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Journal articles on the topic 'Accelerometrics'

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Author: Grafiati

Published: 10 December 2022

Last updated: 28 January 2023

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1

Brancewicz, Therese M., and Alan R. Reich. "Speech Rate Reduction and "Nasality" in Normal Speakers." Journal of Speech, Language, and Hearing Research 32, no. 4 (December 1989): 837–48. http://dx.doi.org/10.1044/jshr.3204.837.

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This study explored the effects of reduced speech rate on nasal/voice accelerometric measures and nasality ratings. Nasal/voice accelerometric measures were obtained from normal adults for various speech stimuli and speaking rates. Stimuli included three sentences (one obstruent-loaded, one semivowel-loaded, and one containing a single nasal), and /p/ syllable trains. Speakers read the stimuli at their normal rate, half their normal rate, and as slowly as possible. In addition, a computer program paced each speaker at rates of 1, 2, and 3 syllables per second. The nasal/voice accelerometric values revealed significant stimulus effects but no rate effects. The nasality ratings of experienced listeners, evaluated as a function of stimulus and speaking rate, were compared to the accelerometric measures. The nasality scale values demonstrated small, but statistically significant, stimulus and rate effects. However, the nasality percepts were poorly correlated with the nasal/voice accelerometric measures.

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2

Redenbaugh, Margaret A., and Alan R. Reich. "Correspondence between an Accelerometric Nasal/Voice Amplitude Ratio and Listeners' Direct Magnitude Estimations of Hypernasality." Journal of Speech, Language, and Hearing Research 28, no. 2 (June 1985): 273–81. http://dx.doi.org/10.1044/jshr.2802.273.

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Miniature accelerometers were used to transduce nasal and anterior-neck tissue vibrations of 12 hypernasal and 3 normal children. The accelerometric voltages provided an analog implementation of Horii's (1980) nasal/voice ratio. Simultaneous audio recordings were later evaluated for hypernasality by listeners. Listeners' direct magnitude estimations (DME) of hypernasality were highly correlated with the accelerometric nasal/voice ratio when the stimulus sentences contained obstruents, nonnasal semivowels, and vowels. No correlation existed between DME and accelerometric values when the stimulus sentences contained primarily nasal semivowels and vowels.

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3

Sáez, N., X. Ruiz, Jna Gavaldà, J. Pallarés, and V. Shevtsova. "Comparative ISS accelerometric analyses." Acta Astronautica 94, no. 2 (February 2014): 681–89. http://dx.doi.org/10.1016/j.actaastro.2013.09.005.

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4

Smid, Annemarie, Jan Willem J. Elting, J. Marc C. van Dijk, Bert Otten, D. L. Marinus Oterdoom, Katalin Tamasi, Tjitske Heida, Teus van Laar, and Gea Drost. "Intraoperative Quantification of MDS-UPDRS Tremor Measurements Using 3D Accelerometry: A Pilot Study." Journal of Clinical Medicine 11, no. 9 (April 19, 2022): 2275. http://dx.doi.org/10.3390/jcm11092275.

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The most frequently used method for evaluating tremor in Parkinson’s disease (PD) is currently the internationally standardized Movement Disorder Society—Unified PD Rating Scale (MDS-UPDRS). However, the MDS-UPDRS is associated with limitations, such as its inherent subjectivity and reliance on experienced raters. Objective motor measurements using accelerometry may overcome the shortcomings of visually scored scales. Therefore, the current study focuses on translating the MDS-UPDRS tremor tests into an objective scoring method using 3D accelerometry. An algorithm to measure and classify tremor according to MDS-UPDRS criteria is proposed. For this study, 28 PD patients undergoing neurosurgical treatment and 26 healthy control subjects were included. Both groups underwent MDS-UPDRS tests to rate tremor severity, while accelerometric measurements were performed at the index fingers. All measurements were performed in an off-medication state. Quantitative measures were calculated from the 3D acceleration data, such as tremor amplitude and area-under-the-curve of power in the 4–6 Hz range. Agreement between MDS-UPDRS tremor scores and objective accelerometric scores was investigated. The trends were consistent with the logarithmic relationship between tremor amplitude and MDS-UPDRS score reported in previous studies. The accelerometric scores showed a substantial concordance (>69.6%) with the MDS-UPDRS ratings. However, accelerometric kinetic tremor measures poorly associated with the given MDS-UPDRS scores (R2 < 0.3), mainly due to the noise between 4 and 6 Hz found in the healthy controls. This study shows that MDS-UDPRS tremor tests can be translated to objective accelerometric measurements. However, discrepancies were found between accelerometric kinetic tremor measures and MDS-UDPRS ratings. This technology has the potential to reduce rater dependency of MDS-UPDRS measurements and allow more objective intraoperative monitoring of tremor.

