Academic literature on the topic 'Magneto-inertial measurement units'

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Journal articles on the topic "Magneto-inertial measurement units"

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Paloschi, Davide, Marco Bravi, Emiliano Schena, Sandra Miccinilli, Michelangelo Morrone, Silvia Sterzi, Paola Saccomandi, and Carlo Massaroni. "Validation and Assessment of a Posture Measurement System with Magneto-Inertial Measurement Units." Sensors 21, no. 19 (October 3, 2021): 6610. http://dx.doi.org/10.3390/s21196610.

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Inappropriate posture and the presence of spinal disorders require specific monitoring systems. In clinical settings, posture evaluation is commonly performed with visual observation, electrogoniometers or motion capture systems (MoCaps). Developing a measurement system that can be easily used also in non-structured environments would be highly beneficial for accurate posture monitoring. This work proposes a system based on three magneto-inertial measurement units (MIMU), placed on the backs of seventeen volunteers on the T3, T12 and S1 vertebrae. The reference system used for validation is a stereophotogrammetric motion capture system. The volunteers performed forward bending and sit-to-stand tests. The measured variables for identifying the posture were the kyphosis and the lordosis angles, as well as the range of movement (ROM) of the body segments. The comparison between MIMU and MoCap provided a maximum RMSE of 5.6° for the kyphosis and the lordosis angles. The average lumbo-pelvic contribution during forward bending (41.8 ± 8.6%) and the average lumbar ROM during sit-to-stand (31.8 ± 9.8° for sitting down, 29.6 ± 7.6° for standing up) obtained with the MIMU system agree with the literature. In conclusion, the MIMU system, which is wearable, inexpensive and easy to set up in non-structured environments, has been demonstrated to be effective in posture evaluation.
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Horenstein, Rachel E., Yohann R. Goudeau, Cara L. Lewis, and Sandra J. Shefelbine. "Using Magneto-Inertial Measurement Units to Pervasively Measure Hip Joint Motion during Sports." Sensors 20, no. 17 (September 2, 2020): 4970. http://dx.doi.org/10.3390/s20174970.

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The use of wireless sensors to measure motion in non-laboratory settings continues to grow in popularity. Thus far, most validated systems have been applied to measurements in controlled settings and/or for prescribed motions. The aim of this study was to characterize adolescent hip joint motion of elite-level athletes (soccer players) during practice and recreationally active peers (controls) in after-school activities using a magneto-inertial measurement unit (MIMU) system. Opal wireless sensors (APDM Inc., Portland OR, USA) were placed at the sacrum and laterally on each thigh (three sensors total). Hip joint motion was characterized by hip acceleration and hip orientation for one hour of activity on a sports field. Our methods and analysis techniques can be applied to other joints and activities. We also provide recommendations in order to guide future work using MIMUs to pervasively assess joint motions of clinical relevance.
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Zedda, A., E. Gusai, M. Caruso, S. Bertuletti, S. Spanu, A. Pibiri, M. Monticone, A. Cereatti, and D. Pani. "A home-based tele-rehabilitation system for stroke patients exploiting magneto-inertial measurement units." Gait & Posture 74 (September 2019): 37–38. http://dx.doi.org/10.1016/j.gaitpost.2019.07.499.

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Nez, Alexis, Laetitia Fradet, Frédéric Marin, Tony Monnet, and Patrick Lacouture. "Identification of Noise Covariance Matrices to Improve Orientation Estimation by Kalman Filter." Sensors 18, no. 10 (October 16, 2018): 3490. http://dx.doi.org/10.3390/s18103490.

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Magneto-inertial measurement units (MIMUs) are a promising way to perform human motion analysis outside the laboratory. To do so, in the literature, orientation provided by an MIMU is used to deduce body segment orientation. This is generally achieved by means of a Kalman filter that fuses acceleration, angular velocity, and magnetic field measures. A critical point when implementing a Kalman filter is the initialization of the covariance matrices that characterize mismodelling and input error from noisy sensors. The present study proposes a methodology to identify the initial values of these covariance matrices that optimize orientation estimation in the context of human motion analysis. The approach used was to apply motion to the sensor manually, and to compare the orientation obtained via the Kalman filter to a measurement from an optoelectronic system acting as a reference. Testing different sets of values for each parameter of the covariance matrices, and comparing each MIMU measurement with the reference measurement, enabled identification of the most effective values. Moreover, with these optimized initial covariance matrices, the orientation estimation was greatly improved. The method, as presented here, provides a unique solution to the problem of identifying the optimal covariance matrices values for Kalman filtering. However, the methodology should be improved in order to reduce the duration of the whole process.
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Germanotta, Marco, Ilaria Mileti, Ilaria Conforti, Zaccaria Del Prete, Irene Aprile, and Eduardo Palermo. "Estimation of Human Center of Mass Position through the Inertial Sensors-Based Methods in Postural Tasks: An Accuracy Evaluation." Sensors 21, no. 2 (January 16, 2021): 601. http://dx.doi.org/10.3390/s21020601.

