Search results for "Accelerometry"

showing 10 items of 120 documents

Physical Activity Scaled to Preferred Walking Speed as a Predictor of Walking Difficulty in Older Adults: A 2-Year Follow-up

2021

Abstract Background The usual accelerometry-based measures of physical activity (PA) are dependent on physical performance. We investigated the associations between PA relative to walking performance and the prevalence and incidence of early and advanced walking difficulties compared to generally used measures of PA. Methods Perceived walking difficulty was evaluated in 994 community-dwelling participants at baseline (age 75, 80, or 85 years) and 2 years later over 2 km (early difficulty) and 500 m (advanced difficulty). We used a thigh-mounted accelerometer to assess moderate-to-vigorous PA, daily mean acceleration, and relative PA as movement beyond the intensity of preferred walking spee…

Agingmedicine.medical_specialtyPhysical activityWalkingmobility limitation03 medical and health sciencesexercise intensity0302 clinical medicinePhysical medicine and rehabilitationcut-pointKilometerAccelerometryHumansMedicine030212 general & internal medicineMobility LimitationExerciseaskelmittaritAgedbusiness.industryIncidence (epidemiology)ennusteetliikuntarajoitteetphysical performancekävelyWalking SpeedPreferred walking speedaccelerometerDifficulty walkingMobility LimitationdisablementExercise intensityObservational studyGeriatrics and Gerontologybusinesshuman activitiesfyysinen aktiivisuusikääntyneet030217 neurology & neurosurgeryFollow-Up StudiesThe Journals of Gerontology: Series A
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Detection of steering direction using EEG recordings based on sample entropy and time-frequency analysis.

2016

Monitoring driver's intentions beforehand is an ambitious aim, which will bring a huge impact on the society by preventing traffic accidents. Hence, in this preliminary study we recorded high resolution electroencephalography (EEG) from 5 subjects while driving a car under real conditions along with an accelerometer which detects the onset of steering. Two sensor-level analyses, sample entropy and time-frequency analysis, have been implemented to observe the dynamics before the onset of steering. Thus, in order to classify the steering direction we applied a machine learning algorithm consisting of: dimensionality reduction and classification using principal-component-analysis (PCA) and sup…

Automobile DrivingSupport Vector MachineComputer scienceSpeech recognitionEntropyElectroencephalography03 medical and health sciencesEntropy (classical thermodynamics)0302 clinical medicine0502 economics and businessAccelerometrymedicineEntropy (information theory)HumansEntropy (energy dispersal)Entropy (arrow of time)050210 logistics & transportationPrincipal Component Analysismedicine.diagnostic_testbusiness.industryEntropy (statistical thermodynamics)Dimensionality reduction05 social sciencesPattern recognitionElectroencephalographyTime–frequency analysisSupport vector machineSample entropyPrincipal component analysisArtificial intelligencebusiness030217 neurology & neurosurgeryAlgorithmsEntropy (order and disorder)Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
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The Effect of Pedometer Step Goal, Feedback and Self-Monitoring Interventions on Accelerometer-Measured Physical Activity in Children.

2014

This study assessed the utility of 3-week goal-setting, self-monitoring and step-feedback pedometer interventions for increasing physical activity (PA) in children, and the relative impact of individual and group-standardised goals. Three classes of primary school children (n = 68) were randomised to: (a) individual-standardised goal (IS), (b) group-standardised goal (GS) or (c) open pedometer control (CON) groups. PA was assessed via accelerometry (baseline and end-point). There were no main effects for study group, but there was an interaction between time and group for moderate-to-vigorous PA (MVPA), with MVPA time change differing between IS and CON, as MVPA increased in IS but decrease…

Behavioural scienceIntervention studyRA0421AccelerometryeducationH1Youth.human activitiesPedometry
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Monitoring the Internal and External Loads of Young Team Handball Players during Competition

2021

This study aimed to examine the internal- and external-training-load (ITL and ETL, respectively) during a match of young handball players. Field testing included heart-rate monitoring (memory belt, Suunto) as a marker of ITL and accelerometry (motion-biosensor, Actical Respironcis, Philips) as a marker of ETL. Time motion analysis data were obtained by recording the player’s game activities and later analysed with the Matlab software package. T-test and Pearson-product-moment correlation coefficient were used to examine the differences and the relationship between variables collected in the study. The t-test analysis did not show significant differences between the total distance covered (2…

Competition (economics)lcsh:Sportslcsh:GV557-1198.995business.industryTourism Leisure and Hospitality ManagementApplied psychologyAccelerometry Actical Distance covered Energy expenditure Heart rate MatchMedicineOrthopedics and Sports MedicinePhysical Therapy Sports Therapy and RehabilitationbusinessTeam handballheart rate accelerometry Actical match energy expenditure distance covered
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Discrimination of physiological tremor from pathological tremor using accelerometer and surface EMG signals.