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Folman, Y., E. Goshen, R. Gepstein, R. Sevi, and S. Liberty. "Accelerometric assessment of osseous union." Archives of Orthopaedic and Trauma Surgery 112, no. 4 (1993): 193–97. http://dx.doi.org/10.1007/bf00662288.

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6

Uglešić, Jakov Stanislav, Snježana Markušić, Božo Padovan, and Davor Stanko. "Semi-empirical estimation of the Zagreb ML 5.5 earthquake (2020) ground motion amplification by 1D equivalent linear site response analysis." Geofizika 38, no. 2 (January 24, 2022): 147–73. http://dx.doi.org/10.15233/gfz.2021.38.9.

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The 22 March 2020 Zagreb ML 5.5 earthquake ground shaking resulted in damage to buildings and infrastructure. The most affected buildings were older and cultural heritage buildings (built before 1963) in the old city centre with significant damage extent in the epicentral zone (southeastern foothills of Medvednica Mt.). This study presents site response analysis on the realistic site profiles from the epicentre towards the accelerometric stations QUHS and QARH and comparison with strong motion data recorded during the Zagreb 2020 earthquake. Semi-empirical estimation of the ground motion amplification (i.e., peak ground acceleration at surface) showed that modelled and recorded values are comparable. Moreover, we present 2D model of peak ground acceleration at surface (PGAsurf ) variation for the superimposed site profile from the epicentre towards two accelerometric stations. Ground motion amplification for the Zagreb ML 5.5 earthquake scenario showed that PGAsurf is larger by a factor of 2 than the bedrock value (approx. 0.35 g in the epicentre and 0.20 g on the 12 km distant accelerometric station). This study is a contribution to better understanding of the Zagreb ML 5.5 earthquake effects and significance of local site effects in the damage extent, something that combined with older and heritage buildings resulted in high economic consequences. Therefore, it is important that site-specific ground motion simulation and seismic microzonation of the Zagreb continues with installation of an accelerometric array. This is very important for earthquake retrofitting and resilience of the low, mid- and high-rise buildings with particular care of cultural and historical buildings as well for the further urban planning.

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7

Janiaud, Denis, and Serge Muller. "Accelerometric sensor with flectional vibratory beams." Journal of the Acoustical Society of America 94, no. 2 (August 1993): 1178. http://dx.doi.org/10.1121/1.406941.

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8

Barrey, E., and F. Desbrosse. "Lameness detection using an accelerometric device." Pferdeheilkunde Equine Medicine 12, no. 4 (1996): 617–22. http://dx.doi.org/10.21836/pem19960456.

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9

Boura, Andre. "Accelerometric sensor with plane pendulum structure." Journal of the Acoustical Society of America 89, no. 3 (March 1991): 1485. http://dx.doi.org/10.1121/1.400594.

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10

Badura, Pawel. "Accelerometric signals in automatic balance assessment." Computerized Medical Imaging and Graphics 46 (December 2015): 169–77. http://dx.doi.org/10.1016/j.compmedimag.2015.05.007.

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11

Felicetta, Chiara, Maria D’Amico, Giovanni Lanzano, Rodolfo Puglia, Emiliano Russo, and Lucia Luzi. "Site characterization of Italian accelerometric stations." Bulletin of Earthquake Engineering 15, no. 6 (May 27, 2016): 2329–48. http://dx.doi.org/10.1007/s10518-016-9942-3.