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The estimation of the body’s center of mass (CoM) trajectory is typically obtained using force platforms, or optoelectronic systems (OS), bounding the assessment inside a laboratory setting. The use of magneto-inertial measurement units (MIMUs) allows for more ecological evaluations, and previous studies proposed methods based on either a single sensor or a sensors’ network. In this study, we compared the accuracy of two methods based on MIMUs. Body CoM was estimated during six postural tasks performed by 15 healthy subjects, using data collected by a single sensor on the pelvis (Strapdown Integration Method, SDI), and seven sensors on the pelvis and lower limbs (Biomechanical Model, BM). The accuracy of the two methods was compared in terms of RMSE and estimation of posturographic parameters, using an OS as reference. The RMSE of the SDI was lower in tasks with little or no oscillations, while the BM outperformed in tasks with greater CoM displacement. Moreover, higher correlation coefficients were obtained between the posturographic parameters obtained with the BM and the OS. Our findings showed that the estimation of CoM displacement based on MIMU was reasonably accurate, and the use of the inertial sensors network methods should be preferred to estimate the kinematic parameters.
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Cottam, Daniel S., Amity C. Campbell, Mr Paul C. Davey, Peter Kent, Bruce C. Elliott, and Jacqueline A. Alderson. "Measurement of uni-planar and sport specific trunk motion using magneto-inertial measurement units: The concurrent validity of Noraxon and Xsens systems relative to a retro-reflective system." Gait & Posture 92 (February 2022): 129–34. http://dx.doi.org/10.1016/j.gaitpost.2021.11.012.

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Jardak, Nabil, Ronan Adam, and Sébastien Changey. "A Gyroless Algorithm with Multi-Hypothesis Initialization for Projectile Navigation." Sensors 21, no. 22 (November 11, 2021): 7487. http://dx.doi.org/10.3390/s21227487.

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Projectiles are subjected to a high acceleration shock at launch (20,000 g and higher) and can spin very fast. Thus, the components of onboard navigation units must therefore withstand such constraints in addition to being inexpensive. This makes only a few inertial sensors suitable for projectiles navigation. Particularly, rate gyroscopes which are gun-hardened and have an appropriate operating range are not widely available. On the other hand, magneto-resistive sensors are inexpensive and can satisfy both gun-hardening and operating range requirements, making them an alternative for angular estimation in guided projectiles. This paper presents a gyroless navigation algorithm for projectiles. The lack of gyroscope is handled by the usage of attitude kinematics computed over past attitude estimates of the filter, coupled with a measurement model based on magnetometer and GPS observations of the attitude. The observability of the attitude when considering non-calibrated magnetometers and its dependency on the initialization is addressed. Then, to cope with the initialization dependency of the filter, we proposed a multi-hypothesis initialization algorithm. In terms of performance, the algorithm is shown to provide a high-rate navigation solution with an interesting performance.
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De Bartolo, Daniela, Valeria Belluscio, Giuseppe Vannozzi, Giovanni Morone, Gabriella Antonucci, Gianluca Giordani, Stefania Santucci, et al. "Sensorized Assessment of Dynamic Locomotor Imagery in People with Stroke and Healthy Subjects." Sensors 20, no. 16 (August 13, 2020): 4545. http://dx.doi.org/10.3390/s20164545.