2020

BACKGROUND AND OBJECTIVE: Although careful clinical examination and medical history are the most important steps towards a diagnostic separation between different tremors, the electro-physiological analysis of the tremor using accelerometry and electromyography (EMG) of the affected limbs are promising tools. METHODS: A soft-decision wavelet-based decomposition technique is applied with 8 decomposition stages to estimate the power spectral density of accelerometer and surface EMG signals (sEMG) sampled at 800 Hz. A discrimination factor between physiological tremor (PH) and pathological tremor, namely, essential tremor (ET) and the tremor caused by Parkinson’s disease (PD), is obtained by s…

Computer scienceEssential Tremor0206 medical engineeringBiomedical EngineeringBiophysicsHealth InformaticsBioengineering02 engineering and technologyElectromyographyAccelerometerBiomaterials03 medical and health sciences0302 clinical medicineWaveletAccelerometryTremormedicineHumansSpectral analysisEntropy (energy dispersal)Essential tremormedicine.diagnostic_testbusiness.industryElectromyographySpectral densityPattern recognitionParkinson Diseasemedicine.disease020601 biomedical engineeringnervous system diseasesPhysiological tremorArtificial intelligencebusiness030217 neurology & neurosurgeryInformation SystemsTechnology and health care : official journal of the European Society for Engineering and Medicine
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Physical activity volume and intensity distribution in relation to bone, lean and fat mass in children.

2022

Funder: City of Kuopio

DXAMaleluustoadipositypediatricsMovementlapset (ikäryhmät)Physical Therapy Sports Therapy and RehabilitationliikuntaBone and BonesAbsorptiometry PhotonBone DensityaccelerometryBody CompositionlihavuusHumansOrthopedics and Sports MedicineFemaleintensity gradientChildExercisefyysinen aktiivisuusbone mineral contentlastentaudit
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Comparison of Physical Activity and Sedentary Behaviour between Schoolchildren with Cystic Fibrosis and Healthy Controls: A Gender Analysis

2021

The purpose of this study was to examine differences in sports participation and the levels of physical activity (PA) and sedentary behaviour (SB) between schoolchildren with cystic fibrosis (CF) and a healthy control group (CG) taking into account the gender variable. PA and SB were measured with an accelerometer for 7 consecutive days in 44 children (24 girls

Deportes - Aspectos fisiológicos.Malemedicine.medical_specialtyrespiratory healthCystic FibrosisHealth Toxicology and MutagenesisPopulationPhysical activityAdolescentsCystic fibrosisArticle03 medical and health sciences0302 clinical medicineInternal medicineHealthy controlAccelerometrymedicineGender analysisHumansAparato respiratorio - Enfermedades.030212 general & internal medicineeducationChildActive groupRespiratory healthEstudiantes - Ejercicio físico.Esportseducation.field_of_studyexercisebusiness.industryCystic fibrosis - Patients.Public Health Environmental and Occupational HealthRRespiratory organs - Diseases.030229 sport sciencesSports - Physiological aspects.medicine.diseaseChronic diseaseStudents - Exercise.MalaltiesMedicineadolescenceFemalesportsSedentary BehaviorbusinessFibrosis quística - Pacientes.chronic diseaseInternational Journal of Environmental Research and Public Health
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The Use of Accelerometers and Gyroscopes to Estimate Hip and Knee Angles on Gait Analysis

2014

In this paper the performance of a sensor system, which has been developed to estimate hip and knee angles and the beginning of the gait phase, have been investigated. The sensor system consists of accelerometers and gyroscopes. A new algorithm was developed in order to avoid the error accumulation due to the gyroscopes drift and vibrations due to the ground contact at the beginning of the stance phase. The proposed algorithm have been tested and compared to some existing algorithms on over-ground walking trials with a commercial device for assisted gait. The results have shown the good accuracy of the angles estimation, also in high angle rate movement.

EngineeringTransducersComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONMonitoring AmbulatoryAccelerometerlcsh:Chemical technologySensitivity and SpecificityBiochemistryArticleAnalytical Chemistrylaw.inventionGait (human)gait analysiSettore ING-INF/04 - AutomaticaInertial measurement unitlawAccelerometryHumansHigh anglelcsh:TP1-1185Electrical and Electronic EngineeringGaitInstrumentationSimulationgait analysis; joint angles estimation; inertial sensorsArthrometry ArticularStance phasebusiness.industryReproducibility of ResultsSignal Processing Computer-AssistedGyroscopeEquipment DesignActigraphyinertial sensorsAtomic and Molecular Physics and OpticsEquipment Failure AnalysisVibrationGait analysisgait analysisjoint angles estimationbusinessAlgorithmsSensors
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Predicting who fails to meet the physical activity guideline in pregnancy: a prospective study of objectively recorded physical activity in a populat…

2016

Background A low physical activity (PA) level in pregnancy is associated with several adverse health outcomes. Early identification of pregnant women at risk of physical inactivity could inform strategies to promote PA, but no studies so far have presented attempts to develop prognostic models for low PA in pregnancy. Based on moderate-to-vigorous intensity PA (MVPA) objectively recorded in mid/late pregnancy, our objectives were to describe MVPA levels and compliance with the PA guideline (≥150 MVPA minutes/week), and to develop a prognostic model for non-compliance with the PA guideline. Methods From a multi-ethnic population-based cohort, we analysed data from 555 women with MVPA recorde…

Friends:Medisinske Fag: 700::Klinisk medisinske fag: 750::Gynekologi og obstetrikk: 756 [VDP]Logistic regressionBody fat percentage0302 clinical medicinePregnancyObstetrics and GynaecologyAccelerometryMedicineProspective Studies030212 general & internal medicineProspective cohort studyAdiposityeducation.field_of_studyObstetrics and GynecologyGalvanic Skin ResponseMiddle AgedEuropeParityCohortFemalePsychosocialResearch ArticleAdultmedicine.medical_specialtyAsiaPregnancy Trimester ThirdPhysical ExertionPopulationGuidelines as TopicMulti-ethnicMiddle EastYoung Adult03 medical and health sciencesHumansOccupationseducationExercisePregnancybusiness.industryPhysical activity030229 sport sciencesGuidelinemedicine.diseaseVDP::Medisinske Fag: 700::Klinisk medisinske fag: 750::Gynekologi og obstetrikk: 756North AmericaPhysical therapyPatient ComplianceEnergy MetabolismSkin TemperaturePredictionbusinessForecastingDemography
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Deep Learning for Classifying Physical Activities from Accelerometer Data

2021

Physical inactivity increases the risk of many adverse health conditions, including the world’s major non-communicable diseases, such as coronary heart disease, type 2 diabetes, and breast and colon cancers, shortening life expectancy. There are minimal medical care and personal trainers’ methods to monitor a patient’s actual physical activity types. To improve activity monitoring, we propose an artificial-intelligence-based approach to classify the physical movement activity patterns. In more detail, we employ two deep learning (DL) methods, namely a deep feed-forward neural network (DNN) and a deep recurrent neural network (RNN) for this purpose. We evaluate the proposed models on two phy…

Fysisk aktivitetComputer scienceVDP::Informasjons- og kommunikasjonsteknologi: 550physical activityAccelerometercomputer.software_genresensorsBiochemistryMedical careRNNAnalytical Chemistry:Information and communication technology: 550 [VDP]Accelerometer dataAccelerometryartificial_intelligence_roboticsInstrumentationArtificial neural networkhealthAtomic and Molecular Physics and Opticsmachine learningclassificationHealthFeedforward neural network:Informasjons- og kommunikasjonsteknologi: 550 [VDP]Physical activityTP1-1185Movement activityMachine learningHelseFeed-forward neural networksVDP::Information and communication technology: 550ArticleFysisk aktiviteterMachine learningHumansAccelerometer dataElectrical and Electronic EngineeringExercisebusiness.industryPhysical activitySensorsDeep learningChemical technologydeep learningDeep learningfeed-forward neural networkRecurrent neural networkPhysical activitiesDiabetes Mellitus Type 2Recurrent neural networksaccelerometer dataUCIrecurrent neural networkNeural Networks ComputerArtificial intelligenceClassificationsbusinesscomputerDNN
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