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12

Ricard, Anne, Bernard Dumont Saint Priest, Marjorie Chassier, Margot Sabbagh, and Sophie Danvy. "Genetic consistency between gait analysis by accelerometry and evaluation scores at breeding shows for the selection of jumping competition horses." PLOS ONE 15, no. 12 (December 16, 2020): e0244064. http://dx.doi.org/10.1371/journal.pone.0244064.

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The aim was to assess the efficiency of gaits characteristics in improving jumping performance of sport horses and confront accelerometers and judge scores for this purpose. A sample of 1,477 young jumping horses were measured using accelerometers for walk, trot, and canter. Of these, 702 were genotyped with 541,175 SNPs after quality control. Dataset of 26,914 horses scored by judges in breeding shows for gaits and dataset of 142,682 horses that performed in jumping competitions were used. Analysis of accelerometric data defined three principal components from 64% to 89% of variability explained for each gait. Animal mixed models were used to estimate genetic parameters with the inclusion to up 308,105 ancestors for the relationship matrix. Fixed effects for the accelerometric variables included velocity, gender, age, and event. A GWAS was performed on residuals with the fixed effect of each SNP. The GWAS did not reveal other QTLs for gait traits than the one related to the height at withers. The accelerometric principal components were highly heritable for the one linked to stride frequency and dorsoventral displacement at trot (0.53) and canter (0.41) and moderately for the one linked to longitudinal activities (0.33 for trot, 0.19 for canter). Low heritabilities were found for the walk traits. The genetic correlations of the accelerometric principal components with the jumping competition were essentially nil, except for a negative correlation with longitudinal activity at canter (-0.19). The genetic correlation between the judges’ scores and the jumping competition reached 0.45 for canter (0.31 for trot and 0.17 for walk). But these correlations turned negative when the scores were corrected for the known parental breeding value for competition at the time of the judging. In conclusion, gait traits were not helpful to select for jumping performances. Different gaits may be suitable for a good jumping horse.

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13

Deleflie, F., P. Exertier, P. Berio, G. Metris, O. Laurain, J. M. Lemoine, and S. Loyer. "A first analysis of the mean motion of CHAMP." Advances in Geosciences 1 (June 30, 2003): 95–101. http://dx.doi.org/10.5194/adgeo-1-95-2003.

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Abstract. The present study consists in studying the mean orbital motion of the CHAMP satellite, through a single long arc on a period of time of 200 days in 2001. We actually investigate the sensibility of its mean motion to its accelerometric data, as measures of the surface forces, over that period. In order to accurately determine the mean motion of CHAMP, we use “observed" mean orbital elements computed, by filtering, from 1-day GPS orbits. On the other hand, we use a semi-analytical model to compute the arc. It consists in numerically integrating the effects of the mean potentials (due to the Earth and the Moon and Sun), and the effects of mean surfaces forces acting on the satellite. These later are, in case of CHAMP, provided by an averaging of the Gauss system of equations. Results of the fit of the long arc give a relative sensibility of about 10-3, although our gravitational mean model is not well suited to describe very low altitude orbits. This technique, which is purely dynamical, enables us to control the decreasing of the trajectory altitude, as a possibility to validate accelerometric data on a long term basis.Key words. Mean orbital motion, accelerometric data

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14

Saitua, Aritz, Cristina Castejón-Riber, Francisco Requena, David Argüelles, Natalie Calle-González, Antonia Sánchez de Medina, and Ana Muñoz. "Previous Exercise on a Water Treadmill at Different Depths Affects the Accelerometric Pattern Recorded on a Track in Horses." Animals 12, no. 22 (November 9, 2022): 3086. http://dx.doi.org/10.3390/ani12223086.

