipment, cost and preparation time. OBJECTIVE: Wearable inertial measurement units (IMUs) have been proposed to overcome these issues, but have never been compared to an optoelectronic system. The study aim was therefore to investigate agreement between inertial measurement unit and optoelectronic system in postural sway assessment. METHODS: Thirty healthy volunteers performed four balance tasks. IMU was placed on the sacrum (S2) with a retroreflective marker over the sensor and subjects’ performance was simultaneously recorded by both systems. Total (TOT), anterior-posterior (AP) and medial-lateral (ML) length of trace, range, speed, root mean squared (RMS), and confidence ellipse were computed. RESULTS: ICCs revealed excellent correlations for Length-TOT, Length-AP and Speed-AP, good correlation for Length-ML, Speed-ML, Confidence Ellipse, Range-AP and RMS-AP, and moderate correlation for range-ML and RMS-ML. Bland-Altman plot showed greater estimation for Length-TOT, Length-AP, Speed-AP, confidence ellipse and RMS-AP using optoelectronic system, and for Length-ML, Range-AP, Range-ML, Speed-ML, RMS-ML using IMU. Both systems revealed the same differences among tasks. CONCLUSION: The excellent to good agreement of IMU for length of trace and speed parameters and its user-friendly application suggest its potential implementations in clinical practice.

scholarly journals Accuracy and Repeatability of Spatiotemporal Gait Parameters Measured with an Inertial Measurement Unit

2021 ◽  
Vol 10 (9) ◽  
pp. 1804
Author(s):  
Jorge Posada-Ordax ◽  
Julia Cosin-Matamoros ◽  
Marta Elena Losa-Iglesias ◽  
Ricardo Becerro-de-Bengoa-Vallejo ◽  
Laura Esteban-Gonzalo ◽  
...  
Keyword(s):  
Healthy Subjects ◽  
Inertial Measurement Unit ◽  
Measurement Unit ◽  
Inertial Measurement Units ◽  
Inertial Measurement ◽  
High Speeds ◽  
Controlled Conditions ◽  
Gait Parameters ◽  
Measurement Units ◽  
Accuracy And Repeatability

In recent years, interest in finding alternatives for the evaluation of mobility has increased. Inertial measurement units (IMUs) stand out for their portability, size, and low price. The objective of this study was to examine the accuracy and repeatability of a commercially available IMU under controlled conditions in healthy subjects. A total of 36 subjects, including 17 males and 19 females were analyzed with a Wiva Science IMU in a corridor test while walking for 10 m and in a threadmill at 1.6 km/h, 2.4 km/h, 3.2 km/h, 4 km/h, and 4.8 km/h for one minute. We found no difference when we compared the variables at 4 km/h and 4.8 km/h. However, we found greater differences and errors at 1.6 km/h, 2.4 km/h and 3.2 km/h, and the latter one (1.6 km/h) generated more error. The main conclusion is that the Wiva Science IMU is reliable at high speeds but loses reliability at low speeds.

Systematic Calibration Method for FOG Inertial Measurement Units

2013 ◽  
Vol 662 ◽  
pp. 717-720 ◽  
Author(s):  
Zhen Yu Zheng ◽  
Yan Bin Gao ◽  
Kun Peng He
Keyword(s):  
Inertial Measurement Unit ◽  
Inertial Sensors ◽  
Calibration Method ◽  
State Equation ◽  
Measurement Unit ◽  
Observation System ◽  
Body Frame ◽  
Inertial Measurement ◽  
Measurement Units ◽  
Error Coefficients

As an inertial sensors assembly, the FOG inertial measurement unit (FIMU) must be calibrated before being used. The paper presents a one-time systematic IMU calibration method only using two-axis low precision turntable. First, the detail error model of inertial sensors using defined body frame is established. Then, only velocity taken as observation, system 33 state equation is established including the lever arm effects and nonlinear terms of scale factor error. The turntable experiments verify that the method can identify all the error coefficients of FIMU on low-precision two-axis turntable, after calibration the accuracy of navigation is improved.

scholarly journals Sit-To-Stand Movement Evaluated Using an Inertial Measurement Unit Embedded in Smart Glasses—A Validation Study