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Dynamic motor imagery (dMI) is a motor imagery task associated with movements partially mimicking those mentally represented. As well as conventional motor imagery, dMI has been typically assessed by mental chronometry tasks. In this paper, an instrumented approach was proposed for quantifying the correspondence between upper and lower limb oscillatory movements performed on the spot during the dMI of walking vs. during actual walking. Magneto-inertial measurement units were used to measure limb swinging in three different groups: young adults, older adults and stroke patients. Participants were tested in four experimental conditions: (i) simple limb swinging; (ii) limb swinging while imagining to walk (dMI-task); (iii) mental chronometry task, without any movement (pure MI); (iv) actual level walking at comfortable speed. Limb swinging was characterized in terms of the angular velocity, frequency of oscillations and sinusoidal waveform. The dMI was effective at reproducing upper limb oscillations more similar to those occurring during walking for all the three groups, but some exceptions occurred for lower limbs. This finding could be related to the sensory feedback, stretch reflexes and ground reaction forces occurring for lower limbs and not for upper limbs during walking. In conclusion, the instrumented approach through wearable motion devices adds significant information to the current dMI approach, further supporting their applications in neurorehabilitation for monitoring imagery training protocols in patients with stroke.
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Provenzale, Cecilia, Nicola Di Stefano, Alessia Noccaro, and Fabrizio Taffoni. "Assessing the Bowing Technique in Violin Beginners Using MIMU and Optical Proximity Sensors: A Feasibility Study." Sensors 21, no. 17 (August 29, 2021): 5817. http://dx.doi.org/10.3390/s21175817.

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Bowing is the fundamental motor action responsible for sound production in violin playing. A lot of effort is required to control such a complex technique, especially at the beginning of violin training, also due to a lack of quantitative assessments of bowing movements. Here, we present magneto-inertial measurement units (MIMUs) and an optical sensor interface for the real-time monitoring of the fundamental parameters of bowing. Two MIMUs and a sound recorder were used to estimate the bow orientation and acquire sounds. An optical motion capture system was used as the gold standard for comparison. Four optical sensors positioned on the bow stick measured the stick–hair distance. During a pilot test, a musician was asked to perform strokes using different sections of the bow at different paces. Distance data were used to train two classifiers, a linear discriminant (LD) classifier and a decision tree (DT) classifier, to estimate the bow section used. The DT classifier reached the best classification accuracy (94.2%). Larger data analysis on nine violin beginners showed that the orientation error was less than 2°; the bow tilt correlated with the audio information (r134=−0.973, 95% CI −0.981,−0.962, p<0.001). The results confirmed that the interface provides reliable information on the bowing technique that might improve the learning performance of violin beginners.
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Paradisi, Francesco, Eugenio Di Stanislao, Aurora Summa, Stefano Brunelli, M. Traballesi, and Giuseppe Vannozzi. "Upper body accelerations during level walking in transtibial amputees." Prosthetics and Orthotics International 43, no. 2 (August 16, 2018): 204–12. http://dx.doi.org/10.1177/0309364618792745.

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Background: The observation of upper body movement is gaining interest in the gait analysis community. Recent studies involved the use of body-worn motion sensors, allowing translation of laboratory measurements to real-life settings in the context of patient monitoring and fall prevention. Objectives: It was shown that amputee persons demonstrate altered acceleration patterns due to the presence of prosthetic components, while no information is available on how accelerations propagate upwards to the head during level walking. This descriptive study aims to fill this gap. Study design: Original research report. Methods: Twenty definitive prosthesis users with transtibial amputation and 20 age-matched able-bodied individuals participated in the study. Three magneto-inertial measurement units were placed at head, sternum and pelvis level to assess acceleration root mean square. Three repetitions of the 10-m walking test were performed at a self-selected speed. Results: Acceleration root mean square was significantly larger at pelvis and head level in individuals with amputation than in able-bodied participants, mainly in the transverse plane ( p < 0.05). Differences were also observed in how accelerations propagate upwards, highlighting that a different motor strategy is adopted in amputee persons gait to compensate for increased instability. Conclusion: The obtained parameters allow an objective mobility assessment of amputee persons that can integrate with the traditional clinical approach. Clinical relevance Transtibial amputees exhibit asymmetries due to the sound limb’s support prevalence during gait: this is evidenced by amplified accelerations on the transverse plane and by related differences in upper body movement control. Assessing these accelerations and their attenuations upwards may be helpful to understand amputee’s motor strategies and to improve prosthetic training.
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Dissertations / Theses on the topic "Magneto-inertial measurement units"

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Richard, Vincent. "Multi-body optimization method for the estimation of joint kinematics : prospects of improvement." Thesis, Lyon, 2016. http://www.theses.fr/2016LYSE1090/document.