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During a water treadmill (WT) exercise, horses change their accelerometric patterns. We aimed to analyze if these changes persist during terrestrial locomotion. Six horses were randomly subjected to 40 min duration WT exercises, without water (WW), at the depth of fetlock (FET), carpus (CAR) and stifle (STF), with a day off between them. Before and after 30 min after WT, horses were evaluated at walk and at trot on a track with a triaxial accelerometer fixed on the pectoral (PECT) and sacrum (SML) regions. The percent of change from baseline (before WT and after each exercise session) were calculated. Total, dorsoventral, longitudinal and mediolateral accelerometric activities and dorsoventral displacement increased with the accelerometer in PECT but decreased after WT at STF. Velocity increased with the accelerometer in PECT but decreased with the accelerometer in SML, particularly after WT at STF. A reduction in stride frequency was found with the accelerometer in PECT. SL increased with the accelerometer in SML but decreased with WT at STF. Some accelerometric changes that happened on WT remained shortly in terrestrial locomotion. The reduction in some parameters after WT at STF depth seems to indicate fatigue. This should be considered in training or rehabilitation programs for unfit animals.

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15

Núñez‐Cornú, Francisco Javier, Juan Manuel Sandoval, Edgar Alarcón, Adán Gómez, Carlos Suárez‐Plascencia, Diana Núñez, Elizabeth Trejo‐Gómez, Oscar Sánchez Mariscal, J. Guadalupe Candelas Ortiz, and Luz María Zúñiga‐Medina. "The Jalisco Seismic Accelerometric Telemetric Network (RESAJ)." Seismological Research Letters 89, no. 2A (February 7, 2018): 363–72. http://dx.doi.org/10.1785/0220170157.

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16

Varghese, Lenny A., Joseph O. Mendoza, Maia N. Braden, and Cara E. Stepp. "Accelerometric correlates of nasalized speech in children." Journal of the Acoustical Society of America 135, no. 4 (April 2014): 2197. http://dx.doi.org/10.1121/1.4877165.

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17

Elble, Rodger J. "Gravitational artifact in accelerometric measurements of tremor." Clinical Neurophysiology 116, no. 7 (July 2005): 1638–43. http://dx.doi.org/10.1016/j.clinph.2005.03.014.

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18

Mora, Niccolo, Federico Cocconcelli, Guido Matrella, and Paolo Ciampolini. "Accurate Heartbeat Detection on Ballistocardiogram Accelerometric Traces." IEEE Transactions on Instrumentation and Measurement 69, no. 11 (November 2020): 9000–9009. http://dx.doi.org/10.1109/tim.2020.2998644.

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19

Costa, Giovanni, Luca Moratto, and Peter Suhadolc. "The Friuli Venezia Giulia Accelerometric Network: RAF." Bulletin of Earthquake Engineering 8, no. 5 (September 24, 2009): 1141–57. http://dx.doi.org/10.1007/s10518-009-9157-y.

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20

Albarello, D., M. Francescone, E. Lunedei, E. Paolucci, M. P. Papasidero, G. Peruzzi, and P. Pieruccini. "Seismic characterization and reconstruction of reference ground motion at accelerometric sites of the Italian national accelerometric network (RAN)." Natural Hazards 86, S2 (March 31, 2016): 401–16. http://dx.doi.org/10.1007/s11069-016-2310-4.

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21

Pillard, P., F. X. Ferrand, and E. Viguier. "3D accelerometric gait analysis in dogs using smartphone." Computer Methods in Biomechanics and Biomedical Engineering 16, sup1 (July 2013): 136–38. http://dx.doi.org/10.1080/10255842.2013.815879.

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22

Henriksen, Marius, H. Lund, R. Moe-Nilssen, H. Bliddal, and B. Danneskiod-Samsøe. "Test–retest reliability of trunk accelerometric gait analysis." Gait & Posture 19, no. 3 (June 2004): 288–97. http://dx.doi.org/10.1016/s0966-6362(03)00069-9.

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23

Sáez, N., Jna Gavaldà, X. Ruiz, and V. Shevtsova. "Detecting accelerometric nonlinearities in the international space station." Acta Astronautica 103 (October 2014): 16–25. http://dx.doi.org/10.1016/j.actaastro.2014.06.025.