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5019
Author(s):  
Justine Hellec ◽  
Frédéric Chorin ◽  
Andrea Castagnetti ◽  
Serge S. Colson
Keyword(s):  
Concurrent Validity ◽  
Inertial Measurement Unit ◽  
Vertical Axis ◽  
Measurement Unit ◽  
Vertical Acceleration ◽  
Optoelectronic System ◽  
Inertial Measurement ◽  
Sit To Stand ◽  
Smart Glasses ◽  
Absolute Reliability

Wearable sensors have recently been used to evaluate biomechanical parameters of everyday movements, but few have been located at the head level. This study investigated the relative and absolute reliability (intra- and inter-session) and concurrent validity of an inertial measurement unit (IMU) embedded in smart eyeglasses during sit-to-stand (STS) movements for the measurement of maximal acceleration of the head. Reliability and concurrent validity were investigated in nineteen young and healthy participants by comparing the acceleration values of the glasses’ IMU to an optoelectronic system. Sit-to-stand movements were performed in laboratory conditions using standardized tests. Participants wore the smart glasses and completed two testing sessions with STS movements performed at two speeds (slow and comfortable) under two different conditions (with and without a cervical collar). Both the vertical and anteroposterior acceleration values were collected and analyzed. The use of the cervical collar did not significantly influence the results obtained. The relative reliability intra- and inter-session was good to excellent (i.e., intraclass correlation coefficients were between 0.78 and 0.91) and excellent absolute reliability (i.e., standard error of the measurement lower than 10% of the average test or retest value) was observed for the glasses, especially for the vertical axis. Whatever the testing sessions in all conditions, significant correlations (p < 0.001) were found for the acceleration values recorded either in the vertical axis and in the anteroposterior axis between the glasses and the optoelectronic system. Concurrent validity between the glasses and the optoelectronic system was observed. Our observations indicate that the IMU embedded in smart glasses is accurate to measure vertical acceleration during STS movements. Further studies should investigate the use of these smart glasses to assess the STS movement in unstandardized settings (i.e., clinical and/or home) and to report vertical acceleration values in an elderly population of fallers and non-fallers.

scholarly journals Comparison of Trotting Stance Detection Methods from an Inertial Measurement Unit Mounted on the Horse’s Limb

Sensors ◽  
2020 ◽  
Vol 20 (10) ◽  
pp. 2983
Author(s):  
Marie Sapone ◽  
Pauline Martin ◽  
Khalil Ben Mansour ◽  
Henry Château ◽  
Frédéric Marin
Keyword(s):  
Motion Capture ◽  
Inertial Measurement Unit ◽  
Detection Methods ◽  
Measurement Unit ◽  
Inertial Measurement Units ◽  
Inertial Measurement ◽  
New Methods ◽  
Measurement Units ◽  
Ground Types ◽  
Stride Duration

The development of on-board sensors, such as inertial measurement units (IMU), has made it possible to develop new methods for analyzing horse locomotion to detect lameness. The detection of spatiotemporal events is one of the keystones in the analysis of horse locomotion. This study assesses the performance of four methods for detecting Foot on and Foot off events. They were developed from an IMU positioned on the canon bone of eight horses during trotting recording on a treadmill and compared to a standard gold method based on motion capture. These methods are based on accelerometer and gyroscope data and use either thresholding or wavelets to detect stride events. The two methods developed from gyroscopic data showed more precision than those developed from accelerometric data with a bias less than 0.6% of stride duration for Foot on and 0.1% of stride duration for Foot off. The gyroscope is less impacted by the different patterns of strides, specific to each horse. To conclude, methods using the gyroscope present the potential of further developments to investigate the effects of different gait paces and ground types in the analysis of horse locomotion.

scholarly journals A Separated Calibration Method for Inertial Measurement Units Mounted on Three-Axis Turntables

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2846 ◽  
Author(s):  
Chun-mei Dong ◽  
Shun-qing Ren ◽  
Xi-jun Chen ◽  
Zhen-huan Wang
Keyword(s):  
Inertial Measurement Unit ◽  
Functional Relationship ◽  
Calibration Method ◽  
Measurement Unit ◽  
Model Parameters ◽  
Inertial Measurement ◽  
Measurement Units ◽  
Suboptimal Design ◽  
Calibration Accuracy ◽  
Simulation Results

