Search results for "Wearable devices"

showing 8 items of 8 documents

Minimally Invasive Assessment of Mental Stress based on Wearable Wireless Physiological Sensors and Multivariate Biosignal Processing

2019

The development of connected health technologies for the continuous monitoring of the psychophysical state of individuals performing daily life activities requires the aggregation of non-intrusive sensors and the availability of methods and algorithms for extracting the relevant physiological information. The present study proposes an integrated approach for the objective assessment of mental stress which combines wirelessly connected low invasive biosensors with multivariate physiological time series analysis. In a group of 18 healthy subjects monitored in a relaxed resting state and during two experimental conditions inducing mental stress and sustained attention (respectively, mental ari…

Computer scienceWearable computerwearable deviceElectroencephalographySettore ING-INF/01 - Elettronica03 medical and health sciences0302 clinical medicinetime series analysimedicineTime domainBiosignalEEGstress assessmentTime series030304 developmental biology0303 health sciencesResting state fMRImedicine.diagnostic_testbusiness.industryContinuous monitoringPattern recognitionphysiological signalConnected healthSettore ING-INF/06 - Bioingegneria Elettronica E Informaticaphysiological signals EEG stress assessment time series analysis wearable devicesArtificial intelligencebusiness030217 neurology & neurosurgery
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Multilevel assessment of mental stress via network physiology paradigm using consumer wearable devices

2019

Mental stress is a physiological condition that has a strong negative impact on the quality of life, affecting both the physical and the mental health. For such a reason, accurate measurements of stress level can be helpful to provide mechanisms for prevention and treatment. This paper proposes a procedure for the classification of different mental stress levels by using physiological signals provided by low invasive wearable devices. 17 healthy volunteers participated in this study. Three different mental states were elicited in them: a resting condition, a stressful cognitive state, and a sustained attention task. The acquired physiological signals were: a one lead electrocardiogram (ECG)…

General Computer ScienceComputer scienceStress assessmentPhysiology02 engineering and technologyElectroencephalography03 medical and health sciencesNetwork Physiology0302 clinical medicineQuality of lifeMental stressMachine learningHealthy volunteers0202 electrical engineering electronic engineering information engineeringmedicineRespiratory systemWearable technologyMeasurementmedicine.diagnostic_testbusiness.industryPhysiological conditionCognitionPulse (music)ClassificationMental healthWearable devices020201 artificial intelligence & image processingbusiness030217 neurology & neurosurgeryJournal of Ambient Intelligence and Humanized Computing
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Information Dynamics of the Brain, Cardiovascular and Respiratory Network during Different Levels of Mental Stress

2019

In this study, an analysis of brain, cardiovascular and respiratory dynamics was conducted combining information-theoretic measures with the Network Physiology paradigm during different levels of mental stress. Starting from low invasive recordings of electroencephalographic, electrocardiographic, respiratory, and blood volume pulse signals, the dynamical activity of seven physiological systems was probed with one-second time resolution measuring the time series of the &delta

Information transferInformation dynamicsComputer scienceStress assessmentGeneral Physics and Astronomylcsh:Astrophysics030204 cardiovascular system & hematologyNetwork topologynetwork physiologyInformation Theory Network Physiology StressArticlePhysics and Astronomy (all)03 medical and health sciences0302 clinical medicineRhythmwearable deviceslcsh:QB460-466stress assessmentlcsh:ScienceSubnetworkNetwork physiologyPulse (signal processing)Node (networking)Information dynamics; Network physiology; Stress assessment; Wearable deviceslcsh:QC1-999Wearable devicesPeripheralInformation dynamics; Network physiology; Stress assessment; Wearable devices; Physics and Astronomy (all)lcsh:QWakefulnessinformation dynamicsNeurosciencelcsh:Physics030217 neurology & neurosurgeryEntropy
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Technological advancements in the analysis of human motion and posture management through digital devices

2021

Technological development of motion and posture analyses is rapidly progressing, especially in rehabilitation settings and sport biomechanics. Consequently, clear discrimination among different measurement systems is required to diversify their use as needed. This review aims to resume the currently used motion and posture analysis systems, clarify and suggest the appropriate approaches suitable for specific cases or contexts. The currently gold standard systems of motion analysis, widely used in clinical settings, present several limitations related to marker placement or long procedure time. Fully automated and markerless systems are overcoming these drawbacks for conducting biomechanical…

Motion analysisRehabilitationbusiness.industryEmerging technologiesmedicine.medical_treatmentPostureRasterstereographyReviewSports biomechanicsMotion captureMotion (physics)Wearable devicesInertial measurement unitRisk analysis (engineering)Gait analysisGait analysis; Inertial measurement unit; Motion capture; Posture; Rasterstereography; Wearable devicesMedicineOrthopedics and Sports MedicineGait analysisbusinessMotion captureWearable technology
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Multivariate correlation measures reveal structure and strength of brain–body physiological networks at rest and during mental stress