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24

Castellaro, S., and D. Albarello. "Reconstructing seismic ground motion at reference site conditions: the case of accelerometric records of the Italian National Accelerometric Network (RAN)." Bulletin of Earthquake Engineering 15, no. 6 (October 18, 2016): 2377–91. http://dx.doi.org/10.1007/s10518-016-0032-3.

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25

Gewolb, Ira H., and Frank L. Vice. "Use of a non-invasive accelerometric method for diagnosing gastroesophageal reflux in premature infants." Journal of Perinatology 41, no. 8 (March 23, 2021): 1879–85. http://dx.doi.org/10.1038/s41372-021-01034-5.

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Abstract Objective To evaluate the clinical usefulness of a non-invasive accelerometric device to diagnose GER in preterm babies. Study design An accelerometer was taped over the sub-xiphoid process in 110 preterm (GA 29.6 ± 3.3 wk) infants (133 studies). Low frequency, sub-audible signals were captured via digital recording (sampling rate 200 Hz), then re-sampled (rate = 60 Hz) to create a spectrogram (focused range 0–30 Hz). Mean amplitude in the focused range was calculated. Results Of 85 studies with simultaneous pH-metry and accelerometry, 18 had concurrent positive and 23 had concurrent negative scores, 42 had negative pH scores when accelerometry was positive (≥1 µV), consistent with non-acid reflux. Eleven infants at high risk of aspiration received surgical interventions. All but 1 had negative pH scores while 10/11 had positive accelerometry. Conclusions The non-invasiveness of this accelerometric technique allows for GER screening and for repeated testing to assess efficacy of interventions.

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26

Lariviere, Ophelie, Thomas Provot, Laura Valdes-Tamayo, Maxime Bourgain, and Delphine Chadefaux. "Force Pattern and Acceleration Waveform Repeatability of Amateur Runners." Proceedings 49, no. 1 (June 15, 2020): 136. http://dx.doi.org/10.3390/proceedings2020049136.

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Although accelerometers’ responses during running are not perfectly understood, they are widely used to study performance and the risk of injury. To outline the typical tibial acceleration pattern during running, this study aims to investigate the repeatability of acceleration signals with respect to the ground reaction force waveforms. Ten amateur runners were asked to perform ten trials along a straight line. One participant was asked to perform this protocol over ten sessions. Tibial accelerations and ground reaction forces were measured during the stance phase. The coefficient of multiple correlation R was computed to study the intra- and inter-test and subject repeatability of accelerometric and force waveforms. A good (R>0.8) intra- and inter-test repeatability was observed for all measured signals. Similar results were observed for intra-subject repeatability. A good inter-subject repeatability was observed only for the longitudinal acceleration and vertical and antero-posterior forces. Typical accelerometric signatures were outlined for each case studied.

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Mousavi, Mehdi, Sinan Akkar, and Mustafa Erdik. "A Candidate Proxy to be used in Intensity-Based Triggering Mechanism for Parametric CAT-Bond Insurance: Istanbul Case Study." Earthquake Spectra 35, no. 2 (May 2019): 565–88. http://dx.doi.org/10.1193/081018eqs201m.

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We study the suitability of average peak ground acceleration ( PGA) as a ground-motion proxy for parametric catastrophe bond (CAT bond) design. We tie the selection of PGA (as a triggering parameter for CAT bonds) to computational convenience (fast retrieval from the recorded ground motion) and loss correlation (optimum monetary return on the investor side). Our case studies advocate that PGA, as a candidate ground-motion proxy, can be used confidently for parametric CAT bonds, particularly applications associated with dense coverage of seismic networks. It is still a compelling ground-motion proxy even if the seismic network coverage is sparse, provided that the accelerometric stations are deployed in the vicinity of assets that financially represent the most significant portion of the insured building stock. We establish an event-based risk model of the Istanbul city (via Monte Carlo simulations) to depict the rationale behind our proposition and compare its performance with other competing (more sophisticated) proxies in terms of accelerometric network density and spatial distribution as well as the different risk levels used in risk management.