Inertial Measurement Unit (IMU) calibration accuracy is easily affected by turntable errors, so the primary aim of this study is to reduce the dependence on the turntable’s precision during the calibration process. Firstly, the indicated-output of the IMU considering turntable errors is constructed and with the introduction of turntable errors, the functional relationship between turntable errors and the indicated-output was derived. Then, based on a D-suboptimal design, a calibration method for simultaneously identifying the IMU error model parameters and the turntable errors was proposed. Simulation results showed that some turntable errors could thus be effectively calibrated and automatically compensated. Finally, the theoretical validity was verified through experiments. Compared with the traditional method, the method proposed in this paper can significantly reduce the influence of the turntable errors on the IMU calibration accuracy.

scholarly journals Localization of Biobotic Insects Using Low-Cost Inertial Measurement Units

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4486
Author(s):  
Jeremy Cole ◽  
Alper Bozkurt ◽  
Edgar Lobaton
Keyword(s):  
Disaster Response ◽  
Inertial Measurement Unit ◽  
Optimization Problem ◽  
Low Cost ◽  
Boundary Value ◽  
Measurement Unit ◽  
Navigation Problem ◽  
Inertial Measurement ◽  
Measurement Units ◽  
Gromphadorhina Portentosa

Disaster robotics is a growing field that is concerned with the design and development of robots for disaster response and disaster recovery. These robots assist first responders by performing tasks that are impractical or impossible for humans. Unfortunately, current disaster robots usually lack the maneuverability to efficiently traverse these areas, which often necessitate extreme navigational capabilities, such as centimeter-scale clearance. Recent work has shown that it is possible to control the locomotion of insects such as the Madagascar hissing cockroach (Gromphadorhina portentosa) through bioelectrical stimulation of their neuro-mechanical system. This provides access to a novel agent that can traverse areas that are inaccessible to traditional robots. In this paper, we present a data-driven inertial navigation system that is capable of localizing cockroaches in areas where GPS is not available. We pose the navigation problem as a two-point boundary-value problem where the goal is to reconstruct a cockroach’s trajectory between the starting and ending states, which are assumed to be known. We validated our technique using nine trials that were conducted in a circular arena using a biobotic agent equipped with a thorax-mounted, low-cost inertial measurement unit. Results show that we can achieve centimeter-level accuracy. This is accomplished by estimating the cockroach’s velocity—using regression models that have been trained to estimate the speed and heading from the inertial signals themselves—and solving an optimization problem so that the boundary-value constraints are satisfied.

scholarly journals Quantification of the relative arm-use in patients with hemiparesis using inertial measurement units

2020 ◽  
Author(s):  
Ann David ◽  
StephenSukumaran ReethaJanetSureka ◽  
Sankaralingam Gayathri ◽  
Salai Jeyseelan Annamalai ◽  
Selvaraj Samuelkamleshkumar ◽  
...  
Keyword(s):  
Inertial Measurement Unit ◽  
Measurement Unit ◽  
Hand Dominance ◽  
Healthy Controls ◽  
Functional Movement ◽  
Inertial Measurement ◽  
Video Recordings ◽  
Measurement Units ◽  
Natural Settings ◽  
Functional Movements

Background: The most popular method for measuring upper limb activity is based on accelerometry. However, this method is prone to overestimation and is agnostic to the functional utility of a movement. In this study, we used an inertial measurement unit(IMU)-based gross movement score to quantify arm-use in hemiparetic patients at home. Objectives: (i) Validate the gross movement score detected by wrist-worn IMUs against functional movements identified by human assessors. (ii) Test the feasibility of using wrist-worn IMUs to measure arm-use in patients' natural settings. Methods: To validate the gross movement score two independent assessors analyzed and annotated the video recordings of 5 hemiparetic patients and 10 healthy controls performing a set of activities while wearing IMUs. The second study tracked arm-use of 5 hemiparetic patients and 5 healthy controls using two wrist-worn IMUs for 7 days and 3 days, respectively. The IMU data obtained from this study was used to develop quantitative measures (total and relative arm-use (RAU)) and a visualization method for arm-use. Results: The gross movement score detects functional movement with 50-60% accuracy in hemiparetic patients, and is robust to non-functional movements. Healthy controls showed a slight bias towards the dominant arm (RAU: 40.52)°. Patients' RAU varied between 15-47° depending upon their impairment level and pre-stroke hand dominance. Conclusions: The gross movement score performs moderately well in detecting functional movements while rejecting non-functional movements. The patients' total arm-use is less than healthy controls, and their relative arm-use is skewed towards the less-impaired arm.

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