inertial measurement
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Sensors ◽  
2022 ◽  
Vol 22 (2) ◽  
pp. 436
Author(s):  
Rémy Hubaut ◽  
Romain Guichard ◽  
Julia Greenfield ◽  
Mathias Blandeau

Musculoskeletal disorders in the workplace are a growing problem in Europe. The measurement of these disorders in a working environment presents multiple limitations concerning equipment and measurement reliability. The aim of this study was to evaluate the use of inertial measurement units against a reference system for their use in the workplace. Ten healthy volunteers conducted three lifting methods (snatching, pushing, and pulling) for manhole cover using a custom-made tool weighting 20 and 30 kg. Participants’ back and dominant arm were equipped with IMU, EMG, and reflective markers for VICON analysis and perception of effort was estimated at each trial using a Visual Analog Scale (VAS). The Bland–Altman method was used and results showed good agreement between IMU and VICON systems for Yaw, Pitch and Roll angles (bias values < 1, −4.4 < LOA < 3.6°). EMG results were compared to VAS results and results showed that both are a valuable means to assess efforts during tasks. This study therefore validates the use of inertial measurement units (IMU) for motion capture and its combination with electromyography (EMG) and a Visual Analogic Scale (VAS) to assess effort for use in real work situations.


Sensors ◽  
2022 ◽  
Vol 22 (1) ◽  
pp. 376
Author(s):  
Cornelis J. de Ruiter ◽  
Erik Wilmes ◽  
Pepijn S. van Ardenne ◽  
Niels Houtkamp ◽  
Reinder A. Prince ◽  
...  

Inertial measurement units (IMUs) fixed to the lower limbs have been reported to provide accurate estimates of stride lengths (SLs) during walking. Due to technical challenges, validation of such estimates in running is generally limited to speeds (well) below 5 m·s−1. However, athletes sprinting at (sub)maximal effort already surpass 5 m·s−1 after a few strides. The present study aimed to develop and validate IMU-derived SLs during maximal linear overground sprints. Recreational athletes (n = 21) completed two sets of three 35 m sprints executed at 60, 80, and 100% of subjective effort, with an IMU on the instep of each shoe. Reference SLs from start to ~30 m were obtained with a series of video cameras. SLs from IMUs were obtained by double integration of horizontal acceleration with a zero-velocity update, corrected for acceleration artefacts at touch-down of the feet. Peak sprint speeds (mean ± SD) reached at the three levels of effort were 7.02 ± 0.80, 7.65 ± 0.77, and 8.42 ± 0.85 m·s−1, respectively. Biases (±Limits of Agreement) of SLs obtained from all participants during sprints at 60, 80, and 100% effort were 0.01% (±6.33%), −0.75% (±6.39%), and −2.51% (±8.54%), respectively. In conclusion, in recreational athletes wearing IMUs tightly fixed to their shoes, stride length can be estimated with reasonable accuracy during maximal linear sprint acceleration.


2022 ◽  
Vol 18 (67) ◽  
pp. 15-28
Author(s):  
Randall Gutiérrez-Vargas ◽  
José Pino-Ortega ◽  
Alexis Ugalde-Ramírez ◽  
Braulio Sánchez-Ureña ◽  
Luis Blanco-Romero ◽  
...  

This study aimed to compare physical and physiological demands in youth basketball players according to gender, playing positions, and match outcomes. 64 players (32 female and 32 male) from eight youth sub-elite basketball teams were monitored using an Ultra-Wide Band system and inertial measurement unit in three consecutive matches. The results showed some significant differences, although with magnitudes qualified as small. When the teams won, the guards covered a greater distance at 0-6 km/h than when they lost. When teams lost, the centers covered more distance at 12-18 km/h and 18-21 km/h. The winning female teams presented a lower maximal heart rate (HRmax) compared to the losing teams. The forwards of the winning teams performed greater efforts at 70-80% HRmax, while the forwards of losing teams performed more efforts at 90-95% HRmax. The greatest number of accelerations and decelerations were performed by the female guards and the male forwards. The number of jumps was higher in the male guards and forwards than in the female ones. HRmax was higher in the forwards of the female teams. Efforts at 80%-90% HRmax were higher in male centers. When the female teams won, they had a lower HRmax than when they lost. When efforts exceed 90% of HRmax the teams lost. In conclusion, despite the differences found, the effect of these contextual variables on physical and physiological demands is unclear. Nevertheless, knowing the game's requirements can help the design of training that enhances the performance of youth basketball players


Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 209
Author(s):  
Tianyu Chen ◽  
Gongliu Yang ◽  
Qingzhong Cai ◽  
Zeyang Wen ◽  
Wenlong Zhang