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Das, Mousumi, Tilendra Choudhary, L. N. Sharma, and M. K. Bhuyan. "Noninvasive Accelerometric Approach for Cuffless Continuous Blood Pressure Measurement." IEEE Transactions on Instrumentation and Measurement 70 (2021): 1–9. http://dx.doi.org/10.1109/tim.2021.3122182.

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Giuberti, Matteo, Marco Martalò, and Gianluigi Ferrari. "A hybrid radio/accelerometric approach to arm posture recognition." Journal of Ambient Intelligence and Smart Environments 7, no. 4 (July 13, 2015): 563–78. http://dx.doi.org/10.3233/ais-150326.

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BARREY, E., M. HERMELIN, J. L. VAUDELIN, D. POIREL, and J. P. VALETTE. "Utilisation of an accelerometric device in equine gait analysis." Equine Veterinary Journal 26, S17 (June 10, 2010): 7–12. http://dx.doi.org/10.1111/j.2042-3306.1994.tb04864.x.

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BARREY, E., B. AUVINET, and ANNE COUROUCÉ. "Gait evaluation of race trotters using an accelerometric device." Equine Veterinary Journal 27, S18 (May 1995): 156–60. http://dx.doi.org/10.1111/j.2042-3306.1995.tb04910.x.

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Halling Thomsen, Maj, Anders Tolver Jensen, Helle Sørensen, Casper Lindegaard, and Pia Haubro Andersen. "Symmetry indices based on accelerometric data in trotting horses." Journal of Biomechanics 43, no. 13 (September 2010): 2608–12. http://dx.doi.org/10.1016/j.jbiomech.2010.05.004.

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Bhattarai, M., U. Gautam, R. Pandey, L. Bollinger, B. Hernandej, and V. Boutin. "Capturing first records at the Nepal NSC accelerometric network." Journal of Nepal Geological Society 43 (November 1, 2011): 137–44. http://dx.doi.org/10.3126/jngs.v43i0.25145.

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34

Hoff, J. I., A. A. v/d Plas, E. A. H. Wagemans, and J. J. van Hilten. "Accelerometric assessment of levodopa-induced dyskinesias in Parkinson's disease." Movement Disorders 16, no. 1 (January 2001): 58–61. http://dx.doi.org/10.1002/1531-8257(200101)16:1<58::aid-mds1018>3.0.co;2-9.

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Dubert, D., J. Ollé, R. Jurado, Jna Gavaldà, A. Laverón-Simavilla, X. Ruiz, and V. Shevtsova. "Characterization of the Accelerometric Environment of DCMIX2/3 Experiments." Microgravity Science and Technology 30, no. 5 (August 3, 2018): 683–97. http://dx.doi.org/10.1007/s12217-018-9640-7.

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Rovithis, E., K. Makra, A. Savvaidis, and E. Kirtas. "THE ACCELEROMETRIC NETWORK OF THE INDES-MUSA PROJECT IN THE KALOCHORI AREA: CONFIGURATION, DOCUMENTATION AND PRELIMINARY DATA INTERPRETATION." Bulletin of the Geological Society of Greece 50, no. 2 (July 27, 2017): 1100. http://dx.doi.org/10.12681/bgsg.11816.

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A network of seven accelerometric stations on both ground surface and structures has been recently installed, as part of a multi-sensor network for monitoring seismic motion and ground subsidence in the broader area of Kalochori, west of Thessaloniki in Northern Greece, within the INDES-MUSA project. This network includes ground installations within the urban area, structural stations on top of structures and a freefield station away from the building stock. The documentation of stations is presented including shear wave velocity profiles of the subsoil at each location. A set of thirtynine earthquakes recorded so far by the accelerometric network is reported, followed by data processing procedures performed in the acquired waveforms. Comparisons of the processed earthquake recordings are presented referring to (a) the urbanground and the free-field stations in terms of peak ground acceleration, indicating amplification trends of ground motion, and (b) the structural and the nearby urban ground stations by means of top-to-base ratios in the frequency domain, towards a preliminary identification of the fundamental vibrational characteristics of the instrumented structures. The processed acceleration data are available through the INDES-MUSA Web-GIS portal.