2021

In this work, we extend to the multivariate case the classical correlation analysis used in the field of network physiology to probe dynamic interactions between organ systems in the human body. To this end, we define different correlation-based measures of the multivariate interaction (MI) within and between the brain and body subnetworks of the human physiological network, represented, respectively, by the time series of delta, theta, alpha, and beta electroencephalographic (EEG) wave amplitudes, and of heart rate, respiration amplitude, and pulse arrival time (PAT) variability. MI is computed: (i) considering all variables in the two subnetworks to evaluate overall brain–body interaction…

Multivariate statisticsTechnology and EngineeringElectroencephalographybrain-heart connectionNetwork topologynetwork physiologylcsh:RC321-571Correlation03 medical and health sciences0302 clinical medicinewearable devicesMedicine and Health SciencesmedicineMultiple correlationSubnetworklcsh:Neurosciences. Biological psychiatry. Neuropsychiatryinformation theory030304 developmental biologyMathematicsOriginal Researchphysiological stressbrain-body interactionsNetwork physiology brain–heart connection cardiovascular oscillations EEG waves physiological stress time series analysis wearable devices0303 health sciencesnetwork physiology; brain-heart connection; cardiovascular oscillations; EEG waves; physiological stressmedicine.diagnostic_testPulse (signal processing)General NeuroscienceCardiorespiratory fitnessbrain–heart connectionMathematics and Statisticscardiovascular oscillationsnetworkstime series analysisphysiologySettore ING-INF/06 - Bioingegneria Elettronica E InformaticaNeuroscience030217 neurology & neurosurgeryEEG wavesNeuroscience
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Assessment of mental stress through the analysis of physiological signals acquired from wearable devices

2019

Mental stress is a physiological state that directly correlates to the quality of life of individuals. Generally speaking, but especially true for disabled or elderly subjects, the assessment of such condition represents a very strong indicator correlated to the difficulties, and, in some case, to the frustration that derives from the execution of a task that results troublesome to be accomplished. This article describes a novel procedure for the assessment of the mental stress level through the use of low invasive wireless wearable devices. The information contained in electrocardiogram, respiratory signal, blood volume pulse, and electroencephalogram was extracted to set up an estimator f…

Network physiologybusiness.industryComputer scienceStress assessmentEstimatorCognitionBlood volume pulseClassificationIndustrial and Manufacturing EngineeringRandom forestTask (project management)Mental stressMachine learningSet (psychology)businessWearable technologyWearable devices MeasurementCognitive psychology
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Tracking oneself for others: communal and self-motivational value of sharing exercise data online

2021

Self-tracking is increasingly popular in recreational sport. Leisure sports practitioners use wearable devices that are connected to online platforms to record, analyse, and share their exercise data. While doing that they interact with a digital system, with themselves, and with peers. This paper examines social-communicative aspects of self-tracking, and the support that these aspects and their associated practices may provide for physical activity behaviour. Data for the study was collected using an online survey and in-depth interviews with Finnish trail runners. The results indicate that sharing exercise data with others on a regular basis can support physical activity behaviour becaus…

online platformsdata sharingGeography Planning and DevelopmentApplied psychologyPhysical activityrecreational sportssosiaalinen mediasosiaalinen tuki050109 social psychologyliikuntaSocial supportwearable devicesComputerApplications_MISCELLANEOUS0502 economics and businessmobiilisovellukset0501 psychology and cognitive sciencesseurantaRecreationWearable technologyself-trackingliikuntateknologiakuntoliikuntayhteisöllisyysbusiness.industry05 social sciencesexercise dataComputingMilieux_PERSONALCOMPUTINGjakaminenSelf trackingTourism Leisure and Hospitality ManagementTracking (education)PsychologybusinessValue (mathematics)050212 sport leisure & tourismLeisure Studies
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Validity of three smartwatches in estimating energy expenditure during outdoor walking and running.

2022

Commercially wrist-worn devices often present inaccurate estimations of energy expenditure (EE), with large between-device differences. We aimed to assess the validity of the Apple Watch Series 6 (AW), Garmin FENIX 6 (GF) and Huawei Watch GT 2e (HW) in estimating EE during outdoor walking and running. Twenty young normal-weight Chinese adults concurrently wore three index devices randomly positioned at both wrists during walking at 6 km/h and running at 10 km/h for 2 km on a 400- meter track. As a criterion, EE was assessed by indirect calorimetry (COSMED K5). For walking, EE from AW and GF was significantly higher than that obtained by the K5 (p < 0.001 and 0.002, respectively), but…

tarkkuusPhysiologyphysical activityälykellotmonitorointikävelyjuoksuvalidation accuracywearable deviceshealth monitoringvalidointiPhysiology (medical)mittarit (mittaus)puettava teknologiafyysinen aktiivisuusenergiankulutus (aineenvaihdunta)Frontiers in physiology
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