Pedestrian Navigation System (PNS) is one of the research focuses of indoor positioning in GNSS-denied environments based on the MEMS Inertial Measurement Unit (MIMU). However, in the foot-mounted pedestrian navigation system with MIMU or mobile phone as the main carrier, it is difficult to make the sampling time of gyros and accelerometers completely synchronous. The gyro-accelerometer asynchronous time affects the positioning of PNS. To solve this problem, a new error model of gyro-accelerometer asynchronous time is built. The effect of gyro-accelerometer asynchronous time on pedestrian navigation is analyzed. A filtering model is designed to calibrate the gyro-accelerometer asynchronous time, and a zero-velocity detection method based on the rate of attitude change is proposed. The indoor experiment shows that the gyro-accelerometer asynchronous time is estimated effectively, and the positioning accuracy of PNS is improved by the proposed method after compensating for the errors caused by gyro-accelerometer asynchronous time.


Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 199
Author(s):  
Ciro Mennella ◽  
Susanna Alloisio ◽  
Antonio Novellino ◽  
Federica Viti

Technology-aided hand functional assessment has received considerable attention in recent years. Its applications are required to obtain objective, reliable, and sensitive methods for clinical decision making. This systematic review aims to investigate and discuss characteristics of technology-aided hand functional assessment and their applications, in terms of the adopted sensing technology, evaluation methods and purposes. Based on the shortcomings of current applications, and opportunities offered by emerging systems, this review aims to support the design and the translation to clinical practice of technology-aided hand functional assessment. To this end, a systematic literature search was led, according to recommended PRISMA guidelines, in PubMed and IEEE Xplore databases. The search yielded 208 records, resulting into 23 articles included in the study. Glove-based systems, instrumented objects and body-networked sensor systems appeared from the search, together with vision-based motion capture systems, end-effector, and exoskeleton systems. Inertial measurement unit (IMU) and force sensing resistor (FSR) resulted the sensing technologies most used for kinematic and kinetic analysis. A lack of standardization in system metrics and assessment methods emerged. Future studies that pertinently discuss the pathophysiological content and clinimetrics properties of new systems are required for leading technologies to clinical acceptance.


Robotica ◽  
2021 ◽  
pp. 1-14
Author(s):  
Rahul Jain ◽  
Vijay Bhaskar Semwal ◽  
Praveen Kaushik

Abstract Human gait data can be collected using inertial measurement units (IMUs). An IMU is an electronic device that uses an accelerometer and gyroscope to capture three-axial linear acceleration and three-axial angular velocity. The data so collected are time series in nature. The major challenge associated with these data is the segmentation of signal samples into stride-specific information, that is, individual gait cycles. One empirical approach for stride segmentation is based on timestamps. However, timestamping is a manual technique, and it requires a timing device and a fixed laboratory set-up which usually restricts its applicability outside of the laboratory. In this study, we have proposed an automatic technique for stride segmentation of accelerometry data for three different walking activities. The autocorrelation function (ACF) is utilized for the identification of stride boundaries. Identification and extraction of stride-specific data are done by devising a concept of tuning parameter ( $t_{p}$ ) which is based on minimum standard deviation ( $\sigma$ ). Rigorous experimentation is done on human activities and postural transition and Osaka University – Institute of Scientific and Industrial Research gait inertial sensor datasets. Obtained mean stride duration for level walking, walking upstairs, and walking downstairs is 1.1, 1.19, and 1.02 s with 95% confidence interval [1.08, 1.12], [1.15, 1.22], and [0.97, 1.07], respectively, which is on par with standard findings reported in the literature. Limitations of accelerometry and ACF are also discussed. stride segmentation; human activity recognition; accelerometry; gait parameter estimation; gait cycle; inertial measurement unit; autocorrelation function; wearable sensors; IoT; edge computing; tinyML.


2021 ◽  
Vol 11 (24) ◽  
pp. 12025
Author(s):  
Stefan Marković ◽  
Milivoj Dopsaj ◽  
Sašo Tomažič ◽  
Anton Kos ◽  
Aleksandar Nedeljković ◽  
...  

The aim of the present study was to determine if an inertial measurement unit placed on the metatarsal part of the foot can provide valid and reliable data for an accurate estimate of vertical jump height. Thirteen female volleyball players participated in the study. All players were members of the Republic of Serbia national team. Measurement of the vertical jump height was performed for the two exemplary jumping tasks, squat jump and counter-movement jump. Vertical jump height estimation was performed using the flight time method for both devices. The presented results support a high level of concurrent validity of an inertial measurement unit in relation to a force plate for estimating vertical jump height (CMJ t = 0.897, p = 379; ICC = 0.975; SQJ t = −0.564, p = 0.578; ICC = 0.921) as well as a high level of reliability (ICC > 0.872) for inertial measurement unit results. The proposed inertial measurement unit positioning may provide an accurate vertical jump height estimate for in-field measurement of jump height as an alternative to other devices. The principal advantages include the small size of the sensor unit and possible simultaneous monitoring of multiple athletes.


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