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Rovithis, Emmanouil, Konstantia Makra, Emmanouil Kirtas, Charalambos Manesis, Dimitrios Bliziotis, and Kiriaki Konstantinidou. "Field Monitoring of Strong Ground Motion in Urban Areas: The Kalochori Accelerometric Network (KAN), Database and Web-GIS Portal." Earthquake Spectra 34, no. 2 (May 2018): 471–501. http://dx.doi.org/10.1193/052917eqs098dp.

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The Kalochori Accelerometric Network (KAN) has been operating since 2014 in the urban area of Kalochori, 7 km west of Thessaloniki in Northern Greece. KAN is composed of seven accelerometric stations: three ground stations installed in distinct urban zones (i.e., residential, industrial, and tanks zone); three stations on top of a selected structure within each urban zone; and one free-field station away from the built environment. The stations are documented with installation and operating features, available characteristics of the housing structures, and geotechnical data. A set of 78 earthquakes that have been recorded by KAN between 16 January 2014 and 31 December 2016 are reported, allowing investigation of local site effects on seismic motion, variation of ground surface motion within different urban environments, and evaluation of dynamic response features of the instrumented structures. KAN stations monographs, processed acceleration recordings, and metadata of the recorded earthquakes are available online through a Web-GIS platform. Indicative example applications are discussed for possible data use in the field of soil and structural dynamics. The DOI linked to the complete set of KAN data is 10.6084/m9.figshare.5044804.

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Prochazka, Ales, Ondrej Dostal, Pavel Cejnar, Hagar Ibrahim Mohamed, Zbysek Pavelek, Martin Valis, and Oldrich Vysata. "Deep Learning for Accelerometric Data Assessment and Ataxic Gait Monitoring." IEEE Transactions on Neural Systems and Rehabilitation Engineering 29 (2021): 360–67. http://dx.doi.org/10.1109/tnsre.2021.3051093.

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García-Soidán, Jose L., Raquel Leirós-Rodríguez, Vicente Romo-Pérez, and Jesús García-Liñeira. "Accelerometric Assessment of Postural Balance in Children: A Systematic Review." Diagnostics 11, no. 1 (December 22, 2020): 8. http://dx.doi.org/10.3390/diagnostics11010008.

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The correct development of postural control in children is fundamental to ensure that they fully reach their psychomotor capacities. However, this capacity is one of the least studied in the clinical and academic scope regarding children. The objective of this study was to analyze the degree of implementation of accelerometry as an evaluation technique for postural control in children and how it is being used. Methods: A systematic search was conducted in PubMed, SpringerLink, SportsDiscus, Medline, Scopus, and Web of Science with the following terms: balance, postural control, children, kids, accelerometry, and accelerometer. Results: The search generated a total of 18 articles. Two groups of studies were differentiated: those which exclusively included healthy individuals (n = 5) and those which included children with pathologies (n = 13). Accelerometry is being used in children mainly to assess the gait and static balance, as well as to identify the differences between healthy children and children with developmental disorders. Conclusions: Accelerometry has a discrete degree of implementation as an evaluation tool to assess postural control. It is necessary to define a systematic method for the evaluation of postural control in pediatrics, in order to delve into the development of this capacity and its alterations in different neurodevelopmental disorders.

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Celaya-Padilla, Jose, Carlos Galván-Tejada, F. López-Monteagudo, O. Alonso-González, Arturo Moreno-Báez, Antonio Martínez-Torteya, Jorge Galván-Tejada, Jose Arceo-Olague, Huizilopoztli Luna-García, and Hamurabi Gamboa-Rosales. "Speed Bump Detection Using Accelerometric Features: A Genetic Algorithm Approach." Sensors 18, no. 2 (February 3, 2018): 443. http://dx.doi.org/10.3390/s18020443.