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L'analyse du mouvement humain s'appuie généralement sur des techniques de suivi de marqueurs cutanés pour reconstruire la cinématique articulaire. Cependant, ces techniques d'acquisition présentent d'importantes limites dont les " artefacts de tissus mous " (i.e., le mouvement relatif entre les marqueurs cutanés et le squelette sous-jacent). La méthode d'optimisation multi-segmentaire viseà compenser ces artefacts en imposant aux trajectoires de marqueurs les degrés de liberté d'un modèle cinématique prédéfini. Les liaisons mécaniques modélisant classiquement les articulations empêchent toutefois une estimation satisfaisante de la cinématique articulaire. Cette thèse aborde des perspectives d'amélioration de la méthode d'optimisation multi-segmentaire pour l'estimation de la cinématique articulaire du membre inférieur,à travers différentes approches : (1) la reconstruction de la cinématique par suivi de la vitesse angulaire, de l'accélération et de l'orientation de centrales inertiellesà la place du suivi de marqueurs, (2) l'introduction d'un modèle articulaire élastique basé sur la matrice de raideur du genou, permettant une estimation physiologique de la cinématique articulaire et (3) l'introduction d'un modèle des artefacts de tissus mous " cinématique-dépendant ", visantà évaluer et compenser les artefacts de tissus mous simultanément avec l'estimation la cinématique articulaire. Ce travail a démontré la polyvalence de la méthode d'optimisation multi-segmentaire. Les résultats obtenus laissent espérer une amélioration significative de cette méthode qui devient de plus en plus utilisée en biomécanique, en particulier pour la modélisation musculo-squelettique
Human movement analysis generally relies on skin markers monitoring techniques to reconstruct the joint kinematics. However, these acquisition techniques have important limitations including the "soft tissue artefacts" (i.e., the relative movement between the skin markers and the underlying bones). The multi-body optimization method aims to compensate for these artefacts by imposing the degrees of freedom from a predefined kinematic model to markers trajectories. The mechanical linkages typically used for modeling the joints however prevent a satisfactory estimate of the joint kinematics. This thesis addresses the prospects of improvement of the multi-body optimization method for the estimation of joint kinematics of the lower limb through different approaches: (1) the reconstruction of the kinematics by monitoring the angular velocity, the acceleration and the orientation of magneto-inertial measurement units instead of tracking markers, (2) the introduction of an elastic joint model based on the knee stiffness matrix, enabling a physiological estimation of joint kinematics and (3) the introduction of a "kinematic-dependent" soft tissue artefact model to assess and compensate for soft tissue artefact concurrently with estimating the joint kinematics. This work demonstrated the versatility of the multi-body optimization method. The results give hope for significant improvement in this method which is becoming increasingly used in biomechanics, especially for musculoskeletal modeling
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Book chapters on the topic "Magneto-inertial measurement units"

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Cereatti, Andrea, Ugo Della Croce, and Angelo M. Sabatini. "Three-Dimensional Human Kinematic Estimation Using Magneto-Inertial Measurement Units." In Handbook of Human Motion, 221–44. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-14418-4_162.

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Cereatti, Andrea, Ugo Della Croce, and Angelo M. Sabatini. "Three-Dimensional Human Kinematic Estimation Using Magneto-Inertial Measurement Units." In Handbook of Human Motion, 1–24. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-30808-1_162-1.

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Conference papers on the topic "Magneto-inertial measurement units"

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Liu, Yu-Tao, Yong-An Zhang, and Ming Zeng. "Joint parameter estimation using Magneto and Inertial measurement units." In 2017 36th Chinese Control Conference (CCC). IEEE, 2017. http://dx.doi.org/10.23919/chicc.2017.8027688.

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Rossanigo, Rachele, Marco Caruso, Francesca Salis, Stefano Bertuletti, Ugo Della Croce, and Andrea Cereatti. "An Optimal Procedure for Stride Length Estimation Using Foot-Mounted Magneto-Inertial Measurement Units." In 2021 IEEE International Symposium on Medical Measurements and Applications (MeMeA). IEEE, 2021. http://dx.doi.org/10.1109/memea52024.2021.9478604.

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Paloschi, Davide, Mario Cigada, Stefania Ballone, Omar De Bartolomeo, Alfredo Cigada, and Paola Saccomandi. "Analysis on the plié and grand plié in classical ballet with magneto-inertial measurement units." In 2022 IEEE International Workshop on Metrology for Industry 4.0 & IoT (MetroInd4.0&IoT). IEEE, 2022. http://dx.doi.org/10.1109/metroind4.0iot54413.2022.9831587.

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