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Charvátová, Hana, Aleš Procházka, and Oldřich Vyšata. "Motion Assessment for Accelerometric and Heart Rate Cycling Data Analysis." Sensors 20, no. 5 (March 10, 2020): 1523. http://dx.doi.org/10.3390/s20051523.

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Abstract:

Motion analysis is an important topic in the monitoring of physical activities and recognition of neurological disorders. The present paper is devoted to motion assessment using accelerometers inside mobile phones located at selected body positions and the records of changes in the heart rate during cycling, under different body loads. Acquired data include 1293 signal segments recorded by the mobile phone and the Garmin device for uphill and downhill cycling. The proposed method is based upon digital processing of the heart rate and the mean power in different frequency bands of accelerometric data. The classification of the resulting features was performed by the support vector machine, Bayesian methods, k-nearest neighbor method, and neural networks. The proposed criterion is then used to find the best positions for the sensors with the highest discrimination abilities. The results suggest the sensors be positioned on the spine for the classification of uphill and downhill cycling, yielding an accuracy of 96.5% and a cross-validation error of 0.04 evaluated by a two-layer neural network system for features based on the mean power in the frequency bands ⟨ 3 , 8 ⟩ and ⟨ 8 , 15 ⟩ Hz. This paper shows the possibility of increasing this accuracy to 98.3% by the use of more features and the influence of appropriate sensor positioning for motion monitoring and classification.

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King, George A., Nancy Torres, Charlie Potter, and Karen J. Coleman. "Comparison of Two Tri-Axial Accelerometric Measures of Energy Expenditure." Medicine & Science in Sports & Exercise 36, Supplement (May 2004): S198. http://dx.doi.org/10.1249/00005768-200405001-00945.

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Smith, Maia P., Marie Standl, Joachim Heinrich, and Holger Schulz. "Accelerometric estimates of physical activity vary unstably with data handling." PLOS ONE 12, no. 11 (November 6, 2017): e0187706. http://dx.doi.org/10.1371/journal.pone.0187706.

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King, George A., Nancy Torres, Charlie Potter, and Karen J. Coleman. "Comparison of Two Tri-Axial Accelerometric Measures of Energy Expenditure." Medicine & Science in Sports & Exercise 36, Supplement (May 2004): S198. http://dx.doi.org/10.1097/00005768-200405001-00945.

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Auvinet, Bernard, Gilles Berrut, Claude Touzard, Laurent Moutel, Nadine Collet, Denis Chaleil, and Eric Barrey. "Reference data for normal subjects obtained with an accelerometric device." Gait & Posture 16, no. 2 (October 2002): 124–34. http://dx.doi.org/10.1016/s0966-6362(01)00203-x.

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Thoumie, P., R. C. van Lummel, S. C. Heikens, and R. M. A. van der Slikke. "22.32 Accelerometric assessment of gait parameters inorthopaedic and stroke patients." Gait & Posture 21 (June 2005): S151. http://dx.doi.org/10.1016/s0966-6362(05)80500-4.

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Aytürk, Zübeyde, Rezzak Yilmaz, and M. Cenk Akbostanci. "Re-emergent tremor in Parkinson’s disease: Clinical and accelerometric properties." Journal of Clinical Neuroscience 37 (March 2017): 31–33. http://dx.doi.org/10.1016/j.jocn.2016.11.007.

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Badura, Pawel, and Ewa Pietka. "Automatic Berg Balance Scale assessment system based on accelerometric signals." Biomedical Signal Processing and Control 24 (February 2016): 114–19. http://dx.doi.org/10.1016/j.bspc.2015.10.005.

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Barrey, E., P. Galloux, and J. P. Valette. "Relationships between accelerometric and kinematic measurements in a running horse." Journal of Biomechanics 27, no. 6 (January 1994): 793. http://dx.doi.org/10.1016/0021-9290(94)91307-2.

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Schutz, Y., S. Weinsier, P. Terrier, and D. Durrer. "A new accelerometric method to assess the daily walking practice." International Journal of Obesity 26, no. 1 (January 2002): 111–18. http://dx.doi.org/10.1038/sj.ijo.0801856.

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